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Khan R, Rahman NU, Hayat MF, Ghernaout D, Salih AAM, Ashraf GA, Samad A, Mahmood MA, Rahman N, Sohail M, Iqbal S, Abdullaev S, Khan A. Unveiling cutting-edge developments: architectures and nanostructured materials for application in optoelectronic artificial synapses. NANOSCALE 2024; 16:14589-14620. [PMID: 39011743 DOI: 10.1039/d4nr00904e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/17/2024]
Abstract
One possible result of low-level characteristics in the traditional von Neumann formulation system is brain-inspired photonics technology based on human brain idea. Optoelectronic neural devices, which are accustomed to imitating the sensory role of biological synapses by adjusting connection measures, can be used to fabricate highly reliable neurologically calculating devices. In this case, nanosized materials and device designs are attracting attention since they provide numerous potential benefits in terms of limited cool contact, rapid transfer fluidity, and the capture of photocarriers. In addition, the combination of classic nanosized photodetectors with recently generated digital synapses offers promising results in a variety of practical applications, such as data processing and computation. Herein, we present the progress in constructing improved optoelectronic synaptic devices that rely on nanomaterials, for example, 0-dimensional (quantum dots), 1-dimensional, and 2-dimensional composites, besides the continuously developing mixed heterostructures. Furthermore, the challenges and potential prospects linked with this field of study are discussed in this paper.
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Affiliation(s)
- Rajwali Khan
- National Water and Energy Center, United Arab Emirates University, Al Ain, 15551, United Arab Emirates.
- Department of Physics, University of Lakki Marwat, Lakki Marwat, 2842, KP, Pakistan
| | - Naveed Ur Rahman
- National Water and Energy Center, United Arab Emirates University, Al Ain, 15551, United Arab Emirates.
- Department of Physics, University of Lakki Marwat, Lakki Marwat, 2842, KP, Pakistan
| | | | - Djamel Ghernaout
- Chemical Engineering Department, College of Engineering, University of Ha'il, PO Box 2440, Ha'il 81441, Saudi Arabia
- Chemical Engineering Department, Faculty of Engineering, University of Blida, PO Box 270, Blida 09000, Algeria
| | - Alsamani A M Salih
- Chemical Engineering Department, College of Engineering, University of Ha'il, PO Box 2440, Ha'il 81441, Saudi Arabia
- Department of Chemical Engineering, Faculty of Engineering, Al Neelain University, Khartoum 12702, Sudan
| | | | - Abdus Samad
- Department of Physics, University of Lakki Marwat, Lakki Marwat, 2842, KP, Pakistan
| | | | - Nasir Rahman
- Department of Physics, University of Lakki Marwat, Lakki Marwat, 2842, KP, Pakistan
| | - Mohammad Sohail
- Department of Physics, University of Lakki Marwat, Lakki Marwat, 2842, KP, Pakistan
| | - Shahid Iqbal
- Department of Physics, University of Wisconsin, La Crosse, WI 54601, USA
| | - Sherzod Abdullaev
- Senior Researcher, Engineering School, Central Asian University, Tashkent, Uzbekistan
- Senior Researcher, Scientific and Innovation Department, Tashkent State Pedagogical University, Uzbekistan
| | - Alamzeb Khan
- Yale University School of Medicine, New Haven, Connecticut, USA
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2
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Pereira ME, Deuermeier J, Martins R, Barquinha P, Kiazadeh A. Unlocking Neuromorphic Vision: Advancements in IGZO-Based Optoelectronic Memristors with Visible Range Sensitivity. ACS APPLIED ELECTRONIC MATERIALS 2024; 6:5230-5243. [PMID: 39070089 PMCID: PMC11270833 DOI: 10.1021/acsaelm.4c00752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 06/20/2024] [Accepted: 06/24/2024] [Indexed: 07/30/2024]
Abstract
Optoelectronic memristors based on amorphous oxide semiconductors (AOSs) are promising devices for the development of spiking neural network (SNN) hardware in neuromorphic vision sensors. In such devices, the conductance state can be controlled by both optical and electrical stimuli, while the typical persistent photoconductivity (PPC) of AOS materials can be used to emulate synaptic functions. However, due to the large band gap of these materials, sensitivity to visible light (red/green/blue) is difficult to accomplish, which hinders applications requiring color discrimination. In this work, we report a 4 μm2 hydrogen-doped (H-doped) indium-gallium-zinc oxide (IGZO) optoelectronic memristor that emulates all of the important rules of SNNs such as short- to long-term memory transition (STM-LTM), paired-pulse facilitation (PPF), spike-time-dependent plasticity (STDP), and learning and forgetting capabilities. By the incorporation of hydrogen gas in the sputtering deposition of IGZO, visible sensitivity was achieved for green and blue wavelengths. Additionally, extremely high light/dark ratios of 179, 93, and 12 are demonstrated for wavelengths of 365, 405, and 505 nm, respectively, due to hydrogen-induced subgap states and device miniaturization. Therefore, the proposed device shows remarkable potential for integration with the pixel circuits of IGZO-based displays with extreme resolution for a true intelligent self-processing display.
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Affiliation(s)
- Maria Elias Pereira
- i3N/CENIMAT,
Department of Materials Science, NOVA School
of Science and Technology and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
| | - Jonas Deuermeier
- i3N/CENIMAT,
Department of Materials Science, NOVA School
of Science and Technology and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
| | - Rodrigo Martins
- i3N/CENIMAT,
Department of Materials Science, NOVA School
of Science and Technology and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
| | - Pedro Barquinha
- i3N/CENIMAT,
Department of Materials Science, NOVA School
of Science and Technology and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
| | - Asal Kiazadeh
- i3N/CENIMAT,
Department of Materials Science, NOVA School
of Science and Technology and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
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Merces L, Ferro LMM, Nawaz A, Sonar P. Advanced Neuromorphic Applications Enabled by Synaptic Ion-Gating Vertical Transistors. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2305611. [PMID: 38757653 PMCID: PMC11251569 DOI: 10.1002/advs.202305611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 12/07/2023] [Indexed: 05/18/2024]
Abstract
Bioinspired synaptic devices have shown great potential in artificial intelligence and neuromorphic electronics. Low energy consumption, multi-modal sensing and recording, and multifunctional integration are critical aspects limiting their applications. Recently, a new synaptic device architecture, the ion-gating vertical transistor (IGVT), has been successfully realized and timely applied to perform brain-like perception, such as artificial vision, touch, taste, and hearing. In this short time, IGVTs have already achieved faster data processing speeds and more promising memory capabilities than many conventional neuromorphic devices, even while operating at lower voltages and consuming less power. This work focuses on the cutting-edge progress of IGVT technology, from outstanding fabrication strategies to the design and realization of low-voltage multi-sensing IGVTs for artificial-synapse applications. The fundamental concepts of artificial synaptic IGVTs, such as signal processing, transduction, plasticity, and multi-stimulus perception are discussed comprehensively. The contribution draws special attention to the development and optimization of multi-modal flexible sensor technologies and presents a roadmap for future high-end theoretical and experimental advancements in neuromorphic research that are mostly achievable by the synaptic IGVTs.
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Affiliation(s)
- Leandro Merces
- Research Center for MaterialsArchitectures, and Integration of Nanomembranes (MAIN)Chemnitz University of Technology09126ChemnitzGermany
| | - Letícia Mariê Minatogau Ferro
- Research Center for MaterialsArchitectures, and Integration of Nanomembranes (MAIN)Chemnitz University of Technology09126ChemnitzGermany
| | - Ali Nawaz
- Center for Sensors and DevicesBruno Kessler Foundation (FBK)Trento38123Italy
| | - Prashant Sonar
- School of Chemistry and PhysicsQueensland University of Technology (QUT)BrisbaneQLD4000Australia
- Centre for Materials ScienceQueensland University of Technology2 George StreetBrisbaneQLD4000Australia
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4
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Sakib NU, Karim Sadaf MU, Pannone A, Ghosh S, Zheng Y, Ravichandran H, Das S. A Crayfish-Inspired Sensor Fusion Platform for Super Additive Integration of Visual, Chemical, and Tactile Information. NANO LETTERS 2024; 24:6948-6956. [PMID: 38810209 DOI: 10.1021/acs.nanolett.4c01187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
The concept of cross-sensor modulation, wherein one sensor modality can influence another's response, is often overlooked in traditional sensor fusion architectures, leading to missed opportunities for enhancing data accuracy and robustness. In contrast, biological systems, such as aquatic animals like crayfish, demonstrate superior sensor fusion through multisensory integration. These organisms adeptly integrate visual, tactile, and chemical cues to perform tasks such as evading predators and locating prey. Drawing inspiration from this, we propose a neuromorphic platform that integrates graphene-based chemitransistors, monolayer molybdenum disulfide (MoS2) based photosensitive memtransistors, and triboelectric tactile sensors to achieve "Super-Additive" responses to weak chemical, visual, and tactile cues and demonstrate contextual response modulation, also referred to as the "Inverse Effectiveness Effect." We hold the view that integrating bio-inspired sensor fusion principles across various modalities holds promise for a wide range of applications.
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Affiliation(s)
- Najam U Sakib
- Engineering Science and Mechanics, Penn State University, University Park, Pennsylvania 16802, United States
| | - Muhtasim Ul Karim Sadaf
- Engineering Science and Mechanics, Penn State University, University Park, Pennsylvania 16802, United States
| | - Andrew Pannone
- Engineering Science and Mechanics, Penn State University, University Park, Pennsylvania 16802, United States
| | - Subir Ghosh
- Engineering Science and Mechanics, Penn State University, University Park, Pennsylvania 16802, United States
| | - Yikai Zheng
- Engineering Science and Mechanics, Penn State University, University Park, Pennsylvania 16802, United States
| | - Harikrishnan Ravichandran
- Engineering Science and Mechanics, Penn State University, University Park, Pennsylvania 16802, United States
| | - Saptarshi Das
- Engineering Science and Mechanics, Penn State University, University Park, Pennsylvania 16802, United States
- Electrical Engineering, Penn State University, University Park, Pennsylvania 16802, United States
- Materials Science and Engineering, Penn State University, University Park, Pennsylvania 16802, United States
- Materials Research Institute, Penn State University, University Park, Pennsylvania 16802, United States
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Bai C, Wu G, Yang J, Zeng J, Liu Y, Wang J. 2D materials-based photodetectors combined with ferroelectrics. NANOTECHNOLOGY 2024; 35:352001. [PMID: 38697050 DOI: 10.1088/1361-6528/ad4652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 05/01/2024] [Indexed: 05/04/2024]
Abstract
Photodetectors are essential optoelectronic devices that play a critical role in modern technology by converting optical signals into electrical signals, which are one of the most important sensors of the informational devices in current 'Internet of Things' era. Two-dimensional (2D) material-based photodetectors have excellent performance, simple design and effortless fabrication processes, as well as enormous potential for fabricating highly integrated and efficient optoelectronic devices, which has attracted extensive research attention in recent years. The introduction of spontaneous polarization ferroelectric materials further enhances the performance of 2D photodetectors, moreover, companying with the reduction of power consumption. This article reviews the recent advances of materials, devices in ferroelectric-modulated photodetectors. This review starts with the introduce of the basic terms and concepts of the photodetector and various ferroelectric materials applied in 2D photodetectors, then presents a variety of typical device structures, fundamental mechanisms and potential applications under ferroelectric polarization modulation. Finally, we summarize the leading challenges currently confronting ferroelectric-modulated photodetectors and outline their future perspectives.
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Affiliation(s)
- Chongyang Bai
- Key Laboratory of Polar Materials and Devices, Ministry of Education, Department of Electronic Science, East China Normal University, Shanghai 200241, People's Republic of China
| | - Guangjian Wu
- State Key Laboratory of Integrated Chips and Systems, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, People's Republic of China
| | - Jing Yang
- Key Laboratory of Polar Materials and Devices, Ministry of Education, Department of Electronic Science, East China Normal University, Shanghai 200241, People's Republic of China
- Chongqing Key Laboratory of Precision Optics, Chongqing Institute of East China Normal University, Chongqing 401120, People's Republic of China
| | - Jinhua Zeng
- State Key Laboratory of Integrated Chips and Systems, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, People's Republic of China
| | - Yihan Liu
- State Key Laboratory of Integrated Chips and Systems, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, People's Republic of China
| | - Jianlu Wang
- State Key Laboratory of Integrated Chips and Systems, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, People's Republic of China
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Wang Z, Li M, Yang H, Shao S, Li J, Deng M, Kang K, Fang Y, Wang H, Zhao J. Enhancement-Mode Carbon Nanotube Optoelectronic Synaptic Transistors with Large and Controllable Threshold Voltage Modulation Window for Broadband Flexible Vision Systems. ACS NANO 2024; 18:14298-14311. [PMID: 38787538 DOI: 10.1021/acsnano.4c00166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
The development of large-scale integration of optoelectronic neuromorphic devices with ultralow power consumption and broadband responses is essential for high-performance bionics vision systems. In this work, we developed a strategy to construct large-scale (40 × 30) enhancement-mode carbon nanotube optoelectronic synaptic transistors with ultralow power consumption (33.9 aJ per pulse) and broadband responses (from 365 to 620 nm) using low-work function yttrium (Y)-gate electrodes and the mixture of eco-friendly photosensitive Ag2S quantum dots (QDs) and ionic liquids (ILs)-cross-linking-poly(4-vinylphenol) (PVP) (ILs-c-PVP) as the dielectric layers. Solution-processable carbon nanotube thin-film transistors (TFTs) showed enhancement-mode characteristics with the wide and controllable threshold voltage window (-1 V∼0 V) owing to use of the low-work-function Y-gate electrodes. It is noted that carbon nanotube optoelectronic synaptic transistors exhibited high on/off ratios (>106), small hysteresis and low operating voltage (≤2 V), and enhancement mode even under the illumination of ultraviolet (UV, 365 nm), blue (450 nm), and green (550 nm) to red (620 nm) pulse lights when introducing eco-friendly Ag2S QDs in dielectric layers, demonstrating that they have the strong fault-tolerant ability for the threshold voltage drifts caused by various manufacturing scenarios. Furthermore, some important bionic functions including a high paired pulse facilitation index (PPF index, up to 290%), learning and memory function with the long duration (200 s), and rapid recovery (2 s). Pavlov's dog experiment (retention time up to 20 min) and visual memory forgetting experiments (the duration of high current for 180 s) are also demonstrated. Significantly, the optoelectronic synaptic transistors can be used to simulate the adaptive process of vision in varying light conditions, and we demonstrated the dynamic transition of light adaptation to dark adaptation based on light-induced conditional behavior. This work undoubtedly provides valuable insights for the future development of artificial vision systems.
