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Sun Y, Wang H, Xie D. Recent Advance in Synaptic Plasticity Modulation Techniques for Neuromorphic Applications. NANO-MICRO LETTERS 2024; 16:211. [PMID: 38842588 PMCID: PMC11156833 DOI: 10.1007/s40820-024-01445-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 05/14/2024] [Indexed: 06/07/2024]
Abstract
Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artificial intelligence. However, great efforts have been devoted to exploring biomimetic mechanisms of plasticity simulation in the last few years. Recent progress in various plasticity modulation techniques has pushed the research of synaptic electronics from static plasticity simulation to dynamic plasticity modulation, improving the accuracy of neuromorphic computing and providing strategies for implementing neuromorphic sensing functions. Herein, several fascinating strategies for synaptic plasticity modulation through chemical techniques, device structure design, and physical signal sensing are reviewed. For chemical techniques, the underlying mechanisms for the modification of functional materials were clarified and its effect on the expression of synaptic plasticity was also highlighted. Based on device structure design, the reconfigurable operation of neuromorphic devices was well demonstrated to achieve programmable neuromorphic functions. Besides, integrating the sensory units with neuromorphic processing circuits paved a new way to achieve human-like intelligent perception under the modulation of physical signals such as light, strain, and temperature. Finally, considering that the relevant technology is still in the basic exploration stage, some prospects or development suggestions are put forward to promote the development of neuromorphic devices.
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Affiliation(s)
- Yilin Sun
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, 100081, People's Republic of China.
| | - Huaipeng Wang
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - Dan Xie
- School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China.
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2
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Monakhov KY. Oxovanadium electronics for in-memory, neuromorphic, and quantum computing applications. MATERIALS HORIZONS 2024; 11:1838-1842. [PMID: 38334459 DOI: 10.1039/d3mh01926h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
Vanadium is a critical raw material. In the nearby future, it may, however, become one of the key elements of computer devices based on two-dimensional arrays of spin qubits for quantum information processing or charge- and resistance-based data memory cells for non-volatile in-memory and neuromorphic computing. The research and development (R&D) of vanadium-containing electronic materials and methods for their responsible fabrication underpins the transition to innovative hybrid semiconductors for energy- and resource-efficient memory and information processing technologies. The combination of standard and emerging solid-state semiconductors with stimuli-responsive oxo complexes of vanadium(IV,V) is envisioned to result in electronics with a new room-temperature device nanophysics, and the ability to modulate and control it at the sub-nanometer level. The development of exponential (Boolean) logics based on the oxovanadium-comprising circuitry and crossbar arrays of individual memristive cells for in-memory computing, the implementation of basic synaptic functions via dynamic electrical pulses for neuromorphic computing, and the readout and control of spin networks and interfaces for quantum computing are strategically important future areas of molecular chemistry and applied physics of vanadium.
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Affiliation(s)
- Kirill Yu Monakhov
- Leibniz Institute of Surface Engineering (IOM), Permoserstr. 15, Leipzig 04318, Germany.
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3
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Dong X, Sun H, Li S, Zhang X, Chen J, Zhang X, Zhao Y, Li Y. Versatile Cu2ZnSnS4-based synaptic memristor for multi-field-regulated neuromorphic applications. J Chem Phys 2024; 160:154702. [PMID: 38619459 DOI: 10.1063/5.0206100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 03/28/2024] [Indexed: 04/16/2024] Open
Abstract
Integrating both electrical and light-modulated multi-type neuromorphic functions in a single synaptic memristive device holds the most potential for realizing next-generation neuromorphic systems, but is still challenging yet achievable. Herein, a simple bi-terminal optoelectronic synaptic memristor is newly proposed based on kesterite Cu2ZnSnS4, exhibiting stable nonvolatile resistive switching with excellent spatial uniformity and unique optoelectronic synaptic behaviors. The device demonstrates not only low switching voltage (-0.39 ± 0.08 V), concentrated Set/Reset voltage distribution (<0.08/0.15 V), and long retention time (>104 s) but also continuously modulable conductance by both electric (different width/interval/amplitude) and light (470-808 nm with different intensity) stimulus. These advantages make the device good electrically and optically simulated synaptic functions, including excitatory and inhibitory, paired-pulsed facilitation, short-/long-term plasticity, spike-timing-dependent plasticity, and "memory-forgetting" behavior. Significantly, decimal arithmetic calculation (addition, subtraction, and commutative law) is realized based on the linear conductance regulation, and high precision pattern recognition (>88%) is well achieved with an artificial neural network constructed by 5 × 5 × 4 memristor array. Predictably, such kesterite-based optoelectronic memristors can greatly open the possibility of realizing multi-functional neuromorphic systems.
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Affiliation(s)
- Xiaofei Dong
- Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Hao Sun
- Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Siyuan Li
- Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Xiang Zhang
- Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Jiangtao Chen
- Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Xuqiang Zhang
- Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Yun Zhao
- Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Yan Li
- Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
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Guo F, Liu Y, Zhang M, Yu W, Li S, Zhang B, Hu B, Li S, Sun A, Jiang J, Hao L. VO 2 /MoO 3 Heterojunctions Artificial Optoelectronic Synapse Devices for Near-Infrared Optical Communication. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024:e2310767. [PMID: 38456772 DOI: 10.1002/smll.202310767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 02/23/2024] [Indexed: 03/09/2024]
Abstract
Artificial optoelectronic synapses (OES) have attracted extensive attention in brain-inspired information processing and neuromorphic computing. However, OES at near-infrared wavelengths have rarely been reported, seriously limiting the application in modern optical communication. Herein, high-performance near-infrared OES devices based on VO2 /MoO3 heterojunctions are presented. The textured MoO3 films are deposited on the sputtered VO2 film by using the glancing-angle deposition technique to form a heterojunction device. Through tuning the oxygen defects in the VO2 film, the fabricated VO2 /MoO3 heterojunction exhibits versatile electrical synaptic functions. Benefiting from the highly efficient light harvesting and the unique interface effect, the photonic synaptic characteristics, mainly including the short/long-term plasticity and learning experience behavior are successfully realized at the O (1342 nm) and C (1550 nm) optical communication wavebands. Moreover, a single OES device can output messages accurately by converting light signals of the Morse code to distinct synaptic currents. More importantly, a 3 × 3 artificial OES array is constructed to demonstrate the impressive image perceiving and learning capabilities. This work not only indicates the feasibility of defect and interface engineering in modulating the synaptic plasticity of OES devices, but also provides effective strategies to develop advanced artificial neuromorphic visual systems for next-generation optical communication systems.
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Affiliation(s)
- Fuhai Guo
- College of Science, China University of Petroleum, Qingdao, Shandong, 266580, China
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong, 266580, China
| | - Yunjie Liu
- College of Science, China University of Petroleum, Qingdao, Shandong, 266580, China
| | - Mingcong Zhang
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong, 266580, China
| | - Weizhuo Yu
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong, 266580, China
| | - Siqi Li
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong, 266580, China
| | - Bo Zhang
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong, 266580, China
| | - Bing Hu
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong, 266580, China
| | - Shuangshuang Li
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong, 266580, China
| | - Ankai Sun
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong, 266580, China
| | - Jianyu Jiang
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong, 266580, China
| | - Lanzhong Hao
- School of Materials Science and Engineering, China University of Petroleum, Qingdao, Shandong, 266580, China
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5
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Naik BR, Arya N, Balakrishnan V. Paper based flexible MoS 2-CNT hybrid memristors. NANOTECHNOLOGY 2024; 35:215201. [PMID: 38364265 DOI: 10.1088/1361-6528/ad2a01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 02/16/2024] [Indexed: 02/18/2024]
Abstract
We report for the first time MoS2/CNT hybrid nanostructures for memristor applications on flexible and bio-degradable cellulose paper. In our approach, we varied two different weight percentages (10% and 20%) of CNT's in MoS2to improve the MoS2conductivity and investigate the memristor device characteristics. The device with 10% CNT shows a lowVSETvoltage of 2.5 V, which is comparatively small for planar devices geometries. The device exhibits a long data retention time and cyclic current-voltage stability of ∼104s and 102cycles, making it a potential candidate in flexible painted electronics. Along with good electrical performance, it also demonstrates a high mechanical stability for 1000 bending cycles. The conduction mechanism in the MoS2-CNT hybrid structure is corroborated by percolation and defect-induced filament formation. Additionally, the device displays synaptic plasticity performance, simulating potentiation and depression processes. Furthermore, such flexible and biodegradable cellulose-based paper electronics may pave the way to address the environmental pollution caused by electronic waste in the near future.
