1
|
Kim C, Roe DG, Lim DU, Choi YY, Kang MS, Kim DH, Cho JH. Toward human-like adaptability in robotics through a retention-engineered synaptic control system. SCIENCE ADVANCES 2024; 10:eadn6217. [PMID: 38924417 PMCID: PMC11204284 DOI: 10.1126/sciadv.adn6217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 05/21/2024] [Indexed: 06/28/2024]
Abstract
Although advanced robots can adeptly mimic human movement and aesthetics, they are still unable to adapt or evolve in response to external experiences. To address this limitation, we propose an innovative approach that uses parallel-processable retention-engineered synaptic devices in the control system. This approach aims to simulate a human-like learning system without necessitating complex computational systems. The retention properties of the synaptic devices were modulated by adjusting the amount of Ag/AgCl ink sprayed. This changed the voltage drop across the interface between the gate electrode and the electrolyte. Furthermore, the unrestricted movement of ions in the electrolyte enhanced the signal multiplexing capability of the ion gel, enabling device-level parallel processing. By integrating the unique characteristics of the synaptic devices with actuators, we successfully emulated a human-like workout process that includes feedback between acute and chronic responses. The proposed control system offers an innovative approach to reducing system complexity and achieving a human-like learning system in the field of biomimicry.
Collapse
Affiliation(s)
- Chan Kim
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Dong Gue Roe
- School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Dong Un Lim
- Hydrogen Energy Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon 305-600 Republic of Korea
| | - Yoon Young Choi
- Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Moon Sung Kang
- Department of Chemical and Biomolecular Engineering, Institute of Emergent Materials, Sogang University, Seoul 04107, Republic of Korea
| | - Dong-Hwan Kim
- School of Chemical Engineering, Biomedical Institute for Convergence at SKKU (BICS), Sungkyunkwan University (SKKU), Suwon 16419, Republic of Korea
| | - Jeong Ho Cho
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul 03722, Republic of Korea
| |
Collapse
|
2
|
Lee J, Lee J, Bang H, Yoon TW, Ko JH, Zhang G, Park JS, Jeon I, Lee S, Kang B. One-Shot Remote Integration of Macromolecular Synaptic Elements on a Chip for Ultrathin Flexible Neural Network System. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2402361. [PMID: 38762775 DOI: 10.1002/adma.202402361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 04/23/2024] [Indexed: 05/20/2024]
Abstract
The field of biomimetic electronics that mimic synaptic functions has expanded significantly to overcome the limitations of the von Neumann bottleneck. However, the scaling down of the technology has led to an increasingly intricate manufacturing process. To address the issue, this work presents a one-shot integrable electropolymerization (OSIEP) method with remote controllability for the deposition of synaptic elements on a chip by exploiting bipolar electrochemistry. Condensing synthesis, deposition, and patterning into a single fabrication step is achieved by combining alternating-current voltage superimposed on direct-current voltage-bipolar electropolymerization and a specially designed dual source/drain bipolar electrodes. As a result, uniform 6 × 5 arrays of poly(3,4-ethylenedioxythiophene) channels are successfully fabricated on flexible ultrathin parylene substrates in one-shot process. The channels exhibited highly uniform characteristics and are directly used as electrochemical synaptic transistor with synaptic plasticity over 100 s. The synaptic transistors have demonstrated promising performance in an artificial neural network (NN) simulation, achieving a high recognition accuracy of 95.20%. Additionally, the array of synaptic transistor is easily reconfigured to a multi-gate synaptic circuit to implement the principles of operant conditioning. These results provide a compelling fabrication strategy for realizing cost-effective and disposable NN systems with high integration density.
Collapse
Affiliation(s)
- Jiyun Lee
- SKKU Advanced Institute of Nanotechnology (SAINT) and Department of Nano Science and Technology, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
| | - Jaehoon Lee
- SKKU Advanced Institute of Nanotechnology (SAINT) and Department of Nano Science and Technology, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
| | - Hyeonsu Bang
- Department of Electrical and Computer Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
| | - Tae Woong Yoon
- SKKU Advanced Institute of Nanotechnology (SAINT) and Department of Nano Science and Technology, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
| | - Jong Hwan Ko
- Department of Electrical and Computer Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
- College of Information and Communication Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
| | - Guobing Zhang
- Special Display and Imaging Innovation Center of Anhui Province, National Engineering Lab of Special Display Technology, Academy of Opto-Electronic Technology, Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, School of Chemistry and Chemical Engineering, Hefei University of Technology, Key Laboratory of Advance Functional Materials and Devices of Anhui Province, Hefei, 230009, China
| | - Ji-Sang Park
- SKKU Advanced Institute of Nanotechnology (SAINT) and Department of Nano Science and Technology, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
- Department of Nano Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
| | - Il Jeon
- SKKU Advanced Institute of Nanotechnology (SAINT) and Department of Nano Science and Technology, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
- Department of Nano Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
| | - Sungjoo Lee
- SKKU Advanced Institute of Nanotechnology (SAINT) and Department of Nano Science and Technology, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
- Department of Nano Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
| | - Boseok Kang
- SKKU Advanced Institute of Nanotechnology (SAINT) and Department of Nano Science and Technology, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
- Department of Nano Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, 16419, South Korea
| |
Collapse
|
3
|
Lai BR, Chen KT, Chaurasiya R, You SX, Hsu WD, Chen JS. Unveiling transient current response in bilayer oxide-based physical reservoirs for time-series data analysis. NANOSCALE 2024; 16:3061-3070. [PMID: 38240625 DOI: 10.1039/d3nr05401b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Physical reservoirs employed to map time-series data and analyze extracted features have attracted interest owing to their low training cost and mitigated interconnection complexity. This study reports a physical reservoir based on a bilayer oxide-based dynamic memristor. The proposed device exhibits a nonlinear current response and short-term memory (STM), satisfying the requirements of reservoir computing (RC). These characteristics are validated using a compact model to account for resistive switching (RS) via the dynamic evolution of the internal state variable and the relocation of oxygen vacancies. Mathematically, the transient current response can be quantitatively described according to a simple set of equations to correlate the theoretical framework with experimental results. Furthermore, the device shows significant reliability and ability to distinguish 4-bit inputs and four diverse neural firing patterns. Therefore, this work shows the feasibility of implementing physical reservoirs in hardware and advances the understanding of the dynamic response.
Collapse
Affiliation(s)
- Bo-Ru Lai
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
| | - Kuan-Ting Chen
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
| | - Rajneesh Chaurasiya
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
- Department of Electronics and Communication Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Chennai, India
| | - Song-Xian You
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
| | - Wen-Dung Hsu
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
| | - Jen-Sue Chen
- Department of Materials Science and Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
- Academy of Innovative Semiconductor and Sustainable Manufacturing, National Cheng Kung University, Tainan 70101, Taiwan
| |
Collapse
|
4
|
Pan D, Hu J, Wang B, Xia X, Cheng Y, Wang C, Lu Y. Biomimetic Wearable Sensors: Emerging Combination of Intelligence and Electronics. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2303264. [PMID: 38044298 PMCID: PMC10837381 DOI: 10.1002/advs.202303264] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 10/03/2023] [Indexed: 12/05/2023]
Abstract
Owing to the advancement of interdisciplinary concepts, for example, wearable electronics, bioelectronics, and intelligent sensing, during the microelectronics industrial revolution, nowadays, extensively mature wearable sensing devices have become new favorites in the noninvasive human healthcare industry. The combination of wearable sensing devices with bionics is driving frontier developments in various fields, such as personalized medical monitoring and flexible electronics, due to the superior biocompatibilities and diverse sensing mechanisms. It is noticed that the integration of desired functions into wearable device materials can be realized by grafting biomimetic intelligence. Therefore, herein, the mechanism by which biomimetic materials satisfy and further enhance system functionality is reviewed. Next, wearable artificial sensory systems that integrate biomimetic sensing into portable sensing devices are introduced, which have received significant attention from the industry owing to their novel sensing approaches and portabilities. To address the limitations encountered by important signal and data units in biomimetic wearable sensing systems, two paths forward are identified and current challenges and opportunities are presented in this field. In summary, this review provides a further comprehensive understanding of the development of biomimetic wearable sensing devices from both breadth and depth perspectives, offering valuable guidance for future research and application expansion of these devices.