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Affiliation(s)
- Zebin Wang
- Institute of Nano Science and Technology, University of Science and Technology of China, No. 166 Ren Ai Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
- Division of Nanodevices and Related Nanomaterials, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
| | - Min Li
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
- Division of Nanodevices and Related Nanomaterials, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
| | - Hongchao Yang
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
| | - Shuangshuang Shao
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
- Division of Nanodevices and Related Nanomaterials, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
| | - Jiaqi Li
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
- Division of Nanodevices and Related Nanomaterials, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
| | - Meng Deng
- Institute of Nano Science and Technology, University of Science and Technology of China, No. 166 Ren Ai Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
- Division of Nanodevices and Related Nanomaterials, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
| | - Kaixiang Kang
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
- Division of Nanodevices and Related Nanomaterials, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
| | - Yuxiao Fang
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
- Division of Nanodevices and Related Nanomaterials, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
| | - Hua Wang
- Key Laboratory of Interface Science and Engineering in Advanced Materials of Ministry of Education, Taiyuan University of Technology, NO.79, Yingze West Main Street, Taiyuan, Shanxi Province 030024, P.R. China
| | - Jianwen Zhao
- School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
- Division of Nanodevices and Related Nanomaterials, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, No. 398 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu Province 215123, PR China
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Wang J, Ilyas N, Ren Y, Ji Y, Li S, Li C, Liu F, Gu D, Ang KW. Technology and Integration Roadmap for Optoelectronic Memristor. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2307393. [PMID: 37739413 DOI: 10.1002/adma.202307393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/10/2023] [Indexed: 09/24/2023]
Abstract
Optoelectronic memristors (OMs) have emerged as a promising optoelectronic Neuromorphic computing paradigm, opening up new opportunities for neurosynaptic devices and optoelectronic systems. These OMs possess a range of desirable features including minimal crosstalk, high bandwidth, low power consumption, zero latency, and the ability to replicate crucial neurological functions such as vision and optical memory. By incorporating large-scale parallel synaptic structures, OMs are anticipated to greatly enhance high-performance and low-power in-memory computing, effectively overcoming the limitations of the von Neumann bottleneck. However, progress in this field necessitates a comprehensive understanding of suitable structures and techniques for integrating low-dimensional materials into optoelectronic integrated circuit platforms. This review aims to offer a comprehensive overview of the fundamental performance, mechanisms, design of structures, applications, and integration roadmap of optoelectronic synaptic memristors. By establishing connections between materials, multilayer optoelectronic memristor units, and monolithic optoelectronic integrated circuits, this review seeks to provide insights into emerging technologies and future prospects that are expected to drive innovation and widespread adoption in the near future.
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Affiliation(s)
- Jinyong Wang
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Nasir Ilyas
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Yujing Ren
- Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, 117585, Singapore
| | - Yun Ji
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Sifan Li
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Changcun Li
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Fucai Liu
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Deen Gu
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Kah-Wee Ang
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
- Institute of Materials Research and Engineering, A*STAR, Singapore, 138634, Singapore
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Xu Y, Liu D, Dai S, Zhang J, Guo Z, Liu X, Xiong L, Huang J. Stretchable and neuromorphic transistors for pain perception and sensitization emulation. MATERIALS HORIZONS 2024; 11:958-968. [PMID: 38099601 DOI: 10.1039/d3mh01766d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Pain perception nociceptors (PPN), an important type of sensory neuron, are capable of sending out alarm signals when the human body is exposed to destructive stimuli. Simulating the human ability to perceive the external environment and spontaneously avoid injury is a critical function of neural sensing of artificial intelligence devices. The demand for developing artificial PPN has subsequently increased. However, due to the application scenarios of bionic electronic devices such as human skin, electronic prostheses, and robot bodies, where a certain degree of surface deformation constantly occurs, the ideal artificial PPN should have the stretchability to adapt to real scenarios. Here, an organic semiconductor nanofiber artificial pain perception nociceptor (NAPPN) based on a pre-stretching strategy is demonstrated to achieve key pain aspects such as threshold, sensitization, and desensitization. Remarkably, while stretching up to 50%, the synaptic behaviors and injury warning ability of NAPPN can be retained. To verify the wearability of the device, NAPPN was attached to a curved human finger joint, on which PPN behaviors were successfully mimicked. This provides a promising strategy for realizing neural sensing function on either deformed or mobile electronic devices.
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Affiliation(s)
- Yutong Xu
- School of Materials Science and Engineering, Tongji University, Shanghai 201804, P. R. China.
| | - Dapeng Liu
- School of Materials Science and Engineering, Tongji University, Shanghai 201804, P. R. China.
| | - Shilei Dai
- School of Materials Science and Engineering, Tongji University, Shanghai 201804, P. R. China.
| | - Junyao Zhang
- School of Materials Science and Engineering, Tongji University, Shanghai 201804, P. R. China.
| | - Ziyi Guo
- School of Materials Science and Engineering, Tongji University, Shanghai 201804, P. R. China.
| | - Xu Liu
- School of Materials Science and Engineering, Tongji University, Shanghai 201804, P. R. China.
| | - Lize Xiong
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Shanghai Fourth People's Hospital Affiliated to Tongji University, Tongji University, Shanghai, 200434, P. R. China.
| | - Jia Huang
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Shanghai Fourth People's Hospital Affiliated to Tongji University, Tongji University, Shanghai, 200434, P. R. China.
- School of Materials Science and Engineering, Tongji University, Shanghai 201804, P. R. China.
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Zheng Y, Ghosh S, Das S. A Butterfly-Inspired Multisensory Neuromorphic Platform for Integration of Visual and Chemical Cues. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023:e2307380. [PMID: 38069632 DOI: 10.1002/adma.202307380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 11/25/2023] [Indexed: 12/23/2023]
Abstract
Unisensory cues are often insufficient for animals to effectively engage in foraging, mating, and predatory activities. In contrast, integration of cues collected from multiple sensory organs enhances the overall perceptual experience and thereby facilitates better decision-making. Despite the importance of multisensory integration in animals, the field of artificial intelligence (AI) and neuromorphic computing has primarily focused on processing unisensory information. This lack of emphasis on multisensory integration can be attributed to the absence of a miniaturized hardware platform capable of co-locating multiple sensing modalities and enabling in-sensor and near-sensor processing. In this study, this limitation is addressed by utilizing the chemo-sensing properties of graphene and the photo-sensing capability of monolayer molybdenum disulfide (MoS2 ) to create a multisensory platform for visuochemical integration. Additionally, the in-memory-compute capability of MoS2 memtransistors is leveraged to develop neural circuits that facilitate multisensory decision-making. The visuochemical integration platform is inspired by intricate courtship of Heliconius butterflies, where female species rely on the integration of visual cues (such as wing color) and chemical cues (such as pheromones) generated by the male butterflies for mate selection. The butterfly-inspired visuochemical integration platform has significant implications in both robotics and the advancement of neuromorphic computing, going beyond unisensory intelligence and information processing.
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Affiliation(s)
- Yikai Zheng
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
| | - Subir Ghosh
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
| | - Saptarshi Das
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
- Electrical Engineering, Penn State University, University Park, PA, 16802, USA
- Materials Science and Engineering, Penn State University, University Park, PA, 16802, USA
- Materials Research Institute, Penn State University, University Park, PA, 16802, USA
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10
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Li QX, Liu YL, Cao YY, Wang TY, Zhu H, Ji L, Liu WJ, Sun QQ, Zhang DW, Chen L. Ferroelectric artificial synapse for neuromorphic computing and flexible applications. FUNDAMENTAL RESEARCH 2023; 3:960-966. [PMID: 38933007 PMCID: PMC11197568 DOI: 10.1016/j.fmre.2022.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 12/10/2021] [Accepted: 02/09/2022] [Indexed: 10/19/2022] Open
Abstract
Research of artificial synapses is increasing in popularity with the development of bioelectronics and the appearance of wearable devices. Because the high-temperature treatment process of inorganic materials is not compatible with flexible substrates, organic ferroelectric materials that are easier to process have emerged as alternatives. An organic synaptic device based on P(VDF-TrFE) was prepared in this study. The device showed reliable P/E endurance over 104 cycles and a data storage retention capability at 80 °C over 104 s. Simultaneously, it possessed excellent synaptic functions, including short-term/ long-term synaptic plasticity and spike-timing-dependent plasticity. In addition, the ferroelectric performance of the device remained stable even under bending (7 mm bending radius) or after 500 bending cycles. This work shows that low-temperature processed organic ferroelectric materials can provide new ideas for the future development of wearable electronics and flexible artificial synapses.
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Affiliation(s)
- Qing-Xuan Li
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Yi-Lun Liu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Yuan-Yuan Cao
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Tian-Yu Wang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Hao Zhu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No.825 Zhangheng Road, Shanghai 201203, China
| | - Li Ji
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Wen-Jun Liu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - Qing-Qing Sun
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
| | - David Wei Zhang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
- National Integrated Circuit Innovation Center, No.825 Zhangheng Road, Shanghai 201203, China
| | - Lin Chen
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
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11
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Han MJ, Tsukruk VV. Trainable Bilingual Synaptic Functions in Bio-enabled Synaptic Transistors. ACS NANO 2023; 17:18883-18892. [PMID: 37721448 PMCID: PMC10569090 DOI: 10.1021/acsnano.3c04113] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 09/14/2023] [Indexed: 09/19/2023]
Abstract
The signal transmission of the nervous system is regulated by neurotransmitters. Depending on the type of neurotransmitter released by presynaptic neurons, neuron cells can either be excited or inhibited. Maintaining a balance between excitatory and inhibitory synaptic responses is crucial for the nervous system's versatility, elasticity, and ability to perform parallel computing. On the way to mimic the brain's versatility and plasticity traits, creating a preprogrammed balance between excitatory and inhibitory responses is required. Despite substantial efforts to investigate the balancing of the nervous system, a complex circuit configuration has been suggested to simulate the interaction between excitatory and inhibitory synapses. As a meaningful approach, an optoelectronic synapse for balancing the excitatory and inhibitory responses assisted by light mediation is proposed here by deploying humidity-sensitive chiral nematic phases of known polysaccharide cellulose nanocrystals. The environment-induced pitch tuning changes the polarization of the helicoidal organization, affording different hysteresis effects with the subsequent excitatory and inhibitory nonvolatile behavior in the bio-electrolyte-gated transistors. By applying voltage pulses combined with stimulation of chiral light, the artificial optoelectronic synapse tunes not only synaptic functions but also learning pathways and color recognition. These multifunctional bio-based synaptic field-effect transistors exhibit potential for enhanced parallel neuromorphic computing and robot vision technology.
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Affiliation(s)
- Moon Jong Han
- Department
of Electronic Engineering, Gachon University, Seongnam 13120, Republic of Korea
| | - Vladimir V. Tsukruk
- School
of Materials Science and Engineering, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
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12
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Sadaf MUK, Sakib NU, Pannone A, Ravichandran H, Das S. A bio-inspired visuotactile neuron for multisensory integration. Nat Commun 2023; 14:5729. [PMID: 37714853 PMCID: PMC10504285 DOI: 10.1038/s41467-023-40686-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 08/03/2023] [Indexed: 09/17/2023] Open
Abstract
Multisensory integration is a salient feature of the brain which enables better and faster responses in comparison to unisensory integration, especially when the unisensory cues are weak. Specialized neurons that receive convergent input from two or more sensory modalities are responsible for such multisensory integration. Solid-state devices that can emulate the response of these multisensory neurons can advance neuromorphic computing and bridge the gap between artificial and natural intelligence. Here, we introduce an artificial visuotactile neuron based on the integration of a photosensitive monolayer MoS2 memtransistor and a triboelectric tactile sensor which minutely captures the three essential features of multisensory integration, namely, super-additive response, inverse effectiveness effect, and temporal congruency. We have also realized a circuit which can encode visuotactile information into digital spiking events, with probability of spiking determined by the strength of the visual and tactile cues. We believe that our comprehensive demonstration of bio-inspired and multisensory visuotactile neuron and spike encoding circuitry will advance the field of neuromorphic computing, which has thus far primarily focused on unisensory intelligence and information processing.