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Affiliation(s)
- B Raju Naik
- School of Mechanical and Materials Engineering, Indian Institute of Technology, Mandi, Himachal Pradesh-175075, India
| | - Nitika Arya
- School of Mechanical and Materials Engineering, Indian Institute of Technology, Mandi, Himachal Pradesh-175075, India
| | - Viswanath Balakrishnan
- School of Mechanical and Materials Engineering, Indian Institute of Technology, Mandi, Himachal Pradesh-175075, India
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6
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Wang J, Ilyas N, Ren Y, Ji Y, Li S, Li C, Liu F, Gu D, Ang KW. Technology and Integration Roadmap for Optoelectronic Memristor. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2307393. [PMID: 37739413 DOI: 10.1002/adma.202307393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/10/2023] [Indexed: 09/24/2023]
Abstract
Optoelectronic memristors (OMs) have emerged as a promising optoelectronic Neuromorphic computing paradigm, opening up new opportunities for neurosynaptic devices and optoelectronic systems. These OMs possess a range of desirable features including minimal crosstalk, high bandwidth, low power consumption, zero latency, and the ability to replicate crucial neurological functions such as vision and optical memory. By incorporating large-scale parallel synaptic structures, OMs are anticipated to greatly enhance high-performance and low-power in-memory computing, effectively overcoming the limitations of the von Neumann bottleneck. However, progress in this field necessitates a comprehensive understanding of suitable structures and techniques for integrating low-dimensional materials into optoelectronic integrated circuit platforms. This review aims to offer a comprehensive overview of the fundamental performance, mechanisms, design of structures, applications, and integration roadmap of optoelectronic synaptic memristors. By establishing connections between materials, multilayer optoelectronic memristor units, and monolithic optoelectronic integrated circuits, this review seeks to provide insights into emerging technologies and future prospects that are expected to drive innovation and widespread adoption in the near future.
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Affiliation(s)
- Jinyong Wang
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Nasir Ilyas
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Yujing Ren
- Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, 117585, Singapore
| | - Yun Ji
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Sifan Li
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
| | - Changcun Li
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Fucai Liu
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Deen Gu
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
- State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China
| | - Kah-Wee Ang
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore
- Institute of Materials Research and Engineering, A*STAR, Singapore, 138634, Singapore
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7
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Wang Y, Guo D, Jiang J, Wang H, Shang Y, Zheng J, Huang R, Li W, Wang S. Element Regulation and Dimensional Engineering Co-Optimization of Perovskite Memristors for Synaptic Plasticity Applications. ACS APPLIED MATERIALS & INTERFACES 2024. [PMID: 38422456 DOI: 10.1021/acsami.3c18053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
Capitalizing on rapid carrier migration characteristics and outstanding photoelectric conversion performance, halide perovskite memristors demonstrate an exceptional resistive switching performance. However, they have consistently faced constraints due to material stability issues. This study systematically employs elemental modulation and dimension engineering to effectively control perovskite memristors with different dimensions and A-site elements. Compared to pure 3D and 2D perovskites, the quasi-2D perovskite memristor, specifically BA0.15MA0.85PbI3, is identified as the optimal choice through observations of resistive switching (HRS current < 10-5 A, ON/OFF ratio > 103, endurance cycles > 1000, and retention time > 104 s) and synaptic plasticity characteristics. Subsequently, a comprehensive investigation into various synaptic plasticity aspects, including paired-pulse facilitation (PPF), spike-variability-dependent plasticity (SVDP), spike-rate-dependent plasticity (SRDP), and spike-timing-dependent plasticity (STDP), is conducted. Practical applications, such as memory-forgetting-memory and recognition of the Modified National Institute of Standards and Technology (MNIST) database handwritten data set (accuracy rate reaching 94.8%), are explored and successfully realized. This article provides good theoretical guidance for synaptic-like simulation in perovskite memristors.
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Affiliation(s)
- Yucheng Wang
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Dingyun Guo
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Junyu Jiang
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Hexin Wang
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Yueyang Shang
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Jiawei Zheng
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Ruixi Huang
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Wei Li
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Shaoxi Wang
- School of Microelectronics, Northwestern Polytechnical University, Xi'an 710072, China
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8
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Wang W, Wang Y, Yin F, Niu H, Shin YK, Li Y, Kim ES, Kim NY. Tailoring Classical Conditioning Behavior in TiO 2 Nanowires: ZnO QDs-Based Optoelectronic Memristors for Neuromorphic Hardware. NANO-MICRO LETTERS 2024; 16:133. [PMID: 38411720 PMCID: PMC10899558 DOI: 10.1007/s40820-024-01338-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 12/28/2023] [Indexed: 02/28/2024]
Abstract
Neuromorphic hardware equipped with associative learning capabilities presents fascinating applications in the next generation of artificial intelligence. However, research into synaptic devices exhibiting complex associative learning behaviors is still nascent. Here, an optoelectronic memristor based on Ag/TiO2 Nanowires: ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors. Effective implementation of synaptic behaviors, including long and short-term plasticity, and learning-forgetting-relearning behaviors, were achieved in the device through the application of light and electrical stimuli. Leveraging the optoelectronic co-modulated characteristics, a simulation of neuromorphic computing was conducted, resulting in a handwriting digit recognition accuracy of 88.9%. Furthermore, a 3 × 7 memristor array was constructed, confirming its application in artificial visual memory. Most importantly, complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli, respectively. After training through associative pairs, reflexes could be triggered solely using light stimuli. Comprehensively, under specific optoelectronic signal applications, the four features of classical conditioning, namely acquisition, extinction, recovery, and generalization, were elegantly emulated. This work provides an optoelectronic memristor with associative behavior capabilities, offering a pathway for advancing brain-machine interfaces, autonomous robots, and machine self-learning in the future.
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Affiliation(s)
- Wenxiao Wang
- School of Information Science and Engineering, University of Jinan, Jinan, 250022, People's Republic of China
- RFIC Centre, NDAC Centre, Kwangwoon University, Nowon-gu, Seoul, 139-701, South Korea
- Department of Electronics Engineering, Kwangwoon University, Nowon-Gu, Seoul, 139-701, South Korea
| | - Yaqi Wang
- School of Information Science and Engineering, University of Jinan, Jinan, 250022, People's Republic of China
| | - Feifei Yin
- RFIC Centre, NDAC Centre, Kwangwoon University, Nowon-gu, Seoul, 139-701, South Korea
- Department of Electronics Engineering, Kwangwoon University, Nowon-Gu, Seoul, 139-701, South Korea
| | - Hongsen Niu
- RFIC Centre, NDAC Centre, Kwangwoon University, Nowon-gu, Seoul, 139-701, South Korea
- Department of Electronics Engineering, Kwangwoon University, Nowon-Gu, Seoul, 139-701, South Korea
| | - Young-Kee Shin
- Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul, 08826, South Korea
| | - Yang Li
- School of Information Science and Engineering, University of Jinan, Jinan, 250022, People's Republic of China.
- School of Microelectronics, Shandong University, Jinan, 250101, People's Republic of China.
| | - Eun-Seong Kim
- RFIC Centre, NDAC Centre, Kwangwoon University, Nowon-gu, Seoul, 139-701, South Korea.
- Department of Electronics Engineering, Kwangwoon University, Nowon-Gu, Seoul, 139-701, South Korea.
| | - Nam-Young Kim
- RFIC Centre, NDAC Centre, Kwangwoon University, Nowon-gu, Seoul, 139-701, South Korea.
- Department of Electronics Engineering, Kwangwoon University, Nowon-Gu, Seoul, 139-701, South Korea.
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9
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Zhou H, Li S, Ang KW, Zhang YW. Recent Advances in In-Memory Computing: Exploring Memristor and Memtransistor Arrays with 2D Materials. NANO-MICRO LETTERS 2024; 16:121. [PMID: 38372805 PMCID: PMC10876512 DOI: 10.1007/s40820-024-01335-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 12/25/2023] [Indexed: 02/20/2024]
Abstract
The conventional computing architecture faces substantial challenges, including high latency and energy consumption between memory and processing units. In response, in-memory computing has emerged as a promising alternative architecture, enabling computing operations within memory arrays to overcome these limitations. Memristive devices have gained significant attention as key components for in-memory computing due to their high-density arrays, rapid response times, and ability to emulate biological synapses. Among these devices, two-dimensional (2D) material-based memristor and memtransistor arrays have emerged as particularly promising candidates for next-generation in-memory computing, thanks to their exceptional performance driven by the unique properties of 2D materials, such as layered structures, mechanical flexibility, and the capability to form heterojunctions. This review delves into the state-of-the-art research on 2D material-based memristive arrays, encompassing critical aspects such as material selection, device performance metrics, array structures, and potential applications. Furthermore, it provides a comprehensive overview of the current challenges and limitations associated with these arrays, along with potential solutions. The primary objective of this review is to serve as a significant milestone in realizing next-generation in-memory computing utilizing 2D materials and bridge the gap from single-device characterization to array-level and system-level implementations of neuromorphic computing, leveraging the potential of 2D material-based memristive devices.
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Affiliation(s)
- Hangbo Zhou
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore, 138632, Republic of Singapore
| | - Sifan Li
- Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117583, Republic of Singapore
| | - Kah-Wee Ang
- Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117583, Republic of Singapore.
