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Lee W, Kim T, Kim H, Kim Y. Controlled Migration of Lithium Cations by Diamine Bridges in Water-Processable Polymer-Based Solid-State Electrolyte Memory Layers for Organic Synaptic Transistors. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2403645. [PMID: 39011779 DOI: 10.1002/adma.202403645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 05/30/2024] [Indexed: 07/17/2024]
Abstract
Synaptic transistors require sufficient retention (memory) performances of current signals to exactly mimic biological synapses. Ion migration has been proposed to achieve high retention characteristics but less attention has been paid to polymer-based solid-state electrolytes (SSEs) for organic synaptic transistors (OSTRs). Here, OSTRs with water-processable polymer-based SSEs, featuring ion migration-controllable molecular bridges, which are prepared by reactions of poly(4-styrenesulfonic acid) (PSSA), diethylenetriamine (DETA), and lithium hydroxide (LiOH) are demonstrated. The ion conductivity of PSSA:LiOH:DETA (1:0.4:X, PLiD) films is remarkably changed by the molar ratio (X) of DETA, which is attributed to the extended distances between the PSSA chains by the DETA bridges. The devices with the PLiD layers deliver noticeably changed hysteresis reaching an optimum at X = 0.2, leading to the longest retention of current signals upon single/double pulses. The long-term potentiation test confirms that the present OSTRs can gradually build up the postsynaptic current by gate pulses of -2 V, while the long-term depression can be adjusted by varying the depression gate pulses (≈0.2-1.2 V). The artificial neural network simulations disclose that the present OSTRs with the ion migration-controlled PLiD layers can perform synaptic processes with an accuracy of ≈96%.
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Affiliation(s)
- Woongki Lee
- Organic Nanoelectronics Laboratory and KNU Institute for Nanophotonics Applications (KINPA), Department of Chemical Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea
- Department of Chemistry and Centre for Processable Electronics, Imperial College London, London, W12 0BZ, UK
| | - Taehoon Kim
- Organic Nanoelectronics Laboratory and KNU Institute for Nanophotonics Applications (KINPA), Department of Chemical Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea
| | - Hwajeong Kim
- Organic Nanoelectronics Laboratory and KNU Institute for Nanophotonics Applications (KINPA), Department of Chemical Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea
- Priority Research Center, Research Institute of Environmental Science & Technology, Kyungpook National University, Daegu, 41566, Republic of Korea
| | - Youngkyoo Kim
- Organic Nanoelectronics Laboratory and KNU Institute for Nanophotonics Applications (KINPA), Department of Chemical Engineering, Kyungpook National University, Daegu, 41566, Republic of Korea
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2
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Liu J, Wang Y, Liu Y, Wu Y, Bian B, Shang J, Li R. Recent Progress in Wearable Near-Sensor and In-Sensor Intelligent Perception Systems. SENSORS (BASEL, SWITZERLAND) 2024; 24:2180. [PMID: 38610389 PMCID: PMC11014300 DOI: 10.3390/s24072180] [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: 03/02/2024] [Revised: 03/25/2024] [Accepted: 03/27/2024] [Indexed: 04/14/2024]
Abstract
As the Internet of Things (IoT) becomes more widespread, wearable smart systems will begin to be used in a variety of applications in people's daily lives, not only requiring the devices to have excellent flexibility and biocompatibility, but also taking into account redundant data and communication delays due to the use of a large number of sensors. Fortunately, the emerging paradigms of near-sensor and in-sensor computing, together with the proposal of flexible neuromorphic devices, provides a viable solution for the application of intelligent low-power wearable devices. Therefore, wearable smart systems based on new computing paradigms are of great research value. This review discusses the research status of a flexible five-sense sensing system based on near-sensor and in-sensor architectures, considering material design, structural design and circuit design. Furthermore, we summarize challenging problems that need to be solved and provide an outlook on the potential applications of intelligent wearable devices.
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Affiliation(s)
- Jialin Liu
- CAS Key Laboratory of Magnetic Materials and Devices, Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, China Academy of Sciences, Ningbo 315201, China; (J.L.); (Y.W.); (Y.L.); (Y.W.); (B.B.)
- College of Materials Science and Opto-Electronic Technology, University of China Academy of Sciences, Beijing 100049, China
| | - Yitao Wang
- CAS Key Laboratory of Magnetic Materials and Devices, Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, China Academy of Sciences, Ningbo 315201, China; (J.L.); (Y.W.); (Y.L.); (Y.W.); (B.B.)
| | - Yiwei Liu
- CAS Key Laboratory of Magnetic Materials and Devices, Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, China Academy of Sciences, Ningbo 315201, China; (J.L.); (Y.W.); (Y.L.); (Y.W.); (B.B.)