Collapse
Affiliation(s)
- Donglei Pan
- College of Light Industry and Food EngineeringGuangxi UniversityNanningGuangxi530004China
- Key Laboratory of Industrial BiocatalysisMinistry of EducationDepartment of Chemical EngineeringTsinghua UniversityBeijing100084China
| | - Jiawang Hu
- Key Laboratory of Industrial BiocatalysisMinistry of EducationDepartment of Chemical EngineeringTsinghua UniversityBeijing100084China
| | - Bin Wang
- Key Laboratory of Industrial BiocatalysisMinistry of EducationDepartment of Chemical EngineeringTsinghua UniversityBeijing100084China
| | - Xuanjie Xia
- Key Laboratory of Industrial BiocatalysisMinistry of EducationDepartment of Chemical EngineeringTsinghua UniversityBeijing100084China
| | - Yifan Cheng
- Key Laboratory of Industrial BiocatalysisMinistry of EducationDepartment of Chemical EngineeringTsinghua UniversityBeijing100084China
| | - Cheng‐Hua Wang
- College of Light Industry and Food EngineeringGuangxi UniversityNanningGuangxi530004China
| | - Yuan Lu
- Key Laboratory of Industrial BiocatalysisMinistry of EducationDepartment of Chemical EngineeringTsinghua UniversityBeijing100084China
| |
Collapse
|
5
|
Zhao J, Tong L, Niu J, Fang Z, Pei Y, Zhou Z, Sun Y, Wang Z, Wang H, Lou J, Yan X. A bidirectional thermal sensory leaky integrate-and-fire (LIF) neuron model based on bipolar NbO x volatile threshold devices with ultra-low operating current. NANOSCALE 2023; 15:17599-17608. [PMID: 37874690 DOI: 10.1039/d3nr03034b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Brain-like artificial intelligence (AI) will become the main form and important platform in future computing. It will play an important and unique role in simulating brain functions, efficiently implementing AI algorithms, and improving computing power. Developing artificial neurons that can send facilitation/depression signals to artificial synapses, sense, and process temperature information is of great significance for achieving more efficient and compact brain-like computing systems. Herein, we have constructed a NbOx bipolar volatile threshold memristor, which could be operated by 1 μA ultra-low current and up to ∼104 switching ratios. By using a leaky integrate-and-fire (LIF) artificial neuron model, a bipolar LIF artificial neuron is constructed, which can realize the conventional threshold-driven firing, all-or-nothing spiking, refractory periods, and intensity-modulated frequency response bidirectionally at the positive/negative voltage stimulation, which will give the artificial synapse facilitation/depression signals. Furthermore, this bipolar LIF neuron can also explore different temperatures to output different signals, which could be constructed as a more compact thermal sensory neuron to avoid external harm to artificial robots. This study is of great significance for improving the computational efficiency of the system more effectively, achieving high integration density and low energy consumption artificial neural networks to meet the needs of brain-like neural computing.
Collapse
Affiliation(s)
- Jianhui Zhao
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.
| | - Liang Tong
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.
| | - Jiangzhen Niu
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.
| | - Ziliang Fang
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.
| | - Yifei Pei
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Physics Science and Technology, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China
| | - Zhenyu Zhou
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.
| | - Yong Sun
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.
| | - Zhongrong Wang
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.
| | - Hong Wang
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.
| | - Jianzhong Lou
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.
| | - Xiaobing Yan
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electronic and Information Engineering, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China.
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Physics Science and Technology, Institute of Life Science and Green Development, Hebei University, Baoding 071002, China
| |
Collapse
|
6
|
Chen W, Zhai L, Zhang S, Zhao Z, Hu Y, Xiang Y, Liu H, Xu Z, Jiang L, Wen L. Cascade-heterogated biphasic gel iontronics for electronic-to-multi-ionic signal transmission. Science 2023; 382:559-565. [PMID: 37917701 DOI: 10.1126/science.adg0059] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Accepted: 09/22/2023] [Indexed: 11/04/2023]
Abstract
Currently, electronics and iontronics in abiotic-biotic systems can only use electrons and single-species ions as unitary signal carriers. Thus, a mechanism of gating transmission for multiple biosignals in such devices is needed to match and modulate complex aqueous-phase biological systems. Here we report the use of cascade-heterogated biphasic gel iontronics to achieve diverse electronic-to-multi-ionic signal transmission. The cascade-heterogated property determined the transfer free energy barriers experienced by ions and ionic hydration-dehydration states under an electric potential field, fundamentally enhancing the distinction of cross-interface transmission between different ions by several orders of magnitude. Such heterogated or chemical-heterogated iontronics with programmable features can be coupled with multi-ion cross-interface mobilities for hierarchical and selective cross-stage signal transmission. We expect that such iontronics would be ideal candidates for a variety of biotechnology applications.
Collapse
Affiliation(s)
- Weipeng Chen
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Linxin Zhai
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P. R. China
| | - Suli Zhang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, P. R. China
- Beijing Key Laboratory of Metabolic Disorder Related Cardiovascular Disease, Capital Medical University, Beijing 100069, P. R. China
| | - Ziguang Zhao
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Yuhao Hu
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Yun Xiang
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
| | - Huirong Liu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, P. R. China
- Beijing Key Laboratory of Metabolic Disorder Related Cardiovascular Disease, Capital Medical University, Beijing 100069, P. R. China
| | - Zhiping Xu
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P. R. China
| | - Lei Jiang
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Liping Wen
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| |
Collapse
|
7
|
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
|
8
|
Wei H, Xu Z, Ni Y, Yang L, Sun L, Gong J, Zhang S, Qu S, Xu W. Mixed-Dimensional Nanoparticle-Nanowire Channels for Flexible Optoelectronic Artificial Synapse with Enhanced Photoelectric Response and Asymmetric Bidirectional Plasticity. NANO LETTERS 2023; 23:8743-8752. [PMID: 37698378 DOI: 10.1021/acs.nanolett.3c02836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/13/2023]
Abstract
A mixed-dimensional dual-channel synaptic transistor composed of inorganic nanoparticles and organic nanowires was fabricated to expand the photoelectric gain range. The device can actualize the sensitization features of the nociceptor and shows improved responsiveness to visible light. Under electrical pulses with different polarities, the apparatus exhibits reconfigurable asymmetric bidirectional plasticity. Moreover, the devices demonstrate good operational tolerance and mechanical stability, retaining more than 60% of their maximum responsiveness after 100 consecutive/bidirectional and 1000 flex/flat operations. The improved photoelectric response of the device endows a high image recognition accuracy of greater than 80%. Asymmetric bidirectional plasticity is used as punishment/reward in a psychological experiment to emulate the improvement of learning motivation and enables real-time forward and backward deflection (+7 and -25°) of artificial muscle. The mixed-dimensional optoelectronic artificial synapses with switchable behavior and electron/hole transport type have important prospects for neuromorphic processing and artificial somatosensory nerves.