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Affiliation(s)
| | - Najam U Sakib
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
| | - Andrew Pannone
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
| | | | - Saptarshi Das
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA.
- Electrical Engineering, Penn State University, University Park, PA, 16802, USA.
- Materials Science and Engineering, Penn State University, University Park, PA, 16802, USA.
- Materials Research Institute, Penn State University, University Park, PA, 16802, USA.
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13
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Ju D, Kim S, Jang J, Kim S. Improved Uniformity of TaO x-Based Resistive Switching Memory Device by Inserting Thin SiO 2 Layer for Neuromorphic System. MATERIALS (BASEL, SWITZERLAND) 2023; 16:6136. [PMID: 37763413 PMCID: PMC10532643 DOI: 10.3390/ma16186136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 08/31/2023] [Accepted: 09/06/2023] [Indexed: 09/29/2023]
Abstract
RRAM devices operating based on the creation of conductive filaments via the migration of oxygen vacancies are widely studied as promising candidates for next-generation memory devices due to their superior memory characteristics. However, the issues of variation in the resistance state and operating voltage remain key issues that must be addressed. In this study, we propose a TaOx/SiO2 bilayer device, where the inserted SiO2 layer localizes the conductive path, improving uniformity during cycle-to-cycle endurance and retention. Transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS) confirm the device structure and chemical properties. In addition, various electric pulses are used to investigate the neuromorphic system properties of the device, revealing its good potential for future memory device applications.
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Affiliation(s)
| | | | | | - Sungjun Kim
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea
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14
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Vats G, Hodges B, Ferguson AJ, Wheeler LM, Blackburn JL. Optical Memory, Switching, and Neuromorphic Functionality in Metal Halide Perovskite Materials and Devices. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2205459. [PMID: 36120918 DOI: 10.1002/adma.202205459] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 08/20/2022] [Indexed: 06/15/2023]
Abstract
Metal halide perovskite based materials have emerged over the past few decades as remarkable solution-processable optoelectronic materials with many intriguing properties and potential applications. These emerging materials have recently been considered for their promise in low-energy memory and information processing applications. In particular, their large optical cross-sections, high photoconductance contrast, large carrier-diffusion lengths, and mixed electronic/ionic transport mechanisms are attractive for enabling memory elements and neuromorphic devices that are written and/or read in the optical domain. Here, recent progress toward memory and neuromorphic functionality in metal halide perovskite materials and devices where photons are used as a critical degree of freedom for switching, memory, and neuromorphic functionality is reviewed.
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Affiliation(s)
- Gaurav Vats
- National Renewable Energy Laboratory, Golden, CO, 80401, USA
- Department of Physics and Astronomy, Katholieke Universiteit Leuven, Celestijnenlaan 200D, Leuven, B-3001, Belgium
| | - Brett Hodges
- National Renewable Energy Laboratory, Golden, CO, 80401, USA
| | | | - Lance M Wheeler
- National Renewable Energy Laboratory, Golden, CO, 80401, USA
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15
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Su J, Li Y, Xie D, Jiang J. Vertical 0.6 V sub-10 nm oxide-homojunction transistor gated by a silk fibroin/sodium alginate crosslinking hydrogel for pain-sensitization enhancement emulation. MATERIALS HORIZONS 2023; 10:1745-1756. [PMID: 36809465 DOI: 10.1039/d2mh01431a] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
The sensory nervous system of humans mainly depends on continuous training and memory to improve the pain-perceptional abilities for the complex noxious information in the real world and make appropriate responses. Unfortunately, the solid-state device for emulating this pain recognition with ultralow voltage operation still remains to be a great challenge. Herein, a vertical transistor with an ultrashort channel of ∼9.6 nm and ultralow voltage of ∼0.6 V based on protonic silk fibroin/sodium alginate crosslinking hydrogel electrolyte is successfully demonstrated. Such a hydrogel electrolyte with high ionic conductivity allows the transistor to work in an ultralow voltage, while the vertical transistor structure makes it have an ultrashort channel. Pain perception, memory, and sensitization can be integrated into this vertical transistor. Furthermore, using the photogating effect of light stimulus, the device displays multi-state pain-sensitization enhancement abilities through Pavlovian training. Most importantly, the cortical reorganization that reveals a close relationship among the pain stimulus, memory, and sensitization is finally realized. Therefore, this device can provide a great opportunity for multi-dimensional pain assessment, which is of great significance for the new generation of bio-inspired intelligent electronics, such as bionic robots, and smart medical equipment.
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Affiliation(s)
- Jingya Su
- Hunan Key Laboratory of Nanophotonics and Devices, Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, China.
| | - Yanran Li
- Hunan Key Laboratory of Nanophotonics and Devices, Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, China.
| | - Dingdong Xie
- Hunan Key Laboratory of Nanophotonics and Devices, Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, China.
| | - Jie Jiang
- Hunan Key Laboratory of Nanophotonics and Devices, Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, China.
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16
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Wang X, Yang H, Li E, Cao C, Zheng W, Chen H, Li W. Stretchable Transistor-Structured Artificial Synapses for Neuromorphic Electronics. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 19:e2205395. [PMID: 36748849 DOI: 10.1002/smll.202205395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 01/12/2023] [Indexed: 05/04/2023]
Abstract
Stretchable synaptic transistors, a core technology in neuromorphic electronics, have functions and structures similar to biological synapses and can concurrently transmit signals and learn. Stretchable synaptic transistors are usually soft and stretchy and can accommodate various mechanical deformations, which presents significant prospects in soft machines, electronic skin, human-brain interfaces, and wearable electronics. Considerable efforts have been devoted to developing stretchable synaptic transistors to implement electronic device neuromorphic functions, and remarkable advances have been achieved. Here, this review introduces the basic concept of artificial synaptic transistors and summarizes the recent progress in device structures, functional-layer materials, and fabrication processes. Classical stretchable synaptic transistors, including electric double-layer synaptic transistors, electrochemical synaptic transistors, and optoelectronic synaptic transistors, as well as the applications of stretchable synaptic transistors in light-sensory systems, tactile-sensory systems, and multisensory artificial-nerves systems, are discussed. Finally, the current challenges and potential directions of stretchable synaptic transistors are analyzed. This review presents a detailed introduction to the recent progress in stretchable synaptic transistors from basic concept to applications, providing a reference for the development of stretchable synaptic transistors in the future.
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Affiliation(s)
- Xiumei Wang
- School of Science, Anhui Agricultural University, Hefei, 230036, China
| | - Huihuang Yang
- School of Science, Anhui Agricultural University, Hefei, 230036, China
| | - Enlong Li
- Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception, Institute of Optoelectronics, Department of Materials Science, Fudan University, Shanghai, 200433, China
| | - Chunbin Cao
- School of Science, Anhui Agricultural University, Hefei, 230036, China
| | - Wen Zheng
- School of Science, Anhui Agricultural University, Hefei, 230036, China
- School of Information & Computer, Anhui Agricultural University, Hefei, 230036, China
| | - Huipeng Chen
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou, 350002, China
- Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou, 350100, China
| | - Wenwu Li
- Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception, Institute of Optoelectronics, Department of Materials Science, Fudan University, Shanghai, 200433, China
- National Key Laboratory of Integrated Circuit Chips and Systems, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, China
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17
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Zhang ZC, Chen XD, Lu TB. Recent progress in neuromorphic and memory devices based on graphdiyne. SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS 2023; 24:2196240. [PMID: 37090847 PMCID: PMC10116926 DOI: 10.1080/14686996.2023.2196240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/20/2023] [Accepted: 03/24/2023] [Indexed: 05/03/2023]
Abstract
Graphdiyne (GDY) is an emerging two-dimensional carbon allotrope featuring a direct bandgap and fascinating physical and chemical properties, and it has demonstrated its promising potential in applications of catalysis, energy conversion and storage, electrical/optoelectronic devices, etc. In particular, the recent breakthrough in the synthesis of large-area, high-quality and ultrathin GDY films provides a feasible approach to developing high-performance electrical devices based on GDY. Recently, various GDY-based electrical and optoelectronic devices including multibit optoelectronic memories, ultrafast nonvolatile memories, artificial synapses and memristors have been proposed, in which GDY plays a crucial role. It is essential to summarize the recent breakthrough of GDY in device applications as a guidance, especially considering that the existing GDY-related reviews mainly focus on the applications in catalysis and energy-related fields. Herein, we review GDY-based novel memory and neuromorphic devices and their applications in neuromorphic computing and artificial visual systems. This review will provide an insight into the design and preparation of GDY-based devices and broaden the application fields of GDY.
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Affiliation(s)
- Zhi-Cheng Zhang
- The Key Laboratory of Weak Light Nonlinear Photonics, Ministry of Education, School of Physics, Nankai University, Tianjin, China
| | - Xu-Dong Chen
- The Key Laboratory of Weak Light Nonlinear Photonics, Ministry of Education, School of Physics, Nankai University, Tianjin, China
- MOE International Joint Laboratory of Materials Microstructure, Institute for New Energy Materials and Low Carbon Technologies, School of Material Science and Engineering, Tianjin University of Technology, Tianjin, China
| | - Tong-Bu Lu
- MOE International Joint Laboratory of Materials Microstructure, Institute for New Energy Materials and Low Carbon Technologies, School of Material Science and Engineering, Tianjin University of Technology, Tianjin, China
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18
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Zhang Y, Huang Z, Jiang J. Emerging photoelectric devices for neuromorphic vision applications: principles, developments, and outlooks. SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS 2023; 24:2186689. [PMID: 37007672 PMCID: PMC10054230 DOI: 10.1080/14686996.2023.2186689] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 02/16/2023] [Accepted: 02/28/2023] [Indexed: 06/19/2023]
Abstract
The traditional von Neumann architecture is gradually failing to meet the urgent need for highly parallel computing, high-efficiency, and ultra-low power consumption for the current explosion of data. Brain-inspired neuromorphic computing can break the inherent limitations of traditional computers. Neuromorphic devices are the key hardware units of neuromorphic chips to implement the intelligent computing. In recent years, the development of optogenetics and photosensitive materials has provided new avenues for the research of neuromorphic devices. The emerging optoelectronic neuromorphic devices have received a lot of attentions because they have shown great potential in the field of visual bionics. In this paper, we summarize the latest visual bionic applications of optoelectronic synaptic memristors and transistors based on different photosensitive materials. The basic principle of bio-vision formation is first introduced. Then the device structures and operating mechanisms of optoelectronic memristors and transistors are discussed. Most importantly, the recent progresses of optoelectronic synaptic devices based on various photosensitive materials in the fields of visual perception are described. Finally, the problems and challenges of optoelectronic neuromorphic devices are summarized, and the future development of visual bionics is also proposed.
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Affiliation(s)
- Yi Zhang
- Hunan Key Laboratory of Nanophotonics and Devices, Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, China
| | - Zhuohui Huang
- Hunan Key Laboratory of Nanophotonics and Devices, Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, China
| | - Jie Jiang
- Hunan Key Laboratory of Nanophotonics and Devices, Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, China
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19
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Jeon DY, Park J, Park SJ, Kim GT. Junctionless Electric-Double-Layer MoS 2 Field-Effect Transistor with a Sub-5 nm Thick Electrostatically Highly Doped Channel. ACS APPLIED MATERIALS & INTERFACES 2023; 15:8298-8304. [PMID: 36740775 DOI: 10.1021/acsami.2c19596] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Junctionless transistors are suitable for sub-3 nm applications because of their extremely simple structure and high electrical performance, which compensate for short-channel effects. Two-dimensional semiconductor transition-metal dichalcogenide materials, such as MoS2, may also resolve technical and fundamental issues for Si-based technology. Here, we present the first junctionless electric-double-layer field-effect transistor with an electrostatically highly doped 5 nm thick MoS2 channel. A double-gated MoS2 transistor with an ionic-liquid top gate and a conventional bottom gate demonstrated good transfer characteristics with a 104 on-off current ratio, a 70 mV dec-1 subthreshold swing at a 0 V bottom-gate bias, and drain-current versus top-gate-voltage characteristics were shifted left significantly with increasing bottom-gate bias due to an electrostatically increased overall charge carrier concentration in the MoS2 channel. When a bottom-gate bias of 80 V was applied, a shoulder and two clear peak features were identified in the transconductance and its derivative, respectively; this outcome is typical of Si-based junctionless transistors. Furthermore, the decrease in electron mobility induced by a transverse electric field was reduced with increasing bottom-gate bias. Numerical simulations and analytical models were used to support these findings, which clarify the operation of junctionless MoS2 transistors with an electrostatically highly doped channel.