- College of Materials Science and Opto-Electronic Technology, University of China Academy of Sciences, Beijing 100049, China
| | - Yuanzhao Wu
- CAS Key Laboratory of Magnetic Materials and Devices, Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, China Academy of Sciences, Ningbo 315201, China; (J.L.); (Y.W.); (Y.L.); (Y.W.); (B.B.)
- College of Materials Science and Opto-Electronic Technology, University of China Academy of Sciences, Beijing 100049, China
| | - Baoru Bian
- CAS Key Laboratory of Magnetic Materials and Devices, Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, China Academy of Sciences, Ningbo 315201, China; (J.L.); (Y.W.); (Y.L.); (Y.W.); (B.B.)
- College of Materials Science and Opto-Electronic Technology, University of China Academy of Sciences, Beijing 100049, China
| | - Jie Shang
- CAS Key Laboratory of Magnetic Materials and Devices, Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, China Academy of Sciences, Ningbo 315201, China; (J.L.); (Y.W.); (Y.L.); (Y.W.); (B.B.)
- College of Materials Science and Opto-Electronic Technology, University of China Academy of Sciences, Beijing 100049, China
- Materials and Optoelectronics Research Center, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Runwei Li
- CAS Key Laboratory of Magnetic Materials and Devices, Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, China Academy of Sciences, Ningbo 315201, China; (J.L.); (Y.W.); (Y.L.); (Y.W.); (B.B.)
- College of Materials Science and Opto-Electronic Technology, University of China Academy of Sciences, Beijing 100049, China
- Materials and Optoelectronics Research Center, University of Chinese Academy of Sciences, Beijing 100049, China
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3
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Liu G, Xue Z, Zhang X, Liu Q, Kuang Y, He M, Xu J, Lv M, Xiu H, Zhai G, Liu D, Xia Y, Dai N, Dai M. Multifunctional Multigate One-Transistor with Thin Advanced Materials, Logic-in-Memory, and Artificial Synaptic Behaviors. ACS APPLIED MATERIALS & INTERFACES 2023; 15:55957-55964. [PMID: 37992220 DOI: 10.1021/acsami.3c10366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
The high device density and fabrication complexity have hampered the development of the electronics. The advanced designs, which could implement the functions of the circuits with higher device density but less fabrication complexity, are hence required. Meanwhile, the MoS2-based devices have recently attracted considerable attention owing to their advantages such as the ultrathin thickness. However, the MoS2-based multifunctional multigate one-transistor (MGT) designs with logic-in-memory and artificial synaptic functions have rarely been reported. Here, an MGT structure based on the MoS2 channel is proposed, with both the logic-in-memory and artificial synaptic behaviors and with more controllable processes than the manual transfer. The proposed MoS2-based MGT functions could be attributed to the semijunction mechanism and enhanced effect of the additional terminals with improved controllability. This study is the first to demonstrate that the neuromorphic computing, logic gate, and memory functions can all be achieved in a MoS2 MGT device without using any additional layers or plasticity to a transistor. The reported results provide a new strategy for developing brain-like systems and next-generation electronics using multifunctional designs and ultrathin materials.