Collapse
Affiliation(s)
- Huanhuan Wei
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Engineering Research Center of Thin Film Optoelectronics Technology, College of Electronic Information and Optical Engineering of Nankai University, National Institute for Advanced Materials, Nankai University, Ministry of Education, Tianjin 300350, People's Republic of China
- Institutes of Physical Science and Information Technology, School of Materials Science and Engineering, Key Laboratory of Structure and Functional Regulation of Hybrid Materials, Anhui University, Ministry of Education, Hefei 230601, People's Republic of China
| | - Zhipeng Xu
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Engineering Research Center of Thin Film Optoelectronics Technology, College of Electronic Information and Optical Engineering of Nankai University, National Institute for Advanced Materials, Nankai University, Ministry of Education, Tianjin 300350, People's Republic of China
| | - Yao Ni
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Engineering Research Center of Thin Film Optoelectronics Technology, College of Electronic Information and Optical Engineering of Nankai University, National Institute for Advanced Materials, Nankai University, Ministry of Education, Tianjin 300350, People's Republic of China
| | - Lu Yang
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Engineering Research Center of Thin Film Optoelectronics Technology, College of Electronic Information and Optical Engineering of Nankai University, National Institute for Advanced Materials, Nankai University, Ministry of Education, Tianjin 300350, People's Republic of China
| | - Lin Sun
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Engineering Research Center of Thin Film Optoelectronics Technology, College of Electronic Information and Optical Engineering of Nankai University, National Institute for Advanced Materials, Nankai University, Ministry of Education, Tianjin 300350, People's Republic of China
| | - Jiangdong Gong
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Engineering Research Center of Thin Film Optoelectronics Technology, College of Electronic Information and Optical Engineering of Nankai University, National Institute for Advanced Materials, Nankai University, Ministry of Education, Tianjin 300350, People's Republic of China
| | - Song Zhang
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Engineering Research Center of Thin Film Optoelectronics Technology, College of Electronic Information and Optical Engineering of Nankai University, National Institute for Advanced Materials, Nankai University, Ministry of Education, Tianjin 300350, People's Republic of China
| | - Shangda Qu
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Engineering Research Center of Thin Film Optoelectronics Technology, College of Electronic Information and Optical Engineering of Nankai University, National Institute for Advanced Materials, Nankai University, Ministry of Education, Tianjin 300350, People's Republic of China
| | - Wentao Xu
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, Engineering Research Center of Thin Film Optoelectronics Technology, College of Electronic Information and Optical Engineering of Nankai University, National Institute for Advanced Materials, Nankai University, Ministry of Education, Tianjin 300350, People's Republic of China
| |
Collapse
|
9
|
Gao X, Zhu J, Yin J. Mechanistic Insights into Synaptic Plasticity Behaviors of Electrolyte-Gated Flexible Transistor Devices. ACS APPLIED MATERIALS & INTERFACES 2023; 15:39530-39538. [PMID: 37556764 DOI: 10.1021/acsami.3c07235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
Biological synaptic function simulation using flexible electronic devices based on low-dimensional semiconductor materials is an emerging and rapidly evolving research field with promising applications in brain-like computers and artificial intelligence systems. In this work, we present the fabrication of solution compatible MoS2 thin-film transistors on the ultrathin polymethyl methacrylate substrates via layer-by-layer assembly followed by a one-step transfer printing method. The MoS2 transport channel is controlled by ionic liquid gating with 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, resulting in excellent synaptic performances for emulating memory and perception synapse functions. To investigate the synaptic behaviors, we conduct a series of synaptic spike-dependent experiments and propose an advanced model that delineates the long-term plasticity and short-term plasticity with separate characteristic factors. These findings provide insights into the fundamental mechanisms of synaptic plasticity in electric double-layer devices and contribute to a better understanding of their synaptic performances. In addition, we examine the effects of bending conditions on synaptic plasticity and synaptic weights, unveiling the synergistic interplay between mechanical deformation and synaptic behaviors. Our experimental results, combined with the developed model, are in good agreement and shed light on the influence of mechanical flexibility on the synaptic properties of the devices. In summary, this study establishes a solid foundation for further development of flexible synaptic devices from both practical and theoretical perspectives.
Collapse
Affiliation(s)
- Xiangxiang Gao
- School of Materials Science and Engineering, Nankai University, Tianjin 300071, China
- Advanced Interdisciplinary Research Center for Flexible Electronics, Academy of Advanced Interdisciplinary Research, Xidian University, Xi'an 710071, China
| | - Jian Zhu
- School of Materials Science and Engineering, Nankai University, Tianjin 300071, China
| | - Jun Yin
- School of Materials Science and Engineering, Nankai University, Tianjin 300071, China
| |
Collapse
|
10
|
Kim J, Song S, Lee JM, Nam S, Kim J, Hwang DK, Park SK, Kim YH. Metal-Oxide Heterojunction Optoelectronic Synapse and Multilevel Memory Devices Enabled by Broad Spectral Photocarrier Modulation. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 19:e2301186. [PMID: 37116095 DOI: 10.1002/smll.202301186] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/29/2023] [Indexed: 06/19/2023]
Abstract
Broad spectral response and high photoelectric conversion efficiency are key milestones for realizing multifunctional, low-power optoelectronic devices such as artificial synapse and reconfigurable memory devices. Nevertheless, the wide bandgap and narrow spectral response of metal-oxide semiconductors are problematic for efficient metal-oxide optoelectronic devices such as photonic synapse and optical memory devices. Here, a simple titania (TiO2 )/indium-gallium-zinc-oxide (IGZO) heterojunction structure is proposed for efficient multifunctional optoelectronic devices, enabling widen spectral response range and high photoresponsivity. By overlaying a TiO2 film on IGZO, the light absorption range extends to red light, along with enhanced photoresponsivity in the full visible light region. By implementing the TiO2 /IGZO heterojunction structure, various synaptic behaviors are successfully emulated such as short-term memory/long-term memory and paired pulse facilitation. Also, the TiO2 /IGZO synaptic transistor exhibits a recognition rate up to 90.3% in recognizing handwritten digit images. Moreover, by regulating the photocarrier dynamics and retention behavior using gate-bias modulation, a reconfigurable multilevel (≥8 states) memory is demonstrated using visible light.
Collapse
Affiliation(s)
- Jeehoon Kim
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Seungho Song
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea
- Center for Opto-Electronic Materials and Devices, Post-Silicon Semiconductor Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
| | - Jong-Min Lee
- School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, 06974, Republic of Korea
| | - San Nam
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| | - Jaehyun Kim
- Department of Chemistry and Materials Research Center, Northwestern University, 2145 Sheridan Road, Evanston, IL, 60208, USA
| | - Do Kyung Hwang
- Center for Opto-Electronic Materials and Devices, Post-Silicon Semiconductor Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
- Division of Nanoscience and Technology, KIST School, University of Science and Technology (UST), Seoul, 02792, Republic of Korea
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul, 02841, Republic of Korea
| | - Sung Kyu Park
- School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, 06974, Republic of Korea
| | - Yong-Hoon Kim
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea
| |
Collapse
|
11
|
Shao L, Xu X, Liu Y, Zhao Y. Adaptive Memory of a Neuromorphic Transistor with Multi-Sensory Signal Fusion. ACS APPLIED MATERIALS & INTERFACES 2023; 15:35272-35279. [PMID: 37461139 DOI: 10.1021/acsami.3c06429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
One of the ultimate goals of artificial intelligence is to achieve the capability of memory evolution and adaptability to changing environments, which is termed adaptive memory. To realize adaptive memory in artificial neuromorphic devices, artificial synapses with multi-sensing capability are required to collect and analyze various sensory cues from the external changing environments. However, due to the lack of platforms for mediating multiple sensory signals, most artificial synapses have been mainly limited to unimodal or bimodal sensory devices. Herein, we present a multi-modal artificial sensory synapse (MASS) based on an organic synapse to realize sensory fusion and adaptive memory. The MASS receives optical, electrical, and pressure information and in turn generates typical synaptic behaviors, mimicking the multi-sensory neurons in the brain. Sophisticated synaptic behaviors, such as Pavlovian dogs, writing/erasing, signal accumulation, and offset, were emulated to demonstrate the joint efforts of bimodal sensory cues. Moreover, associative memory can be formed in the device and be subsequently reshaped by signals from a third perception, mimicking modification of the memory and cognition when encountering a new environment. Our MASS provides a step toward next-generation artificial neural networks with an adaptive memory capability.
