1
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Jaafar AH, Al Habsi SKS, Braben T, Venables C, Francesconi MG, Stasiuk GJ, Kemp NT. Unique Coexistence of Two Resistive Switching Modes in a Memristor Device Enables Multifunctional Neuromorphic Computing Properties. ACS APPLIED MATERIALS & INTERFACES 2024; 16:43816-43826. [PMID: 39129500 DOI: 10.1021/acsami.4c07820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
We report on hybrid memristor devices consisting of germanium dioxide nanoparticles (GeO2 NP) embedded within a poly(methyl methacrylate) (PMMA) thin film. Besides exhibiting forming-free resistive switching and an uncommon "ON" state in pristine conditions, the hybrid (nanocomposite) devices demonstrate a unique form of mixed-mode switching. The observed stopping voltage-dependent switching enables state-of-the-art bifunctional synaptic behavior with short-term (volatile/temporal) and long-term (nonvolatile/nontemporal) modes that are switchable depending on the stopping voltage applied. The short-term memory mode device is demonstrated to further emulate important synaptic functions such as short-term potentiation (STP), short-term depression (STD), paired-pulse facilitation (PPF), post-tetanic potentiation (PTP), spike-voltage-dependent plasticity (SVDP), spike-duration-dependent plasticity (SDDP), and, more importantly, the "learning-forgetting-rehearsal" behavior. The long-term memory mode gives additional long-term potentiation (LTP) and long-term depression (LTD) characteristics for long-term plasticity applications. The work shows a unique coexistence of the two resistive switching modes, providing greater flexibility in device design for future adaptive and reconfigurable neuromorphic computing systems at the hardware level.
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Affiliation(s)
- Ayoub H Jaafar
- School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, U.K
| | | | - Thomas Braben
- School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, U.K
| | - Craig Venables
- School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, U.K
| | | | - Graeme J Stasiuk
- Department of Imaging Chemistry and Biology, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, U.K
| | - Neil T Kemp
- School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, U.K
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2
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Islam R, Shi Y, de Oliveira Silva GV, Sachdev M, Miao GX. Volatile and Nonvolatile Programmable Iontronic Memristor with Lithium Imbued TiO x for Neuromorphic Computing Applications. ACS NANO 2024; 18:22045-22054. [PMID: 39110089 DOI: 10.1021/acsnano.4c05137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/21/2024]
Abstract
We demonstrate a lithium (Li) imbued TiOx iontronic device that exhibits synapse-like short-term plasticity behavior without requiring a forming process beforehand or a compliance current during switching. A solid-state electrolyte lithium phosphorus oxynitride (LiPON) behaves as the ion source, and the embedding and releasing of Li ions inside the cathodic like TiOx renders volatile conductance responses from the device and offers a natural platform for hardware simulating neuron functionalities. Besides, these devices possess high uniformity and great endurance as no conductive filaments are present. Different short-term pulse-based phenomena, including paired pulse facilitation, post-tetanic potentiation, and spike rate-dependent plasticity, were observed with self-relaxation characteristics. Based on the voltage excitation period, the time scale of the volatile memory can be tuned. Temperature measurement reveals the ion displacement-induced conductance channels become frozen below 220 K. In addition, the volatile analog devices can be configured into nonvolatile memory units with multibit storage capabilities after an electroforming process. Therefore, on the same platform, we can configure volatile units as nonlinear dynamic reservoirs for performing neuromorphic training and the nonvolatile units as the weight storage layer. We proceed to use voice recognition as an example with the tunable time constant relationship and obtain 94.4% accuracy with a minimal training data set. Thus, this iontronic platform can effectively process and update temporal information for reservoir and neuromorphic computing paradigms.
