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Yu C, Li S, Pan Z, Liu Y, Wang Y, Zhou S, Gao Z, Tian H, Jiang K, Wang Y, Zhang J. Gate-Controlled Neuromorphic Functional Transition in an Electrochemical Graphene Transistor. NANO LETTERS 2024; 24:1620-1628. [PMID: 38277130 DOI: 10.1021/acs.nanolett.3c04193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2024]
Abstract
Neuromorphic devices have attracted significant attention as potential building blocks for the next generation of computing technologies owing to their ability to emulate the functionalities of biological nervous systems. The essential components in artificial neural networks such as synapses and neurons are predominantly implemented by dedicated devices with specific functionalities. In this work, we present a gate-controlled transition of neuromorphic functions between artificial neurons and synapses in monolayer graphene transistors that can be employed as memtransistors or synaptic transistors as required. By harnessing the reliability of reversible electrochemical reactions between carbon atoms and hydrogen ions, we can effectively manipulate the electric conductivity of graphene transistors, resulting in a high on/off resistance ratio, a well-defined set/reset voltage, and a prolonged retention time. Overall, the on-demand switching of neuromorphic functions in a single graphene transistor provides a promising opportunity for developing adaptive neural networks for the upcoming era of artificial intelligence and machine learning.
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Affiliation(s)
- Chenglin Yu
- State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University, Beijing 100084, China
| | - Shaorui Li
- State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University, Beijing 100084, China
| | - Zhoujie Pan
- XingJian College, Tsinghua University, Beijing 100084, China
| | - Yanming Liu
- School of Integrated Circuits, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yongchao Wang
- State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University, Beijing 100084, China
- Beijing Innovation Center for Future Chips, Tsinghua University, Beijing 100084, China
| | - Siyi Zhou
- State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University, Beijing 100084, China
| | - Zhiting Gao
- State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University, Beijing 100084, China
- Beijing Innovation Center for Future Chips, Tsinghua University, Beijing 100084, China
| | - He Tian
- School of Integrated Circuits, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Kaili Jiang
- State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University, Beijing 100084, China
- Tsinghua-Foxconn Nanotechnology Research Center, Department of Physics, Tsinghua University, Beijing 100084, China
| | - Yayu Wang
- State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University, Beijing 100084, China
- Frontier Science Center for Quantum Information, Beijing 100084, China
- Hefei National Laboratory, Hefei 230088, China
| | - Jinsong Zhang
- State Key Laboratory of Low Dimensional Quantum Physics, Department of Physics, Tsinghua University, Beijing 100084, China
- Frontier Science Center for Quantum Information, Beijing 100084, China
- Hefei National Laboratory, Hefei 230088, China
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Cao Z, Sun B, Zhou G, Mao S, Zhu S, Zhang J, Ke C, Zhao Y, Shao J. Memristor-based neural networks: a bridge from device to artificial intelligence. NANOSCALE HORIZONS 2023; 8:716-745. [PMID: 36946082 DOI: 10.1039/d2nh00536k] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Since the beginning of the 21st century, there is no doubt that the importance of artificial intelligence has been highlighted in many fields, among which the memristor-based artificial neural network technology is expected to break through the limitation of von Neumann so as to realize the replication of the human brain by enabling strong parallel computing ability and efficient data processing and become an important way towards the next generation of artificial intelligence. A new type of nanodevice, namely memristor, which is based on the variability of its resistance value, not only has very important applications in nonvolatile information storage, but also presents obsessive progressiveness in highly integrated circuits, making it one of the most promising circuit components in the post-Moore era. In particular, memristors can effectively simulate neural synapses and build neural networks; thus, they can be applied for the preparation of various artificial intelligence systems. This study reviews the research progress of memristors in artificial neural networks in detail and highlights the structural advantages and frontier applications of neural networks based on memristors. Finally, some urgent problems and challenges in current research are summarized and corresponding solutions and future development trends are put forward.