- Institute of Materials Research and Engineering, Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, Singapore, 138634, Republic of Singapore.
| | - Yong-Wei Zhang
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore, 138632, Republic of Singapore.
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10
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Liu A, Zhang X, Liu Z, Li Y, Peng X, Li X, Qin Y, Hu C, Qiu Y, Jiang H, Wang Y, Li Y, Tang J, Liu J, Guo H, Deng T, Peng S, Tian H, Ren TL. The Roadmap of 2D Materials and Devices Toward Chips. NANO-MICRO LETTERS 2024; 16:119. [PMID: 38363512 PMCID: PMC10873265 DOI: 10.1007/s40820-023-01273-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 10/30/2023] [Indexed: 02/17/2024]
Abstract
Due to the constraints imposed by physical effects and performance degradation, silicon-based chip technology is facing certain limitations in sustaining the advancement of Moore's law. Two-dimensional (2D) materials have emerged as highly promising candidates for the post-Moore era, offering significant potential in domains such as integrated circuits and next-generation computing. Here, in this review, the progress of 2D semiconductors in process engineering and various electronic applications are summarized. A careful introduction of material synthesis, transistor engineering focused on device configuration, dielectric engineering, contact engineering, and material integration are given first. Then 2D transistors for certain electronic applications including digital and analog circuits, heterogeneous integration chips, and sensing circuits are discussed. Moreover, several promising applications (artificial intelligence chips and quantum chips) based on specific mechanism devices are introduced. Finally, the challenges for 2D materials encountered in achieving circuit-level or system-level applications are analyzed, and potential development pathways or roadmaps are further speculated and outlooked.
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Affiliation(s)
- Anhan Liu
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100049, People's Republic of China
| | - Xiaowei Zhang
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100049, People's Republic of China
| | - Ziyu Liu
- School of Microelectronics, Fudan University, Shanghai, 200433, People's Republic of China
| | - Yuning Li
- School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, 100044, People's Republic of China
| | - Xueyang Peng
- High-Frequency High-Voltage Device and Integrated Circuits R&D Center, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, People's Republic of China
- School of Integrated Circuits, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Xin Li
- State Key Laboratory of Dynamic Measurement Technology, Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement, North University of China, Taiyuan, 030051, People's Republic of China
| | - Yue Qin
- State Key Laboratory of Dynamic Measurement Technology, Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement, North University of China, Taiyuan, 030051, People's Republic of China
| | - Chen Hu
- High-Frequency High-Voltage Device and Integrated Circuits R&D Center, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, People's Republic of China
- School of Integrated Circuits, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Yanqing Qiu
- High-Frequency High-Voltage Device and Integrated Circuits R&D Center, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, People's Republic of China
- School of Integrated Circuits, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Han Jiang
- School of Microelectronics, Fudan University, Shanghai, 200433, People's Republic of China
| | - Yang Wang
- School of Microelectronics, Fudan University, Shanghai, 200433, People's Republic of China
| | - Yifan Li
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100049, People's Republic of China
| | - Jun Tang
- State Key Laboratory of Dynamic Measurement Technology, Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement, North University of China, Taiyuan, 030051, People's Republic of China
| | - Jun Liu
- State Key Laboratory of Dynamic Measurement Technology, Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement, North University of China, Taiyuan, 030051, People's Republic of China
| | - Hao Guo
- State Key Laboratory of Dynamic Measurement Technology, Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement, North University of China, Taiyuan, 030051, People's Republic of China.
| | - Tao Deng
- School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, 100044, People's Republic of China.
| | - Songang Peng
- High-Frequency High-Voltage Device and Integrated Circuits R&D Center, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, People's Republic of China.
- IMECAS-HKUST-Joint Laboratory of Microelectronics, Beijing, 100029, People's Republic of China.
| | - He Tian
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100049, People's Republic of China.
| | - Tian-Ling Ren
- School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100049, People's Republic of China.
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11
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Ma H, Fang H, Xie X, Liu Y, Tian H, Chai Y. Optoelectronic Synapses Based on MXene/Violet Phosphorus van der Waals Heterojunctions for Visual-Olfactory Crossmodal Perception. NANO-MICRO LETTERS 2024; 16:104. [PMID: 38300424 PMCID: PMC10834395 DOI: 10.1007/s40820-024-01330-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 12/11/2023] [Indexed: 02/02/2024]
Abstract
The crossmodal interaction of different senses, which is an important basis for learning and memory in the human brain, is highly desired to be mimicked at the device level for developing neuromorphic crossmodal perception, but related researches are scarce. Here, we demonstrate an optoelectronic synapse for vision-olfactory crossmodal perception based on MXene/violet phosphorus (VP) van der Waals heterojunctions. Benefiting from the efficient separation and transport of photogenerated carriers facilitated by conductive MXene, the photoelectric responsivity of VP is dramatically enhanced by 7 orders of magnitude, reaching up to 7.7 A W-1. Excited by ultraviolet light, multiple synaptic functions, including excitatory postsynaptic currents, paired-pulse facilitation, short/long-term plasticity and "learning-experience" behavior, were demonstrated with a low power consumption. Furthermore, the proposed optoelectronic synapse exhibits distinct synaptic behaviors in different gas environments, enabling it to simulate the interaction of visual and olfactory information for crossmodal perception. This work demonstrates the great potential of VP in optoelectronics and provides a promising platform for applications such as virtual reality and neurorobotics.
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Affiliation(s)
- Hailong Ma
- Center for Advancing Materials Performance From the Nanoscale (CAMP-Nano), State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China
| | - Huajing Fang
- Center for Advancing Materials Performance From the Nanoscale (CAMP-Nano), State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China.
| | - Xinxing Xie
- Center for Advancing Materials Performance From the Nanoscale (CAMP-Nano), State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China
| | - Yanming Liu
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China
| | - He Tian
- Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, People's Republic of China.
| | - Yang Chai
- Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, People's Republic of China.
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12
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Kwon JY, Kim JE, Kim JS, Chun SY, Soh K, Yoon JH. Artificial sensory system based on memristive devices. EXPLORATION (BEIJING, CHINA) 2024; 4:20220162. [PMID: 38854486 PMCID: PMC10867403 DOI: 10.1002/exp.20220162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 10/16/2023] [Indexed: 06/11/2024]
Abstract
In the biological nervous system, the integration and cooperation of parallel system of receptors, neurons, and synapses allow efficient detection and processing of intricate and disordered external information. Such systems acquire and process environmental data in real-time, efficiently handling complex tasks with minimal energy consumption. Memristors can mimic typical biological receptors, neurons, and synapses by implementing key features of neuronal signal-processing functions such as selective adaption in receptors, leaky integrate-and-fire in neurons, and synaptic plasticity in synapses. External stimuli are sensitively detected and filtered by "artificial receptors," encoded into spike signals via "artificial neurons," and integrated and stored through "artificial synapses." The high operational speed, low power consumption, and superior scalability of memristive devices make their integration with high-performance sensors a promising approach for creating integrated artificial sensory systems. These integrated systems can extract useful data from a large volume of raw data, facilitating real-time detection and processing of environmental information. This review explores the recent advances in memristor-based artificial sensory systems. The authors begin with the requirements of artificial sensory elements and then present an in-depth review of such elements demonstrated by memristive devices. Finally, the major challenges and opportunities in the development of memristor-based artificial sensory systems are discussed.
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Affiliation(s)
- Ju Young Kwon
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)SeoulRepublic of Korea
| | - Ji Eun Kim
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)SeoulRepublic of Korea
- Department of Materials Science and EngineeringKorea UniversitySeoulRepublic of Korea
| | - Jong Sung Kim
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)SeoulRepublic of Korea
- Department of Materials Science and EngineeringKorea UniversitySeoulRepublic of Korea
| | - Suk Yeop Chun
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)SeoulRepublic of Korea
- KU‐KIST Graduate School of Converging Science and TechnologyKorea UniversitySeoulRepublic of Korea
| | - Keunho Soh
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)SeoulRepublic of Korea
- Department of Materials Science and EngineeringKorea UniversitySeoulRepublic of Korea
| | - Jung Ho Yoon
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)SeoulRepublic of Korea
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13
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Zhang Q, Jiang Q, Fan F, Liu G, Chen Y, Zhang B. MoS 2 Quantum Dot-Optimized Conductive Channels for a Conjugated Polymer-Based Synaptic Memristor. ACS APPLIED MATERIALS & INTERFACES 2023; 15:59630-59642. [PMID: 38103041 DOI: 10.1021/acsami.3c12674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2023]
Abstract
Donor-acceptor-type conjugated polymers are widely used in memristors due to their unique push-pull electron structures and charge transfer mechanisms. However, the inherently inhomogeneous microstructure of polymer films and their low crystallinity produce randomness that destabilizes formed conductive channels, giving polymer-based memristors unstable switching behavior. In this contribution, we prepared a synaptic device based on PM6-MoS2 QD (molybdenum disulfide quantum dot) nanocomposites. In the composites, MoS2 QDs provided the active centers for forming conductive channels via electron trapping and detrapping. They also controlled the directional formation of conductive channels between PM6 and MoS2 QDs, reducing randomness and giving devices a narrow switching voltage range and cycling longevity. The device exhibited continuous multistage conductance states under a direct current voltage sweep and simulated a variety of synaptic functions, including long-term potentiation, long-term depression, short-term potentiation, short-term depression, paired-pulse facilitation, spiking-rate-dependent plasticity, and "learning experience" behavior. The memristor could also perform arithmetic, including "counting" and "subtraction" operations. This work provides a new approach to improving the performance of memristors for neuromorphic computing.