Collapse
Affiliation(s)
- Lin Shao
- Laboratory of Molecular Materials and Devices, Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
| | - Xinzhao Xu
- Laboratory of Molecular Materials and Devices, Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
| | - Yunqi Liu
- Laboratory of Molecular Materials and Devices, Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
| | - Yan Zhao
- Laboratory of Molecular Materials and Devices, Department of Materials Science, Fudan University, Shanghai 200433, P. R. China
| |
Collapse
|
12
|
Oh J, Yang SY, Kim S, Lee C, Cha JH, Jang BC, Im SG, Choi SY. Imidazole-based artificial synapses for neuromorphic computing: a cluster-type conductive filament via controllable nanocluster nucleation. MATERIALS HORIZONS 2023; 10:2035-2046. [PMID: 37039721 DOI: 10.1039/d2mh01522f] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Memristive synapses based on conductive bridging RAMs (CBRAMs) utilize a switching layer having low binding energy with active metals for excellent analog conductance modulation, but the resulting unstable conductive filaments cause fluctuation and drift of the conductance. This tunability-stability dilemma makes it difficult to implement practical neuromorphic computing. A novel method is proposed to enhance the stability and controllability of conductive filaments by introducing imidazole groups that boost the nucleation of Cu nanoclusters in the ultrathin polymer switching layer through the initiated chemical vapor deposition (iCVD) process. It is confirmed that conductive filaments based on nanoclusters with specific gaps are generated in the copolymer medium using this method. Furthermore, by modulating the tunneling gaps, an ultra-wide conductance range of analog tunable conductive filaments is achieved from several hundreds of nS to a few mS with a sub-1 V driving voltage. Through this, both reliable and stable analog switching are achieved with low cycle-to-cycle and device-to-device weight update variations and separable state retention with 32 states. This approach paves the way for the extension of state availability in synaptic devices to overcome the tunability-stability dilemma, which is essential for the synaptic elements in neuromorphic systems.
Collapse
Affiliation(s)
- Jungyeop Oh
- School of Electrical Engineering, Graphene/2D Materials Research Center, KAIST, Daejeon 34141, Korea.
| | - Sang Yoon Yang
- School of Electrical Engineering, Graphene/2D Materials Research Center, KAIST, Daejeon 34141, Korea.
| | - Sungkyu Kim
- Department of Nanotechnology and Advanced Materials Engineering, Sejong University, Seoul, 05006, Korea
| | - Changhyeon Lee
- Department of Chemical and Biomolecular Engineering, Graphene/2D Materials research Center, KAIST, Daejeon 34141, Korea
| | - Jun-Hwe Cha
- School of Electrical Engineering, Graphene/2D Materials Research Center, KAIST, Daejeon 34141, Korea.
| | - Byung Chul Jang
- School of Electronics Engineering, Kyungpook National University, Daegu, 41566, Korea
| | - Sung Gap Im
- Department of Chemical and Biomolecular Engineering, Graphene/2D Materials research Center, KAIST, Daejeon 34141, Korea
| | - Sung-Yool Choi
- School of Electrical Engineering, Graphene/2D Materials Research Center, KAIST, Daejeon 34141, Korea.
| |
Collapse
|
13
|
Liu X, Sun C, Guo Z, Xia X, Jiang Q, Ye X, Shang J, Zhang Y, Zhu X, Li RW. Near-Sensor Reservoir Computing for Gait Recognition via a Multi-Gate Electrolyte-Gated Transistor. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2300471. [PMID: 36950731 DOI: 10.1002/advs.202300471] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/23/2023] [Indexed: 05/27/2023]
Abstract
The recent emergence of various smart wearable electronics has furnished the rapid development of human-computer interaction, medical health monitoring technologies, etc. Unfortunately, processing redundant motion and physiological data acquired by multiple wearable sensors using conventional off-site digital computers typically result in serious latency and energy consumption problems. In this work, a multi-gate electrolyte-gated transistor (EGT)-based reservoir device for efficient multi-channel near-sensor computing is reported. The EGT, exhibiting rich short-term dynamics under voltage modulation, can implement nonlinear parallel integration of the time-series signals thus extracting the temporal features such as the synchronization state and collective frequency in the inputs. The flexible EGT integrated with pressure sensors can perform on-site gait information analysis, enabling the identification of motion behaviors and Parkinson's disease. This near-sensor reservoir computing system offers a new route for rapid analysis of the motion and physiological signals with significantly improved efficiency and will lead to robust smart flexible wearable electronics.
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
| | - 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
| | - Zhecheng Guo
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China
| | - Xiangling Xia
- 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
| | - Qian Jiang
- 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
| | - 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
- College of Materials Sciences and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jie Shang
- 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
| | - Yuejun Zhang
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, 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
| | - 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
|
14
|
Ge S, Sang D, Zou L, Yao Y, Zhou C, Fu H, Xi H, Fan J, Meng L, Wang C. A Review on the Progress of Optoelectronic Devices Based on TiO 2 Thin Films and Nanomaterials. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:1141. [PMID: 37049236 PMCID: PMC10096923 DOI: 10.3390/nano13071141] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 03/18/2023] [Accepted: 03/21/2023] [Indexed: 06/19/2023]
Abstract
Titanium dioxide (TiO2) is a kind of wide-bandgap semiconductor. Nano-TiO2 devices exhibit size-dependent and novel photoelectric performance due to their quantum limiting effect, high absorption coefficient, high surface-volume ratio, adjustable band gap, etc. Due to their excellent electronic performance, abundant presence, and high cost performance, they are widely used in various application fields such as memory, sensors, and photodiodes. This article provides an overview of the most recent developments in the application of nanostructured TiO2-based optoelectronic devices. Various complex devices are considered, such as sensors, photodetectors, light-emitting diodes (LEDs), storage applications, and field-effect transistors (FETs). This review of recent discoveries in TiO2-based optoelectronic devices, along with summary reviews and predictions, has important implications for the development of transitional metal oxides in optoelectronic applications for researchers.