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Affiliation(s)
- Rabiul Islam
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo N2L 3G1, Ontario, Canada
- Institute for Quantum Computing, University of Waterloo, Waterloo N2L 3G1, Ontario, Canada
| | - Yu Shi
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo N2L 3G1, Ontario, Canada
- Institute for Quantum Computing, University of Waterloo, Waterloo N2L 3G1, Ontario, Canada
| | - Gabriel Vinicius de Oliveira Silva
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo N2L 3G1, Ontario, Canada
- Institute for Quantum Computing, University of Waterloo, Waterloo N2L 3G1, Ontario, Canada
| | - Manoj Sachdev
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo N2L 3G1, Ontario, Canada
| | - Guo-Xing Miao
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo N2L 3G1, Ontario, Canada
- Institute for Quantum Computing, University of Waterloo, Waterloo N2L 3G1, Ontario, Canada
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3
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Pan Z, Zhang J, Liu X, Zhao L, Ma J, Luo C, Sun Y, Dan Z, Gao W, Lu X, Li J, Huo N. Thermally Oxidized Memristor and 1T1R Integration for Selector Function and Low-Power Memory. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2401915. [PMID: 38958519 DOI: 10.1002/advs.202401915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 06/02/2024] [Indexed: 07/04/2024]
Abstract
Resistive switching memories have garnered significant attention due to their high-density integration and rapid in-memory computing beyond von Neumann's architecture. However, significant challenges are posed in practical applications with respect to their manufacturing process complexity, a leakage current of high resistance state (HRS), and the sneak-path current problem that limits their scalability. Here, a mild-temperature thermal oxidation technique for the fabrication of low-power and ultra-steep memristor based on Ag/TiOx/SnOx/SnSe2/Au architecture is developed. Benefiting from a self-assembled oxidation layer and the formation/rupture of oxygen vacancy conductive filaments, the device exhibits an exceptional threshold switching behavior with high switch ratio exceeding 106, low threshold voltage of ≈1 V, long-term retention of >104 s, an ultra-small subthreshold swing of 2.5 mV decade-1 and high air-stability surpassing 4 months. By decreasing temperature, the device undergoes a transition from unipolar volatile to bipolar nonvolatile characteristics, elucidating the role of oxygen vacancies migration on the resistive switching process. Further, the 1T1R structure is established between a memristor and a 2H-MoTe2 transistor by the van der Waals (vdW) stacking approach, achieving the functionality of selector and multi-value memory with lower power consumption. This work provides a mild-thermal oxidation technology for the low-cost production of high-performance memristors toward future in-memory computing applications.
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Affiliation(s)
- Zhidong Pan
- School of Semiconductor Science and Technology, South China Normal University, Foshan, 528225, P. R. China
| | - Jielian Zhang
- School of Semiconductor Science and Technology, South China Normal University, Foshan, 528225, P. R. China
| | - Xueting Liu
- School of Semiconductor Science and Technology, South China Normal University, Foshan, 528225, P. R. China
| | - Lei Zhao
- School of Semiconductor Science and Technology, South China Normal University, Foshan, 528225, P. R. China
| | - Jingyi Ma
- School of Semiconductor Science and Technology, South China Normal University, Foshan, 528225, P. R. China
| | - Chunlai Luo
- School of South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, P. R. China
| | - Yiming Sun
- School of Semiconductor Science and Technology, South China Normal University, Foshan, 528225, P. R. China
| | - Zhiying Dan
- School of Semiconductor Science and Technology, South China Normal University, Foshan, 528225, P. R. China
| | - Wei Gao
- School of Semiconductor Science and Technology, South China Normal University, Foshan, 528225, P. R. China
| | - Xubing Lu
- School of South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, P. R. China
| | - Jingbo Li
- College of Optical Science and Engineering, Zhejiang University, Hangzhou, 310027, P. R. China
| | - Nengjie Huo
- School of Semiconductor Science and Technology, South China Normal University, Foshan, 528225, P. R. China
- Guangdong Provincial Key Laboratory of Chip and Integration Technology, Guangzhou, 510631, P. R. China
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4
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Woo KS, Park H, Ghenzi N, Talin AA, Jeong T, Choi JH, Oh S, Jang YH, Han J, Williams RS, Kumar S, Hwang CS. Memristors with Tunable Volatility for Reconfigurable Neuromorphic Computing. ACS NANO 2024; 18:17007-17017. [PMID: 38952324 DOI: 10.1021/acsnano.4c03238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/03/2024]
Abstract
Neuromorphic computing promises an energy-efficient alternative to traditional digital processors in handling data-heavy tasks, primarily driven by the development of both volatile (neuronal) and nonvolatile (synaptic) resistive switches or memristors. However, despite their energy efficiency, memristor-based technologies presently lack functional tunability, thus limiting their competitiveness with arbitrarily programmable (general purpose) digital computers. This work introduces a two-terminal bilayer memristor, which can be tuned among neuronal, synaptic, and hybrid behaviors. The varying behaviors are accessed via facile control over the filament formed within the memristor, enabled by the interplay between the two active ionic species (oxygen vacancies and metal cations). This solution is unlike single-species ion migration employed in most other memristors, which makes their behavior difficult to control. By reconfiguring a single crossbar array of hybrid memristors, two different applications that usually require distinct types of devices are demonstrated - reprogrammable heterogeneous reservoir computing and arbitrary non-Euclidean graph networks. Thus, this work outlines a potential path toward functionally reconfigurable postdigital computers.