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Affiliation(s)
- Qiongshan Zhang
- Key Laboratory for Advanced Materials and Joint International Research Laboratory of Precision Chemistry and Molecular Engineering, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Qizhi Jiang
- Key Laboratory for Advanced Materials and Joint International Research Laboratory of Precision Chemistry and Molecular Engineering, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Fei Fan
- School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
- Shanghai i-Reader Biotech Co., Ltd., Shanghai 201114, China
| | - Gang Liu
- School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Yu Chen
- Key Laboratory for Advanced Materials and Joint International Research Laboratory of Precision Chemistry and Molecular Engineering, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Bin Zhang
- Key Laboratory for Advanced Materials and Joint International Research Laboratory of Precision Chemistry and Molecular Engineering, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
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14
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Ding G, Zhao J, Zhou K, Zheng Q, Han ST, Peng X, Zhou Y. Porous crystalline materials for memories and neuromorphic computing systems. Chem Soc Rev 2023; 52:7071-7136. [PMID: 37755573 DOI: 10.1039/d3cs00259d] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/28/2023]
Abstract
Porous crystalline materials usually include metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs) and zeolites, which exhibit exceptional porosity and structural/composition designability, promoting the increasing attention in memory and neuromorphic computing systems in the last decade. From both the perspective of materials and devices, it is crucial to provide a comprehensive and timely summary of the applications of porous crystalline materials in memory and neuromorphic computing systems to guide future research endeavors. Moreover, the utilization of porous crystalline materials in electronics necessitates a shift from powder synthesis to high-quality film preparation to ensure high device performance. This review highlights the strategies for preparing porous crystalline materials films and discusses their advancements in memory and neuromorphic electronics. It also provides a detailed comparative analysis and presents the existing challenges and future research directions, which can attract the experts from various fields (e.g., materials scientists, chemists, and engineers) with the aim of promoting the applications of porous crystalline materials in memory and neuromorphic computing systems.
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Affiliation(s)
- Guanglong Ding
- Institute for Advanced Study, Shenzhen University, Shenzhen, China.
| | - JiYu Zhao
- Institute for Advanced Study, Shenzhen University, Shenzhen, China.
- State Key Laboratory of Fine Chemicals, Frontiers Science Center for Smart Materials, Dalian University of Technology, Dalian 116024, China
- State Key Laboratory of Fine Chemicals, College of Materials Science and Engineering, Shenzhen University, Shenzhen 518060, China
| | - Kui Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen, China.
| | - Qi Zheng
- Institute for Advanced Study, Shenzhen University, Shenzhen, China.
| | - Su-Ting Han
- College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 518060, China
| | - Xiaojun Peng
- State Key Laboratory of Fine Chemicals, Frontiers Science Center for Smart Materials, Dalian University of Technology, Dalian 116024, China
- State Key Laboratory of Fine Chemicals, College of Materials Science and Engineering, Shenzhen University, Shenzhen 518060, China
| | - Ye Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen, China.
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15
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Bak J, Kim S, Park K, Yoon J, Yang M, Kim UJ, Hosono H, Park J, You B, Kwon O, Cho B, Park SW, Hahm MG, Lee M. Reinforcing Synaptic Plasticity of Defect-Tolerant States in Alloyed 2D Artificial Transistors. ACS APPLIED MATERIALS & INTERFACES 2023; 15:39539-39549. [PMID: 37614002 DOI: 10.1021/acsami.3c07578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Abstract
While two-dimensional (2D) materials possess the desirable future of neuromorphic computing platforms, unstable charging and de-trapping processes, which are inherited from uncontrollable states, such as the interface trap between nanocrystals and dielectric layers, can deteriorate the synaptic plasticity in field-effect transistors. Here, we report a facile and effective strategy to promote artificial synaptic devices by providing physical doping in 2D transition-metal dichalcogenide nanomaterials. Our experiments demonstrate that the introduction of niobium (Nb) into 2D WSe2 nanomaterials produces charge trap levels in the band gap and retards the decay of the trapped charges, thereby accelerating the artificial synaptic plasticity by encouraging improved short-/long-term plasticity, increased multilevel states, lower power consumption, and better symmetry and asymmetry ratios. Density functional theory calculations also proved that the addition of Nb to 2D WSe2 generates defect tolerance levels, thereby governing the charging and de-trapping mechanisms of the synaptic devices. Physically doped electronic synapses are expected to be a promising strategy for the development of bioinspired artificial electronic devices.
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Affiliation(s)
- Jina Bak
- Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
| | - Seunggyu Kim
- Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
| | - Kyumin Park
- Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
| | - Jeechan Yoon
- Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
| | - Mino Yang
- Korea Basic Science Institute Seoul, 145 anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Un Jeong Kim
- Advanced Sensor Lab, Samsung Advanced Institute of Technology, 130 Samsung-ro, Yeongtong-gu, Suwon, Gyeonggi 16678, Republic of Korea
| | - Hideo Hosono
- MDX Research Center for Element Strategy, International Research Frontiers Initiative, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama 226-8503, Japan
| | - Jihyang Park
- Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
| | - Bolim You
- Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
| | - Ojun Kwon
- Department of Advanced Material Engineering, Chungbuk National University, 1 Chungdae-ro, Seowon-Gu, Cheongju, Chungbuk 28644, Republic of Korea
| | - Byungjin Cho
- Department of Advanced Material Engineering, Chungbuk National University, 1 Chungdae-ro, Seowon-Gu, Cheongju, Chungbuk 28644, Republic of Korea
- Department of Urban, Energy, and Environmental Engineering, Chungbuk National University, 1 Chungdae-ro, Seowon-Gu, Cheongju, Chungbuk 28644, Republic of Korea
| | - Sang-Won Park
- Department of Chemical and Materials Engineering, University of Suwon, 17 Wauan-gil, Bongdam-eup, Hwaseong, Gyeonggi 18323, Republic of Korea
| | - Myung Gwan Hahm
- Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
| | - Moonsang Lee
- Department of Materials Science and Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
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16
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Wei Y, Liu Y, Lin Q, Liu T, Wang S, Chen H, Li C, Gu X, Zhang X, Huang H. Organic Optoelectronic Synapses for Sound Perception. NANO-MICRO LETTERS 2023; 15:133. [PMID: 37221281 PMCID: PMC10205940 DOI: 10.1007/s40820-023-01116-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/24/2023] [Indexed: 05/25/2023]
Abstract
The neuromorphic systems for sound perception is under highly demanding for the future bioinspired electronics and humanoid robots. However, the sound perception based on volume, tone and timbre remains unknown. Herein, organic optoelectronic synapses (OOSs) are constructed for unprecedented sound recognition. The volume, tone and timbre of sound can be regulated appropriately by the input signal of voltages, frequencies and light intensities of OOSs, according to the amplitude, frequency, and waveform of the sound. The quantitative relation between recognition factor (ζ) and postsynaptic current (I = Ilight - Idark) is established to achieve sound perception. Interestingly, the bell sound for University of Chinese Academy of Sciences is recognized with an accuracy of 99.8%. The mechanism studies reveal that the impedance of the interfacial layers play a critical role in the synaptic performances. This contribution presents unprecedented artificial synapses for sound perception at hardware levels.
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Affiliation(s)
- Yanan Wei
- College of Materials Science and Opto-Electronic Technology and Center of Materials Science and Optoelectronics Engineering, CAS Center for Excellence in Topological Quantum Computation, CAS Key Laboratory of Vacuum Physic, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Youxing Liu
- School of Materials Science and Engineering, Peking University, Beijing, 100871, People's Republic of China
| | - Qijie Lin
- College of Materials Science and Opto-Electronic Technology and Center of Materials Science and Optoelectronics Engineering, CAS Center for Excellence in Topological Quantum Computation, CAS Key Laboratory of Vacuum Physic, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Tianhua Liu
- College of Materials Science and Opto-Electronic Technology and Center of Materials Science and Optoelectronics Engineering, CAS Center for Excellence in Topological Quantum Computation, CAS Key Laboratory of Vacuum Physic, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Song Wang
- College of Materials Science and Opto-Electronic Technology and Center of Materials Science and Optoelectronics Engineering, CAS Center for Excellence in Topological Quantum Computation, CAS Key Laboratory of Vacuum Physic, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Hao Chen
- College of Materials Science and Opto-Electronic Technology and Center of Materials Science and Optoelectronics Engineering, CAS Center for Excellence in Topological Quantum Computation, CAS Key Laboratory of Vacuum Physic, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Congqi Li
- College of Materials Science and Opto-Electronic Technology and Center of Materials Science and Optoelectronics Engineering, CAS Center for Excellence in Topological Quantum Computation, CAS Key Laboratory of Vacuum Physic, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Xiaobin Gu
- College of Materials Science and Opto-Electronic Technology and Center of Materials Science and Optoelectronics Engineering, CAS Center for Excellence in Topological Quantum Computation, CAS Key Laboratory of Vacuum Physic, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Xin Zhang
- College of Materials Science and Opto-Electronic Technology and Center of Materials Science and Optoelectronics Engineering, CAS Center for Excellence in Topological Quantum Computation, CAS Key Laboratory of Vacuum Physic, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China.
| | - Hui Huang
- College of Materials Science and Opto-Electronic Technology and Center of Materials Science and Optoelectronics Engineering, CAS Center for Excellence in Topological Quantum Computation, CAS Key Laboratory of Vacuum Physic, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China.
