1
|
Liu X, Sun C, Ye X, Zhu X, Hu C, Tan H, He S, Shao M, Li RW. Neuromorphic Nanoionics for Human-Machine Interaction: From Materials to Applications. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2311472. [PMID: 38421081 DOI: 10.1002/adma.202311472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 02/06/2024] [Indexed: 03/02/2024]
Abstract
Human-machine interaction (HMI) technology has undergone significant advancements in recent years, enabling seamless communication between humans and machines. Its expansion has extended into various emerging domains, including human healthcare, machine perception, and biointerfaces, thereby magnifying the demand for advanced intelligent technologies. Neuromorphic computing, a paradigm rooted in nanoionic devices that emulate the operations and architecture of the human brain, has emerged as a powerful tool for highly efficient information processing. This paper delivers a comprehensive review of recent developments in nanoionic device-based neuromorphic computing technologies and their pivotal role in shaping the next-generation of HMI. Through a detailed examination of fundamental mechanisms and behaviors, the paper explores the ability of nanoionic memristors and ion-gated transistors to emulate the intricate functions of neurons and synapses. Crucial performance metrics, such as reliability, energy efficiency, flexibility, and biocompatibility, are rigorously evaluated. Potential applications, challenges, and opportunities of using the neuromorphic computing technologies in emerging HMI technologies, are discussed and outlooked, shedding light on the fusion of humans with machines.
Collapse
Affiliation(s)
- Xuerong Liu
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- College of Materials Sciences and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Cui Sun
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Xiaoyu Ye
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Xiaojian Zhu
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Cong Hu
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Hongwei Tan
- Department of Applied Physics, Aalto University, Aalto, FI-00076, Finland
| | - Shang He
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Mengjie Shao
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Run-Wei Li
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| |
Collapse
|
2
|
Mondal SK, Prakasan L, Kolluru N, Pradhan JR, Dasgupta S. Inkjet-Printed, High-Performance MoS 2 Transistors and Unipolar Logic Electronics. ACS APPLIED MATERIALS & INTERFACES 2024; 16:42392-42405. [PMID: 39080865 DOI: 10.1021/acsami.4c05529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Two-dimensional (2D) semiconductor field-effect film transistors combine large carrier mobility with mechanical flexibility and therefore can be ideally suitable for wearable electronics or at the sensor interfaces of smart sensor systems. However, such applications require large-area solution processing as opposed to single-flake devices, where the critical challenge to overcome is the high interflake resistance values. In this report, using a narrow-channel, near-vertical transport device architecture, we have fabricated inkjet-printed sub-20 nm channel electrolyte-gated transistors with predominantly intraflake carrier transport. Therefore, the electronics transport in these transistors is not dominated by the high interflake resistance, and the intraflake material properties including doping density, defect concentration, contact resistance, and threshold voltage modulation can be examined and optimized independently to achieve a current density as high as 280 μA·μm-1. In addition, through the passivation of the sulfur vacancies with a tailored surface treatment, we demonstrate an impressive On-Off current ratio exceeding 1 × 107, complemented by a low subthreshold swing of 100 mV·decade-1. Next, exploiting these high-performance transistors, unipolar depletion-load-type inverters have been fabricated that show a maximum gain of 31. Furthermore, we have realized NAND, NOR, and OR gates, demonstrating their seamless operation at a frequency of 1 kHz. Therefore, this work represents an important step forward to realize electronic circuits based on printed 2D thin film transistors.
Collapse
Affiliation(s)
- Sandeep Kumar Mondal
- Department of Materials Engineering, Indian Institute of Science (IISc), CV Raman Avenue, Bangalore 560012, India
| | - Lakshmi Prakasan
- Department of Materials Engineering, Indian Institute of Science (IISc), CV Raman Avenue, Bangalore 560012, India
| | - Naveen Kolluru
- Department of Materials Engineering, Indian Institute of Science (IISc), CV Raman Avenue, Bangalore 560012, India
| | - Jyoti Ranjan Pradhan
- Department of Materials Engineering, Indian Institute of Science (IISc), CV Raman Avenue, Bangalore 560012, India
| | - Subho Dasgupta
- Department of Materials Engineering, Indian Institute of Science (IISc), CV Raman Avenue, Bangalore 560012, India
| |
Collapse
|
3
|
Wei H, Gong J, Liu J, He G, Ni Y, Fu C, Yang L, Guo J, Xu Z, Xu W. Thermally and Mechanically Stable Perovskite Artificial Synapse as Tuned by Phase Engineering for Efferent Neuromuscular Control. NANO LETTERS 2024. [PMID: 39023921 DOI: 10.1021/acs.nanolett.4c02240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
The doping of perovskites with mixed cations and mixed halides is an effective strategy to optimize phase stability. In this study, we introduce a cubic black phase perovskite CsyFA(1-y)Pb(BrxI(1-x))3 artificial synapse, using phase engineering by adjusting the cesium-bromide content. Low-bromine mixed perovskites are suitable to improve the electric pulse excitation sensitivity and stability of the device. Specifically, the low-bromine and low-cesium mixed perovskite (x = 0.15, y = 0.22) annealed at 373 K allows the device to maintain logic response even after 1000 mechanical flex/flat cycles. The device also shows good thermal stability up to temperatures of 333 K. We have demonstrated reflex-arc behavior with MCMHP synaptic units, capable of making sensory warnings at high frequency. This compositionally engineered, dual-mixed perovskite synaptic device provides significant potential for perceptual soft neurorobotic systems and prostheses.