Collapse
Affiliation(s)
- Shunhao Ge
- Shandong Key Laboratory of Optical Communication Science and Technology, School of Physics Science and Information Technology, Liaocheng University, Liaocheng 252000, China
| | - Dandan Sang
- Shandong Key Laboratory of Optical Communication Science and Technology, School of Physics Science and Information Technology, Liaocheng University, Liaocheng 252000, China
| | - Liangrui Zou
- Shandong Key Laboratory of Optical Communication Science and Technology, School of Physics Science and Information Technology, Liaocheng University, Liaocheng 252000, China
| | - Yu Yao
- Shandong Key Laboratory of Optical Communication Science and Technology, School of Physics Science and Information Technology, Liaocheng University, Liaocheng 252000, China
| | - Chuandong Zhou
- Shandong Key Laboratory of Optical Communication Science and Technology, School of Physics Science and Information Technology, Liaocheng University, Liaocheng 252000, China
| | - Hailong Fu
- Zhejiang Province Key Laboratory of Quantum Technology and Device, Department of Physics, Zhejiang University, Hangzhou 310027, China
| | - Hongzhu Xi
- Anhui Huadong Photoelectric Technology Research Institute, Wuhu 241002, China
| | - Jianchao Fan
- Shandong Liaocheng Laixin Powder Materials Science and Technology Co., Ltd., Liaocheng 252000, China
| | - Lijian Meng
- Instituto Superior de Engenharia do Porto, Polytechnic of Porto, Rua António Bernardino de Almeida, 4249-015 Porto, Portugal
| | - Cong Wang
- College of Mathematics and Physics, Beijing University of Chemical Technology, Beijing 100029, China
| |
Collapse
|
15
|
Patil H, Kim H, Kadam KD, Rehman S, Patil SA, Aziz J, Dongale TD, Ali Sheikh Z, Khalid Rahmani M, Khan MF, Kim DK. Flexible Organic-Inorganic Halide Perovskite-Based Diffusive Memristor for Artificial Nociceptors. ACS APPLIED MATERIALS & INTERFACES 2023; 15:13238-13248. [PMID: 36867070 DOI: 10.1021/acsami.2c16481] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
With the current evolution in the artificial intelligence technology, more biomimetic functions are essential to execute increasingly complicated tasks and respond to challenging work environments. Therefore, an artificial nociceptor plays a significant role in the advancement of humanoid robots. Organic-inorganic halide perovskites (OHPs) have the potential to mimic the biological neurons due to their inherent ion migration. Herein, a versatile and reliable diffusive memristor built on an OHP is reported as an artificial nociceptor. This OHP diffusive memristor showed threshold switching properties with excellent uniformity, forming-free behavior, a high ION/IOFF ratio (104), and bending endurance over >102 cycles. To emulate the biological nociceptor functionalities, four significant characteristics of the artificial nociceptor, such as threshold, no adaptation, relaxation, and sensitization, are demonstrated. Further, the feasibility of OHP nociceptors in artificial intelligence is being investigated by fabricating a thermoreceptor system. These findings suggest a prospective application of an OHP-based diffusive memristor in the future neuromorphic intelligence platform.
Collapse
Affiliation(s)
- Harshada Patil
- Department of Electrical Engineering, Sejong University, 209-Neungdong-ro, Gwangjin-gu, 05006 Seoul, Republic of Korea
| | - Honggyun Kim
- Department of Electrical Engineering, Sejong University, 209-Neungdong-ro, Gwangjin-gu, 05006 Seoul, Republic of Korea
| | - Kalyani D Kadam
- Department of Electrical Engineering, Sejong University, 209-Neungdong-ro, Gwangjin-gu, 05006 Seoul, Republic of Korea
- Department of Convergence Engineering for Intelligent Drone, Sejong University, 05006 Seoul, Republic of Korea
| | - Shania Rehman
- Department of Electrical Engineering, Sejong University, 209-Neungdong-ro, Gwangjin-gu, 05006 Seoul, Republic of Korea
| | - Supriya A Patil
- Department of Nanotechnology and Advanced Materials Engineering, Sejong University, Seoul 05006, Republic of Korea
| | - Jamal Aziz
- Department of Electrical Engineering, Sejong University, 209-Neungdong-ro, Gwangjin-gu, 05006 Seoul, Republic of Korea
| | - Tukaram D Dongale
- Computational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416004, India
| | - Zulfqar Ali Sheikh
- Department of Electrical Engineering, Sejong University, 209-Neungdong-ro, Gwangjin-gu, 05006 Seoul, Republic of Korea
- Department of Convergence Engineering for Intelligent Drone, Sejong University, 05006 Seoul, Republic of Korea
| | - Mehr Khalid Rahmani
- School of Electronics Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea
| | - Muhammad Farooq Khan
- Department of Electrical Engineering, Sejong University, 209-Neungdong-ro, Gwangjin-gu, 05006 Seoul, Republic of Korea
| | - Deok-Kee Kim
- Department of Electrical Engineering, Sejong University, 209-Neungdong-ro, Gwangjin-gu, 05006 Seoul, Republic of Korea
- Department of Convergence Engineering for Intelligent Drone, Sejong University, 05006 Seoul, Republic of Korea
| |
Collapse
|
16
|
Shan X, Wu Z, Xie Y, Lin X, Zhou B, Zhang Y, Yan X, Ren T, Wang F, Zhang K. Centimetre-scale single crystal α-MoO 3: oxygen assisted self-standing growth and low-energy consumption synaptic devices. NANOSCALE 2023; 15:1200-1209. [PMID: 36533724 DOI: 10.1039/d2nr04530c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
High-density storage and neuromorphic devices based on 2D materials are hindered by large-scale growth. Moreover, the lack of a mature mechanism makes it difficult to obtain high-quality single crystals in large-scale 2D materials. In this work, we prepared a centimeter-scale single crystal α-MoO3via an oxygen assisted substrate-free self-standing growth method and mechanism and constructed high-performance synaptic devices based on the centimeter-scale α-MoO3. The oxygen assisted growth mechanism of α-MoO3 was developed from the periodic bond chain theory. The large-scale α-MoO3 is up to 2 cm and exhibits high homogeneity and single crystalline characteristic. Furthermore, with an optimized oxygen partial pressure (18%), the centimeter-scale α-MoO3 makes the as-prepared memristor achieve continuous conductance modulation. Moreover, the trap-controlled electron conducting mechanism of the memristor was demonstrated through I-V curve fitting analysis at various temperatures, in which the high resistance state section demonstrates space-charge-limited conduction (SCLC) mode. Moreover, the as-prepared α-MoO3 memristors exhibit low-energy consumption and well emulate the essential synaptic behaviors including excitatory/inhibitory postsynaptic current, paired-pulse facilitation and long-term plasticity.
Collapse
Affiliation(s)
- Xin Shan
- School of Materials Science and Engineering, Tianjin University of Technology, Tianjin 300384, China
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.
| | - Zeyu Wu
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.
| | - Yangyang Xie
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.
| | - Xin Lin
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.
| | - Baozeng Zhou
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.
| | - Yupeng Zhang
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.
| | - Xiaobing Yan
- College of Electronic and Information Engineering, Hebei University, Baoding 071000, China
| | - Tianling Ren
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Fang Wang
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.
| | - Kailiang Zhang
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin 300384, China.
| |
Collapse
|
17
|
Wang WS, Zhu LQ. Recent advances in neuromorphic transistors for artificial perception applications: FOCUS ISSUE REVIEW. SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS 2022; 24:10-41. [PMID: 36605031 PMCID: PMC9809405 DOI: 10.1080/14686996.2022.2152290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/09/2022] [Accepted: 11/22/2022] [Indexed: 06/17/2023]
Abstract
Conventional von Neumann architecture is insufficient in establishing artificial intelligence (AI) in terms of energy efficiency, computing in memory and dynamic learning. Delightedly, rapid developments in neuromorphic computing provide a new paradigm to solve this dilemma. Furthermore, neuromorphic devices that can realize synaptic plasticity and neuromorphic function have extraordinary significance for neuromorphic system. A three-terminal neuromorphic transistor is one of the typical representatives. In addition, human body has five senses, including vision, touch, auditory sense, olfactory sense and gustatory sense, providing abundant information for brain. Inspired by the human perception system, developments in artificial perception system will give new vitality to intelligent robots. This review discusses the operation mechanism, function and application of neuromorphic transistors. The latest progresses in artificial perception systems based on neuromorphic transistors are provided. Finally, the opportunities and challenges of artificial perception systems are summarized.