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17
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Cho DY, Kim KJ, Lee KS, Lübben M, Chen S, Valov I. Chemical Influence of Carbon Interface Layers in Metal/Oxide Resistive Switches. ACS APPLIED MATERIALS & INTERFACES 2023; 15:18528-18536. [PMID: 36989142 PMCID: PMC10103050 DOI: 10.1021/acsami.3c00920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/21/2023] [Indexed: 06/19/2023]
Abstract
Thin layers introduced between a metal electrode and a solid electrolyte can significantly alter the transport of mass and charge at the interfaces and influence the rate of electrode reactions. C films embedded in functional materials can change the chemical properties of the host, thereby altering the functionality of the whole device. Using X-ray spectroscopies, here we demonstrate that the chemical and electronic structures in a representative redox-based resistive switching (RS) system, Ta2O5/Ta, can be tuned by inserting a graphene or ultrathin amorphous C layer. The results of the orbitalwise analyses of synchrotron Ta L3-edge, C K-edge, and O K-edge X-ray absorption spectroscopy showed that the C layers between Ta2O5 and Ta are significantly oxidized to form COx and, at the same time, oxidize the Ta layers with different degrees of oxidation depending on the distance: full oxidation at the nearest 5 nm Ta and partial oxidation in the next 15 nm Ta. The depth-resolved information on the electronic structure for each layer further revealed a significant modification of the band alignments due to C insertion. Full oxidation of the Ta metal near the C interlayer suggests that the oxygen-vacancy-related valence change memory mechanism for the RS can be suppressed, thereby changing the RS functionalities fundamentally. The knowledge on the origin of C-enhanced surfaces can be applied to other metal/oxide interfaces and used for the advanced design of memristive devices.
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Affiliation(s)
- Deok-Yong Cho
- IPIT
and Department of Physics, Jeonbuk National
University, Jeonju 54896, Republic of Korea
| | - Ki-jeong Kim
- Pohang
Accelerator Laboratory, Pohang 37673, Republic of Korea
| | - Kug-Seung Lee
- Pohang
Accelerator Laboratory, Pohang 37673, Republic of Korea
| | - Michael Lübben
- Peter
Gruenberg
Institute, Research Centre Juelich, Juelich 52425, Germany
| | - Shaochuan Chen
- IWE2, RWTH Aachen University, Sommerfed strasse 24, Aachen 52074, Germany
| | - Ilia Valov
- Peter
Gruenberg
Institute, Research Centre Juelich, Juelich 52425, Germany
- Institute
of Electrochemistry and Energy Systems “acad. E. Budewski”, Bulgarian Academy of Sciences, “acad. G Bonchev” street Bl.10, Sofia 1113, Bulgaria
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18
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Desai TR, Kundale SS, Dongale TD, Gurnani C. Evaluation of Cellulose–MXene Composite Hydrogel Based Bio-Resistive Random Access Memory Material as Mimics for Biological Synapses. ACS APPLIED BIO MATERIALS 2023; 6:1763-1773. [PMID: 36976913 DOI: 10.1021/acsabm.2c01073] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
We report a memory device based on organic-inorganic hybrid cellulose-Ti3C2TX MXene composite hydrogel (CMCH) as a switching layer sandwiched between Ag top and FTO bottom electrodes. The device (Ag/CMCH/FTO) was fabricated by a simple, solution-processed route and exhibits reliable and reproducible bipolar resistive switching. Multilevel switching behavior was observed at low operating voltages (±0.5 to ±1 V). Furthermore, the capacitive-coupled memristive characteristics of the device were corroborated with electrochemical impedance spectroscopy and this affirmed the filamentary conduction switching mechanism (LRS-HRS). The synaptic functions of the CMCH-based memory device were evaluated, wherein potentiation/depression properties over 8 × 103 electric pulses were observed. The device also exhibited spike time-dependent plasticity-based symmetric Hebbian learning rule of a biological synapse. This hybrid hydrogel is expected to be a potential switching material for low-cost, sustainable, and biocompatible memory storage devices and artificial synaptic applications.
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19
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Hwang Y, Park B, Hwang S, Choi SW, Kim HS, Kim AR, Choi JW, Yoon J, Kwon JD, Kim Y. A Bioinspired Ultra Flexible Artificial van der Waals 2D-MoS 2 Channel/LiSiO x Solid Electrolyte Synapse Arrays via Laser-Lift Off Process for Wearable Adaptive Neuromorphic Computing. SMALL METHODS 2023:e2201719. [PMID: 36960927 DOI: 10.1002/smtd.202201719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 02/06/2023] [Indexed: 06/18/2023]
Abstract
Wearable electronic devices with next-generation biocompatible, mechanical, ultraflexible, and portable sensors are a fast-growing technology. Hardware systems enabling artificial neural networks while consuming low power and processing massive in situ personal data are essential for adaptive wearable neuromorphic edging computing. Herein, the development of an ultraflexible artificial-synaptic array device with concrete-mechanical cyclic endurance consisting of a novel heterostructure with an all-solid-state 2D MoS2 channel and LiSiOx (lithium silicate) is demonstrated. Enabled by the sequential fabrication process of all layers, by excluding the transfer process, artificial van der Waals devices combined with the 2D-MoS2 channel and LiSiOx solid electrolyte exhibit excellent neuromorphic synaptic characteristics with a nonlinearity of 0.55 and asymmetry ratio of 0.22. Based on the excellent flexibility of colorless polyimide substrates and thin-layered structures, the fabricated flexible neuromorphic synaptic devices exhibit superior long-term potentiation and long-term depression cyclic endurance performance, even when bent over 700 times or on curved surfaces with a diameter of 10 mm. Thus, a high classification accuracy of 95% is achieved without any noticeable performance degradation in the Modified National Institute of Standards and Technology. These results are promising for the development of personalized wearable artificial neural systems in the future.