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Affiliation(s)
- Dae-Young Jeon
- Institute of Advanced Composite Materials, Korea Institute of Science and Technology, Joellabuk-do55324, South Korea
- Department of Electrical Engineering, Gyeongsang National University, Jinju52828, Gyeongnam, South Korea
| | - Jimin Park
- Institute of Advanced Composite Materials, Korea Institute of Science and Technology, Joellabuk-do55324, South Korea
| | - So Jeong Park
- School of Electrical Engineering, Korea University, Seoul136-701, South Korea
| | - Gyu-Tae Kim
- School of Electrical Engineering, Korea University, Seoul136-701, South Korea
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20
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Subbulakshmi Radhakrishnan S, Chakrabarti S, Sen D, Das M, Schranghamer TF, Sebastian A, Das S. A Sparse and Spike-Timing-Based Adaptive Photoencoder for Augmenting Machine Vision for Spiking Neural Networks. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2202535. [PMID: 35674268 DOI: 10.1002/adma.202202535] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/31/2022] [Indexed: 06/15/2023]
Abstract
The representation of external stimuli in the form of action potentials or spikes constitutes the basis of energy efficient neural computation that emerging spiking neural networks (SNNs) aspire to imitate. With recent evidence suggesting that information in the brain is more often represented by explicit firing times of the neurons rather than mean firing rates, it is imperative to develop novel hardware that can accelerate sparse and spike-timing-based encoding. Here a medium-scale integrated circuit composed of two cascaded three-stage inverters and one XOR logic gate fabricated using a total of 21 memtransistors based on photosensitive 2D monolayer MoS2 for spike-timing-based encoding of visual information, is introduced. It is shown that different illumination intensities can be encoded into sparse spiking with time-to-first-spike representing the illumination information, that is, higher intensities invoke earlier spikes and vice versa. In addition, non-volatile and analog programmability in the photoencoder is exploited for adaptive photoencoding that allows expedited spiking under scotopic (low-light) and deferred spiking under photopic (bright-light) conditions, respectively. Finally, low energy expenditure of less than 1 µJ by the 2D-memtransistor-based photoencoder highlights the benefits of in-sensor and bioinspired design that can be transformative for the acceleration of SNNs.
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Affiliation(s)
| | - Shakya Chakrabarti
- Electrical Engineering and Computer Science, Penn State University, University Park, PA, 16802, USA
| | - Dipanjan Sen
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
| | - Mayukh Das
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
| | - Thomas F Schranghamer
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
| | - Amritanand Sebastian
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
| | - Saptarshi Das
- Engineering Science and Mechanics, Penn State University, University Park, PA, 16802, USA
- Electrical Engineering and Computer Science, Penn State University, University Park, PA, 16802, USA
- Materials Science and Engineering, Penn State University, University Park, PA, 16802, USA
- Materials Research Institute, Penn State University, University Park, PA, 16802, USA
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21
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Shen R, Jiang Y, Li Z, Tian J, Li S, Li T, Chen Q. Near-Infrared Artificial Optical Synapse Based on the P(VDF-TrFE)-Coated InAs Nanowire Field-Effect Transistor. MATERIALS (BASEL, SWITZERLAND) 2022; 15:8247. [PMID: 36431733 PMCID: PMC9698720 DOI: 10.3390/ma15228247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/27/2022] [Accepted: 11/08/2022] [Indexed: 06/16/2023]
Abstract
Optical synapse is the basic component for optical neuromorphic computing and is attracting great attention, mainly due to its great potential in many fields, such as image recognition, artificial intelligence and artificial visual perception systems. However, optical synapse with infrared (IR) response has rarely been reported. InAs nanowires (NWs) have a direct narrow bandgap and a large surface to volume ratio, making them a promising material for IR detection. Here, we demonstrate a near-infrared (NIR) (750 to 1550 nm) optical synapse for the first time based on a poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE))-coated InAs NW field-effect transistor (FET). The responsivity of the P(VDF-TrFE)-coated InAs NW FET reaches 839.3 A/W under 750 nm laser illumination, demonstrating the advantage of P(VDF-TrFE) coverage. The P(VDF-TrFE)-coated InAs NW device exhibits optical synaptic behaviors in response to NIR light pulses, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF) and a transformation from short-term plasticity (STP) to long-term plasticity (LTP). The working mechanism is attributed to the polarization effect in the ferroelectric P(VDF-TrFE) layer, which dominates the trapping and de-trapping characteristics of photogenerated holes. These findings have significant implications for the development of artificial neural networks.
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Affiliation(s)
- Rui Shen
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
| | - Yifan Jiang
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
| | - Zhiwei Li
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
| | - Jiamin Tian
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
| | - Shuo Li
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
| | - Tong Li
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Qing Chen
- Key Laboratory for the Physics and Chemistry of Nanodevices, School of Electronics, Peking University, Beijing 100871, China
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22
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Programmable ferroelectric bionic vision hardware with selective attention for high-precision image classification. Nat Commun 2022; 13:7019. [PMID: 36384983 PMCID: PMC9669032 DOI: 10.1038/s41467-022-34565-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Accepted: 10/28/2022] [Indexed: 11/18/2022] Open
Abstract
Selective attention is an efficient processing strategy to allocate computational resources for pivotal optical information. However, the hardware implementation of selective visual attention in conventional intelligent system is usually bulky and complex along with high computational cost. Here, programmable ferroelectric bionic vision hardware to emulate the selective attention is proposed. The tunneling effect of photogenerated carriers are controlled by dynamic variation of energy barrier, enabling the modulation of memory strength from 9.1% to 47.1% without peripheral storage unit. The molecular polarization of ferroelectric P(VDF-TrFE) layer enables a single device not only multiple nonvolatile states but also the implementation of selective attention. With these ferroelectric devices are arrayed together, UV light information can be selectively recorded and suppressed the with high current decibel level. Furthermore, the device with positive polarization exhibits high wavelength dependence in the image attention processing, and the fabricated ferroelectric sensory network exhibits high accuracy of 95.7% in the pattern classification for multi-wavelength images. This study can enrich the neuromorphic functions of bioinspired sensing devices and pave the way for profound implications of future bioinspired optoelectronics.
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23
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Cho KG, Seol KH, Kim MS, Hong K, Lee KH. Tuning Threshold Voltage of Electrolyte-Gated Transistors by Binary Ion Doping. ACS APPLIED MATERIALS & INTERFACES 2022; 14:50004-50012. [PMID: 36301020 DOI: 10.1021/acsami.2c15229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Electrolyte-gated transistors (EGTs) operating at low voltages have attracted significant attention in widespread applications, including neuromorphic devices, nonvolatile memories, chemical/biosensors, and printed electronics. To increase the practicality of the EGTs in electronic circuits, systematic control of threshold voltage (Vth), which determines the power consumption and noise margin of the circuits, is essential. In this study, we present a simple strategy for systematically tuning Vth to almost half of the operating potential range of the EGT by controlling the electrochemical doping of electrolyte ions into organic p-type semiconductors. The type of anion in the ionogel determines Vth as well as other transistor characteristics, such as the subthreshold swing and mobility, because the positive hole carriers are the majority carriers. More importantly, Vth can be finely controlled by binary anion doping using ionogels with two anions with varying molar fractions at a fixed cation. In addition, the binary anion doping successfully controls the inversion characteristics of ion-gated inverters. As unlimited combinations of ion pairs are possible for ionogels, this study opens a route for controlling the device characteristics to expand the practicality and applicability of ionogel-based EGTs for next-generation ionic/electronic devices.
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Affiliation(s)
- Kyung Gook Cho
- Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon22212, Republic of Korea
| | - Kyoung Hwan Seol
- Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon22212, Republic of Korea
| | - Min Su Kim
- Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon22212, Republic of Korea
| | - Kihyon Hong
- Department of Materials Science and Engineering, Chungnam National University (CNU), Daejeon34134, Republic of Korea
| | - Keun Hyung Lee
- Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon22212, Republic of Korea
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24
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Yang R, Yin L, Lu J, Lu B, Pi X, Li S, Zhuge F, Lu Y, Shao W, Ye Z. Optoelectronic Artificial Synaptic Device Based on Amorphous InAlZnO Films for Learning Simulations. ACS APPLIED MATERIALS & INTERFACES 2022; 14:46866-46875. [PMID: 36194768 DOI: 10.1021/acsami.2c14029] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Neuromorphic computing, which mimics brain function, can address the shortcomings of the "von Neumann" system and is one of the critical components of next-generation computing. The use of light to stimulate artificial synapses has the advantages of low power consumption, low latency, and high stability. We demonstrate amorphous InAlZnO-based light-stimulated artificial synaptic devices with a thin-film transistor structure. The devices exhibit fundamental synaptic properties, including excitatory postsynaptic current, paired-pulse facilitation (PPF), and short-term plasticity to long-term plasticity conversion under light stimulation. The PPF index stimulated by 375 nm light is 155.9% when the time interval is 0.1 s. The energy consumption of each synaptic event is 2.3 pJ, much lower than that of ordinary MOS devices and other optical-controlled synaptic devices. The relaxation time constant reaches 277 s after only 10 light spikes, which shows the great synaptic plasticity of the device. In addition, we simulated the learning-forgetting-relearning-forgetting behavior and learning efficiency of human beings under different moods by changing the gate voltage. This work is expected to promote the development of high-performance optoelectronic synaptic devices for neuromorphic computing.
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Affiliation(s)
- Ruqi Yang
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China
| | - Lei Yin
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China
| | - Jianguo Lu
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China
- Wenzhou Key Laboratory of Novel Optoelectronic and Nano Materials, Institute of Wenzhoum, Zhejiang University, Wenzhou325006, China
| | - Bojing Lu
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China
| | - Xiaodong Pi
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China
| | - Siqin Li
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China
| | - Fei Zhuge
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo315201, China
| | - Yangdan Lu
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China
| | - Wenyi Shao
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China
| | - Zhizhen Ye
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou310027, China
- Wenzhou Key Laboratory of Novel Optoelectronic and Nano Materials, Institute of Wenzhoum, Zhejiang University, Wenzhou325006, China
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25
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Mahata C, Park J, Ismail M, Kim DH, Kim S. Improved Resistive Switching with Low-Power Synaptic Behaviors of ZnO/Al 2O 3 Bilayer Structure. MATERIALS (BASEL, SWITZERLAND) 2022; 15:6663. [PMID: 36234005 PMCID: PMC9572464 DOI: 10.3390/ma15196663] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 06/16/2023]
Abstract
In this work, the resistive switching behavior of bilayer ZnO/Al2O3-based resistive-switching random access memory (RRAM) devices is demonstrated. The polycrystalline nature of the ZnO layer confirms the grain boundary, which helps easy oxygen ion diffusion. Multilevel resistance states were modulated under DC bias by varying the current compliance from 0.1 mA to 0.8 mA, the SET operations where the low resistance state of the memristor device was reduced from 25 kΩ to 2.4 kΩ. The presence of Al2O3 acts as a redox layer and facilitates oxygen vacancy exchange that demonstrates stable gradual conductance change. Stepwise disruption of conductive filaments was monitored depending on the slow DC voltage sweep rate. This is attributed to the atomic scale modulation of oxygen vacancies with four distinct reproducible quantized conductance states, which shows multilevel data storage capability. Moreover, several crucial synaptic properties such as potentiation/depression under identical presynaptic pulses and the spike-rate-dependent plasticity were implemented on ITO/ZnO/Al2O3/TaN memristor. The postsynaptic current change was monitored defining the long-term potentiation by increasing the presynaptic stimulus frequency from 5 Hz to 100 Hz. Moreover, the repetitive pulse voltage stimulation transformed the short-term plasticity to long-term plasticity during spike-number-dependent plasticity.
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Affiliation(s)
- Chandreswar Mahata
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Korea
| | - Jongmin Park
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Korea
| | - Muhammad Ismail
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Korea
| | - Dae Hwan Kim
- School of Electrical Engineering, Kookmin University, Seoul 02707, Korea
| | - Sungjun Kim
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Korea
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26
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Wang C, Xu X, Pi X, Butala MD, Huang W, Yin L, Peng W, Ali M, Bodepudi SC, Qiao X, Xu Y, Sun W, Yang D. Neuromorphic device based on silicon nanosheets. Nat Commun 2022; 13:5216. [PMID: 36064545 PMCID: PMC9445003 DOI: 10.1038/s41467-022-32884-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 08/22/2022] [Indexed: 11/09/2022] Open
Abstract
Silicon is vital for its high abundance, vast production, and perfect compatibility with the well-established CMOS processing industry. Recently, artificially stacked layered 2D structures have gained tremendous attention via fine-tuning properties for electronic devices. This article presents neuromorphic devices based on silicon nanosheets that are chemically exfoliated and surface-modified, enabling self-assembly into hierarchical stacking structures. The device functionality can be switched between a unipolar memristor and a feasibly reset-able synaptic device. The memory function of the device is based on the charge storage in the partially oxidized SiNS stacks followed by the discharge activated by the electric field at the Au-Si Schottky interface, as verified in both experimental and theoretical means. This work further inspired elegant neuromorphic computation models for digit recognition and noise filtration. Ultimately, it brings silicon - the most established semiconductor - back to the forefront for next-generation computations.