Collapse
Affiliation(s)
| | - Jiangdong Gong
- School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China
- Center for Intelligent Medical Equipment and Devices, Institute for Innovative Medical Devices, Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu 215123, People's Republic of China
| | - Jiaqi Liu
- Institute of Photoelectronic Thin Film Devices and Technology, Nankai University, Tianjin 300350, People's Republic of China
| | | | - Yao Ni
- School of Integrated Circuits, Guangdong University of Technology, Guangzhou, Guangdong 510006, People's Republic of China
| | | | - Lu Yang
- Institute of Photoelectronic Thin Film Devices and Technology, Nankai University, Tianjin 300350, People's Republic of China
| | - Jiahao Guo
- School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China
- Center for Intelligent Medical Equipment and Devices, Institute for Innovative Medical Devices, Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu 215123, People's Republic of China
| | - Zhipeng Xu
- Institute of Photoelectronic Thin Film Devices and Technology, Nankai University, Tianjin 300350, People's Republic of China
| | - Wentao Xu
- Institute of Photoelectronic Thin Film Devices and Technology, Nankai University, Tianjin 300350, People's Republic of China
| |
Collapse
|
4
|
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.
Collapse
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
| |
Collapse
|
5
|
Sung J, Chung S, Jang Y, Jang H, Kim J, Lee C, Lee D, Jeong D, Cho K, Kim YS, Kang J, Lee W, Lee E. Unveiling the Role of Side Chain for Improving Nonvolatile Characteristics of Conjugated Polymers-Based Artificial Synapse. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2400304. [PMID: 38408158 DOI: 10.1002/advs.202400304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Indexed: 02/28/2024]
Abstract
Interest has grown in services that consume a significant amount of energy, such as large language models (LLMs), and research is being conducted worldwide on synaptic devices for neuromorphic hardware. However, various complex processes are problematic for the implementation of synaptic properties. Here, synaptic characteristics are implemented through a novel method, namely side chain control of conjugated polymers. The developed devices exhibit the characteristics of the biological brain, especially spike-timing-dependent plasticity (STDP), high-pass filtering, and long-term potentiation/depression (LTP/D). Moreover, the fabricated synaptic devices show enhanced nonvolatile characteristics, such as long retention time (≈102 s), high ratio of Gmax/Gmin, high linearity, and reliable cyclic endurance (≈103 pulses). This study presents a new pathway for next-generation neuromorphic computing by modulating conjugated polymers with side chain control, thereby achieving high-performance synaptic properties.
Collapse
Affiliation(s)
- Junho Sung
- Department of Chemical Engineering, Kumoh National Institute of Technology, Gumi, 39177, Republic of Korea
| | - Sein Chung
- Department of Chemical Engineering, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Yongchan Jang
- Department of Polymer Science and Engineering, Department of Energy Engineering Convergence, Kumoh National Institute of Technology, Gumi, 39177, Republic of Korea
| | - Hyoik Jang
- Department of Chemical Engineering, Kumoh National Institute of Technology, Gumi, 39177, Republic of Korea
| | - Jiyeon Kim
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 08826, Republic of Korea
| | - Chan Lee
- Department of Chemical and Biological Engineering, and Institute of Chemical Processes, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea
| | - Donghwa Lee
- Department of Chemical Engineering, Kumoh National Institute of Technology, Gumi, 39177, Republic of Korea
| | - Dongyeong Jeong
- Department of Chemical Engineering, Kumoh National Institute of Technology, Gumi, 39177, Republic of Korea
| | - Kilwon Cho
- Department of Chemical Engineering, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea
| | - Youn Sang Kim
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 08826, Republic of Korea
- Department of Chemical and Biological Engineering, and Institute of Chemical Processes, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea
- Advanced Institute of Convergence Technology, Suwon, 16229, Republic of Korea
| | - Joonhee Kang
- Department of Nanoenergy Engineering, Pusan National University, Busan, 46241, Republic of Korea
| | - Wonho Lee
- Department of Polymer Science and Engineering, Department of Energy Engineering Convergence, Kumoh National Institute of Technology, Gumi, 39177, Republic of Korea
| | - Eunho Lee
- Department of Chemical and Biomolecular Engineering, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea
| |
Collapse
|
6
|
Wang W, Wang Y, Yin F, Niu H, Shin YK, Li Y, Kim ES, Kim NY. Tailoring Classical Conditioning Behavior in TiO 2 Nanowires: ZnO QDs-Based Optoelectronic Memristors for Neuromorphic Hardware. NANO-MICRO LETTERS 2024; 16:133. [PMID: 38411720 PMCID: PMC10899558 DOI: 10.1007/s40820-024-01338-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 12/28/2023] [Indexed: 02/28/2024]
Abstract
Neuromorphic hardware equipped with associative learning capabilities presents fascinating applications in the next generation of artificial intelligence. However, research into synaptic devices exhibiting complex associative learning behaviors is still nascent. Here, an optoelectronic memristor based on Ag/TiO2 Nanowires: ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors. Effective implementation of synaptic behaviors, including long and short-term plasticity, and learning-forgetting-relearning behaviors, were achieved in the device through the application of light and electrical stimuli. Leveraging the optoelectronic co-modulated characteristics, a simulation of neuromorphic computing was conducted, resulting in a handwriting digit recognition accuracy of 88.9%. Furthermore, a 3 × 7 memristor array was constructed, confirming its application in artificial visual memory. Most importantly, complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli, respectively. After training through associative pairs, reflexes could be triggered solely using light stimuli. Comprehensively, under specific optoelectronic signal applications, the four features of classical conditioning, namely acquisition, extinction, recovery, and generalization, were elegantly emulated. This work provides an optoelectronic memristor with associative behavior capabilities, offering a pathway for advancing brain-machine interfaces, autonomous robots, and machine self-learning in the future.