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Affiliation(s)
- Guanyi Liu
- Department of Spine Surgery, Ningbo No. 6 Hospital, 1059 Zhongshandong Road, Ningbo, Zhejiang 315040, People's Republic of China
| | - Zhibiao Xue
- Energy Division, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang Province 315201, China
- School of Materials Science and Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China
| | - Xiaoyang Zhang
- Energy Division, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang Province 315201, China
- Nano Science and Technology Institute, University of Science and Technology of China, Suzhou, Jiangsu 215123, China
| | - Qitao Liu
- Energy Division, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang Province 315201, China
| | - Yongbo Kuang
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
- Energy Division, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang Province 315201, China
| | - Meng He
- Institute of Microelectronics of the Chinese Academy of Sciences, Beijing 100029, China
| | - Ji Xu
- Energy Division, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang Province 315201, China
| | - Mingming Lv
- Energy Division, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang Province 315201, China
| | - Hao Xiu
- Energy Division, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang Province 315201, China
| | - Gangpeng Zhai
- Energy Division, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang Province 315201, China
- Nano Science and Technology Institute, University of Science and Technology of China, Suzhou, Jiangsu 215123, China
| | - Deyu Liu
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
- Energy Division, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang Province 315201, China
| | - Yang Xia
- Institute of Microelectronics of the Chinese Academy of Sciences, Beijing 100029, China
| | - Ning Dai
- State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
- Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
| | - Mingzhi Dai
- Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
- Energy Division, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang Province 315201, China
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Li Z, Wang T, Meng J, Zhu H, Sun Q, Zhang DW, Chen L. Flexible aluminum-doped hafnium oxide ferroelectric synapse devices for neuromorphic computing. MATERIALS HORIZONS 2023; 10:3643-3650. [PMID: 37340846 DOI: 10.1039/d3mh00645j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/22/2023]
Abstract
The HfO2-based ferroelectric tunnel junction has received outstanding attention owing to its high-speed and low-power characteristics. In this work, aluminum-doped HfO2 (HfAlO) ferroelectric thin films are deposited on a muscovite substrate (Mica). We investigate the bending effect on the ferroelectric characteristics of the Au/Ti/HfAlO/Pt/Ti/Mica device. After 1000 bending times, the ferroelectric properties and the fatigue characteristics are largely degraded. The finite element analysis indicates that crack formation is the main reason for the fatigue damage under threshold bending diameters. Moreover, the HfAlO-based ferroelectric synaptic device exhibits excellent performance of neuromorphic computing. The artificial synapse can mimic the paired-pulse facilitation and long-term potentiation/depression of biological synapses. Meanwhile, the accuracy of digit recognition is 88.8%. This research provides a new research idea for the further development of hafnium-based ferroelectric devices.
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Affiliation(s)
- Zhenhai Li
- School of Microelectronics, Fudan University, Shanghai 200433, P. R. China.
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Tianyu Wang
- School of Microelectronics, Fudan University, Shanghai 200433, P. R. China.
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Jialin Meng
- School of Microelectronics, Fudan University, Shanghai 200433, P. R. China.
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Hao Zhu
- School of Microelectronics, Fudan University, Shanghai 200433, P. R. China.
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Qingqing Sun
- School of Microelectronics, Fudan University, Shanghai 200433, P. R. China.
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - David Wei Zhang
- School of Microelectronics, Fudan University, Shanghai 200433, P. R. China.
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Lin Chen
- School of Microelectronics, Fudan University, Shanghai 200433, P. R. China.
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
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5
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Gong H, Lin J, Sun H. Nanocrystal Array Engineering and Optoelectronic Applications of Organic Small-Molecule Semiconductors. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:2087. [PMID: 37513098 PMCID: PMC10386679 DOI: 10.3390/nano13142087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/10/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023]
Abstract
Organic small-molecule semiconductor materials have attracted extensive attention because of their excellent properties. Due to the randomness of crystal orientation and growth location, however, the preparation of continuous and highly ordered organic small-molecule semiconductor nanocrystal arrays still face more challenges. Compared to organic macromolecules, organic small molecules exhibit better crystallinity, and therefore, they exhibit better semiconductor performance. The formation of organic small-molecule crystals relies heavily on weak interactions such as hydrogen bonds, van der Waals forces, and π-π interactions, which are very sensitive to external stimuli such as mechanical forces, high temperatures, and organic solvents. Therefore, nanocrystal array engineering is more flexible than that of the inorganic materials. In addition, nanocrystal array engineering is a key step towards practical application. To resolve this problem, many conventional nanocrystal array preparation methods have been developed, such as spin coating, etc. In this review, the typical and recent progress of nanocrystal array engineering are summarized. It is the typical and recent innovations that the array of nanocrystal array engineering can be patterned on the substrate through top-down, bottom-up, self-assembly, and crystallization methods, and it can also be patterned by constructing a series of microscopic structures. Finally, various multifunctional and emerging applications based on organic small-molecule semiconductor nanocrystal arrays are introduced.