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Affiliation(s)
- Chenhao Wang
- State Key Laboratory of Silicon Materials & School of Materials Science and Engineering, Zhejiang University, 310027, Hangzhou, PR China
| | - Xinyi Xu
- ZJU-Hangzhou Global Scientific and Technological Innovation Centre, 310027, Hangzhou, PR China
- State Key Laboratory of Silicon Materials & School of Micro-Nanoelectronics, Zhejiang University, 310027, Hangzhou, PR China
- College of Information Science and Electronics Engineering, Zhejiang University, 310027, Hangzhou, PR China
- ZJU-UIUC Institute (ZJUI), Zhejiang University, 314400, Jiaxing, PR China
| | - Xiaodong Pi
- State Key Laboratory of Silicon Materials & School of Materials Science and Engineering, Zhejiang University, 310027, Hangzhou, PR China
- ZJU-Hangzhou Global Scientific and Technological Innovation Centre, 310027, Hangzhou, PR China
| | - Mark D Butala
- ZJU-UIUC Institute (ZJUI), Zhejiang University, 314400, Jiaxing, PR China
| | - Wen Huang
- New Energy Technology Engineering Laboratory of Jiangsu Provence & School of Science, Nanjing University of Posts and Telecommunications, 210023, Nanjing, PR China
| | - Lei Yin
- State Key Laboratory of Silicon Materials & School of Materials Science and Engineering, Zhejiang University, 310027, Hangzhou, PR China
| | - Wenbing Peng
- State Key Laboratory of Silicon Materials & School of Materials Science and Engineering, Zhejiang University, 310027, Hangzhou, PR China
| | - Munir Ali
- ZJU-Hangzhou Global Scientific and Technological Innovation Centre, 310027, Hangzhou, PR China
- State Key Laboratory of Silicon Materials & School of Micro-Nanoelectronics, Zhejiang University, 310027, Hangzhou, PR China
| | - Srikrishna Chanakya Bodepudi
- ZJU-Hangzhou Global Scientific and Technological Innovation Centre, 310027, Hangzhou, PR China
- State Key Laboratory of Silicon Materials & School of Micro-Nanoelectronics, Zhejiang University, 310027, Hangzhou, PR China
| | - Xvsheng Qiao
- State Key Laboratory of Silicon Materials & School of Materials Science and Engineering, Zhejiang University, 310027, Hangzhou, PR China
| | - Yang Xu
- ZJU-Hangzhou Global Scientific and Technological Innovation Centre, 310027, Hangzhou, PR China.
- State Key Laboratory of Silicon Materials & School of Micro-Nanoelectronics, Zhejiang University, 310027, Hangzhou, PR China.
- College of Information Science and Electronics Engineering, Zhejiang University, 310027, Hangzhou, PR China.
- ZJU-UIUC Institute (ZJUI), Zhejiang University, 314400, Jiaxing, PR China.
| | - Wei Sun
- State Key Laboratory of Silicon Materials & School of Materials Science and Engineering, Zhejiang University, 310027, Hangzhou, PR China.
| | - Deren Yang
- State Key Laboratory of Silicon Materials & School of Materials Science and Engineering, Zhejiang University, 310027, Hangzhou, PR China.
- ZJU-Hangzhou Global Scientific and Technological Innovation Centre, 310027, Hangzhou, PR China.
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27
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Lee Y, Park J, Chung D, Lee K, Kim S. Multi-level Cells and Quantized Conductance Characteristics of Al 2O 3-Based RRAM Device for Neuromorphic System. NANOSCALE RESEARCH LETTERS 2022; 17:84. [PMID: 36057011 PMCID: PMC9440974 DOI: 10.1186/s11671-022-03722-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 08/24/2022] [Indexed: 06/15/2023]
Abstract
Recently, various resistance-based memory devices are being studied to replace charge-based memory devices to satisfy high-performance memory requirements. Resistance random access memory (RRAM) shows superior performances such as fast switching speed, structural scalability, and long retention. This work presented the different filament control by the DC voltages and verified its characteristics as a synaptic device by pulse measurement. Firstly, two current-voltage (I-V) curves are characterized by controlling a range of DC voltages. The retention and endurance for each different I-V curve were measured to prove the reliability of the RRAM device. The detailed voltage manipulation confirmed the characteristics of multi-level cell (MLC) and conductance quantization. Lastly, synaptic functions such as potentiation and depression, paired-pulse depression, excitatory post-synaptic current, and spike-timing-dependent plasticity were verified. Collectively, we concluded that Pt/Al2O3/TaN is appropriate for the neuromorphic device.
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Affiliation(s)
- Yunseok Lee
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul, 04620, Republic of Korea
| | - Jongmin Park
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul, 04620, Republic of Korea
| | - Daewon Chung
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul, 04620, Republic of Korea
| | - Kisong Lee
- Department of Information and Communication Engineering, Dongguk University, Seoul, 04620, Republic of Korea
| | - Sungjun Kim
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul, 04620, Republic of Korea.
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28
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Li Q, Wang T, Fang Y, Hu X, Tang C, Wu X, Zhu H, Ji L, Sun QQ, Zhang DW, Chen L. Ultralow Power Wearable Organic Ferroelectric Device for Optoelectronic Neuromorphic Computing. NANO LETTERS 2022; 22:6435-6443. [PMID: 35737934 DOI: 10.1021/acs.nanolett.2c01768] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In order to imitate brain-inspired biological information processing systems, various neuromorphic computing devices have been proposed, most of which were prepared on rigid substrates and have energy consumption levels several orders of magnitude higher than those of biological synapses (∼10 fJ per spike). Herein, a new type of wearable organic ferroelectric artificial synapse is proposed, which has two modulation modes (optical and electrical modulation). Because of the high photosensitivity of organic semiconductors and the ultrafast polarization switching of ferroelectric materials, the synaptic device has an ultrafast operation speed of 30 ns and an ultralow power consumption of 0.0675 aJ per synaptic event. Under combined photoelectric modulation, the artificial synapse realizes associative learning. The proposed artificial synapse with ultralow power consumption demonstrates good synaptic plasticity under different bending strains. This provides new avenues for the construction of ultralow power artificial intelligence system and the development of future wearable devices.
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Affiliation(s)
- Qingxuan Li
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
| | - Tianyu Wang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Yuqing Fang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
| | - Xuemeng Hu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
| | - Chengkang Tang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
| | - Xiaohan Wu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Hao Zhu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Li Ji
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Qing-Qing Sun
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - David Wei Zhang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
- National Integrated Circuit Innovation Center, Shanghai 201203, China
| | - Lin Chen
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
- National Integrated Circuit Innovation Center, Shanghai 201203, China
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29
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Islam MM, Krishnaprasad A, Dev D, Martinez-Martinez R, Okonkwo V, Wu B, Han SS, Bae TS, Chung HS, Touma J, Jung Y, Roy T. Multiwavelength Optoelectronic Synapse with 2D Materials for Mixed-Color Pattern Recognition. ACS NANO 2022; 16:10188-10198. [PMID: 35612988 DOI: 10.1021/acsnano.2c01035] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Neuromorphic visual systems emulating biological retina functionalities have enormous potential for in-sensor computing, with prospects of making artificial intelligence ubiquitous. Conventionally, visual information is captured by an image sensor, stored by memory units, and eventually processed by the machine learning algorithm. Here, we present an optoelectronic synapse device with multifunctional integration of all the processes required for real time object identification. Ultraviolet-visible wavelength-sensitive MoS2 FET channel with infrared sensitive PtTe2/Si gate electrode enables the device to sense, store, and process optical data for a wide range of the electromagnetic spectrum, while maintaining a low dark current. The device exhibits optical stimulation-controlled short-term and long-term potentiation, electrically driven long-term depression, synaptic weight update for multiple wavelengths of light ranging from 300 nm in ultraviolet to 2 μm in infrared. An artificial neural network developed using the extracted weight update parameters of the device can be trained to identify both single wavelength and mixed wavelength patterns. This work demonstrates a device that could potentially be used for realizing a multiwavelength neuromorphic visual system for pattern recognition and object identification.
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Affiliation(s)
- Molla Manjurul Islam
- NanoScience Technology Center, University of Central Florida, Orlando, Florida 32826, United States
- Department of Physics, University of Central Florida, Orlando, Florida 32816, United States
| | - Adithi Krishnaprasad
- NanoScience Technology Center, University of Central Florida, Orlando, Florida 32826, United States
- Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Florida 32816, United States
| | - Durjoy Dev
- NanoScience Technology Center, University of Central Florida, Orlando, Florida 32826, United States
- Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Florida 32816, United States
| | - Ricardo Martinez-Martinez
- NanoScience Technology Center, University of Central Florida, Orlando, Florida 32826, United States
- Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Florida 32816, United States
| | - Victor Okonkwo
- NanoScience Technology Center, University of Central Florida, Orlando, Florida 32826, United States
| | - Benjamin Wu
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794, United States
| | - Sang Sub Han
- NanoScience Technology Center, University of Central Florida, Orlando, Florida 32826, United States
| | - Tae-Sung Bae
- Analytical Research Division, Korea Basic Science Institute, Jeonju 54907, South Korea
| | - Hee-Suk Chung
- Analytical Research Division, Korea Basic Science Institute, Jeonju 54907, South Korea
| | - Jimmy Touma
- Air Force Research Lab, Eglin Air Force Base, Florida 32542, United States
| | - Yeonwoong Jung
- NanoScience Technology Center, University of Central Florida, Orlando, Florida 32826, United States
- Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Florida 32816, United States
- Department of Materials Science and Engineering, University of Central Florida, Orlando, Florida 32816, United States
| | - Tania Roy
- NanoScience Technology Center, University of Central Florida, Orlando, Florida 32826, United States
- Department of Physics, University of Central Florida, Orlando, Florida 32816, United States
- Department of Electrical and Computer Engineering, University of Central Florida, Orlando, Florida 32816, United States
- Department of Materials Science and Engineering, University of Central Florida, Orlando, Florida 32816, United States
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30
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Xia F, Xia T, Xiang L, Ding S, Li S, Yin Y, Xi M, Jin C, Liang X, Hu Y. Carbon Nanotube-Based Flexible Ferroelectric Synaptic Transistors for Neuromorphic Computing. ACS APPLIED MATERIALS & INTERFACES 2022; 14:30124-30132. [PMID: 35735118 DOI: 10.1021/acsami.2c07825] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Biological nervous systems evolved in nature have marvelous information processing capacities, which have great reference value for modern information technologies. To expand the function of electronic devices with applications in smart health monitoring and treatment, wearable energy-efficient computing, neuroprosthetics, etc., flexible artificial synapses for neuromorphic computing will play a crucial role. Here, carbon nanotube-based ferroelectric synaptic transistors are realized on ultrathin flexible substrates via a low-temperature approach not exceeding 90 °C to grow ferroelectric dielectrics in which the single-pulse, paired-pulse, and repetitive-pulse responses testify to well-mimicked plasticity in artificial synapses. The long-term potentiation and long-term depression processes in the device demonstrate a dynamic range as large as 2000×, and 360 distinguishable conductance states are achieved with a weight increase/decrease nonlinearity of no more than 1 by applying stepped identical pulses. The stability of the device is verified by the almost unchanged performance after the device is kept in ambient conditions without additional passivation for 240 days. An artificial neural network-based simulation is conducted to benchmark the hardware performance of the neuromorphic devices in which a pattern recognition accuracy of 95.24% is achieved.
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Affiliation(s)
- Fan Xia
- Key Laboratory for the Physics and Chemistry of Nanodevices, Center for Carbon-Based Electronics, and School of Electronics, Peking University, Beijing 100871, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Tian Xia
- Key Laboratory for the Physics and Chemistry of Nanodevices, Center for Carbon-Based Electronics, and School of Electronics, Peking University, Beijing 100871, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Li Xiang
- Key Laboratory for the Physics and Chemistry of Nanodevices, Center for Carbon-Based Electronics, and School of Electronics, Peking University, Beijing 100871, China
- College of Materials and Engineering, Hunan University, Changsha 410082, China
| | - Sujuan Ding
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027, China
- Jihua Laboratory, Foshan 528200, Guangdong, China
| | - Shuo Li
- Key Laboratory for the Physics and Chemistry of Nanodevices, Center for Carbon-Based Electronics, and School of Electronics, Peking University, Beijing 100871, China
| | - Yucheng Yin
- Electrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States
| | - Meiqi Xi
- Key Laboratory for the Physics and Chemistry of Nanodevices, Center for Carbon-Based Electronics, and School of Electronics, Peking University, Beijing 100871, China
| | - Chuanhong Jin
- State Key Laboratory of Silicon Materials, School of Materials Science and Engineering, Zhejiang University, Hangzhou 310027, China
- Jihua Laboratory, Foshan 528200, Guangdong, China
| | - Xuelei Liang
- Key Laboratory for the Physics and Chemistry of Nanodevices, Center for Carbon-Based Electronics, and School of Electronics, Peking University, Beijing 100871, China
| | - Youfan Hu
- Key Laboratory for the Physics and Chemistry of Nanodevices, Center for Carbon-Based Electronics, and School of Electronics, Peking University, Beijing 100871, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
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31
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Materials Horizons Emerging Investigator Series: Dr Jie Jiang, Central South University, China. MATERIALS HORIZONS 2022; 9:1330-1331. [PMID: 35470839 DOI: 10.1039/d2mh90027k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Our Emerging Investigator Series features exceptional work by early-career researchers working in the field of materials science.
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32
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Xie D, Yin K, Yang ZJ, Huang H, Li X, Shu Z, Duan H, He J, Jiang J. Polarization-perceptual anisotropic two-dimensional ReS 2 neuro-transistor with reconfigurable neuromorphic vision. MATERIALS HORIZONS 2022; 9:1448-1459. [PMID: 35234765 DOI: 10.1039/d1mh02036f] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Polarization is a common and unique phenomenon in nature, which reveals more camouflage features of objects. However, current polarization-perceptual devices based on conventional physical architectures face enormous challenges for high-performance computation due to the traditional von Neumann bottleneck. In this work, a novel polarization-perceptual neuro-transistor with reconfigurable anisotropic vision is proposed based on a two-dimensional ReS2 phototransistor. The device exhibits excellent photodetection ability and superior polarization sensitivity due to its direct band gap semiconductor property and strong anisotropic crystal structure, respectively. The fascinating polarization-sensitive neuromorphic behavior, such as polarization memory consolidation and reconfigurable visual imaging, are successfully realized. In particular, the regulated polarization responsivity and dichroic ratio are successfully emulated through our artificial compound eyes. More importantly, two intriguing polarization-perceptual applications for polarized navigation with reconfigurable adaptive learning abilities and three-dimensional visual polarization imaging are also experimentally demonstrated. The proposed device may provide a promising opportunity for future polarization perception systems in intelligent humanoid robots and autonomous vehicles.