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Affiliation(s)
- Yunjeong Hwang
- Department of Energy and Electronic Materials, Surface Materials Division, Korea Institute of Materials Science (KIMS), 797 Changwondaero, Sungsan-gu, Changwon, Gyeongnam, 51508, Republic of Korea
| | - Byeongjin Park
- Department of Energy and Electronic Materials, Surface Materials Division, Korea Institute of Materials Science (KIMS), 797 Changwondaero, Sungsan-gu, Changwon, Gyeongnam, 51508, Republic of Korea
- School of Materials Science and Engineering, Pusan National University, 2 Busandaehak-ro 63-beon-gil, Geumjeong-gu, Busan, 46241, Republic of Korea
| | - Seungkwon Hwang
- Department of Energy and Electronic Materials, Surface Materials Division, Korea Institute of Materials Science (KIMS), 797 Changwondaero, Sungsan-gu, Changwon, Gyeongnam, 51508, Republic of Korea
- School of Materials Science and Engineering, Pusan National University, 2 Busandaehak-ro 63-beon-gil, Geumjeong-gu, Busan, 46241, Republic of Korea
| | - Soo-Won Choi
- Department of Energy and Electronic Materials, Surface Materials Division, Korea Institute of Materials Science (KIMS), 797 Changwondaero, Sungsan-gu, Changwon, Gyeongnam, 51508, Republic of Korea
- School of Materials Science and Engineering, Pusan National University, 2 Busandaehak-ro 63-beon-gil, Geumjeong-gu, Busan, 46241, Republic of Korea
| | - Han Seul Kim
- Department of Advanced Materials Engineering, Chungbuk National University, 1 Chungdae-ro, Seowon-gu, Cheongju, 28644, Republic of Korea
| | - Ah Ra Kim
- Department of Energy and Electronic Materials, Surface Materials Division, Korea Institute of Materials Science (KIMS), 797 Changwondaero, Sungsan-gu, Changwon, Gyeongnam, 51508, Republic of Korea
| | - Jin Woo Choi
- Department of Data Information and Physics, Kongju National University, 56 Gongjudaehak-ro, Gongju, Chungcheongnam-do, 32588, Republic ofKorea
| | - Jongwon Yoon
- Department of Energy and Electronic Materials, Surface Materials Division, Korea Institute of Materials Science (KIMS), 797 Changwondaero, Sungsan-gu, Changwon, Gyeongnam, 51508, Republic of Korea
| | - Jung-Dae Kwon
- Department of Energy and Electronic Materials, Surface Materials Division, Korea Institute of Materials Science (KIMS), 797 Changwondaero, Sungsan-gu, Changwon, Gyeongnam, 51508, Republic of Korea
| | - Yonghun Kim
- Department of Energy and Electronic Materials, Surface Materials Division, Korea Institute of Materials Science (KIMS), 797 Changwondaero, Sungsan-gu, Changwon, Gyeongnam, 51508, Republic of Korea
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20
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Baek JH, Kwak KJ, Kim SJ, Kim J, Kim JY, Im IH, Lee S, Kang K, Jang HW. Two-Terminal Lithium-Mediated Artificial Synapses with Enhanced Weight Modulation for Feasible Hardware Neural Networks. NANO-MICRO LETTERS 2023; 15:69. [PMID: 36943534 PMCID: PMC10030746 DOI: 10.1007/s40820-023-01035-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 02/01/2023] [Indexed: 05/25/2023]
Abstract
Recently, artificial synapses involving an electrochemical reaction of Li-ion have been attributed to have remarkable synaptic properties. Three-terminal synaptic transistors utilizing Li-ion intercalation exhibits reliable synaptic characteristics by exploiting the advantage of non-distributed weight updates owing to stable ion migrations. However, the three-terminal configurations with large and complex structures impede the crossbar array implementation required for hardware neuromorphic systems. Meanwhile, achieving adequate synaptic performances through effective Li-ion intercalation in vertical two-terminal synaptic devices for array integration remains challenging. Here, two-terminal Au/LixCoO2/Pt artificial synapses are proposed with the potential for practical implementation of hardware neural networks. The Au/LixCoO2/Pt devices demonstrated extraordinary neuromorphic behaviors based on a progressive dearth of Li in LixCoO2 films. The intercalation and deintercalation of Li-ion inside the films are precisely controlled over the weight control spike, resulting in improved weight control functionality. Various types of synaptic plasticity were imitated and assessed in terms of key factors such as nonlinearity, symmetricity, and dynamic range. Notably, the LixCoO2-based neuromorphic system outperformed three-terminal synaptic transistors in simulations of convolutional neural networks and multilayer perceptrons due to the high linearity and low programming error. These impressive performances suggest the vertical two-terminal Au/LixCoO2/Pt artificial synapses as promising candidates for hardware neural networks.
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Affiliation(s)
- Ji Hyun Baek
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Kyung Ju Kwak
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Seung Ju Kim
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Jaehyun Kim
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Jae Young Kim
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - In Hyuk Im
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Sunyoung Lee
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Kisuk Kang
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea.
| | - Ho Won Jang
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea.
- Advanced Institute of Convergence Technology, Seoul National University, Suwon, 16229, Korea.
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21
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Lu N, Hu X, Jiang J, Guo H, Zuo GZ, Zhuo Z, Wu X, Zeng XC. Highly anisotropic and ultra-diffusive vacancies in α-antimonene. NANOSCALE 2023; 15:4821-4829. [PMID: 36794788 DOI: 10.1039/d3nr00194f] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
α-Antimonene has recently been successfully fabricated in experiment; hence, it is timely to examine how various types of point defects in α-antimonene can affect its novel electronic properties. Herein, we present a comprehensive investigation of a total of nine possible types of point defects in α-antimonene via first-principles calculations. Particular attention is placed on the structural stability of the point defects and the effects of point defects on the electronic properties of α-antimonene. Compared with its structural analogs, such as phosphorene, graphene, and silicene, we find that most defects in α-antimonene can be more easily generated, and that among the nine types of point defects, the single vacancy SV-(5|9) is likely the most stable one while its presence can be orders of magnitude higher in concentration than that in phosphorene. Moreover, we find that the vacancy exhibits anisotropic and low diffusion barriers, of merely 0.10/0.30 eV in the zigzag/armchair direction. Notably, at room temperature, the migration of SV-(5|9) in the zigzag direction of α-antimonene is estimated to be three orders faster than that along the armchair direction, and also three orders faster than that of phosphorene in the same direction. Overall, the point defects in α-antimonene can significantly affect the electronic properties of the host two-dimensional (2D) semiconductor and thus the light absorption capability. The anisotropic, ultra-diffusive, and charge tunable single vacancies, along with the high oxidation resistance, render the α-antimonene sheet a unique 2D semiconductor (beyond the phosphorene) for developing vacancy-enabled nanoelectronics.
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Affiliation(s)
- Ning Lu
- Anhui Province Key Laboratory of Optoelectric Materials Science and Technology, Key Laboratory of Functional Molecular Solids Ministry of Education, Anhui Laboratory of Molecule-Based Materials, and Department of Physics, Anhui Normal University, Wuhu, Anhui, 241000, China.
| | - Xin Hu
- Anhui Province Key Laboratory of Optoelectric Materials Science and Technology, Key Laboratory of Functional Molecular Solids Ministry of Education, Anhui Laboratory of Molecule-Based Materials, and Department of Physics, Anhui Normal University, Wuhu, Anhui, 241000, China.
| | - Jiaxin Jiang
- Anhui Province Key Laboratory of Optoelectric Materials Science and Technology, Key Laboratory of Functional Molecular Solids Ministry of Education, Anhui Laboratory of Molecule-Based Materials, and Department of Physics, Anhui Normal University, Wuhu, Anhui, 241000, China.
| | - Hongyan Guo
- Anhui Province Key Laboratory of Optoelectric Materials Science and Technology, Key Laboratory of Functional Molecular Solids Ministry of Education, Anhui Laboratory of Molecule-Based Materials, and Department of Physics, Anhui Normal University, Wuhu, Anhui, 241000, China.
| | - Gui Zhong Zuo
- Institute of Plasma Physics, HIPS, Chinese Academy of Sciences, Hefei, 230031, China
| | - Zhiwen Zhuo
- Anhui Province Key Laboratory of Optoelectric Materials Science and Technology, Key Laboratory of Functional Molecular Solids Ministry of Education, Anhui Laboratory of Molecule-Based Materials, and Department of Physics, Anhui Normal University, Wuhu, Anhui, 241000, China.
| | - Xiaojun Wu
- Hefei National Laboratory for Physical Sciences at the Microscale, CAS Key Laboratory of Materials for Energy Conversion, and School of Chemistry and Materials Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Xiao Cheng Zeng
- Department of Materials Science & Engineering, City University of Hong Kong, Kowloon, 999077, Hong Kong.
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22
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Giri A, Park G, Jeong U. Layer-Structured Anisotropic Metal Chalcogenides: Recent Advances in Synthesis, Modulation, and Applications. Chem Rev 2023; 123:3329-3442. [PMID: 36719999 PMCID: PMC10103142 DOI: 10.1021/acs.chemrev.2c00455] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
The unique electronic and catalytic properties emerging from low symmetry anisotropic (1D and 2D) metal chalcogenides (MCs) have generated tremendous interest for use in next generation electronics, optoelectronics, electrochemical energy storage devices, and chemical sensing devices. Despite many proof-of-concept demonstrations so far, the full potential of anisotropic chalcogenides has yet to be investigated. This article provides a comprehensive overview of the recent progress made in the synthesis, mechanistic understanding, property modulation strategies, and applications of the anisotropic chalcogenides. It begins with an introduction to the basic crystal structures, and then the unique physical and chemical properties of 1D and 2D MCs. Controlled synthetic routes for anisotropic MC crystals are summarized with example advances in the solution-phase synthesis, vapor-phase synthesis, and exfoliation. Several important approaches to modulate dimensions, phases, compositions, defects, and heterostructures of anisotropic MCs are discussed. Recent significant advances in applications are highlighted for electronics, optoelectronic devices, catalysts, batteries, supercapacitors, sensing platforms, and thermoelectric devices. The article ends with prospects for future opportunities and challenges to be addressed in the academic research and practical engineering of anisotropic MCs.