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Affiliation(s)
- Kyung Seok Woo
- Department of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul 08826, Republic of Korea
- Sandia National Laboratories, Livermore, California 94551, United States
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas 77843, United States
- Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Hyungjun Park
- Department of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul 08826, Republic of Korea
| | - Nestor Ghenzi
- Department of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul 08826, Republic of Korea
- Universidad de Avellaneda UNDAV and Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Mario Bravo 1460, Avellaneda, Buenos Aires 1872, Argentina
| | - A Alec Talin
- Sandia National Laboratories, Livermore, California 94551, United States
| | - Taeyoung Jeong
- Department of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul 08826, Republic of Korea
- Electronic Materials Research Center, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea
| | - Jung-Hae Choi
- Electronic Materials Research Center, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea
| | - Sangheon Oh
- Sandia National Laboratories, Livermore, California 94551, United States
| | - Yoon Ho Jang
- Department of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul 08826, Republic of Korea
| | - Janguk Han
- Department of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul 08826, Republic of Korea
| | - R Stanley Williams
- Sandia National Laboratories, Livermore, California 94551, United States
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas 77843, United States
| | - Suhas Kumar
- Sandia National Laboratories, Livermore, California 94551, United States
| | - Cheol Seong Hwang
- Department of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul 08826, Republic of Korea
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Kapur O, Guo D, Reynolds J, Newbrook D, Han Y, Beanland R, Jiang L, de Groot CHK, Huang R. An ultra high-endurance memristor using back-end-of-line amorphous SiC. Sci Rep 2024; 14:14008. [PMID: 38890324 PMCID: PMC11189404 DOI: 10.1038/s41598-024-64499-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Accepted: 06/10/2024] [Indexed: 06/20/2024] Open
Abstract
Integrating resistive memory or neuromorphic memristors into mainstream silicon technology can be substantially facilitated if the memories are built in the back-end-of-line (BEOL) and stacked directly above the logic circuitries. Here we report a promising memristor employing a plasma-enhanced chemical vapour deposition (PECVD) bilayer of amorphous SiC/Si as device layer and Cu as an active electrode. Its endurance exceeds one billion cycles with an ON/OFF ratio of ca. two orders of magnitude. Resistance drift is observed in the first 200 million cycles, after which the devices settle with a coefficient of variation of ca. 10% for both the low and high resistance states. Ohmic conduction in the low resistance state is attributed to the formation of Cu conductive filaments inside the bilayer structure, where the nanoscale grain boundaries in the Si layer provide the pre-defined pathway for Cu ion migration. Rupture of the conductive filament leads to current conduction dominated by reverse bias Schottky emission. Multistate switching is achieved by precisely controlling the pulse conditions for potential neuromorphic computing applications. The PECVD deposition method employed here has been frequently used to deposit typical BEOL SiOC low-k interlayer dielectrics. This makes it a unique memristor system with great potential for integration.