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Affiliation(s)
- Dingdong Xie
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Kai Yin
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Zhong-Jian Yang
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Han Huang
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Xiaohui Li
- School of Physics and Information Technology, Shanxi Normal University, Xi'an 710119, P. R. China
| | - Zhiwen Shu
- State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, P. R. China
| | - Huigao Duan
- State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, P. R. China
| | - Jun He
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Jie Jiang
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
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33
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Li Y, Yin K, Diao Y, Fang M, Yang J, Zhang J, Cao H, Liu X, Jiang J. A biopolymer-gated ionotronic junctionless oxide transistor array for spatiotemporal pain-perception emulation in nociceptor network. NANOSCALE 2022; 14:2316-2326. [PMID: 35084010 DOI: 10.1039/d1nr07896h] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Capable of reflecting the location and intensity of external harmful stimuli, a nociceptor network is of great importance for receiving pain-perception information. However, the hardware-based implementation of a nociceptor network through the use of a transistor array remains a great challenge in the area of brain-inspired neuromorphic applications. Herein, a simple ionotronic junctionless oxide transistor array with pain-perception abilities is successfully realized due to a coplanar-gate proton-coupling effect in sodium alginate biopolymer electrolyte. Several important pain-perception characteristics of nociceptors are emulated, such as a pain threshold, the memory of prior injury, and sensitization behavior due to pathway alterations. In particular, a good graded pain-perception network system has been successfully established through coplanar capacitance and resistance. More importantly, clear polarity reversal of Lorentz-type spatiotemporal pain-perception emulation can be finally realized in our projection-dependent nociceptor network. This work may provide new avenues for bionic medical machines and humanoid robots based on these intriguing pain-perception abilities.
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Affiliation(s)
- Yanran Li
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Kai Yin
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Yu Diao
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Mei Fang
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Junliang Yang
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Jian Zhang
- School of Material Science and Engineering, Guilin University of Electronic Technology, Guilin, 541004, P. R. China
| | - Hongtao Cao
- Laboratory of Advanced Nano Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China
| | - Xiaoliang Liu
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
| | - Jie Jiang
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China.
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Shen C, Gao X, Chen C, Ren S, Xu JL, Xia YD, Wang SD. ZnO nanowire optoelectronic synapse for neuromorphic computing. NANOTECHNOLOGY 2021; 33:065205. [PMID: 34736234 DOI: 10.1088/1361-6528/ac3687] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 11/04/2021] [Indexed: 06/13/2023]
Abstract
Artificial synapses that integrate functions of sensing, memory and computing are highly desired for developing brain-inspired neuromorphic hardware. In this work, an optoelectronic synapse based on the ZnO nanowire (NW) transistor is achieved, which can be used to emulate both the short-term and long-term synaptic plasticity. Synaptic potentiation is present when the device is stimulated by light pulses, arising from the light-induced O2desorption and the persistent photoconductivity behavior of the ZnO NW. On the other hand, synaptic depression occurs when the device is stimulated by electrical pulses in dark, which is realized by introducing a charge trapping layer in the gate dielectric to trap carriers. Simulation of a neural network utilizing the ZnO NW synapses is carried out, demonstrating a high recognition accuracy over 90% after only 20 training epochs for recognizing the Modified National Institute of Standards and Technology digits. The present nanoscale optoelectronic synapse has great potential in the development of neuromorphic visual systems.
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Affiliation(s)
- Cong Shen
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, People's Republic of China
| | - Xu Gao
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, People's Republic of China
| | - Cheng Chen
- School of Optoelectronic Science and Engineering, Key Laboratory of Advanced Optical Manufacturing Technologies of Jiangsu Province, Soochow University, Suzhou, Jiangsu 215006, People's Republic of China
| | - Shan Ren
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, People's Republic of China
| | - Jian-Long Xu
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, People's Republic of China
| | - Yi-Dong Xia
- Department of Materials Science and Engineering, College of Engineering and Applied Sciences, Nanjing University, Nanjing, Jiangsu 210093, People's Republic of China
| | - Sui-Dong Wang
- Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, People's Republic of China
- Macao Institute of Materials Science and Engineering (MIMSE), Macau University of Science and Technology, Taipa 999078, Macau, People's Republic of China
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35
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Ding G, Yang B, Chen RS, Mo WA, Zhou K, Liu Y, Shang G, Zhai Y, Han ST, Zhou Y. Reconfigurable 2D WSe 2 -Based Memtransistor for Mimicking Homosynaptic and Heterosynaptic Plasticity. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2021; 17:e2103175. [PMID: 34528382 DOI: 10.1002/smll.202103175] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 07/30/2021] [Indexed: 06/13/2023]
Abstract
The mimicking of both homosynaptic and heterosynaptic plasticity using a high-performance synaptic device is important for developing human-brain-like neuromorphic computing systems to overcome the ever-increasing challenges caused by the conventional von Neumann architecture. However, the commonly used synaptic devices (e.g., memristors and transistors) require an extra modulate terminal to mimic heterosynaptic plasticity, and their capability of synaptic plasticity simulation is limited by the low weight adjustability. In this study, a WSe2 -based memtransistor for mimicking both homosynaptic and heterosynaptic plasticity is fabricated. By applying spikes on either the drain or gate terminal, the memtransistor can mimic common homosynaptic plasticity, including spiking rate dependent plasticity, paired pulse facilitation/depression, synaptic potentiation/depression, and filtering. Benefitting from the multi-terminal input and high adjustability, the resistance state number and linearity of the memtransistor can be improved by optimizing the conditions of the two inputs. Moreover, the device can successfully mimic heterosynaptic plasticity without introducing an extra terminal and can simultaneously offer versatile reconfigurability of excitatory and inhibitory plasticity. These highly adjustable and reconfigurable characteristics offer memtransistors more freedom of choice for tuning synaptic weight, optimizing circuit design, and building artificial neuromorphic computing systems.
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Affiliation(s)
- Guanglong Ding
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Baidong Yang
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, P. R. China
- Shenzhen Key Laboratory of Flexible Memory Materials and Devices, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Ruo-Si Chen
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, P. R. China
- Shenzhen Key Laboratory of Flexible Memory Materials and Devices, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Wen-Ai Mo
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, P. R. China
- Shenzhen Key Laboratory of Flexible Memory Materials and Devices, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Kui Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Yang Liu
- Shenzhen Key Laboratory of Flexible Memory Materials and Devices, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Gang Shang
- Shenzhen Key Laboratory of Flexible Memory Materials and Devices, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Yongbiao Zhai
- Shenzhen Key Laboratory of Flexible Memory Materials and Devices, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Su-Ting Han
- Shenzhen Key Laboratory of Flexible Memory Materials and Devices, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Ye Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China
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Yin L, Cheng R, Wen Y, Liu C, He J. Emerging 2D Memory Devices for In-Memory Computing. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2021; 33:e2007081. [PMID: 34105195 DOI: 10.1002/adma.202007081] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Revised: 12/27/2020] [Indexed: 06/12/2023]
Abstract
It is predicted that the conventional von Neumann computing architecture cannot meet the demands of future data-intensive computing applications due to the bottleneck between the processing and memory units. To try to solve this problem, in-memory computing technology, where calculations are carried out in situ within each nonvolatile memory unit, has been intensively studied. Among various candidate materials, 2D layered materials have recently demonstrated many new features that have been uniquely exploited to build next-generation electronics. Here, the recent progress of 2D memory devices is reviewed for in-memory computing. For each memory configuration, their operation mechanisms and memory characteristics are described, and their pros and cons are weighed. Subsequently, their versatile applications for in-memory computing technology, including logic operations, electronic synapses, and random number generation are presented. Finally, the current challenges and potential strategies for future 2D in-memory computing systems are also discussed at the material, device, circuit, and architecture levels. It is hoped that this manuscript could give a comprehensive review of 2D memory devices and their applications in in-memory computing, and be helpful for this exciting research area.
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Affiliation(s)
- Lei Yin
- Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education, and School of Physics and Technology, Wuhan University, Wuhan, 430072, P. R. China
| | - Ruiqing Cheng
- Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education, and School of Physics and Technology, Wuhan University, Wuhan, 430072, P. R. China
| | - Yao Wen
- Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education, and School of Physics and Technology, Wuhan University, Wuhan, 430072, P. R. China
| | - Chuansheng Liu
- Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education, and School of Physics and Technology, Wuhan University, Wuhan, 430072, P. R. China
| | - Jun He
- Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education, and School of Physics and Technology, Wuhan University, Wuhan, 430072, P. R. China
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37
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Li E, He W, Yu R, He L, Wu X, Chen Q, Liu Y, Chen H, Guo T. High-Density Reconfigurable Synaptic Transistors Targeting a Minimalist Neural Network. ACS APPLIED MATERIALS & INTERFACES 2021; 13:28564-28573. [PMID: 34100580 DOI: 10.1021/acsami.1c05484] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Enormous synaptic devices are required to build a parallel, precise, and efficient neural computing system. To further improve the energy efficiency of neuromorphic computing, a single high-density synaptic (HDS) device with multiple nonvolatile synaptic states is suggested to reduce the number of synaptic devices in the neural network, although such a powerful synaptic device is rarely demonstrated. Here, a photoisomerism material, namely, diarylethene, whose energy level varies with the wavelength of illumination is first introduced to construct a powerful HDS device. The multiple synaptic states of the HDS device are intrinsically converted under UV-vis regulation and remain nonvolatile after the removal of illumination. More importantly, the conversion is reconfigurable and reversible under different light conditions, and the synaptic characteristics are comprehensively mimicked in each state. Finally, compared with a two-layer multilayer perceptron (MLP) architecture based on static synaptic devices, the HDS device-based architecture reduces the device number by 16 times to achieve a minimalist neural computing structure. The invention of the HDS device opens up a revolutionary paradigm for the establishment of a brain-like network.
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Affiliation(s)
- Enlong Li
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
- Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou 350100, China
| | - Weixin He
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
| | - Rengjian Yu
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
| | - Lihua He
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
| | - Xiaomin Wu
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
| | - Qizhen Chen
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
| | - Yuan Liu
- State Key Laboratory for Chemo/Biosensing and Chemometrics, School of Physics and Electronics, Hunan University, Changsha 410082, China
| | - Huipeng Chen
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
- Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou 350100, China
| | - Tailiang Guo
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
- Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou 350100, China
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38
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Lee G, Baek JH, Ren F, Pearton SJ, Lee GH, Kim J. Artificial Neuron and Synapse Devices Based on 2D Materials. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2021; 17:e2100640. [PMID: 33817985 DOI: 10.1002/smll.202100640] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 03/05/2021] [Indexed: 06/12/2023]
Abstract
Neuromorphic systems, which emulate neural functionalities of a human brain, are considered to be an attractive next-generation computing approach, with advantages of high energy efficiency and fast computing speed. After these neuromorphic systems are proposed, it is demonstrated that artificial synapses and neurons can mimic neural functions of biological synapses and neurons. However, since the neuromorphic functionalities are highly related to the surface properties of materials, bulk material-based neuromorphic devices suffer from uncontrollable defects at surfaces and strong scattering caused by dangling bonds. Therefore, 2D materials which have dangling-bond-free surfaces and excellent crystallinity have emerged as promising candidates for neuromorphic computing hardware. First, the fundamental synaptic behavior is reviewed, such as synaptic plasticity and learning rule, and requirements of artificial synapses to emulate biological synapses. In addition, an overview of recent advances on 2D materials-based synaptic devices is summarized by categorizing these into various working principles of artificial synapses. Second, the compulsory behavior and requirements of artificial neurons such as the all-or-nothing law and refractory periods to simulate a spike neural network are described, and the implementation of 2D materials-based artificial neurons to date is reviewed. Finally, future challenges and outlooks of 2D materials-based neuromorphic devices are discussed.
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Affiliation(s)
- Geonyeop Lee
- Department of Chemical and Biological Engineering, Korea University, Seoul, 02841, Korea
| | - Ji-Hwan Baek
- Department of Material Science and Engineering, Seoul National University, Seoul, 08826, Korea
| | - Fan Ren
- Department of Chemical Engineering, University of Florida, Gainesville, FL, 32611, USA
| | - Stephen J Pearton
- Department of Materials Science and Engineering, University of Florida, Gainesville, FL, 32611, USA
| | - Gwan-Hyoung Lee
- Department of Material Science and Engineering, Seoul National University, Seoul, 08826, Korea
- Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Korea
- Institute of Engineering Research, Seoul National University, Seoul, 08826, Korea
- Institute of Applied Physics, Seoul National University, Seoul, 08826, Korea
| | - Jihyun Kim
- Department of Chemical and Biological Engineering, Korea University, Seoul, 02841, Korea
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39
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Jo H, Lee W, Jung H, Park DM, Lee H, Kang MS. Ionically Connected Floating Electrodes for Long-Distance (>1 mm) Coplanar-Gating Graphene Transistors. ACS APPLIED MATERIALS & INTERFACES 2021; 13:13541-13547. [PMID: 33719404 DOI: 10.1021/acsami.0c21663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Exploiting the long-range polarizability of an electrolyte based on ion migration, electric double-layer transistors (EDLTs) can be constructed in an unconventional configuration; here, the gate electrode is placed coplanarly with the device channel. In this paper, we demonstrate the influence of the distance factors of the electrolyte layer on the operation of EDLTs with a coplanar gate. As the promptness of the electric double-layer formation depends on the distance between the channel and the gate, the dynamic characteristics of a remote-gated transistor degrade with long distances. To suppress this degradation, we suggest using multiple coplanar floating gates bridged through ionic dielectric layers. Unlike remotely gated EDLTs that utilize a single extended electrolyte layer, the devices with multiple segmented electrolyte layers operate effectively even when they are gated from a distance longer than 1 mm.