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Affiliation(s)
- Zelin Cao
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
- Shaanxi International Joint Research Center for Applied Technology of Controllable Neutron Source, School of Science, Xijing University, Xi'an 710123, China
| | - Bai Sun
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
| | - Guangdong Zhou
- College of Artificial Intelligence, Brain-inspired Computing & Intelligent Control of Chongqing Key Lab, Southwest University, Chongqing 400715, China
| | - Shuangsuo Mao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, Fujian Normal University, Fuzhou, Fujian 350117, China
| | - Shouhui Zhu
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Jie Zhang
- School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Chuan Ke
- School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Yong Zhao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, Fujian Normal University, Fuzhou, Fujian 350117, China
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
- School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Jinyou Shao
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
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Sun B, Ngai JHL, Zhou G, Zhou Y, Li Y. Voltage-Controlled Conversion from CDS to MDS in an Azobenzene-Based Organic Memristor for Information Storage and Logic Operations. ACS APPLIED MATERIALS & INTERFACES 2022; 14:41304-41315. [PMID: 36041038 DOI: 10.1021/acsami.2c12850] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
For organic memristors, non-zero-crossing current-voltage (I-V) curves are often observed, which can be attributed to capacitive effects. If the conversion between the capacitance-dominated state (CDS) and the memristance-dominated state (MDS) can be realized in a controllable manner, more device functions can be obtained. In this work, a two-terminal memristor using a common organic dye, azobenzene (AZB), as the active layer was prepared. It is found that as the applied voltage gradually increases, the device can transition from CDS to MDS. In the low voltage range (<1 V), the device is in CDS, and the capacitance is significantly increased by ∼104 compared to the theoretical value. In the high voltage range (>1 V), the device is in MDS, achieving an HRS (high resistance state)/LRS (low resistance state) resistance ratio of ∼104, and the logic operations are achieved. Through the analysis of the I-V curve, energy diagram of the materials, and computer simulation results, the mechanisms of CDS, MDS, and their conversion are proposed. This work provides an in-depth understanding of the working mechanism of organic memristors and demonstrates the potential of AZB-based organic memristors for information storage and logic display applications.
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Affiliation(s)
- Bai Sun
- Department of Chemical Engineering and Waterloo Institute for Nanotechnology (WIN), University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, Canada
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, No. 28, Xianning West Road, Xi'an, Shaanxi 710049, China
| | - Jenner H L Ngai
- Department of Chemical Engineering and Waterloo Institute for Nanotechnology (WIN), University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, Canada
- Security and Disruptive Technologies, National Research Council Canada, 1200 Montreal Road, Ottawa, Ontario K1A 0R6, Canada
| | - Guangdong Zhou
- School of Artificial Intelligence, Southwest University, Chongqing 400715, China
| | - Yongzan Zhou
- Department of Mechanics and Mechatronics Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - Yuning Li
- Department of Chemical Engineering and Waterloo Institute for Nanotechnology (WIN), University of Waterloo, 200 University Avenue West, Waterloo, Ontario N2L 3G1, Canada
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Nirmal KA, Nhivekar GS, Khot AC, Dongale TD, Kim TG. Unraveling the Effect of the Water Content in the Electrolyte on the Resistive Switching Properties of Self-Assembled One-Dimensional Anodized TiO 2 Nanotubes. J Phys Chem Lett 2022; 13:7870-7880. [PMID: 35979996 DOI: 10.1021/acs.jpclett.2c01075] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The applied potential, time, and water content are crucial factors in the electrochemical anodization process because the growth of one-dimensional nanotubes can be accelerated by enhancing the corrosive effect. We investigated the effect of the water content on the resistive switching (RS) properties of Ti foils by anodizing the foils and varying the water content in an electrolyte (1-10 vol %). By increasing the water content, we facilitated a slow transition from nanopores to nanotubes and realized an increase in the tube wall diameter and tube length. All of the fabricated memristive devices exhibited a reliable and reproducible bipolar resistive switching effect. The optimized device exhibited bipolar RS properties with good dc endurance (104 cycles) and data retention capability (105 s). Our results suggest that as the water content increases to 5 vol %, the RS process improves; further increases in the water content impair the RS process.