Collapse
Affiliation(s)
- Wenxiao Wang
- School of Information Science and Engineering, University of Jinan, Jinan, 250022, People's Republic of China
- RFIC Centre, NDAC Centre, Kwangwoon University, Nowon-gu, Seoul, 139-701, South Korea
- Department of Electronics Engineering, Kwangwoon University, Nowon-Gu, Seoul, 139-701, South Korea
| | - Yaqi Wang
- School of Information Science and Engineering, University of Jinan, Jinan, 250022, People's Republic of China
| | - Feifei Yin
- RFIC Centre, NDAC Centre, Kwangwoon University, Nowon-gu, Seoul, 139-701, South Korea
- Department of Electronics Engineering, Kwangwoon University, Nowon-Gu, Seoul, 139-701, South Korea
| | - Hongsen Niu
- RFIC Centre, NDAC Centre, Kwangwoon University, Nowon-gu, Seoul, 139-701, South Korea
- Department of Electronics Engineering, Kwangwoon University, Nowon-Gu, Seoul, 139-701, South Korea
| | - Young-Kee Shin
- Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul, 08826, South Korea
| | - Yang Li
- School of Information Science and Engineering, University of Jinan, Jinan, 250022, People's Republic of China.
- School of Microelectronics, Shandong University, Jinan, 250101, People's Republic of China.
| | - Eun-Seong Kim
- RFIC Centre, NDAC Centre, Kwangwoon University, Nowon-gu, Seoul, 139-701, South Korea.
- Department of Electronics Engineering, Kwangwoon University, Nowon-Gu, Seoul, 139-701, South Korea.
| | - Nam-Young Kim
- RFIC Centre, NDAC Centre, Kwangwoon University, Nowon-gu, Seoul, 139-701, South Korea.
- Department of Electronics Engineering, Kwangwoon University, Nowon-Gu, Seoul, 139-701, South Korea.
| |
Collapse
|
7
|
Liu Q, Wei Q, Ren H, Zhou L, Zhou Y, Wang P, Wang C, Yin J, Li M. Circular polarization-resolved ultraviolet photonic artificial synapse based on chiral perovskite. Nat Commun 2023; 14:7179. [PMID: 37935714 PMCID: PMC10630371 DOI: 10.1038/s41467-023-43034-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 10/27/2023] [Indexed: 11/09/2023] Open
Abstract
Circularly polarized light (CPL) adds a unique dimension to optical information processing and communication. Integrating CPL sensitivity with light learning and memory in a photonic artificial synapse (PAS) device holds significant value for advanced neuromorphic vision systems. However, the development of such systems has been impeded by the scarcity of suitable CPL active optoelectronic materials. In this work, we employ a helical chiral perovskite hybrid combined with single-wall carbon nanotubes to achieve circularly polarized ultraviolet neuromorphic vision sensing and imaging. The heterostructure demonstrates long-term charge storage as evidenced by multiple-pulsed transient absorption measurements and highly sensitive circular polarization-dependent photodetection, thereby enabling efficient CPL-resolved synaptic and neuromorphic behaviors. Significantly, our PAS sensor arrays adeptly visualize, discriminate, and memorize distinct circularly polarized images with up to 93% recognition accuracy in spiking neural network simulations. These findings underscore the pivotal role of chiral perovskites in advancing PAS technology and circular polarization-enhanced ultraviolet neuromorphic vision systems.
Collapse
Affiliation(s)
- Qi Liu
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Qi Wei
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Hui Ren
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Luwei Zhou
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Yifan Zhou
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Pengzhi Wang
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Chenghao Wang
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Jun Yin
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Mingjie Li
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
- Shenzhen Research Institute, The Hong Kong Polytechnic University, Shenzhen, Guangdong, 518057, China.