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Affiliation(s)
- Hyunwoo Jo
- Department of Chemical and Biomolecular Engineering, Sogang University, Seoul 04107, Republic of Korea
| | - Wonwoo Lee
- School of Electrical Engineering, Soongsil University, Seoul 06987, Republic of Korea
| | - Hyunseung Jung
- School of Electrical Engineering, Soongsil University, Seoul 06987, Republic of Korea
| | - Dong Mok Park
- Department of Chemical and Biomolecular Engineering, Sogang University, Seoul 04107, Republic of Korea
| | - Hojin Lee
- School of Electrical Engineering, Soongsil University, Seoul 06987, Republic of Korea
| | - Moon Sung Kang
- Department of Chemical and Biomolecular Engineering, Sogang University, Seoul 04107, Republic of Korea
- Institute of Emergent Materials, Sogang University, Seoul 04107, Republic of Korea
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40
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Huang W, Xia X, Zhu C, Steichen P, Quan W, Mao W, Yang J, Chu L, Li X. Memristive Artificial Synapses for Neuromorphic Computing. NANO-MICRO LETTERS 2021; 13:85. [PMID: 34138298 PMCID: PMC8006524 DOI: 10.1007/s40820-021-00618-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 01/29/2021] [Indexed: 05/06/2023]
Abstract
Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the von Neumann architecture. This computing is realized based on memristive hardware neural networks in which synaptic devices that mimic biological synapses of the brain are the primary units. Mimicking synaptic functions with these devices is critical in neuromorphic systems. In the last decade, electrical and optical signals have been incorporated into the synaptic devices and promoted the simulation of various synaptic functions. In this review, these devices are discussed by categorizing them into electrically stimulated, optically stimulated, and photoelectric synergetic synaptic devices based on stimulation of electrical and optical signals. The working mechanisms of the devices are analyzed in detail. This is followed by a discussion of the progress in mimicking synaptic functions. In addition, existing application scenarios of various synaptic devices are outlined. Furthermore, the performances and future development of the synaptic devices that could be significant for building efficient neuromorphic systems are prospected.
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Affiliation(s)
- Wen Huang
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China.
| | - Xuwen Xia
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Chen Zhu
- College of Electronic and Optical Engineering and College of Microelectronics, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Parker Steichen
- Department of Materials Science and Engineering, University of Washington, Seattle, WA, 98195-2120, USA
| | - Weidong Quan
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Weiwei Mao
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Jianping Yang
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Liang Chu
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China.
| | - Xing'ao Li
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China.
- Key Laboratory for Organic Electronics and Information Displays and Institute of Advanced Materials, Jiangsu National Synergistic Innovation Center for Advanced Materials, School of Materials Science and Engineering, Nanjing University of Posts and Telecommunications (NUPT), 9 Wenyuan Road, Nanjing, 210023, People's Republic of China.
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Yang Q, Yang H, Lv D, Yu R, Li E, He L, Chen Q, Chen H, Guo T. High-Performance Organic Synaptic Transistors with an Ultrathin Active Layer for Neuromorphic Computing. ACS APPLIED MATERIALS & INTERFACES 2021; 13:8672-8681. [PMID: 33565852 DOI: 10.1021/acsami.0c22271] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
In recent years, much attention has been focused on two-dimensional (2D) material-based synaptic transistor devices because of their inherent advantages of low dimension, simultaneous read-write operation and high efficiency. However, process compatibility and repeatability of these materials are still a big challenge, as well as other issues such as complex transfer process and material selectivity. In this work, synaptic transistors with an ultrathin organic semiconductor layer (down to 7 nm) were obtained by the simple dip-coating process, which exhibited a high current switch ratio up to 106, well off state as low as nearly 10-12 A, and low operation voltage of -3 V. Moreover, various synaptic behaviors were successfully simulated including excitatory postsynaptic current, paired pulse facilitation, long-term potentiation, and long-term depression. More importantly, under ultrathin conditions, excellent memory preservation, and linearity of weight update were obtained because of the enhanced effect of defects and improved controllability of the gate voltage on the ultrathin active layer, which led to a pattern recognition rate up to 85%. This is the first work to demonstrate that the pattern recognition rate, a crucial parameter for neuromorphic computing can be significantly improved by reducing the thickness of the channel layer. Hence, these results not only reveal a simple and effective way to improve plasticity and memory retention of the artificial synapse via thickness modulation but also expand the material selection for the 2D artificial synaptic devices.
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Affiliation(s)
- Qian Yang
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
- Zhicheng College, Fuzhou University, Fuzhou 350002, China
- Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou 350100, China
| | - Huihuang Yang
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
- Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou 350100, China
| | - Dongxu Lv
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
| | - Rengjian Yu
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
| | - Enlong Li
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
| | - Lihua He
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
| | - Qizhen Chen
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
| | - Huipeng Chen
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
- Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou 350100, China
| | - Tailiang Guo
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China
- Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou 350100, China
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Kim TW, Ra HS, Ahn J, Jang J, Taniguchi T, Watanabe K, Shim JW, Lee YT, Hwang DK. Frequency Doubler and Universal Logic Gate Based on Two-Dimensional Transition Metal Dichalcogenide Transistors with Low Power Consumption. ACS APPLIED MATERIALS & INTERFACES 2021; 13:7470-7475. [PMID: 33528986 DOI: 10.1021/acsami.0c21222] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Two-dimensional transition metal dichalcogenide semiconductors are very promising candidates for future electronic applications with low power consumption due to a low leakage current and high on-off current ratio. In this study, we suggest a complementary circuit consisting of ambipolar WSe2 and n-MoS2 field-effect transistors (FETs), which demonstrate dual functions of a frequency doubler and single inversion AND (SAND) logic gate. In order to reduce the power consumption, a high-quality thin h-BN single crystal is used as a gate dielectric that leads to a low operating voltage of less than 5 V. By combining the low operating voltage with a low operating current in the complementary circuit, a low power consumption of 300 nW (a minimum of 10 pW) has been achieved, which is a significant improvement compared to the tens of μW consumed by a graphene channel. The complementary circuit shows the effective frequency doubling of the input with a dynamic range from 20 to 100 Hz. Furthermore, this circuit satisfies all the truth tables of a SAND logic gate that can be used as a universal logic gate like NAND. Considering that the NAND logic gate generally consists of four transistors, it is significantly advantageous to implement the equivalent circuit SAND logic gate with only two FETs. Our results open up possibilities for analog- and logic-circuit applications based on low-dimensional semiconductors.
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Affiliation(s)
- Tae Wook Kim
- Center of Opto-Electronic Materials and Devices, Post-Silicon Semiconductor Institute Korea Institute of Science and Technology (KIST), Seoul 02792, Korea
- Department of Electronic Engineering, Korea University, Seoul 02841, Korea
| | - Hyun Soo Ra
- Center of Opto-Electronic Materials and Devices, Post-Silicon Semiconductor Institute Korea Institute of Science and Technology (KIST), Seoul 02792, Korea
| | - Jongtae Ahn
- Center of Opto-Electronic Materials and Devices, Post-Silicon Semiconductor Institute Korea Institute of Science and Technology (KIST), Seoul 02792, Korea
| | - Jisu Jang
- Center of Opto-Electronic Materials and Devices, Post-Silicon Semiconductor Institute Korea Institute of Science and Technology (KIST), Seoul 02792, Korea
- Division of Nano & Information, KIST School, University of Science and Technology (UST), Seoul 02792, Republic of Korea
| | - Takashi Taniguchi
- Advanced Materials Laboratory, National Institute for Materials Science, Tsukuba 305-0044, Japan
| | - Kenji Watanabe
- Advanced Materials Laboratory, National Institute for Materials Science, Tsukuba 305-0044, Japan
| | - Jae Won Shim
- Department of Electronic Engineering, Korea University, Seoul 02841, Korea
| | - Young Tack Lee
- Department of Electronic Engineering, Inha University, Incheon 22212, Korea
| | - Do Kyung Hwang
- Center of Opto-Electronic Materials and Devices, Post-Silicon Semiconductor Institute Korea Institute of Science and Technology (KIST), Seoul 02792, Korea
- Division of Nano & Information, KIST School, University of Science and Technology (UST), Seoul 02792, Republic of Korea
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43
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Song C, Noh G, Kim TS, Kang M, Song H, Ham A, Jo MK, Cho S, Chai HJ, Cho SR, Cho K, Park J, Song S, Song I, Bang S, Kwak JY, Kang K. Growth and Interlayer Engineering of 2D Layered Semiconductors for Future Electronics. ACS NANO 2020; 14:16266-16300. [PMID: 33301290 DOI: 10.1021/acsnano.0c06607] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Layered materials that do not form a covalent bond in a vertical direction can be prepared in a few atoms to one atom thickness without dangling bonds. This distinctive characteristic of limiting thickness around the sub-nanometer level allowed scientists to explore various physical phenomena in the quantum realm. In addition to the contribution to fundamental science, various applications were proposed. Representatively, they were suggested as a promising material for future electronics. This is because (i) the dangling-bond-free nature inhibits surface scattering, thus carrier mobility can be maintained at sub-nanometer range; (ii) the ultrathin nature allows the short-channel effect to be overcome. In order to establish fundamental discoveries and utilize them in practical applications, appropriate preparation methods are required. On the other hand, adjusting properties to fit the desired application properly is another critical issue. Hence, in this review, we first describe the preparation method of layered materials. Proper growth techniques for target applications and the growth of emerging materials at the beginning stage will be extensively discussed. In addition, we suggest interlayer engineering via intercalation as a method for the development of artificial crystal. Since infinite combinations of the host-intercalant combination are possible, it is expected to expand the material system from the current compound system. Finally, inevitable factors that layered materials must face to be used as electronic applications will be introduced with possible solutions. Emerging electronic devices realized by layered materials are also discussed.
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Affiliation(s)
- Chanwoo Song
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Gichang Noh
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
- Center for Electronic Materials, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea
| | - Tae Soo Kim
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Minsoo Kang
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Hwayoung Song
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Ayoung Ham
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Min-Kyung Jo
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
- Operando Methodology and Measurement Team, Interdisciplinary Materials Measurement Institute, Korea Research Institute of Standards and Science (KRISS), Daejeon 34113, Korea
| | - Seorin Cho
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Hyun-Jun Chai
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Seong Rae Cho
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Kiwon Cho
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Jeongwon Park
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Seungwoo Song
- Operando Methodology and Measurement Team, Interdisciplinary Materials Measurement Institute, Korea Research Institute of Standards and Science (KRISS), Daejeon 34113, Korea
| | - Intek Song
- Department of Applied Chemistry, Andong National University, Andong 36728, Korea
| | - Sunghwan Bang
- Materials & Production Engineering Research Institute, LG Electronics, Pyeongtaek-si 17709, Korea
| | - Joon Young Kwak
- Center for Electronic Materials, Korea Institute of Science and Technology (KIST), Seoul 02792, Korea
| | - Kibum Kang
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
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44
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Hui Z, Qu M, Li X, Guo Y, Li J, Jing L, Wu Z. SnS nanosheets for harmonic pulses generation in near infrared region. NANOTECHNOLOGY 2020; 31:485706. [PMID: 32717736 DOI: 10.1088/1361-6528/aba978] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Two-dimensional materials have attracted increasing attention because of their excellent mechanical, thermodynamic, magnetic, electrical and optical properties. Here, a new two-dimensional material of tin sulfide (SnS) is experimentally prepared. It is layered like black phosphorus and owns distinct optoelectronic properties, but eliminates the disadvantage of instability. The nonlinear saturable absorption characteristics of the SnS nanosheets is investigated at 1563.3 nm by the double-balanced detection method. The obtained modulation depth and saturation intensity are 5.4% and 66.3 MW/cm2, respectively. A passively harmonic mode-locked erbium-doped fiber laser based on the SnS saturable absorber (SA) has been demonstrated. The results show that mode-locking with fundamental frequency of 5.47 MHz is realized at pump power of 28.38 mW. With the increase of pump power, the laser can operate from fundamental frequency to high-order harmonic mode-locking. The maximum repetition rate of 412.73 MHz has been obtained, which is equivalent to the 76th harmonic mode-locking. This work reveals that SnS nanosheets is a novel and efficient SA with high damage threshold, which will find potential applications in optical communication, photoelectric detection, laser medicine, etc.