Collapse
Affiliation(s)
- Wei Sheng Wang
- School of Physical Science and Technology, Ningbo University, Ningbo, Zhejiang, People’s Republic of China
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang, People’s Republic of China
| | - Li Qiang Zhu
- School of Physical Science and Technology, Ningbo University, Ningbo, Zhejiang, People’s Republic of China
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang, People’s Republic of China
| |
Collapse
|
18
|
Ni Y, Liu L, Liu J, Xu W. A High-Strength Neuromuscular System That Implements Reflexes as Controlled by a Multiquadrant Artificial Efferent Nerve. ACS NANO 2022; 16:20294-20304. [PMID: 36318482 DOI: 10.1021/acsnano.2c06122] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
We demonstrate an artificial efferent nerve that distinguishes environment-responsive conditioned and unconditioned reflexes, i.e., hand-retraction reflex and muscle memory, respectively. These reflex modes are immediately switchable by altering the polarity of charge carriers in a parallel-channeled artificial synapse; this ability emulates multiplexed neurotransmission of different neurotransmitters to form glutamine-induced short-term plasticity and acetylcholine-induced long-term plasticity. This is the successful control of high-strength artificial muscle fibers by using an artificial efferent nerve to form a neuromuscular system that can realize curvature and force simultaneously and in which all these aspects far surpass currently available neuromuscular systems. Furthermore, the special four-quadrant information-processing mechanism of our artificial efferent nerve allows complex application extensions, i.e., relative-position tracking of sound sources, immediate switchable learning modes between fast information processing and long-term memory, and high-accuracy pattern cognition. This work is a step toward development of human-compatible artificial neuromuscular systems.
Collapse
Affiliation(s)
- Yao Ni
- Institute of Optoelectronic Thin Film Devices and Technology, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, College of Electronic Information and Optical Engineering, National Institute for Advanced Materials, Nankai University, Tianjin 300350, China
- Shenzhen Research Institute of Nankai University, Nankai University, Shenzhen 518000, China
| | - Lu Liu
- Institute of Optoelectronic Thin Film Devices and Technology, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, College of Electronic Information and Optical Engineering, National Institute for Advanced Materials, Nankai University, Tianjin 300350, China
- Shenzhen Research Institute of Nankai University, Nankai University, Shenzhen 518000, China
| | - Jiaqi Liu
- Institute of Optoelectronic Thin Film Devices and Technology, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, College of Electronic Information and Optical Engineering, National Institute for Advanced Materials, Nankai University, Tianjin 300350, China
- Shenzhen Research Institute of Nankai University, Nankai University, Shenzhen 518000, China
| | - Wentao Xu
- Institute of Optoelectronic Thin Film Devices and Technology, Key Laboratory of Optoelectronic Thin Film Devices and Technology of Tianjin, College of Electronic Information and Optical Engineering, National Institute for Advanced Materials, Nankai University, Tianjin 300350, China
- Shenzhen Research Institute of Nankai University, Nankai University, Shenzhen 518000, China
| |
Collapse
|
19
|
Chen Z, Yu R, Yu X, Li E, Wang C, Liu Y, Guo T, Chen H. Bioinspired Artificial Motion Sensory System for Rotation Recognition and Rapid Self-Protection. ACS NANO 2022; 16:19155-19164. [PMID: 36269153 DOI: 10.1021/acsnano.2c08328] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
As one of the most common synergies between the exteroceptors and proprioceptors, the synergy between visual and vestibule enables the human brain to judge the state of human motion, which is essential for motion recognition and human self-protection. Hence, in this work, an artificial motion sensory system (AMSS) based on artificial vestibule and visual is developed, which consists of a tribo-nanogenerator (TENG) as a vestibule that can sense rotation and synaptic transistor array as retina. The principle of temporal congruency has been successfully realized by multisensory input. In addition, pattern recognition results show that the accuracy of multisensory integration is more than 15% higher than that of single sensory. Moreover, due to the rotation recognition and visual recognition functions of AMSS, we realized multimodal information recognition including angles and numbers in the spiking correlated neural network (SCNN), and the accuracy rate reached 89.82%. Besides, the rapid self-protection of a human was successfully realized by AMSS in the case of simulated amusement rides, and the reaction time of multiple motion sensory integration is only one-third of that of a single vestibule. The development of AMSS based on the synergy of simulated vision and vestibule will show great potential in neural robot, artificial limbs, and soft electronics.
Collapse
Affiliation(s)
- Zhenjia Chen
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou350002, China
| | - Rengjian Yu
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou350002, China
| | - Xipeng Yu
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou350002, China
| | - Enlong Li
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou350002, China
| | - Congyong Wang
- Joint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou350207, China
- Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore117543, Singapore
| | - Yaqian Liu
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou350002, China
| | - Tailiang Guo
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou350002, China
- Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou350100, China
| | - Huipeng Chen
- Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou350002, China
- Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou350100, China
| |
Collapse
|
20
|
Wei Y, Liu W, Yu J, Li Y, Wang Y, Huo Z, Cheng L, Feng Z, Sun J, Sun Q, Wang ZL. Triboelectric Potential Powered High-Performance Organic Transistor Array. ACS NANO 2022; 16:19199-19209. [PMID: 36354955 DOI: 10.1021/acsnano.2c08420] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Triboelectric potential gated transistors have inspired various applications toward mechanical behavior controlled logic circuits, multifunctional sensors, artificial sensory neurons, etc. Their rapid development urgently calls for high-performance devices and corresponding figure of merits to standardize the tribotronic gating properties. Organic semiconductors paired with solution processability promise low-cost manufacture of high-performance tribotronic transistor devices/arrays. Here, we demonstrate a record high-performance tribotronic transistor array composed of an integrated triboelectric nanogenerator (TENG) and a large-area device array of C8-BTBT-PS transistors. The working mechanism of effective triboelectric potential gating is elaborately explained from the aspect of conjugated energy bands of the contact-electrification mediums and organic semiconductors. Driven by the triboelectric potential, the tribotronic transistor shows superior properties of record high current on/off ratios (>108), a steep subthreshold swing (29.89 μm/dec), high stability, and excellent reproducibility. Moreover, tribotronic logic devices modulated by mechanical displacement have also been demonstrated with good stability and a high gain of 1260 V/mm. The demonstrated large-area tribotronic transistor array of organic semiconductor exhibits record high performance and offers an effective R&D platform for mechano-driven electronic terminals, interactive intelligent system, artificial robotic skin, etc.
Collapse
Affiliation(s)
- Yichen Wei
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing101400, P. R. China
- Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, 530004, P. R. China
| | - Wanrong Liu
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, 410083, P. R. China
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, Changsha, 410083, P. R. China
| | - Jinran Yu
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing101400, P. R. China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing100049, P. R. China
| | - Yonghai Li
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing101400, P. R. China
- Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, 530004, P. R. China
| | - Yifei Wang
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing101400, P. R. China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing100049, P. R. China
| | - Ziwei Huo
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing101400, P. R. China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing100049, P. R. China
| | - Liuqi Cheng
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing101400, P. R. China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing100049, P. R. China
| | - Zhenyu Feng
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing101400, P. R. China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing100049, P. R. China
| | - Jia Sun
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, Changsha, 410083, P. R. China
- Hunan Key Laboratory of Nanophotonics and Devices, School of Physics and Electronics, Central South University, Changsha, 410083, P. R. China
| | - Qijun Sun
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing101400, P. R. China
- Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, 530004, P. R. China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing100049, P. R. China
- Shandong Zhongke Naneng Energy Technology Co., Ltd., Dongying, 257061, P. R. China
| | - Zhong Lin Wang
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing101400, P. R. China
- Georgia Institute of Technology, Atlanta, Georgia30332-0245, United States
| |
Collapse
|
21
|
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.