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Affiliation(s)
- Omesh Kapur
- School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Dongkai Guo
- School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Jamie Reynolds
- School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Daniel Newbrook
- School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Yisong Han
- Department of Physics, University of Warwick, Coventry, CV4 7AL, UK
| | - Richard Beanland
- Department of Physics, University of Warwick, Coventry, CV4 7AL, UK
| | - Liudi Jiang
- School of Engineering, University of Southampton, Southampton, SO17 1BJ, UK
| | - C H Kees de Groot
- School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Ruomeng Huang
- School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK.
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6
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Yadav R, Poudyal S, Rajarapu R, Biswal B, Barman PK, Kasiviswanathan S, Novoselov KS, Misra A. Low Power Volatile and Nonvolatile Memristive Devices from 1D MoO 2-MoS 2 Core-Shell Heterostructures for Future Bio-Inspired Computing. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2309163. [PMID: 38150637 DOI: 10.1002/smll.202309163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/05/2023] [Indexed: 12/29/2023]
Abstract
Memristors-based integrated circuits for emerging bio-inspired computing paradigms require an integrated approach utilizing both volatile and nonvolatile memristive devices. Here, an innovative architecture comprising of 1D CVD-grown core-shell heterostructures (CSHSs) of MoO2-MoS2 is employed as memristors manifesting both volatile switching (with high selectivity of 107 and steep slope of 0.6 mV decade-1) and nonvolatile switching phenomena (with Ion/Ioff ≈103 and switching speed of 60 ns). In these CSHSs, the metallic core MoO2 with high current carrying capacity provides a conformal and immaculate interface with semiconducting MoS2 shells and therefore it acts as a bottom electrode for the memristors. The power consumption in volatile devices is as low as 50 pW per set transition and 0.1 fW in standby mode. Voltage-driven current spikes are observed for volatile devices while with nonvolatile memristors, key features of a biological synapse such as short/long-term plasticity and paired pulse facilitation are emulated suggesting their potential for the development of neuromorphic circuits. These CSHSs offer an unprecedented solution for the interfacial issues between metallic electrodes and the layered materials-based switching element with the prospects of developing smaller footprint memristive devices for future integrated circuits.
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Affiliation(s)
- Renu Yadav
- Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India
- Centre for 2D Materials Research and Innovation, Indian Institute of Technology Madras, Chennai, 600036, India
| | - Saroj Poudyal
- Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India
- Centre for 2D Materials Research and Innovation, Indian Institute of Technology Madras, Chennai, 600036, India
| | - Ramesh Rajarapu
- Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India
- Centre for 2D Materials Research and Innovation, Indian Institute of Technology Madras, Chennai, 600036, India
| | - Bubunu Biswal
- Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India
- Centre for 2D Materials Research and Innovation, Indian Institute of Technology Madras, Chennai, 600036, India
| | - Prahalad Kanti Barman
- Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India
- Centre for 2D Materials Research and Innovation, Indian Institute of Technology Madras, Chennai, 600036, India
| | - S Kasiviswanathan
- Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India
| | - Kostya S Novoselov
- Institute for Functional Intelligent Materials, National University of Singapore, Singapore, 117544, Singapore
| | - Abhishek Misra
- Department of Physics, Indian Institute of Technology Madras, Chennai, 600036, India
- Centre for 2D Materials Research and Innovation, Indian Institute of Technology Madras, Chennai, 600036, India
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7
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Woo KS, Han J, Yi SI, Thomas L, Park H, Kumar S, Hwang CS. Tunable stochastic memristors for energy-efficient encryption and computing. Nat Commun 2024; 15:3245. [PMID: 38622148 PMCID: PMC11018740 DOI: 10.1038/s41467-024-47488-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 04/03/2024] [Indexed: 04/17/2024] Open
Abstract
Information security and computing, two critical technological challenges for post-digital computation, pose opposing requirements - security (encryption) requires a source of unpredictability, while computing generally requires predictability. Each of these contrasting requirements presently necessitates distinct conventional Si-based hardware units with power-hungry overheads. This work demonstrates Cu0.3Te0.7/HfO2 ('CuTeHO') ion-migration-driven memristors that satisfy the contrasting requirements. Under specific operating biases, CuTeHO memristors generate truly random and physically unclonable functions, while under other biases, they perform universal Boolean logic. Using these computing primitives, this work experimentally demonstrates a single system that performs cryptographic key generation, universal Boolean logic operations, and encryption/decryption. Circuit-based calculations reveal the energy and latency advantages of the CuTeHO memristors in these operations. This work illustrates the functional flexibility of memristors in implementing operations with varying component-level requirements.