- Photonics Research Institute, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
| |
Collapse
|
8
|
Xu H, Shang D, Luo Q, An J, Li Y, Wu S, Yao Z, Zhang W, Xu X, Dou C, Jiang H, Pan L, Zhang X, Wang M, Wang Z, Tang J, Liu Q, Liu M. A low-power vertical dual-gate neurotransistor with short-term memory for high energy-efficient neuromorphic computing. Nat Commun 2023; 14:6385. [PMID: 37821427 PMCID: PMC10567726 DOI: 10.1038/s41467-023-42172-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 10/03/2023] [Indexed: 10/13/2023] Open
Abstract
Neuromorphic computing aims to emulate the computing processes of the brain by replicating the functions of biological neural networks using electronic counterparts. One promising approach is dendritic computing, which takes inspiration from the multi-dendritic branch structure of neurons to enhance the processing capability of artificial neural networks. While there has been a recent surge of interest in implementing dendritic computing using emerging devices, achieving artificial dendrites with throughputs and energy efficiency comparable to those of the human brain has proven challenging. In this study, we report on the development of a compact and low-power neurotransistor based on a vertical dual-gate electrolyte-gated transistor (EGT) with short-term memory characteristics, a 30 nm channel length, a record-low read power of ~3.16 fW and a biology-comparable read energy of ~30 fJ. Leveraging this neurotransistor, we demonstrate dendrite integration as well as digital and analog dendritic computing for coincidence detection. We also showcase the potential of neurotransistors in realizing advanced brain-like functions by developing a hardware neural network and demonstrating bio-inspired sound localization. Our results suggest that the neurotransistor-based approach may pave the way for next-generation neuromorphic computing with energy efficiency on par with those of the brain.
Collapse
Affiliation(s)
- Han Xu
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China
| | - Dashan Shang
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China.
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Qing Luo
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junjie An
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
| | - Yue Li
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shuyu Wu
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhihong Yao
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
| | - Woyu Zhang
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaoxin Xu
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Chunmeng Dou
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hao Jiang
- Frontier Institute of Chip and System, Fudan University, Shanghai, 200433, China
| | - Liyang Pan
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China
| | - Xumeng Zhang
- Frontier Institute of Chip and System, Fudan University, Shanghai, 200433, China
| | - Ming Wang
- Frontier Institute of Chip and System, Fudan University, Shanghai, 200433, China
| | - Zhongrui Wang
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, 999077, Hong Kong
| | - Jianshi Tang
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China.
| | - Qi Liu
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China.
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China.
- Frontier Institute of Chip and System, Fudan University, Shanghai, 200433, China.
| | - Ming Liu
- State Key Lab of Fabrication Technologies for Integrated Circuits, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100049, China
- Frontier Institute of Chip and System, Fudan University, Shanghai, 200433, China
| |
Collapse
|
9
|
Wang X, Yang S, Qin Z, Hu B, Bu L, Lu G. Enhanced Multiwavelength Response of Flexible Synaptic Transistors for Human Sunburned Skin Simulation and Neuromorphic Computation. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2303699. [PMID: 37358823 DOI: 10.1002/adma.202303699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 06/22/2023] [Indexed: 06/27/2023]
Abstract
In biological species, optogenetics and bioimaging work together to regulate the function of neurons. Similarly, the light-controlled artificial synaptic system not only enhances computational speed but also simulates complex synaptic functions. However, reported synaptic properties are mainly limited to mimicking simple biological functions and single-wavelength responses. Therefore, the development of flexible synaptic devices with multiwavelength optical signal response and multifunctional simulation remains a challenge. Here, flexible organic light-stimulated synaptic transistors (LSSTs) enabled by alumina oxide (AlOX ), with a simple fabrication process, are reported. By embedding AlOX nanoparticles, the excitons separation efficiency is improved, allowing for multiple wavelength responses. Optimized LSSTs can respond to multiple optical and electrical signals in a highly synaptic manner. Multiwavelength optical synaptic plasticity, electrical synaptic plasticity, sunburned skin simulation, learning efficiency model controlled by photoelectric cooperative stimulation, neural network computing, "deer" picture learning and memory functions are successfully proposed, which promote the development for future artificial intelligent systems. Furthermore, as prepared flexible transistors exhibit mechanical flexibility with bending radius down to 2.5 mm and improved photosynaptic plasticity, which facilitating development of neuromorphic computing and multifunction integration systems at the device-level.