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Affiliation(s)
- Kiran A Nirmal
- School of Electrical Engineering, Korea University, Anam-ro 145, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Ganesh S Nhivekar
- Department of Electronics, Yashavantrao Chavan Institute of Science, Satara 415 001, India
| | - Atul C Khot
- School of Electrical Engineering, Korea University, Anam-ro 145, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Tukaram D Dongale
- Computational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416 004, India
| | - Tae Geun Kim
- School of Electrical Engineering, Korea University, Anam-ro 145, Seongbuk-gu, Seoul 02841, Republic of Korea
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Xu J, Zhao X, Zhao X, Wang Z, Tang Q, Xu H, Liu Y. Memristors with Biomaterials for Biorealistic Neuromorphic Applications. SMALL SCIENCE 2022. [DOI: 10.1002/smsc.202200028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Affiliation(s)
- Jiaqi Xu
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Xiaoning Zhao
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Xiaoli Zhao
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Zhongqiang Wang
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Qingxin Tang
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Haiyang Xu
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Yichun Liu
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
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Mao S, Sun B, Zhou G, Guo T, Wang J, Zhao Y. Applications of biomemristors in next generation wearable electronics. NANOSCALE HORIZONS 2022; 7:822-848. [PMID: 35697026 DOI: 10.1039/d2nh00163b] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
With the rapid development of mobile internet and artificial intelligence, wearable electronic devices have a great market prospect. In particular, information storage and processing of real-time collected data are an indispensable part of wearable electronic devices. Biomaterial-based memristive systems are suitable for storage and processing of the obtained information in wearable electronics due to the accompanying merits, i.e. sustainability, lightweight, degradability, low power consumption, flexibility and biocompatibility. So far, many biomaterial-based flexible and wearable memristive devices were prepared by spin coating or other technologies on a flexible substrate at room temperature. However, mechanical deformation caused by mechanical mismatch between devices and soft tissues leads to the instability of device performance. From the current research and practical application, the device will face great challenges when adapting to different working environments. In fact, some interesting studies have been performed to address the above issues while they were not intensively highlighted and overviewed. Herein, the progress in wearable biomemristive devices is reviewed, and the outlook and perspectives are provided in consideration of the existing challenges during the development of wearable biomemristive systems.
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Affiliation(s)
- Shuangsuo Mao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, Fujian Normal University, Fuzhou, Fujian 350117, China.
- College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 351007, China
| | - Bai Sun
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, Fujian Normal University, Fuzhou, Fujian 350117, China.
- College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 351007, China
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Guangdong Zhou
- Scholl of Artificial Intelligence, Southwest University, Chongqing, 400715, China
| | - Tao Guo
- Department of Mechanical and Mechatronics Engineering, Waterloo Institute for Nanotechnology, Centre for Advanced Materials Joining, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - Jiangqiu Wang
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Yong Zhao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, Fujian Normal University, Fuzhou, Fujian 350117, China.
- College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 351007, China
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
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7
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Controlling resistive switching behavior in the solution processed SiO 2-x device by the insertion of TiO 2 nanoparticles. Sci Rep 2022; 12:8405. [PMID: 35589798 PMCID: PMC9120027 DOI: 10.1038/s41598-022-12476-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 05/04/2022] [Indexed: 11/24/2022] Open
Abstract
The resistive switching behavior of the solution processed SiOx device was investigated by inserting TiO2 nanoparticles (NPs). Compared to the pristine SiOx device, the TiO2 NPs inserted SiOx (SiOx@TiO2 NPs) device achieves outstanding switching characteristics, namely a higher ratio of SET/RESET, lower operating voltages, improved cycle-to-cycle variability, faster switching speed, and multiple-RESET states. Density functional theory calculation (DFT) and circuit breaker simulation (CB) were used to detail the origin of the outstanding switching characteristic of the SiOx@TiO2 NPs. The improvement in resistive switching is mainly based on the difference in formation/rupture of the conductive path in the SiO2 and SiO2@TiO2 NPs devices. In particular, the reduction of resistance and lower switching voltage of TiO2 NPs control the formation and rupture of the conductive path to achieve more abrupt switching between SET/RESET with higher on/off ratio. This method of combined DFT calculation and CB offers a promising approach for high-performance non-volatile memory applications.
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Beasley AE, Abdelouahab MS, Lozi R, Tsompanas MA, Powell AL, Adamatzky A. Mem-fractive properties of mushrooms. BIOINSPIRATION & BIOMIMETICS 2022; 16:066026. [PMID: 34624868 DOI: 10.1088/1748-3190/ac2e0c] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 10/08/2021] [Indexed: 06/13/2023]
Abstract
Memristors close the loop forI-Vcharacteristics of the traditional, passive, semi-conductor devices. A memristor is a physical realisation of the material implication and thus is a universal logical element. Memristors are getting particular interest in the field of bioelectronics. Electrical properties of living substrates are not binary and there is nearly a continuous transitions from being non-memristive to mem-fractive (exhibiting a combination of passive memory) to ideally memristive. In laboratory experiments we show that living oyster mushroomsPleurotus ostreatusexhibit mem-fractive properties. We offer a piece-wise polynomial approximation of theI-Vbehaviour of the oyster mushrooms. We also report spiking activity, oscillations in conduced current of the oyster mushrooms.