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Affiliation(s)
- Kyung Seok Woo
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, Republic of Korea
- Sandia National Laboratories, Livermore, CA, USA
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Janguk Han
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, Republic of Korea
| | - Su-In Yi
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Luke Thomas
- Applied Materials Inc., Santa Clara, CA, USA
| | - Hyungjun Park
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, Republic of Korea
| | - Suhas Kumar
- Sandia National Laboratories, Livermore, CA, USA.
| | - Cheol Seong Hwang
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, Republic of Korea.
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Milozzi A, Ricci S, Ielmini D. Memristive tonotopic mapping with volatile resistive switching memory devices. Nat Commun 2024; 15:2812. [PMID: 38561389 PMCID: PMC10985068 DOI: 10.1038/s41467-024-47228-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 03/25/2024] [Indexed: 04/04/2024] Open
Abstract
To reach the energy efficiency and the computing capability of biological neural networks, novel hardware systems and paradigms are required where the information needs to be processed in both spatial and temporal domains. Resistive switching memory (RRAM) devices appear as key enablers for the implementation of large-scale neuromorphic computing systems with high energy efficiency and extended scalability. Demonstrating a full set of spatiotemporal primitives with RRAM-based circuits remains an open challenge. By taking inspiration from the neurobiological processes in the human auditory systems, we develop neuromorphic circuits for memristive tonotopic mapping via volatile RRAM devices. Based on a generalized stochastic device-level approach, we demonstrate the main features of signal processing of cochlea, namely logarithmic integration and tonotopic mapping of signals. We also show that our tonotopic classification is suitable for speech recognition. These results support memristive devices for physical processing of temporal signals, thus paving the way for energy efficient, high density neuromorphic systems.
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Affiliation(s)
- Alessandro Milozzi
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano and IU.NET, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
| | - Saverio Ricci
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano and IU.NET, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
| | - Daniele Ielmini
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano and IU.NET, Piazza Leonardo da Vinci 32, 20133, Milano, Italy.
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Guo J, Liu L, Wang J, Zhao X, Zhang Y, Yan Y. A Diffusive Artificial Synapse Based on Charged Metal Nanoparticles. NANO LETTERS 2024; 24:1951-1958. [PMID: 38315061 DOI: 10.1021/acs.nanolett.3c04224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
We show that a diffusive memristor with analogue switching characteristics can be achieved in a layer of gold nanoparticles (AuNPs) functionalized with charged self-assembled monolayers (deprotonated 11-mercaptoundecanoic acid). The nanoparticle core and the anchored stationary charges are jammed within the layer while the mobile counterions [N(CH3)4+] can respond to the electric field and spontaneously diffuse back to the initial positions upon removal of the field. This metal nanoparticle device is set-step free, energy consumption efficient, mechanically flexible, and analogous to bio-Ca2+ dynamics and has tunable conductance modulation capabilities at the counterion concentrations. The gradual resistive switching behavior enables us to implement several important synaptic functions such as potentiation/depression, spike voltage-dependent plasticity, spike duration-dependent plasticity, spike frequency-dependent plasticity, and paired-pulse facilitation. Finally, on the basis of the paired-pulse facilitation characteristics, the metal nanoparticle diffusive artificial synapse is used for edge extraction with exhibits excellent performance.