Collapse
Affiliation(s)
- Xin Wang
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710054, China
| | - Shuting Yang
- School of Chemistry, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Zongze Qin
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710054, China
| | - Bin Hu
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710054, China
| | - Laju Bu
- School of Chemistry, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Guanghao Lu
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, 710054, China
| |
Collapse
|
10
|
Dai S, Liu X, Liu Y, Xu Y, Zhang J, Wu Y, Cheng P, Xiong L, Huang J. Emerging Iontronic Neural Devices for Neuromorphic Sensory Computing. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2300329. [PMID: 36891745 DOI: 10.1002/adma.202300329] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/22/2023] [Indexed: 06/18/2023]
Abstract
Living organisms have a very mysterious and powerful sensory computing system based on ion activity. Interestingly, studies on iontronic devices in the past few years have proposed a promising platform for simulating the sensing and computing functions of living organisms, because: 1) iontronic devices can generate, store, and transmit a variety of signals by adjusting the concentration and spatiotemporal distribution of ions, which analogs to how the brain performs intelligent functions by alternating ion flux and polarization; 2) through ionic-electronic coupling, iontronic devices can bridge the biosystem with electronics and offer profound implications for soft electronics; 3) with the diversity of ions, iontronic devices can be designed to recognize specific ions or molecules by customizing the charge selectivity, and the ionic conductivity and capacitance can be adjusted to respond to external stimuli for a variety of sensing schemes, which can be more difficult for electron-based devices. This review provides a comprehensive overview of emerging neuromorphic sensory computing by iontronic devices, highlighting representative concepts of both low-level and high-level sensory computing and introducing important material and device breakthroughs. Moreover, iontronic devices as a means of neuromorphic sensing and computing are discussed regarding the pending challenges and future directions.
Collapse
Affiliation(s)
- Shilei Dai
- Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, Tongji University, Shanghai, 200434, P. R. China
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong, 999077, China
| | - Xu Liu
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
| | - Youdi Liu
- Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, State College, PA, 16802, USA
| | - Yutong Xu
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
| | - Junyao Zhang
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
| | - Yue Wu
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
| | - Ping Cheng
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA
| | - Lize Xiong
- Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, Tongji University, Shanghai, 200434, P. R. China
| | - Jia Huang
- Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, Tongji University, Shanghai, 200434, P. R. China
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
| |
Collapse
|
11
|
Huang M, Schwacke M, Onen M, Del Alamo J, Li J, Yildiz B. Electrochemical Ionic Synapses: Progress and Perspectives. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2205169. [PMID: 36300807 DOI: 10.1002/adma.202205169] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 09/13/2022] [Indexed: 06/16/2023]
Abstract
Artificial neural networks based on crossbar arrays of analog programmable resistors can address the high energy challenge of conventional hardware in artificial intelligence applications. However, state-of-the-art two-terminal resistive switching devices based on conductive filament formation suffer from high variability and poor controllability. Electrochemical ionic synapses are three-terminal devices that operate by electrochemical and dynamic insertion/extraction of ions that control the electronic conductivity of a channel in a single solid-solution phase. They are promising candidates for programmable resistors in crossbar arrays because they have shown uniform and deterministic control of electronic conductivity based on ion doping, with very low energy consumption. Here, the desirable specifications of these programmable resistors are presented. Then, an overview of the current progress of devices based on Li+ , O2- , and H+ ions and material systems is provided. Achieving nanosecond speed, low operation voltage (≈1 V), low energy consumption, with complementary metal-oxide-semiconductor compatibility all simultaneously remains a challenge. Toward this goal, a physical model of the device is constructed to provide guidelines for the desired material properties to overcome the remaining challenges. Finally, an outlook is provided, including strategies to advance materials toward the desirable properties and the future opportunities for electrochemical ionic synapses.
Collapse
Affiliation(s)
- Mantao Huang
- Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Miranda Schwacke
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Murat Onen
- Microsystems Technology Laboratories, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Jesús Del Alamo
- Microsystems Technology Laboratories, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Ju Li
- Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Bilge Yildiz
- Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| |
Collapse
|
12
|
Wang X, Ran Y, Li X, Qin X, Lu W, Zhu Y, Lu G. Bio-inspired artificial synaptic transistors: evolution from innovative basic units to system integration. MATERIALS HORIZONS 2023; 10:3269-3292. [PMID: 37312536 DOI: 10.1039/d3mh00216k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The investigation of transistor-based artificial synapses in bioinspired information processing is undergoing booming exploration, and is the stable building block for brain-like computing. Given that the storage and computing separation architecture of von Neumann construction is not conducive to the current explosive information processing, it is critical to accelerate the connection between hardware systems and software simulations of intelligent synapses. So far, various works based on a transistor-based synaptic system successfully simulated functions similar to biological nerves in the human brain. However, the influence of the semiconductor and the device structural design on synaptic properties is still poorly linked. This review concretely emphasizes the recent advances in the novel structure design of semiconductor materials and devices used in synaptic transistors, not only from a single multifunction synaptic device but also to system application with various connected routes and related working mechanisms. Finally, crises and opportunities in transistor-based synaptic interconnection are discussed and predicted.