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Affiliation(s)
- Haoyu Gong
- Key Laboratory of Flexible Electronics (KLoFE), Institute of Advanced Materials (IAM), Nanjing Tech University, 30 South Puzhu Road, Nanjing 211816, China
| | - Jinyi Lin
- Key Laboratory of Flexible Electronics (KLoFE), Institute of Advanced Materials (IAM), Nanjing Tech University, 30 South Puzhu Road, Nanjing 211816, China
| | - Huibin Sun
- Key Laboratory of Flexible Electronics (KLoFE), Institute of Advanced Materials (IAM), Nanjing Tech University, 30 South Puzhu Road, Nanjing 211816, China
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6
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Ercan E, Hung CC, Li GS, Yang YF, Lin YC, Chen WC. Molecular template growth of organic heterojunctions to tailor visual neuroplasticity for high performance phototransistors with ultralow energy consumption. NANOSCALE HORIZONS 2023; 8:632-640. [PMID: 36866736 DOI: 10.1039/d2nh00597b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The optical and charge transport properties of organic semiconductors are strongly influenced by their morphology and molecular structures. Here we report the influence of a molecular template strategy on anisotropic control via weak epitaxial growth of a semiconducting channel for a dinaphtho[2,3-b:2',3'-f]thieno[3,2-b]thiophene (DNTT)/para-sexiphenyl (p-6P) heterojunction. The aim is to improve charge transport and trapping, to enable tailoring of visual neuroplasticity. The proposed phototransistor devices, comprising a molecular heterojunction with optimized molecular template thickness, exhibited an excellent memory ratio (ION/IOFF) and retention characteristics in response to light stimulation, owing to the enhanced orientation/packing of DNTT molecules and a favorable match between the LUMO/HOMO levels of p-6P and DNTT. The best performing heterojunction exhibits visual synaptic functionalities, including an extremely high pair-pulse facilitation index of ∼206%, ultralow energy consumption of 0.54 fJ, and zero-gate operation, under ultrashort pulse light stimulation to mimic human-like sensing, computing, and memory functions. An array of heterojunction photosynapses possess a high degree of visual pattern recognition and learning, to mimic the neuroplasticity of human brain activities through a rehearsal learning process. This study provides a guide to the design of molecular heterojunctions for tailoring high-performance photonic memory and synapses for neuromorphic computing and artificial intelligence systems.
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Affiliation(s)
- Ender Ercan
- Department of Chemical Engineering, National Taiwan University, Taipei, 10617, Taiwan.
- Advanced Research Center of Green Materials Science and Technology, National Taiwan University, Taipei, 10617, Taiwan
| | - Chih-Chien Hung
- Advanced Research Center of Green Materials Science and Technology, National Taiwan University, Taipei, 10617, Taiwan
| | - Guan-Syuan Li
- Department of Chemical Engineering, National Taiwan University, Taipei, 10617, Taiwan.
| | - Yun-Fang Yang
- Department of Chemical Engineering, National Taiwan University, Taipei, 10617, Taiwan.
| | - Yan-Cheng Lin
- Department of Chemical Engineering, National Cheng Kung University, Tainan, 70101, Taiwan
| | - Wen-Chang Chen
- Department of Chemical Engineering, National Taiwan University, Taipei, 10617, Taiwan.
- Advanced Research Center of Green Materials Science and Technology, National Taiwan University, Taipei, 10617, Taiwan
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7
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Yamamoto S. Polymer‐based
neuromorphic devices: resistive switches and organic electrochemical transistors. POLYM INT 2023. [DOI: 10.1002/pi.6520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
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8
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Xie L, Zhang Z, Wu Q, Gao Z, Mi G, Wang R, Sun HB, Zhao Y, Du Y. Intelligent wearable devices based on nanomaterials and nanostructures for healthcare. NANOSCALE 2023; 15:405-433. [PMID: 36519286 DOI: 10.1039/d2nr04551f] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Emerging classes of flexible electronic sensors as alternatives to conventional rigid sensors offer a powerful set of capabilities for detecting and quantifying physiological and physical signals from human skin in personal healthcare. Unfortunately, the practical applications and commercialization of flexible sensors are generally limited by certain unsatisfactory aspects of their performance, such as biocompatibility, low sensing range, power supply, or single sensory function. This review intends to provide up-to-date literature on wearable devices for smart healthcare. A systematic review is provided, from sensors based on nanomaterials and nanostructures, algorithms, to multifunctional integrated devices with stretchability, self-powered performance, and biocompatibility. Typical electromechanical sensors are investigated with a specific focus on the strategies for constructing high-performance sensors based on nanomaterials and nanostructures. Then, the review emphasizes the importance of tailoring the fabrication techniques in order to improve stretchability, biocompatibility, and self-powered performance. The construction of wearable devices with high integration, high performance, and multi-functionalization for multiparameter healthcare is discussed in depth. Integrating wearable devices with appropriate machine learning algorithms is summarized. After interpretation of the algorithms, intelligent predictions are produced to give instructions or predictions for smart implementations. It is desired that this review will offer guidance for future excellence in flexible wearable sensing technologies and provide insight into commercial wearable sensors.