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Affiliation(s)
- Alexander E Beasley
- Unconventional Computing Laboratory, UWE, Bristol, United Kingdom
- Centre for Engineering Research, University of Hertfordshire, United Kingdom
| | - Mohammed-Salah Abdelouahab
- Laboratory of Mathematics and Their Interactions, University Centre Abdelhafid Boussouf, Mila 43000, Algeria
| | - René Lozi
- Université Côte d'Azur, CNRS, LJAD, Nice, France
| | | | - Anna L Powell
- Unconventional Computing Laboratory, UWE, Bristol, United Kingdom
| | - Andrew Adamatzky
- Unconventional Computing Laboratory, UWE, Bristol, United Kingdom
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Sun B, Zhou G, Sun L, Zhao H, Chen Y, Yang F, Zhao Y, Song Q. ABO 3 multiferroic perovskite materials for memristive memory and neuromorphic computing. NANOSCALE HORIZONS 2021; 6:939-970. [PMID: 34652346 DOI: 10.1039/d1nh00292a] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The unique electron spin, transfer, polarization and magnetoelectric coupling characteristics of ABO3 multiferroic perovskite materials make them promising candidates for application in multifunctional nanoelectronic devices. Reversible ferroelectric polarization, controllable defect concentration and domain wall movement originated from the ABO3 multiferroic perovskite materials promotes its memristive effect, which further highlights data storage, information processing and neuromorphic computing in diverse artificial intelligence applications. In particular, ion doping, electrode selection, and interface modulation have been demonstrated in ABO3-based memristive devices for ultrahigh data storage, ultrafast information processing, and efficient neuromorphic computing. These approaches presented today including controlling the dopant in the active layer, altering the oxygen vacancy distribution, modulating the diffusion depth of ions, and constructing the interface-dependent band structure were believed to be efficient methods for obtaining unique resistive switching (RS) behavior for various applications. In this review, internal physical dynamics, preparation technologies, and modulation methods are systemically examined as well as the progress, challenges, and possible solutions are proposed for next generation emerging ABO3-based memristive application in artificial intelligence.
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Affiliation(s)
- Bai Sun
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials (Ministry of Education of China), Southwest Jiaotong University, Chengdu, Sichuan 610031, China.
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Guangdong Zhou
- School of Artificial Intelligence and School of Materials and Energy, Southwest University, Chongqing 400715, China.
| | - Linfeng Sun
- Centre for Quantum Physics, Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE), School of Physics, Beijing Institute of Technology, Beijing 100081, China
| | - Hongbin Zhao
- State Key Laboratory of Advanced Materials for Smart Sensing, General Research Institute for Nonferrous Metals, Beijing, 100088, China
| | - Yuanzheng Chen
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials (Ministry of Education of China), Southwest Jiaotong University, Chengdu, Sichuan 610031, China.
| | - Feng Yang
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Yong Zhao
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials (Ministry of Education of China), Southwest Jiaotong University, Chengdu, Sichuan 610031, China.
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Qunliang Song
- School of Artificial Intelligence and School of Materials and Energy, Southwest University, Chongqing 400715, China.
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Wang L, Zhu H, Wen D. Bioresistive Random-Access Memory with Gold Nanoparticles that Generate the Coulomb Blocking Effect Can Realize Multilevel Data Storage and Synapse Simulation. J Phys Chem Lett 2021; 12:8956-8962. [PMID: 34505773 DOI: 10.1021/acs.jpclett.1c02815] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Gold nanoparticles (Au NPs) have good biocompatibility and special quantum effects. In this Letter, we embedded Au NPs into silkworm hemolymph (SH) to improve the performance of the device and fabricated Al/SH:Au NPs/indium tin oxide (ITO)/glass resistive random access memory. The device exhibits a bipolar switching behavior with a retention time of 104 s. Compared with the Al/SH/ITO device without Au NPs, the device has a higher ON/OFF current ratio (>105) and a smaller Vreset. The improvement in device performance is attributed to the fact that Au NPs act as the electron-trapping center in the device; a Coulomb blockade occurs after electrons are trapped, thereby increasing the resistance of the device in the high-resistance state. Using optimized devices can realize multilevel data storage and can also simulate synaptic characteristics such as potentiation and depression. The device is expected to be applied to high-density, low-cost, degradable, and biocompatible storage devices and neuromorphic computing in the future.
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Affiliation(s)
- Lu Wang
- School of Electronic Engineering, HLJ Province Key Laboratory of Senior-Education for Electronic Engineering, Heilongjiang University, Harbin 150080, China
| | - Hongyu Zhu
- School of Electronic Engineering, HLJ Province Key Laboratory of Senior-Education for Electronic Engineering, Heilongjiang University, Harbin 150080, China
| | - Dianzhong Wen
- School of Electronic Engineering, HLJ Province Key Laboratory of Senior-Education for Electronic Engineering, Heilongjiang University, Harbin 150080, China
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