Collapse
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
| |
Collapse
|
22
|
A low-power stretchable neuromorphic nerve with proprioceptive feedback. Nat Biomed Eng 2022; 7:511-519. [PMID: 35970931 DOI: 10.1038/s41551-022-00918-x] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 06/29/2022] [Indexed: 11/08/2022]
Abstract
By relaying neural signals from the motor cortex to muscles, devices for neurorehabilitation can enhance the movement of limbs in which nerves have been damaged as a consequence of injuries affecting the spinal cord or the lower motor neurons. However, conventional neuroprosthetic devices are rigid and power-hungry. Here we report a stretchable neuromorphic implant that restores coordinated and smooth motions in the legs of mice with neurological motor disorders, enabling the animals to kick a ball, walk or run. The neuromorphic implant acts as an artificial efferent nerve by generating electrophysiological signals from excitatory post-synaptic signals and by providing proprioceptive feedback. The device operates at low power (~1/150 that of a typical microprocessor system), and consists of hydrogel electrodes connected to a stretchable transistor incorporating an organic semiconducting nanowire (acting as an artificial synapse), connected via an ion gel to an artificial proprioceptor incorporating a carbon nanotube strain sensor (acting as an artificial muscle spindle). Stretchable electronics with proprioceptive feedback may inspire the further development of advanced neuromorphic devices for neurorehabilitation.
Collapse
|
23
|
Jin C, Liu W, Xu Y, Huang Y, Nie Y, Shi X, Zhang G, He P, Zhang J, Cao H, Sun J, Yang J. Artificial Vision Adaption Mimicked by an Optoelectrical In 2O 3 Transistor Array. NANO LETTERS 2022; 22:3372-3379. [PMID: 35343229 DOI: 10.1021/acs.nanolett.2c00599] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Simulation of biological visual perception has gained considerable attention. In this paper, an optoelectrical In2O3 transistor array with a negative photoconductivity behavior is designed using a side-gate structure and a screen-printed ion-gel as the gate insulator. This paper is the first to observe a negative photoconductivity in electrolyte-gated oxide devices. Furthermore, an artificial visual perception system capable of self-adapting to environmental lightness is mimicked using the proposed device array. The transistor device array shows a self-adaptive behavior of light under different levels of light intensity, successfully demonstrating the visual adaption with an adjustable threshold range to the external environment. This study provides a new way to create an environmentally adaptive artificial visual perception system and has far-reaching significance for the future of neuromorphic electronics.
Collapse
Affiliation(s)
- Chenxing Jin
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China
- 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
| | - Wanrong Liu
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China
- 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
| | - Yunchao Xu
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China
- 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
| | - Yulong Huang
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China
- 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
| | - Yiling Nie
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China
- 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
| | - Xiaofang Shi
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China
- 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
| | - Gengming Zhang
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China
- 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
| | - Pei He
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China
- 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
| | - Jia Sun
- Hunan Key Laboratory for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China
- 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 for Super Microstructure and Ultrafast Process, School of Physics and Electronics, Central South University, 932 South Lushan Road, Changsha, Hunan 410083, P. R. China
- 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
| |
Collapse
|
24
|
Sun L, Du Y, Yu H, Wei H, Xu W, Xu W. An Artificial Reflex Arc That Perceives Afferent Visual and Tactile Information and Controls Efferent Muscular Actions. Research (Wash D C) 2022; 2022:9851843. [PMID: 35252874 PMCID: PMC8858381 DOI: 10.34133/2022/9851843] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 01/10/2022] [Indexed: 01/01/2023] Open
Abstract
Neural perception and action-inspired electronics is becoming important for interactive human-machine interfaces and intelligent robots. A system that implements neuromorphic environmental information coding, synaptic signal processing, and motion control is desired. We report a neuroinspired artificial reflex arc that possesses visual and somatosensory dual afferent nerve paths and an efferent nerve path to control artificial muscles. A self-powered photoelectric synapse between the afferent and efferent nerves was used as the key information processor. The artificial reflex arc successfully responds to external visual and tactile information and controls the actions of artificial muscle in response to these external stimuli and thus emulates reflex activities through a full reflex arc. The visual and somatosensory information is encoded as impulse spikes, the frequency of which exhibited a sublinear dependence on the obstacle proximity or pressure stimuli. The artificial reflex arc suggests a promising strategy toward developing soft neurorobotic systems and prostheses.
Collapse
Affiliation(s)
- Lin Sun
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Tianjin 300350, China.,Key Laboratory of Photoelectronic Thin Film Devices and Technology of Tianjin, Tianjin 300350, China.,Engineering Research Center of Thin Film Photoelectronic Technology, Ministry of Education, Tianjin 300350, China.,National Institute for Advanced Materials, Tianjin 300350, China
| | - Yi Du
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Tianjin 300350, China.,Key Laboratory of Photoelectronic Thin Film Devices and Technology of Tianjin, Tianjin 300350, China.,Engineering Research Center of Thin Film Photoelectronic Technology, Ministry of Education, Tianjin 300350, China.,National Institute for Advanced Materials, Tianjin 300350, China
| | - Haiyang Yu
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Tianjin 300350, China.,Key Laboratory of Photoelectronic Thin Film Devices and Technology of Tianjin, Tianjin 300350, China.,Engineering Research Center of Thin Film Photoelectronic Technology, Ministry of Education, Tianjin 300350, China.,National Institute for Advanced Materials, Tianjin 300350, China
| | - Huanhuan Wei
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Tianjin 300350, China.,Key Laboratory of Photoelectronic Thin Film Devices and Technology of Tianjin, Tianjin 300350, China.,Engineering Research Center of Thin Film Photoelectronic Technology, Ministry of Education, Tianjin 300350, China.,National Institute for Advanced Materials, Tianjin 300350, China
| | - Wenlong Xu
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Tianjin 300350, China.,Key Laboratory of Photoelectronic Thin Film Devices and Technology of Tianjin, Tianjin 300350, China.,Engineering Research Center of Thin Film Photoelectronic Technology, Ministry of Education, Tianjin 300350, China.,National Institute for Advanced Materials, Tianjin 300350, China
| | - Wentao Xu
- Institute of Photoelectronic Thin Film Devices and Technology of Nankai University, Tianjin 300350, China.,Key Laboratory of Photoelectronic Thin Film Devices and Technology of Tianjin, Tianjin 300350, China.,Engineering Research Center of Thin Film Photoelectronic Technology, Ministry of Education, Tianjin 300350, China.,National Institute for Advanced Materials, Tianjin 300350, China
| |
Collapse
|
25
|
Jin SM, Hwang JH, Lim JA, Lee E. Precrystalline P3HT nanowires: growth-controllable solution processing and effective molecular packing transfer to thin-film. CrystEngComm 2022. [DOI: 10.1039/d1ce01536b] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Solution-processable precrystalline nanowires (NWs) of conjugated polymers (CPs) have garnered significant attention in fundamental research based on crystallization-driven self-assembly and in the roll-to-roll fabrication of optoelectronic devices such as organic...