Collapse
Affiliation(s)
- Xin Wang
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| | - Yixin Ran
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| | - Xiaoqian Li
- Shandong Technology Center of Nanodevices and Integration, School of Microelectronics, Shandong University, Jinan, Shandong Province, 250100, P. R. China
| | - Xinsu Qin
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| | - Wanlong Lu
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| | - Yuanwei Zhu
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| | - Guanghao Lu
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| |
Collapse
|
13
|
He L, Yang Z, Wang Z, Leydecker T, Orgiu E. Organic multilevel (opto)electronic memories towards neuromorphic applications. NANOSCALE 2023. [PMID: 37378458 DOI: 10.1039/d3nr01311a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
In the past decades, neuromorphic computing has attracted the interest of the scientific community due to its potential to circumvent the von Neumann bottleneck. Organic materials, owing to their fine tunablility and their ability to be used in multilevel memories, represent a promising class of materials to fabricate neuromorphic devices with the key requirement of operation with synaptic weight. In this review, recent studies of organic multilevel memory are presented. The operating principles and the latest achievements obtained with devices exploiting the main approaches to reach multilevel operation are discussed, with emphasis on organic devices using floating gates, ferroelectric materials, polymer electrets and photochromic molecules. The latest results obtained using organic multilevel memories for neuromorphic circuits are explored and the major advantages and drawbacks of the use of organic materials for neuromorphic applications are discussed.
Collapse
Affiliation(s)
- Lin He
- Institute of Fundamental and Frontier Sciences (IFFS), University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Zuchong Yang
- Institut national de la recherche scientifique (INRS), Centre Énergie Matériaux Télécommunications, 1650 Boul. Lionel Boulet, Varennes J3X 1S2, Canada.
| | - Zhiming Wang
- Institute of Fundamental and Frontier Sciences (IFFS), University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Tim Leydecker
- Institute of Fundamental and Frontier Sciences (IFFS), University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Emanuele Orgiu
- Institut national de la recherche scientifique (INRS), Centre Énergie Matériaux Télécommunications, 1650 Boul. Lionel Boulet, Varennes J3X 1S2, Canada.
| |
Collapse
|
14
|
Xu Y, Shi Y, Qian C, Xie P, Jin C, Shi X, Zhang G, Liu W, Wan C, Ho JC, Sun J, Yang J. Optically Readable Organic Electrochemical Synaptic Transistors for Neuromorphic Photonic Image Processing. NANO LETTERS 2023. [PMID: 37229610 DOI: 10.1021/acs.nanolett.3c01291] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Optically readable organic synaptic devices have great potential in both artificial intelligence and photonic neuromorphic computing. Herein, a novel optically readable organic electrochemical synaptic transistor (OR-OEST) strategy is first proposed. The electrochemical doping mechanism of the device was systematically investigated, and the basic biological synaptic behaviors that can be read by optical means are successfully achieved. Furthermore, the flexible OR-OESTs are capable of electrically switching the transparency of semiconductor channel materials in a nonvolatile manner, and thus the multilevel memory can be achieved through optical readout. Finally, the OR-OESTs are developed for the preprocessing of photonic images, such as contrast enhancement and denoising, and feeding the processed images into an artificial neural network, achieving a recognition rate of over 90%. Overall, this work provides a new strategy for the implementation of photonic neuromorphic systems.
Collapse
Affiliation(s)
- Yunchao Xu
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
| | - Yiming Shi
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
| | - Chuan Qian
- Low-dimensional Quantum Structures and Quantum Control of Ministry of Education, Department of Physics, Hunan Normal University, Changsha, Hunan 410081, People's Republic of China
| | - Pengshan Xie
- Department of Materials Science and Engineering City University of Hong Kong Kowloon, Hong Kong SAR 999077, People's Republic of China
| | - Chenxing Jin
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
| | - Xiaofang Shi
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
| | - Gengming Zhang
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
| | - Wanrong Liu
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
| | - Changjin Wan
- School of Electronic Science & Engineering, and Collaborative Innovation Centre of Advanced Microstructures, Nanjing University, Nanjing, Jiangsu 210008, People's Republic of China
| | - Johnny C Ho
- Department of Materials Science and Engineering City University of Hong Kong Kowloon, Hong Kong SAR 999077, People's Republic of China
| | - Jia Sun
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
| | - Junliang Yang
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, Changsha, Hunan 410083, People's Republic of China
| |
Collapse
|
15
|
Chen KT, Shih LC, Mao SC, Chen JS. Mimicking Pain-Perceptual Sensitization and Pattern Recognition Based on Capacitance- and Conductance-Regulated Neuroplasticity in Neural Network. ACS APPLIED MATERIALS & INTERFACES 2023; 15:9593-9603. [PMID: 36752572 DOI: 10.1021/acsami.2c20297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Neuromorphic computing, inspired by the biological neuronal system, is a high potential approach to substantially alleviate the cost of computational latency and energy for massive data processing. Artificial synapses with regulable synaptic weights are the basis of neuromorphic computation, providing an efficient and low-power system to overcome the constraints of the von Neumann architecture. Here, we report an ITO/TaOx-based synaptic capacitor and transistor. With the drift motion of mobile-charged ions in the TaOx, the capacitance and channel conductance can be tuned to exhibit synaptic weight modulation. Robust stability in the cycle-to-cycle (C2C) variation is found in capacitance and conductance potentiation/depression weight updating of 0.9 and 1.8%, respectively. Simulation results show a higher classification accuracy of handwritten digit recognition (95%) in capacitance synapses than that in conductance synapses (84%). Besides, the synaptic capacitor consumes much less energy than the synaptic transistor. Moreover, the ITO/TaOx-based capacitor successfully emulates the pain-perceptual sensitization on top of the superior performance, indicating its promising potential in applying the capacitive neural network.