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Affiliation(s)
- Anupam Giri
- Department of Chemistry, Faculty of Science, University of Allahabad, Prayagraj, UP-211002, India
| | - Gyeongbae Park
- Department of Materials Science and Engineering, Pohang University of Science and Technology, Cheongam-Ro 77, Nam-Gu, Pohang, Gyeongbuk790-784, Korea.,Functional Materials and Components R&D Group, Korea Institute of Industrial Technology, Gwahakdanji-ro 137-41, Sacheon-myeon, Gangneung, Gangwon-do25440, Republic of Korea
| | - Unyong Jeong
- Department of Materials Science and Engineering, Pohang University of Science and Technology, Cheongam-Ro 77, Nam-Gu, Pohang, Gyeongbuk790-784, Korea
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23
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Zeng J, Zhao J, Bu T, Liu G, Qi Y, Zhou H, Dong S, Zhang C. A Flexible Tribotronic Artificial Synapse with Bioinspired Neurosensory Behavior. NANO-MICRO LETTERS 2022; 15:18. [PMID: 36580114 PMCID: PMC9800681 DOI: 10.1007/s40820-022-00989-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/04/2022] [Indexed: 06/17/2023]
Abstract
As key components of artificial afferent nervous systems, synaptic devices can mimic the physiological synaptic behaviors, which have attracted extensive attentions. Here, a flexible tribotronic artificial synapse (TAS) with bioinspired neurosensory behavior is developed. The triboelectric potential generated by the external contact electrification is used as the ion-gel-gate voltage of the organic thin film transistor, which can tune the carriers transport through the migration/accumulation of ions. The TAS successfully demonstrates a series of synaptic behaviors by external stimuli, such as excitatory postsynaptic current, paired-pulse facilitation, and the hierarchical memory process from sensory memory to short-term memory and long-term memory. Moreover, the synaptic behaviors remained stable under the strain condition with a bending radius of 20 mm, and the TAS still exhibits excellent durability after 1000 bending cycles. Finally, Pavlovian conditioning has been successfully mimicked by applying force and vibration as food and bell, respectively. This work demonstrates a bioinspired flexible artificial synapse that will help to facilitate the development of artificial afferent nervous systems, which is great significance to the practical application of artificial limbs, robotics, and bionics in future.
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Affiliation(s)
- Jianhua Zeng
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, People's Republic of China
- Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, 530004, People's Republic of China
| | - Junqing Zhao
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, People's Republic of China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Tianzhao Bu
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, People's Republic of China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Guoxu Liu
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, People's Republic of China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Youchao Qi
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, People's Republic of China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Han Zhou
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, People's Republic of China
- Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, 530004, People's Republic of China
| | - Sicheng Dong
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, People's Republic of China
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China
| | - Chi Zhang
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 101400, People's Republic of China.
- Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, 530004, People's Republic of China.
- School of Nanoscience and Technology, University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China.
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24
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Sebastian A, Pendurthi R, Kozhakhmetov A, Trainor N, Robinson JA, Redwing JM, Das S. Two-dimensional materials-based probabilistic synapses and reconfigurable neurons for measuring inference uncertainty using Bayesian neural networks. Nat Commun 2022; 13:6139. [PMID: 36253370 PMCID: PMC9576759 DOI: 10.1038/s41467-022-33699-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 09/27/2022] [Indexed: 12/24/2022] Open
Abstract
Artificial neural networks have demonstrated superiority over traditional computing architectures in tasks such as pattern classification and learning. However, they do not measure uncertainty in predictions, and hence they can make wrong predictions with high confidence, which can be detrimental for many mission-critical applications. In contrast, Bayesian neural networks (BNNs) naturally include such uncertainty in their model, as the weights are represented by probability distributions (e.g. Gaussian distribution). Here we introduce three-terminal memtransistors based on two-dimensional (2D) materials, which can emulate both probabilistic synapses as well as reconfigurable neurons. The cycle-to-cycle variation in the programming of the 2D memtransistor is exploited to achieve Gaussian random number generator-based synapses, whereas 2D memtransistor based integrated circuits are used to obtain neurons with hyperbolic tangent and sigmoid activation functions. Finally, memtransistor-based synapses and neurons are combined in a crossbar array architecture to realize a BNN accelerator for a data classification task.
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Affiliation(s)
- Amritanand Sebastian
- grid.29857.310000 0001 2097 4281Deparment of Engineering Science and Mechanics, Penn State University, University Park, PA 16802 USA
| | - Rahul Pendurthi
- grid.29857.310000 0001 2097 4281Deparment of Engineering Science and Mechanics, Penn State University, University Park, PA 16802 USA
| | - Azimkhan Kozhakhmetov
- grid.29857.310000 0001 2097 4281Department of Materials Science and Engineering, Penn State University, University Park, PA 16802 USA
| | - Nicholas Trainor
- grid.29857.310000 0001 2097 4281Department of Materials Science and Engineering, Penn State University, University Park, PA 16802 USA ,grid.29857.310000 0001 2097 42812D Crystal Consortium Materials Innovation Platform, Penn State University, University Park, PA 16802 USA
| | - Joshua A. Robinson
- grid.29857.310000 0001 2097 4281Department of Materials Science and Engineering, Penn State University, University Park, PA 16802 USA ,grid.29857.310000 0001 2097 4281Department of Chemistry, Penn State University, University Park, PA USA ,grid.29857.310000 0001 2097 4281Department of Physics, Penn State University, University Park, PA USA
| | - Joan M. Redwing
- grid.29857.310000 0001 2097 4281Department of Materials Science and Engineering, Penn State University, University Park, PA 16802 USA ,grid.29857.310000 0001 2097 42812D Crystal Consortium Materials Innovation Platform, Penn State University, University Park, PA 16802 USA ,grid.29857.310000 0001 2097 4281Department of Electrical Engineering and Computer Science, Penn State University, University Park, PA USA
| | - Saptarshi Das
- grid.29857.310000 0001 2097 4281Deparment of Engineering Science and Mechanics, Penn State University, University Park, PA 16802 USA ,grid.29857.310000 0001 2097 4281Department of Materials Science and Engineering, Penn State University, University Park, PA 16802 USA ,grid.29857.310000 0001 2097 4281Department of Electrical Engineering and Computer Science, Penn State University, University Park, PA USA
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25
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Cho SW, Jo C, Kim YH, Park SK. Progress of Materials and Devices for Neuromorphic Vision Sensors. NANO-MICRO LETTERS 2022; 14:203. [PMID: 36242681 PMCID: PMC9569410 DOI: 10.1007/s40820-022-00945-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/08/2022] [Indexed: 05/31/2023]
Abstract
The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords: smaller, faster, and smarter. (1) Smaller: Devices are becoming more compact by integrating previously separated components such as sensors, memory, and processing units. As a prime example, the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits, such as simpler circuitry, lower power consumption, and less data redundancy. (2) Swifter: Owing to the nature of physics, smaller and more integrated devices can detect, process, and react to input more quickly. In addition, the methods for sensing and processing optical information using various materials (such as oxide semiconductors) are evolving. (3) Smarter: Owing to these two main research directions, we can expect advanced applications such as adaptive vision sensors, collision sensors, and nociceptive sensors. This review mainly focuses on the recent progress, working mechanisms, image pre-processing techniques, and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.
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Affiliation(s)
- Sung Woon Cho
- Department of Advanced Components and Materials Engineering, Sunchon National University, Sunchŏn, Jeonnam, 57922, Republic of Korea
| | - Chanho Jo
- Department 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.
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, 16419, Republic of Korea.
| | - Sung Kyu Park
- Department of Electrical and Electronics Engineering, Chung-Ang University, Seoul, 06974, Republic of Korea.
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26
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Xin X, Sun L, Chen J, Bao Y, Tao Y, Lin Y, Bian J, Wang Z, Zhao X, Xu H, Liu Y. Real-time numerical system convertor via two-dimensional WS2-based memristive device. Front Comput Neurosci 2022; 16:1015945. [PMID: 36185713 PMCID: PMC9517377 DOI: 10.3389/fncom.2022.1015945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 08/29/2022] [Indexed: 11/13/2022] Open
Abstract
The intriguing properties of two-dimensional (2D) transition metal dichalcogenides (TMDCs) enable the exploration of new electronic device architectures, particularly the emerging memristive devices for in-memory computing applications. Implementation of arithmetic logic operations taking advantage of the non-linear characteristics of memristor can significantly improve the energy efficiency and simplify the complexity of peripheral circuits. Herein, we demonstrate an arithmetic logic unit function using a lateral volatile memristor based on layered 2D tungsten disulfide (WS2) materials and some combinational logic circuits. Removable oxygen ions were introduced into WS2 materials through oxygen plasma treatment process. The resistive switching of the memristive device caused by the thermophoresis-assisted oxygen ions migration has also been revealed. Based on the characteristics of excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and spike rate dependent plasticity (SRDP), a real-time numerical system convertor was successfully accomplished, which is a significant computing function of arithmetic logic unit. This work paves a new way for developing 2D memristive devices for future arithmetic logic applications.