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Affiliation(s)
- Jiahui Guo
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- State Key Laboratory of Mesoscience and Engineering (State Key Laboratory of Multi-phase Complex Systems), Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
| | - Lin Liu
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jingyu Wang
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xing Zhao
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Yuchun Zhang
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Yong Yan
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China
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10
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Xiao B, Yu X, Li W, Li Q, Watanabe S. Hydrogen-triggered metal filament rupture in Cu-based resistance switches. SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS 2024; 25:2318213. [PMID: 38414574 PMCID: PMC10898265 DOI: 10.1080/14686996.2024.2318213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 02/08/2024] [Indexed: 02/29/2024]
Abstract
Cation-based resistance switches have been considered as promising candidates for memory cells and other novel devices. So far, the most accepted switching processes of such devices are based on the formation/rupture of metallic filaments between two electrodes. Although many recent studies have identified the existence of H2O (and resulting -OH groups) in such devices, their effects on the switching process are still unclear. In the present work, by taking Cu/Ta2O5/Pt device as an example, we have theoretically revealed that H ions may dissociate from -OH groups and accumulate onto the Cu filament in amorphous Ta2O5. After that, the adsorbed H ions will induce a series of changes, such as the elongation of the adjacent Cu-Cu bonds, the weakening of the Cu-Cu bonds, the increase of charge on Cu cations, and the enhancement of diffusivities of Cu cations, all of which eventually lead to the rupture of the Cu filament. Interestingly, our proposed 'H-triggered metal filament rupture' model is similar to the widely studied 'hydrogen embrittlement phenomenon'. The crucial point of this model is the high catalytic activity of Cu towards the splitting of -OH group. Consequently, it is expected that this model could be applicable to other Cu-cation based resistance switches.
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Affiliation(s)
- Bo Xiao
- The Laboratory of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Yantai University, Yantai, China
| | - Xuefang Yu
- The Laboratory of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Yantai University, Yantai, China
| | - Wenzuo Li
- The Laboratory of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Yantai University, Yantai, China
| | - Qingzhong Li
- The Laboratory of Theoretical and Computational Chemistry, School of Chemistry and Chemical Engineering, Yantai University, Yantai, China
| | - Satoshi Watanabe
- Department of Materials Engineering, The University of Tokyo, Tokyo, Japan
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11
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Chen W, Mou Z, Xin Y, Li H, Wang T, Chen Y, Chen L, Yang BR, Chen Z, Luo Y, Liu GS. Self-Assembled Monolayer and Nanoparticles Coenhanced Fragmented Silver Nanowire Network Memristor. ACS APPLIED MATERIALS & INTERFACES 2024; 16:6057-6067. [PMID: 38285926 DOI: 10.1021/acsami.3c15351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Silver nanowire (AgNW) networks with self-assembled structures and synaptic connectivity have been recently reported for constructing neuromorphic memristors. However, resistive switching at the cross-point junctions of the network is unstable due to locally enhanced Joule heating and the Gibbs-Thomson effect, which poses an obstacle to the integration of threshold switching and memory function in the same AgNW memristor. Here, fragmented AgNW networks combined with Ag nanoparticles (AgNPs) and mercapto self-assembled monolayers (SAMs) are devised to construct memristors with stable threshold switching and memory behavior. In the above design, the planar gaps between NW segments are for resistive switching, the AgNPs act as metal islands in the gaps to reduce threshold voltage (Vth) and holding voltage (Vhold), and the SAMs suppress surface atom diffusion to avoid Oswald ripening of the AgNPs, which improves switching stability. The fragmented NW-NP/SAM memristors not only circumvent the side effects of conventional NW-stacked junctions to provide durable threshold switching at >Vth but also exhibit synaptic characteristics such as long-term potentiation at ultralow voltage (≪Vth). The combination of NW segments, nanoparticles, and SAMs blazes a new trail for integrating artificial neurons and synapses in AgNW network memristors.