Collapse
|
26
|
Wang Y, Gong Y, Huang S, Xing X, Lv Z, Wang J, Yang JQ, Zhang G, Zhou Y, Han ST. Memristor-based biomimetic compound eye for real-time collision detection. Nat Commun 2021; 12:5979. [PMID: 34645801 PMCID: PMC8514515 DOI: 10.1038/s41467-021-26314-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 09/29/2021] [Indexed: 11/18/2022] Open
Abstract
The lobula giant movement detector (LGMD) is the movement-sensitive, wide-field visual neuron positioned in the third visual neuropile of lobula. LGMD neuron can anticipate collision and trigger avoidance efficiently owing to the earlier occurring firing peak before collision. Vision chips inspired by the LGMD have been successfully implemented in very-large-scale-integration (VLSI) system. However, transistor-based chips and single devices to simulate LGMD neurons make them bulky, energy-inefficient and complicated. The devices with relatively compact structure and simple operation mode to mimic the escape response of LGMD neuron have not been realized yet. Here, the artificial LGMD visual neuron is implemented using light-mediated threshold switching memristor. The non-monotonic response to light flow field originated from the formation and break of Ag conductive filaments is analogue to the escape response of LGMD neuron. Furthermore, robot navigation with obstacle avoidance capability and biomimetic compound eyes with wide field-of-view (FoV) detection capability are demonstrated.
Collapse
Affiliation(s)
- Yan Wang
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
- Hefei Innovation Research Institute, School of Microelectronics, Beihang University, 230013, Hefei, P. R. China
| | - Yue Gong
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Shenming Huang
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Xuechao Xing
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Ziyu Lv
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Junjie Wang
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Jia-Qin Yang
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Guohua Zhang
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Ye Zhou
- Institute for Advanced Study, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Su-Ting Han
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China.
| |
Collapse
|
27
|
Mu B, Guo L, Liao J, Xie P, Ding G, Lv Z, Zhou Y, Han ST, Yan Y. Near-Infrared Artificial Synapses for Artificial Sensory Neuron System. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2021; 17:e2103837. [PMID: 34418276 DOI: 10.1002/smll.202103837] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/10/2021] [Indexed: 06/13/2023]
Abstract
The computing based on artificial neuron network is expected to break through the von Neumann bottleneck of traditional computer, and to greatly improve the computing efficiency, displaying a broad prospect in the application of artificial visual system. In the specific structural layout, it is a common method to connect the discrete photodetector with the artificial neuron in series, which enhances the complexity of signal recognition, conversion and storage. In this work, organic small molecule IR-780 iodide is inserted into the memory device as both the charge trapping layer and near-infrared (NIR) photoresponsive film. Through electrical and optical regulation, artificial synaptic functions including short-term plasticity, long-term plasticity, and spike rate dependence are realized. In the established artificial sensory neuron system, NIR optical pulses can significantly improve the spiking rate. Moreover, the spiking neural networks are further constructed by simulation for handwritten digit classification. This research may contribute to the development of light driven neural robots, optical signal encryption, and neural computing.
Collapse
Affiliation(s)
- Boyuan Mu
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
- School of Intelligent Construction, Wuchang University of Technology, Wuhan, 430000, P. R. China
| | - Liangchao Guo
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Junhong Liao
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Peng Xie
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Guanglong Ding
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Ziyu Lv
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Ye Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Su-Ting Han
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Yan Yan
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, P. R. China
| |
Collapse
|
28
|
Martins L, Jenkins AS, Alvarez LSE, Borme J, Böhnert T, Ventura J, Freitas PP, Ferreira R. Non-volatile artificial synapse based on a vortex nano-oscillator. Sci Rep 2021; 11:16094. [PMID: 34373533 PMCID: PMC8352962 DOI: 10.1038/s41598-021-95569-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 07/07/2021] [Indexed: 02/07/2023] Open
Abstract
In this work, a new mechanism to combine a non-volatile behaviour with the spin diode detection of a vortex-based spin torque nano-oscillator (STVO) is presented. Experimentally, it is observed that the spin diode response of the oscillator depends on the vortex chirality. Consequently, fixing the frequency of the incoming signal and switching the vortex chirality results in a different rectified voltage. In this way, the chirality can be deterministically controlled via the application of electrical signals injected locally in the device, resulting in a non-volatile control of the output voltage for a given input frequency. Micromagnetic simulations corroborate the experimental results and show the main contribution of the Oersted field created by the input RF current density in defining two distinct spin diode detections for different chiralities. By using two non-identical STVOs, we show how these devices can be used as programmable non-volatile synapses in artificial neural networks.
Collapse
Affiliation(s)
- Leandro Martins
- grid.420330.60000 0004 0521 6935INL, Avenida Mestre José Veiga, s/n, 4715-330 Braga, Portugal ,grid.5808.50000 0001 1503 7226IFIMUP-IN, Rua do Campo Alegre, 678, 4169-007 Porto, Portugal
| | - Alex S. Jenkins
- grid.420330.60000 0004 0521 6935INL, Avenida Mestre José Veiga, s/n, 4715-330 Braga, Portugal
| | | | - Jérôme Borme
- grid.420330.60000 0004 0521 6935INL, Avenida Mestre José Veiga, s/n, 4715-330 Braga, Portugal
| | - Tim Böhnert
- grid.420330.60000 0004 0521 6935INL, Avenida Mestre José Veiga, s/n, 4715-330 Braga, Portugal
| | - João Ventura
- grid.5808.50000 0001 1503 7226IFIMUP-IN, Rua do Campo Alegre, 678, 4169-007 Porto, Portugal
| | - Paulo P. Freitas
- grid.420330.60000 0004 0521 6935INL, Avenida Mestre José Veiga, s/n, 4715-330 Braga, Portugal
| | - Ricardo Ferreira
- grid.420330.60000 0004 0521 6935INL, Avenida Mestre José Veiga, s/n, 4715-330 Braga, Portugal
| |
Collapse
|
29
|
Li MZ, Guo LC, Ding GL, Zhou K, Xiong ZY, Han ST, Zhou Y. Inorganic Perovskite Quantum Dot-Based Strain Sensors for Data Storage and In-Sensor Computing. ACS APPLIED MATERIALS & INTERFACES 2021; 13:30861-30873. [PMID: 34164986 DOI: 10.1021/acsami.1c07928] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Although remarkable improvement has been achieved in stretchable strain sensors, challenges still exist in aspects including intelligent sensing, simultaneous data processing, and scalable fabrication techniques. In this work, a strain-sensitive device is presented by fabricating a CsPbBr3 quantum dots (QDs) floating-gate field-effect transistor (FET) sensing array on thin polyimide (PI) films. The FET exhibits an excellent on/off ratio (>103) and a large memory window (>2 V). With the introduction of CsPbBr3 QDs as the trapping layer, an additional UV response is obtained because of the photogenerated charge carriers that significantly enhance the source-drain current (IDS) of the device. At each electrical state, the IDS varies with the strains and the sensing range is from compressive +12.5% to tensile -10.8%. Excellent data retainability and mechanical durability demonstrate the high quality and reliability of the fabricated sensors. Furthermore, synapse functions including long-term potentiation (LTP), long-term depression (LTD), etc., are emulated at the device level. Linearity factor changes of LTP/LTD in different sensing scenarios demonstrate the reliability of the device and further confirm the different sensing mechanisms with/without UV illumination. Our results exhibit the potential of transistor-based devices for multifunctional intelligent sensing.
Collapse
Affiliation(s)
- Ming-Zheng Li
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, P. R. China
| | - Liang-Chao Guo
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, P. R. China
| | - Guang-Long Ding
- Institute for Advanced Study, Shenzhen University, Shenzhen 518060, P. R. China
| | - Kui Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen 518060, P. R. China
| | - Zi-Yu Xiong
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, P. R. China
| | - Su-Ting Han
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, P. R. China
| | - Ye Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen 518060, P. R. China
| |
Collapse
|