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Affiliation(s)
- Zhanqiang Hui
- School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi 710121, People's Republic of China
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Cheng Y, Shan K, Xu Y, Yang J, He J, Jiang J. Hardware implementation of photoelectrically modulated dendritic arithmetic and spike-timing-dependent plasticity enabled by an ion-coupling gate-tunable vertical 0D-perovskite/2D-MoS 2 hybrid-dimensional van der Waals heterostructure. NANOSCALE 2020; 12:21798-21811. [PMID: 33103690 DOI: 10.1039/d0nr04950f] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Brain-inspired nanodevices have been demonstrated to possess outstanding characteristics for implementing neuromorphic computing. Among these devices, photoelectrically modulated neuromorphic transistors are regarded as the basic building blocks for applications in emerging brain-like devices. However, to date, efficient optoelectronic-hybrid neuromorphic devices are still lacking. Because conventional transistors based on mono-semiconductor materials cannot absorb adequate light to ensure efficient light-matter interactions, they pose significant challenges to the synchronous processing of photoelectric information. Here, a novel photoelectrically modulated neuromorphic device based on an ion-coupling gate-tunable vertical 0D-CsPbBr3-quantum-dots/2D-MoS2 hybrid-dimensional van der Waals heterojunction is demonstrated by using a polymer ion gel electrolyte as the gate dielectric. A super-efficient heterojunction interface for photo-carrier transport is developed by integrating CsPbBr3 quantum dots with 2D-layered MoS2 semiconductors. We experimentally demonstrate that the drain-source current can be modulated by applying spikes to the drain and gate terminals, and the conductance can also be tuned by external light stimulus. Most importantly, photoelectrically modulated spiking Boolean logics, dendritic integrations in both temporal and spatial modes, and Hebbian learning rules can be successfully mimicked in our proposed hybrid-dimensional device using this intriguing optical and electrical synergy approach. These results suggest that the proposed device has great potential in intelligent cognitive systems and neuromorphic computing applications.
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Affiliation(s)
- Yongchao Cheng
- Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha 410083, China.
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46
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Cheng Y, Li H, Liu B, Jiang L, Liu M, Huang H, Yang J, He J, Jiang J. Vertical 0D-Perovskite/2D-MoS 2 van der Waals Heterojunction Phototransistor for Emulating Photoelectric-Synergistically Classical Pavlovian Conditioning and Neural Coding Dynamics. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e2005217. [PMID: 33035390 DOI: 10.1002/smll.202005217] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 09/10/2020] [Indexed: 06/11/2023]
Abstract
Optoelectronic-neuromorphic transistors are vital for next-generation nanoscale brain-like computational systems. However, the hardware implementation of optoelectronic-neuromorphic devices, which are based on conventional transistor architecture, faces serious challenges with respect to the synchronous processing of photoelectric information. This is because mono-semiconductor material cannot absorb adequate light to ensure efficient light-matter interactions. In this work, a novel neuromorphic-photoelectric device of vertical van der Waals heterojunction phototransistors based on a colloidal 0D-CsPbBr3 -quantum-dots/2D-MoS2 heterojunction channel is proposed using a polymer ion gel electrolyte as the gate dielectric. A highly efficient photocarrier transport interface is established by introducing colloidal perovskite quantum dots with excellent light absorption capabilities on the 2D-layered MoS2 semiconductor with strong carrier transport abilities. The device exhibits not only high photoresponsivity but also fundamental synaptic characteristics, such as excitatory postsynaptic current, paired-pulse facilitation, dynamic temporal filter, and light-tunable synaptic plasticity. More importantly, efficiency-adjustable photoelectronic Pavlovian conditioning and photoelectronic hybrid neuronal coding behaviors can be successfully implemented using the optical and electrical synergy approach. The results suggest that the proposed device has potential for applications associated with next-generation brain-like photoelectronic human-computer interactions and cognitive systems.
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Affiliation(s)
- Yongchao Cheng
- Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, 410083, China
| | - Huangjinwei Li
- Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, 410083, China
| | - Biao Liu
- Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, 410083, China
| | - Leyong Jiang
- School of Physics and Electronics, Hunan Normal University, Changsha, 410081, China
| | - Min Liu
- Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, 410083, China
| | - Han Huang
- Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, 410083, China
| | - Junliang Yang
- Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, 410083, China
| | - Jun He
- Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, 410083, China
| | - Jie Jiang
- Hunan Key Laboratory of Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan, 410083, China
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Zhu Y, Huang W, He Y, Yin L, Zhang Y, Yang D, Pi X. Perovskite-Enhanced Silicon-Nanocrystal Optoelectronic Synaptic Devices for the Simulation of Biased and Correlated Random-Walk Learning. RESEARCH 2020; 2020:7538450. [PMID: 33015636 PMCID: PMC7510342 DOI: 10.34133/2020/7538450] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Accepted: 07/30/2020] [Indexed: 11/21/2022]
Abstract
Silicon- (Si-) based optoelectronic synaptic devices mimicking biological synaptic functionalities may be critical to the development of large-scale integrated optoelectronic artificial neural networks. As a type of important Si materials, Si nanocrystals (NCs) have been successfully employed to fabricate optoelectronic synaptic devices. In this work, organometal halide perovskite with excellent optical asborption is employed to improve the performance of optically stimulated Si-NC-based optoelectronic synaptic devices. The improvement is evidenced by the increased optical sensitivity and decreased electrical energy consumption of the devices. It is found that the current simulation of biological synaptic plasticity is essentially enabled by photogating, which is based on the heterojuction between Si NCs and organometal halide perovskite. By using the synaptic plasticity, we have simulated the well-known biased and correlated random-walk (BCRW) learning.
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Affiliation(s)
- Yiyue Zhu
- State Key Laboratory of Silicon Materials and School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China
| | - Wen Huang
- State Key Laboratory of Silicon Materials and School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China
| | - Yifei He
- State Key Laboratory of Silicon Materials and School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China
| | - Lei Yin
- State Key Laboratory of Silicon Materials and School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China
| | - Yiqiang Zhang
- School of Materials Science and Engineering, Henan Institute of Advanced Technology, Zhengzhou University, Zhengzhou, Henan 450001, China
| | - Deren Yang
- State Key Laboratory of Silicon Materials and School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China
| | - Xiaodong Pi
- State Key Laboratory of Silicon Materials and School of Materials Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China.,Institute of Advanced Semiconductors, Hangzhou Innovation Center, Zhejiang University, Hangzhou, Zhejiang 311215, China
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48
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Lv S, Liu X, Li X, Luo W, Xu W, Shi Z, Ren Y, Zhang C, Zhang K. Electrochemical Peeling Few-Layer SnSe 2 for High-Performance Ultrafast Photonics. ACS APPLIED MATERIALS & INTERFACES 2020; 12:43049-43057. [PMID: 32845118 DOI: 10.1021/acsami.0c10079] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
In recent years, the photoelectric properties and nonlinear optical properties of layered metal chalcogenides (LMCs) have attracted extensive attentions. Because of lower phonon thermal conductivity, larger energy storage rate, and larger electron mobility, LMCs are widely studied in the fields of thermoelectric energy conversion, battery electrode materials, and semiconductor devices. As 2D LMCs, SnSe2 nanosheets (Ns) are connected to each other by van der Waals force, which makes it possible to use electrochemical methods to help peel off the thin layer structure. Two-dimensional SnSe2 has obvious adjustable band gap characteristics. Its thickness can be controlled to keep it on the desired band gap. In this article, we prepared a thin layer of SnSe2 by electrochemical methods and detected its nonlinear optical characteristics. It shows that our prepared materials have good optical absorption characteristics; it has a modulation depth of 15% and a saturation intensity of 61 MW/cm2. To investigate the nonlinear effects of SnSe2 in short and long cavities, the Q-mode-locking phenomenon was first achieved in a fiber laser with cavity length of 6 m. After increasing the cavity length to 56 m, the pump power is adjusted to achieve an adjustable repetition frequency from MHz to GHz in turn in an Er-doped fiber laser through utilizing an SnSe2 incorporating a tapered fiber as a saturable absorber (SA). The nonlinear optical properties of thin layer SnSe2 are fully proven, which opens a new way for advanced photonics, optical communication, laser measurement, and other fields.
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Affiliation(s)
- Shuyuan Lv
- Xi'an University of Posts and Telecommunications, Xi'an 710121, P.R. China
| | - Xiaoyu Liu
- Xi'an University of Posts and Telecommunications, Xi'an 710121, P.R. China
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an 710000, P.R. China
| | - Xiaohui Li
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an 710000, P.R. China
| | - Wenfeng Luo
- Xi'an University of Posts and Telecommunications, Xi'an 710121, P.R. China
| | - Wenxiong Xu
- Xi'an University of Posts and Telecommunications, Xi'an 710121, P.R. China
| | - Zhaojiang Shi
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an 710000, P.R. China
| | - Yujie Ren
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an 710000, P.R. China
| | - Chenxi Zhang
- School of Physics and Information Technology, Shaanxi Normal University, Xi'an 710000, P.R. China
| | - Kai Zhang
- Key Laboratory of Nanodevices and Applications, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, Jiangsu 215123, PR China
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Pan X, Jin T, Gao J, Han C, Shi Y, Chen W. Stimuli-Enabled Artificial Synapses for Neuromorphic Perception: Progress and Perspectives. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e2001504. [PMID: 32734644 DOI: 10.1002/smll.202001504] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Revised: 05/27/2020] [Indexed: 06/11/2023]
Abstract
Brain-inspired neuromorphic computing is intended to provide effective emulation of the functionality of the human brain via the integration of electronic components. Recent studies of synaptic plasticity, which represents one of the most significant neurochemical bases of learning and memory, have enhanced the general comprehension of how the brain functions and have thereby eased the development of artificial neuromorphic devices. An understanding of the synaptic plasticity induced by various types of stimuli is essential for neuromorphic system construction. The realization of multiple stimuli-enabled synapses will be important for future neuromorphic computing applications. In this Review, state-of-the-art synaptic devices with particular emphasis on their synaptic behaviors under excitation by a variety of external stimuli are summarized, including electric fields, light, magnetic fields, pressure, and temperature. The switching mechanisms of these synaptic devices are discussed in detail, including ion migration, electron/hole transfer, phase transition, redox-based resistive switching, and other mechanisms. This Review aims to provide a comprehensive understanding of the operating mechanisms of artificial synapses and thus provides the principles required for design of multifunctional neuromorphic systems with parallel processing capabilities.
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Affiliation(s)
- Xuan Pan
- SZU-NUS Collaborative Innovation Center for Optoelectronic Science & Technology, International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology of Ministry of Education, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, China
- Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore, 117542, Singapore
| | - Tengyu Jin
- Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore, 117542, Singapore
- Joint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou, 350207, P. R. China
| | - Jing Gao
- Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore, 117542, Singapore
| | - Cheng Han
- SZU-NUS Collaborative Innovation Center for Optoelectronic Science & Technology, International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology of Ministry of Education, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, China
| | - Yumeng Shi
- SZU-NUS Collaborative Innovation Center for Optoelectronic Science & Technology, International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology of Ministry of Education, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, China
| | - Wei Chen
- Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore, 117542, Singapore
- Joint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou, 350207, P. R. China
- Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore, 117543, Singapore
- National University of Singapore (Suzhou) Research Institute, 377 Lin Quan Street, Suzhou Industrial Park, Jiangsu, 215123, China
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50
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Wu X, Dai D, Ling Y, Chen S, Huang C, Feng S, Huang W. Organic Single-Crystal Transistor with Unique Photo Responses and Its Application as Light-Stimulated Synaptic Devices. ACS APPLIED MATERIALS & INTERFACES 2020; 12:30627-30634. [PMID: 32538621 DOI: 10.1021/acsami.0c05809] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Tremendous progress has been achieved on organic transistor-based photodetectors; however, because of the nonpositive correlation relationship between the photo/dark current ratio (P) and the gate voltage, the claimed best P, R (photoresponsivity), and D* (detectivity) can hardly be obtained simultaneously at a given gate voltage, which severely compromises the device performance. Here, a light and voltage dually gated transistor based on an organic semiconducting single crystal of 2,6-dithienylanthracene (DTAnt) is developed. Attributing to its very low on/off ratio in the dark and the remarkable increment of mobilities under illumination, this phototransistor shows good performance with a P of 3.83 × 103, R of 1.32 A W-1, and D* of 1.94 × 1012 Jones achieved simultaneously at Vg = -100 V. Besides, the good reversibility and repeatability of its light-responsive behavior allows for the construction of an artificial photonic neuromorphic device with demonstrated synaptic functions, including excitatory postsynaptic current, short/long-term memory , and pair-pulse facilitation/depression.
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Affiliation(s)
- Xiaosong Wu
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, 155 Yangqiao West Road, Fuzhou, Fujian 350002, P. R. China
- College of Chemistry and Materials Science, Fujian Normal University, Fuzhou, Fujian 350002, P. R. China
| | - Donghuan Dai
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, 155 Yangqiao West Road, Fuzhou, Fujian 350002, P. R. China
- College of Chemistry and Materials Science, Fujian Normal University, Fuzhou, Fujian 350002, P. R. China
| | - Yao Ling
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, 155 Yangqiao West Road, Fuzhou, Fujian 350002, P. R. China
| | - Shuo Chen
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, 155 Yangqiao West Road, Fuzhou, Fujian 350002, P. R. China
- College of Chemistry and Materials Science, Fujian Normal University, Fuzhou, Fujian 350002, P. R. China
| | - Chongyu Huang
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, 155 Yangqiao West Road, Fuzhou, Fujian 350002, P. R. China
| | - Shiyu Feng
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, 155 Yangqiao West Road, Fuzhou, Fujian 350002, P. R. China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, P. R. China
| | - Weiguo Huang
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, 155 Yangqiao West Road, Fuzhou, Fujian 350002, P. R. China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, P. R. China
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