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Affiliation(s)
- Weizhen Chen
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Key Laboratory of Visible Light Communications of Guangzhou, Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, College of Physics & Optoelectronic Engineering, Jinan University, Guangzhou 510632, China
| | - Zongxia Mou
- Key Laboratory of Biomaterials of Guangdong Higher Education Institutes, Department of Biomedical Engineering, Jinan University, Guangzhou 510632, China
| | - Yijia Xin
- Department of Physics, Jinan University, Guangzhou 510632, China
| | - Haichuan Li
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Key Laboratory of Visible Light Communications of Guangzhou, Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, College of Physics & Optoelectronic Engineering, Jinan University, Guangzhou 510632, China
| | - Tianqi Wang
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Key Laboratory of Visible Light Communications of Guangzhou, Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, College of Physics & Optoelectronic Engineering, Jinan University, Guangzhou 510632, China
| | - Yaofei Chen
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Key Laboratory of Visible Light Communications of Guangzhou, Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, College of Physics & Optoelectronic Engineering, Jinan University, Guangzhou 510632, China
| | - Lei Chen
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Key Laboratory of Visible Light Communications of Guangzhou, Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, College of Physics & Optoelectronic Engineering, Jinan University, Guangzhou 510632, China
| | - Bo-Ru Yang
- State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou 510006, China
| | - Zhe Chen
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Key Laboratory of Visible Light Communications of Guangzhou, Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, College of Physics & Optoelectronic Engineering, Jinan University, Guangzhou 510632, China
| | - Yunhan Luo
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Key Laboratory of Visible Light Communications of Guangzhou, Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, College of Physics & Optoelectronic Engineering, Jinan University, Guangzhou 510632, China
| | - Gui-Shi Liu
- Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Key Laboratory of Visible Light Communications of Guangzhou, Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Education Institutes, College of Physics & Optoelectronic Engineering, Jinan University, Guangzhou 510632, China
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12
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Sun B, Chen Y, Zhou G, Cao Z, Yang C, Du J, Chen X, Shao J. Memristor-Based Artificial Chips. ACS NANO 2024; 18:14-27. [PMID: 38153841 DOI: 10.1021/acsnano.3c07384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2023]
Abstract
Memristors, promising nanoelectronic devices with in-memory resistive switching behavior that is assembled with a physically integrated core processing unit (CPU) and memory unit and even possesses highly possible multistate electrical behavior, could avoid the von Neumann bottleneck of traditional computing devices and show a highly efficient ability of parallel computation and high information storage. These advantages position them as potential candidates for future data-centric computing requirements and add remarkable vigor to the research of next-generation artificial intelligence (AI) systems, particularly those that involve brain-like intelligence applications. This work provides an overview of the evolution of memristor-based devices, from their initial use in creating artificial synapses and neural networks to their application in developing advanced AI systems and brain-like chips. It offers a broad perspective of the key device primitives enabling their special applications from the view of materials, nanostructure, and mechanism models. We highlight these demonstrations of memristor-based nanoelectronic devices that have potential for use in the field of brain-like AI, point out the existing challenges of memristor-based nanodevices toward brain-like chips, and propose the guiding principle and promising outlook for future device promotion and system optimization in the biomedical AI field.
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Affiliation(s)
- Bai Sun
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Yuanzheng Chen
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China
| | - Guangdong Zhou
- College of Artificial Intelligence, Brain-inspired Computing & Intelligent Control of Chongqing Key Lab, Southwest University, Chongqing 400715, People's Republic of China
| | - Zelin Cao
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Chuan Yang
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China
| | - Junmei Du
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China
| | - Xiaoliang Chen
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Jinyou Shao
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
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13
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Im IH, Baek JH, Kim SJ, Kim J, Park SH, Kim JY, Yang JJ, Jang HW. Halide Perovskites-Based Diffusive Memristors for Artificial Mechano-Nociceptive System. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2307334. [PMID: 37708845 DOI: 10.1002/adma.202307334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 08/24/2023] [Indexed: 09/16/2023]
Abstract
Numerous efforts for emulating organ systems comprised of multiple functional units have driven substantial advancements in bio-realistic electronics and systems. The resistance change behavior observed in diffusive memristors shares similarities with the potential change in biological neurons. Here, the diffusive threshold switching phenomenon in Ag-incorporated organometallic halide perovskites is utilized to demonstrate the functions of afferent neurons. Halide perovskites-based diffusive memristors show a low threshold voltage of ≈0.2 V with little variation, attributed to the facile migration of Ag ions uniformly dispersed within the halide matrix. Based on the reversible and reliable volatile threshold switching, the memristors successfully demonstrate fundamental nociceptive functions including threshold firing, relaxation, and sensitization. Furthermore, to replicate the biological mechano-nociceptive phenomenon at a system level, an artificial mechano-nociceptive system is built by integrating a diffusive memristor with a force-sensing resistor. The presented system is capable of detecting and discerning the detrimental impact caused by a heavy steel ball, effectively exhibiting the corresponding sensitization response. By further extending the single nociceptive system into a 5 × 5 array, successful stereoscopic nociception of uneven impulses is achieved in the artificial skin system through array-scale sensitization. These results represent significant progress in the field of bio-inspired electronics and systems.