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27
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Bisht P, Kumar A, Ghosh A, Vullum PE, Sunding MF, Belle BD, Mehta BR. Tailoring the Vertical and Planar Growth of 2D WS 2 Thin Films Using Pulsed Laser Deposition for Enhanced Gas Sensing Properties. ACS APPLIED MATERIALS & INTERFACES 2022; 14:36789-36800. [PMID: 35943092 DOI: 10.1021/acsami.2c07759] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In this study, pulsed laser deposition has been utilized for the controllable synthesis of WS2 thin films with growth orientation ranging from vertically to horizontally aligned layers, and the effect of growth parameters has been investigated. The growth of thin films on SiO2 substrates at three different pressures (30, 50, and 70 mTorr) and three different temperatures (400, 500, and 600 °C) has been studied. Detailed characterizations carried out on the as-grown layers clearly show the formation of the 2H-WS2 phase and its morphological evolution with deposition conditions. Atomic force microscopy and cross-sectional transmission electron microscopy have been used to deduce the growth mechanism of the vertical and planar films with different deposition parameters. The samples grown with a combination of lower temperatures and higher pressures exhibit a vertical flake-like growth with a flake thickness of ∼2-5 nm. However, at higher temperatures and lower pressures, the film growth is observed to be rather planar. The gas sensing parameters and the underlying mechanism have been observed to be quite different for vertically and horizontally grown layers. The vertical layers showed a selective response toward NO2 gas at room temperature (RT) with a limit of detection less than 50 ppb. In comparison, a very subdued and poor gas sensing response was recorded for the planar film at RT. A large specific area and abundance of active edge sites along with the flat basal plane present in the vertically grown layers seem to be responsible for efficient gas sensing toward NO2.
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Affiliation(s)
- Prashant Bisht
- Thin Film Laboratory, Department of Physics, Indian Institute of Technology Delhi, New Delhi 110016, India
| | - Arvind Kumar
- Thin Film Laboratory, Department of Physics, Indian Institute of Technology Delhi, New Delhi 110016, India
| | - Abhishek Ghosh
- Thin Film Laboratory, Department of Physics, Indian Institute of Technology Delhi, New Delhi 110016, India
| | - Per Erik Vullum
- SINTEF Industry, Høgskoleringen, NO: 57046, Trondheim 7491, Norway
| | | | - Branson D Belle
- SINTEF Industry, Materials Physics, Forskningsveien 1, NO: 0373, Oslo 0314, Norway
| | - Bodh Raj Mehta
- Thin Film Laboratory, Department of Physics, Indian Institute of Technology Delhi, New Delhi 110016, India
- Directorate of Research, Innovation and Development, Jaypee Institute of Information Technology, Noida, Uttar Pradesh 201309, India
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28
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Duan H, Cheng S, Qin L, Zhang X, Xie B, Zhang Y, Jie W. Low-Power Memristor Based on Two-Dimensional Materials. J Phys Chem Lett 2022; 13:7130-7138. [PMID: 35900941 DOI: 10.1021/acs.jpclett.2c01962] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The memristor is an excellent candidate for nonvolatile memory and neuromorphic computing. Recently, two-dimensional (2D) materials have been developed for use in memristors with high-performance resistive switching characteristics, such as high on/off ratios, low SET/RESET voltages, good retention and endurance, fast switching speed, and low power and energy consumption. Low-power memristors are highly desired for recent fast-speed and energy-efficient artificial neuromorphic networks. This Perspective focuses on the recent progress of low-power memristors based on 2D materials, providing a condensed overview of relevant developments in memristive performance, physical mechanism, material modification, and device assembly as well as potential applications. The detailed research status of memristors has been reviewed based on different 2D materials from insulating hexagonal boron nitride, semiconducting transition metal dichalcogenides, to some newly developed 2D materials. Furthermore, a brief summary introducing the perspectives and challenges is included, with the aim of providing an insightful guide for this research field.
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Affiliation(s)
- Huan Duan
- College of Chemistry and Materials Science, Sichuan Normal University, Chengdu 610066, China
| | - Siqi Cheng
- College of Chemistry and Materials Science, Sichuan Normal University, Chengdu 610066, China
| | - Ling Qin
- College of Chemistry and Materials Science, Sichuan Normal University, Chengdu 610066, China
| | - Xuelian Zhang
- College of Chemistry and Materials Science, Sichuan Normal University, Chengdu 610066, China
| | - Bingyang Xie
- College of Chemistry and Materials Science, Sichuan Normal University, Chengdu 610066, China
| | - Yang Zhang
- Institute of Modern Optics & Tianjin Key Laboratory of Micro-Scale Optical Information Science and Technology, Nankai University, Tianjin 300071, China
| | - Wenjing Jie
- College of Chemistry and Materials Science, Sichuan Normal University, Chengdu 610066, China
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29
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Liu Y, Zhang W, Zheng W. Quantum Dots Compete at the Acme of MXene Family for the Optimal Catalysis. NANO-MICRO LETTERS 2022; 14:158. [PMID: 35916985 PMCID: PMC9346050 DOI: 10.1007/s40820-022-00908-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 06/25/2022] [Indexed: 05/05/2023]
Abstract
It is well known that two-dimensional (2D) MXene-derived quantum dots (MQDs) inherit the excellent physicochemical properties of the parental MXenes, as a Chinese proverb says, "Indigo blue is extracted from the indigo plant, but is bluer than the plant it comes from." Therefore, 0D QDs harvest larger surface-to-volume ratio, outstanding optical properties, and vigorous quantum confinement effect. Currently, MQDs trigger enormous research enthusiasm as an emerging star of functional materials applied to physics, chemistry, biology, energy conversion, and storage. Since the surface properties of small-sized MQDs include the type of surface functional groups, the functionalized surface directly determines their performance. As the Nobel Laureate Wolfgang Pauli says, "God made the bulk, but the surface was invented by the devil," and it is just on the basis of the abundant surface functional groups, there is lots of space to be thereof excavated from MQDs. We are witnessing such excellence and even more promising to be expected. Nowadays, MQDs have been widely applied to catalysis, whereas the related reviews are rarely reported. Herein, we provide a state-of-the-art overview of MQDs in catalysis over the past five years, ranging from the origin and development of MQDs, synthetic routes of MQDs, and functionalized MQDs to advanced characterization techniques. To explore the diversity of catalytic application and perspectives of MQDs, our review will stimulate more efforts toward the synthesis of optimal MQDs and thereof designing high-performance MQDs-based catalysts.
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Affiliation(s)
- Yuhua Liu
- Key Laboratory of Automobile Materials MOE, and School of Materials Science and Engineering, and Jilin Provincial International Cooperation Key Laboratory of High-Efficiency Clean Energy Materials, and Electron Microscopy Center, and International Center of Future Science, Jilin University, Changchun, 130012, People's Republic of China
| | - Wei Zhang
- Key Laboratory of Automobile Materials MOE, and School of Materials Science and Engineering, and Jilin Provincial International Cooperation Key Laboratory of High-Efficiency Clean Energy Materials, and Electron Microscopy Center, and International Center of Future Science, Jilin University, Changchun, 130012, People's Republic of China.
| | - Weitao Zheng
- Key Laboratory of Automobile Materials MOE, and School of Materials Science and Engineering, and Jilin Provincial International Cooperation Key Laboratory of High-Efficiency Clean Energy Materials, and Electron Microscopy Center, and International Center of Future Science, Jilin University, Changchun, 130012, People's Republic of China.
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30
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Yu L, Xu L, Lu L, Alhalili Z, Zhou X. Thermal Properties of MXenes and Relevant Applications. Chemphyschem 2022; 23:e202200203. [PMID: 35674280 DOI: 10.1002/cphc.202200203] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 05/26/2022] [Indexed: 11/10/2022]
Abstract
The properties and applications of MXenes (a family of layered transition metal carbides, nitrides, and carbonitrides) have aroused enormous research interests for a decade since the successful synthesis of few-layer transition metal carbides in 2011. Though MXenes, as the building blocks, have already been applied in various fields (such as wearable electronics) owing to the distinctive optical, mechanical and electrical properties, their thermal stability and intrinsic thermal properties were less thoroughly investigated compared to other characteristics in early reports. The pioneering theoretical prediction of the thermoelectric nature of MXenes was performed in 2013 while the first experiment-based report concerning the degradation behavior of the 2D structure at elevated temperatures in a controlled atmosphere was published in 2015, followed by numerous discoveries regarding the thermal properties of MXenes. Herein, after a brief description of the synthesis, this Review summarized the latest insights into the thermal stability and thermophysical properties of MXenes, and further associated these unique properties with relevant applications by multiple examples. Finally, current hurdles and challenges in this field were provided along with some advices on potential research directions in the future.
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Affiliation(s)
- LePing Yu
- Institute of Automotive Technology, Wuxi Vocational Institute of Commerce, Wuxi, Jiangsu 214153, People's Republic of China
| | - Lyu Xu
- Institute of Automotive Technology, Wuxi Vocational Institute of Commerce, Wuxi, Jiangsu 214153, People's Republic of China
| | - Lu Lu
- Institute of Automotive Technology, Wuxi Vocational Institute of Commerce, Wuxi, Jiangsu 214153, People's Republic of China
| | - Zahrah Alhalili
- College of Sciences and Arts, Shaqra University, Sajir, Riyadh, Saudi Arabia
| | - XiaoHong Zhou
- Institute of Automotive Technology, Wuxi Vocational Institute of Commerce, Wuxi, Jiangsu 214153, People's Republic of China
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