Collapse
Affiliation(s)
- Kuan-Ting Chen
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 701, Taiwan
| | - Li-Chung Shih
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 701, Taiwan
| | - Shi-Cheng Mao
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 701, Taiwan
| | - Jen-Sue Chen
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 701, Taiwan
| |
Collapse
|
16
|
Sun F, Jiang H, Wang H, Zhong Y, Xu Y, Xing Y, Yu M, Feng LW, Tang Z, Liu J, Sun H, Wang H, Wang G, Zhu M. Soft Fiber Electronics Based on Semiconducting Polymer. Chem Rev 2023; 123:4693-4763. [PMID: 36753731 DOI: 10.1021/acs.chemrev.2c00720] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Fibers, originating from nature and mastered by human, have woven their way throughout the entire history of human civilization. Recent developments in semiconducting polymer materials have further endowed fibers and textiles with various electronic functions, which are attractive in applications such as information interfacing, personalized medicine, and clean energy. Owing to their ability to be easily integrated into daily life, soft fiber electronics based on semiconducting polymers have gained popularity recently for wearable and implantable applications. Herein, we present a review of the previous and current progress in semiconducting polymer-based fiber electronics, particularly focusing on smart-wearable and implantable areas. First, we provide a brief overview of semiconducting polymers from the viewpoint of materials based on the basic concepts and functionality requirements of different devices. Then we analyze the existing applications and associated devices such as information interfaces, healthcare and medicine, and energy conversion and storage. The working principle and performance of semiconducting polymer-based fiber devices are summarized. Furthermore, we focus on the fabrication techniques of fiber devices. Based on the continuous fabrication of one-dimensional fiber and yarn, we introduce two- and three-dimensional fabric fabricating methods. Finally, we review challenges and relevant perspectives and potential solutions to address the related problems.
Collapse
Affiliation(s)
- Fengqiang Sun
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
- Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
| | - Hao Jiang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Haoyu Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Yueheng Zhong
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Yiman Xu
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Yi Xing
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Muhuo Yu
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
- Shanghai Key Laboratory of Lightweight Structural Composites, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Liang-Wen Feng
- Key Laboratory of Green Chemistry & Technology, Ministry of Education, College of Chemistry, Sichuan University, Chengdu 610065, China
| | - Zheng Tang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
- Center for Advanced Low-dimension Materials, Donghua University, Shanghai 201620, China
| | - Jun Liu
- National Key Laboratory on Electromagnetic Environment Effects and Electro-Optical Engineering, Nanjing 210007, China
| | - Hengda Sun
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Hongzhi Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Gang Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Meifang Zhu
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| |
Collapse
|
17
|
Fiedler J, Berland K, Borchert JW, Corkery RW, Eisfeld A, Gelbwaser-Klimovsky D, Greve MM, Holst B, Jacobs K, Krüger M, Parsons DF, Persson C, Presselt M, Reisinger T, Scheel S, Stienkemeier F, Tømterud M, Walter M, Weitz RT, Zalieckas J. Perspectives on weak interactions in complex materials at different length scales. Phys Chem Chem Phys 2023; 25:2671-2705. [PMID: 36637007 DOI: 10.1039/d2cp03349f] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Nanocomposite materials consist of nanometer-sized quantum objects such as atoms, molecules, voids or nanoparticles embedded in a host material. These quantum objects can be exploited as a super-structure, which can be designed to create material properties targeted for specific applications. For electromagnetism, such targeted properties include field enhancements around the bandgap of a semiconductor used for solar cells, directional decay in topological insulators, high kinetic inductance in superconducting circuits, and many more. Despite very different application areas, all of these properties are united by the common aim of exploiting collective interaction effects between quantum objects. The literature on the topic spreads over very many different disciplines and scientific communities. In this review, we present a cross-disciplinary overview of different approaches for the creation, analysis and theoretical description of nanocomposites with applications related to electromagnetic properties.