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Affiliation(s)
- Liping Xie
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Zelin Zhang
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Qiushuo Wu
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Zhuxuan Gao
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Gaotian Mi
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Renqiao Wang
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Hong-Bin Sun
- Department of Chemistry, Northeastern University, Shenyang, 110819, China
| | - Yue Zhao
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
| | - Yanan Du
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China
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9
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Fu W, Li J, Li L, Jiang D, Zhu W, Zhang J. High ionic conductivity Li 0.33La 0.557TiO 3nanofiber/polymer composite solid electrolyte for flexible transparent InZnO synaptic transistors. NANOTECHNOLOGY 2021; 32:405207. [PMID: 34225267 DOI: 10.1088/1361-6528/ac1132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 07/05/2021] [Indexed: 06/13/2023]
Abstract
With the rapid development of wearable artificial intelligence devices, there is an increasing demand for flexible oxide neuromorphic transistors with the solid electrolytes. To achieve high-performance flexible synaptic transistors, the solid electrolytes should exhibit good mechanical bending characteristics and high ion conductivity. However, the polymer-based electrolytes with good mechanical bending characteristics show poor ion conductivity (10-6-10-7S cm-1), which limits the performance of flexible synaptic transistors. Thus, it is urgent to improve the ion conductivity of the polymer-based electrolytes. In the work, a new strategy of electrospun Li0.33La0.557TiO3nanofibers-enhanced ion transport pathway is proposed to simultaneously improve the mechanical bending and ion conductivity of polyethylene oxide/polyvinylpyrrolidone-based solid electrolytes. The flexible InZnO synaptic transistors with Li0.33La0.557TiO3nanofibers-based solid electrolytes successfully simulated excitatory post-synaptic current, paired-pulse-facilitation, dynamic time filter, nonlinear summation, two-terminal input dynamic integration and logic function. This work is a useful attempt to develop high-performance synaptic transistors.
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Affiliation(s)
- Wenhui Fu
- School of Material Science and Engineering, Shanghai University, Jiading, Shanghai 201800, People's Republic of China
| | - Jun Li
- School of Material Science and Engineering, Shanghai University, Jiading, Shanghai 201800, People's Republic of China
- Key Laboratory of Advanced Display and System Applications, Ministry of Education, Shanghai University, Shanghai 200072, People's Republic of China
| | - Linkang Li
- School of Material Science and Engineering, Shanghai University, Jiading, Shanghai 201800, People's Republic of China
| | - Dongliang Jiang
- School of Material Science and Engineering, Shanghai University, Jiading, Shanghai 201800, People's Republic of China
| | - Wenqing Zhu
- School of Material Science and Engineering, Shanghai University, Jiading, Shanghai 201800, People's Republic of China
| | - Jianhua Zhang
- Key Laboratory of Advanced Display and System Applications, Ministry of Education, Shanghai University, Shanghai 200072, People's Republic of China
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Wang Y, Huang W, Zhang Z, Fan L, Huang Q, Wang J, Zhang Y, Zhang M. Ultralow-power flexible transparent carbon nanotube synaptic transistors for emotional memory. NANOSCALE 2021; 13:11360-11369. [PMID: 34096562 DOI: 10.1039/d1nr02099d] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Emulating the biological behavior of the human brain with artificial neuromorphic devices is essential for the future development of human-machine interactive systems, bionic sensing systems and intelligent robotic systems. In this paper, artificial flexible transparent carbon nanotube synaptic transistors (F-CNT-STs) with signal transmission and emotional learning functions are realized by adopting the poly(vinyl alcohol) (PVA)/SiO2 proton-conducting electrolyte. Synaptic functions of biological synapses including excitatory and inhibitory behaviors are successfully emulated in the F-CNT-STs. Besides, synaptic plasticity such as spike-duration-dependent plasticity, spike-number-dependent plasticity, spike-amplitude-dependent plasticity, paired-pulse facilitation, short-term plasticity, and long-term plasticity have all been systematically characterized. Moreover, the F-CNT-STs also closely imitate the behavior of human brain learning and emotional memory functions. After 1000 bending cycles at a radius of 3 mm, both the transistor characteristics and the synaptic functions can still be implemented correctly, showing outstanding mechanical capability. The realized F-CNT-STs possess low operating voltage, quick response, and ultra-low power consumption, indicating their high potential to work in low-power biological systems and artificial intelligence systems. The flexible artificial synaptic transistor enables its potential to be generally applicable to various flexible wearable biological and intelligent applications.
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Affiliation(s)
- Yarong Wang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Weihong Huang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Ziwei Zhang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Lingchong Fan
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Qiuyue Huang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Jiaxin Wang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Yiming Zhang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
| | - Min Zhang
- School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, China.
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