Collapse
Affiliation(s)
- J Fiedler
- Department of Physics and Technology, University of Bergen, Allégaten 55, 5007 Bergen, Norway.
| | - K Berland
- Department of Mechanical Engineering and Technology Management, Norwegian University of Life Sciences, Campus Ås Universitetstunet 3, 1430 Ås, Norway
| | - J W Borchert
- 1st Institute of Physics, Georg-August-University, Göttingen, Germany
| | - R W Corkery
- Surface and Corrosion Science, Department of Chemistry, KTH Royal Institute of Technology, SE 100 44 Stockholm, Sweden
| | - A Eisfeld
- Max-Planck-Institut für Physik komplexer Systeme, Nöthnitzer Strasse 38, 01187 Dresden, Germany
| | - D Gelbwaser-Klimovsky
- Schulich Faculty of Chemistry and Helen Diller Quantum Center, Technion-Israel Institute of Technology, Haifa 3200003, Israel
| | - M M Greve
- Department of Physics and Technology, University of Bergen, Allégaten 55, 5007 Bergen, Norway.
| | - B Holst
- Department of Physics and Technology, University of Bergen, Allégaten 55, 5007 Bergen, Norway.
| | - K Jacobs
- Experimental Physics, Saarland University, Center for Biophysics, 66123 Saarbrücken, Germany.,Max Planck School Matter to Life, 69120 Heidelberg, Germany
| | - M Krüger
- Institute for Theoretical Physics, Georg-August-Universität Göttingen, 37073 Göttingen, Germany
| | - D F Parsons
- Department of Chemical and Geological Sciences, University of Cagliari, Cittadella Universitaria, 09042 Monserrato, CA, Italy
| | - C Persson
- Centre for Materials Science and Nanotechnology, University of Oslo, P. O. Box 1048 Blindern, 0316 Oslo, Norway.,Department of Materials Science and Engineering, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden
| | - M Presselt
- Leibniz Institute of Photonic Technology (IPHT), Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - T Reisinger
- Institute for Quantum Materials and Technologies, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
| | - S Scheel
- Institute of Physics, University of Rostock, Albert-Einstein-Str. 23-24, 18059 Rostock, Germany
| | - F Stienkemeier
- Institute of Physics, University of Freiburg, Hermann-Herder-Str. 3, 79104 Freiburg, Germany
| | - M Tømterud
- Department of Physics and Technology, University of Bergen, Allégaten 55, 5007 Bergen, Norway.
| | - M Walter
- Institute of Physics, University of Freiburg, Hermann-Herder-Str. 3, 79104 Freiburg, Germany
| | - R T Weitz
- 1st Institute of Physics, Georg-August-University, Göttingen, Germany
| | - J Zalieckas
- Department of Physics and Technology, University of Bergen, Allégaten 55, 5007 Bergen, Norway.
| |
Collapse
|
18
|
Micro- and nano-devices for electrochemical sensing. Mikrochim Acta 2022; 189:459. [DOI: 10.1007/s00604-022-05548-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/02/2022] [Indexed: 11/24/2022]
Abstract
AbstractElectrode miniaturization has profoundly revolutionized the field of electrochemical sensing, opening up unprecedented opportunities for probing biological events with a high spatial and temporal resolution, integrating electrochemical systems with microfluidics, and designing arrays for multiplexed sensing. Several technological issues posed by the desire for downsizing have been addressed so far, leading to micrometric and nanometric sensing systems with different degrees of maturity. However, there is still an endless margin for researchers to improve current strategies and cope with demanding sensing fields, such as lab-on-a-chip devices and multi-array sensors, brain chemistry, and cell monitoring. In this review, we present current trends in the design of micro-/nano-electrochemical sensors and cutting-edge applications reported in the last 10 years. Micro- and nanosensors are divided into four categories depending on the transduction mechanism, e.g., amperometric, impedimetric, potentiometric, and transistor-based, to best guide the reader through the different detection strategies and highlight major advancements as well as still unaddressed demands in electrochemical sensing.
Graphical Abstract
Collapse
|
19
|
Zare Bidoky F, Frisbie CD. Sub-3 V, MHz-Class Electrolyte-Gated Transistors and Inverters. ACS APPLIED MATERIALS & INTERFACES 2022; 14:21295-21300. [PMID: 35476913 DOI: 10.1021/acsami.2c01585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Electrolyte-gated transistors (EGTs) have emerging applications in physiological recording, neuromorphic computing, sensing, and flexible printed electronics. A challenge for these devices is their slow switching speed, which has several causes. Here, we report the fabrication and characterization of n-type ZnO-based EGTs with signal propagation delays as short as 70 ns. Propagation delays are assessed in dynamically operating inverters and five-stage ring oscillators as a function of channel dimensions and supply voltages up to 3 V. Substantial decreases in switching time are realized by minimizing parasitic resistances and capacitances that are associated with the electrolyte in these devices. Stable switching at 1-10 MHz is achieved in individual inverter stages with 10-40 μm channel lengths, and analysis suggests that further improvements are possible.
Collapse
Affiliation(s)
- Fazel Zare Bidoky
- Department of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Avenue SE, Minneapolis, Minnesota 55455, United States
- DuPont Electronics and Industrial, Emerging Technologies, Experimental Station, 200 Powder Mill Road, Wilmington, Delaware 19803, United States
| | - C Daniel Frisbie
- Department of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Avenue SE, Minneapolis, Minnesota 55455, United States
| |
Collapse
|