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Affiliation(s)
- In Hyuk Im
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Ji Hyun Baek
- 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
- Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Jaehyun Kim
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Sung Hyuk Park
- 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
| | - J Joshua Yang
- Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - 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, Republic of Korea
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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: 14] [Impact Index Per Article: 14.0] [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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Rao TS, Mondal I, Bannur B, Kulkarni GU. A scalable solution recipe for a Ag-based neuromorphic device. DISCOVER NANO 2023; 18:124. [PMID: 37812259 PMCID: PMC10562349 DOI: 10.1186/s11671-023-03906-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 09/28/2023] [Indexed: 10/10/2023]
Abstract
Integration and scalability have posed significant problems in the advancement of brain-inspired intelligent systems. Here, we report a self-formed Ag device fabricated through a chemical dewetting process using an Ag organic precursor, which offers easy processing, scalability, and flexibility to address the above issues to a certain extent. The conditions of spin coating, precursor dilution, and use of solvents were varied to obtain different dewetted structures (broadly classified as bimodal and nearly unimodal). A microscopic study is performed to obtain insight into the dewetting mechanism. The electrical behavior of selected bimodal and nearly unimodal devices is related to the statistical analysis of their microscopic structures. A capacitance model is proposed to relate the threshold voltage (Vth) obtained electrically to the various microscopic parameters. Synaptic functionalities such as short-term potentiation (STP) and long-term potentiation (LTP) were emulated in a representative nearly unimodal and bimodal device, with the bimodal device showing a better performance. One of the cognitive behaviors, associative learning, was emulated in a bimodal device. Scalability is demonstrated by fabricating more than 1000 devices, with 96% exhibiting switching behavior. A flexible device is also fabricated, demonstrating synaptic functionalities (STP and LTP).
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Affiliation(s)
- Tejaswini S Rao
- Chemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur P.O., Bangalore, 560064, India
| | - Indrajit Mondal
- Chemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur P.O., Bangalore, 560064, India
| | - Bharath Bannur
- Chemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur P.O., Bangalore, 560064, India
| | - Giridhar U Kulkarni
- Chemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur P.O., Bangalore, 560064, India.
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16
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Pattnaik DP, Andrews C, Cropper MD, Gabbitas A, Balanov AG, Savel'ev S, Borisov P. Gamma radiation-induced nanodefects in diffusive memristors and artificial neurons. NANOSCALE 2023; 15:15665-15674. [PMID: 37724437 DOI: 10.1039/d3nr01853a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
Abstract
Gamma photons with an average energy of 1.25 MeV are well-known to generate large amounts of defects in semiconductor electronic devices. Here we investigate the novel effect of gamma radiation on diffusive memristors based on metallic silver nanoparticles dispersed in a dielectric matrix of silica. Our experimental findings show that after exposure to radiation, the memristors and artificial neurons made of them demonstrate much better performance in terms of stable volatile resistive switching and higher spiking frequencies, respectively, compared to the pristine samples. At the same time we observe partial oxidation of silver and reduction of silicon within the switching silica layer. We propose nanoinclusions of reduced silicon distributed across the silica layer to be the backbone for metallic nanoparticles to form conductive filaments, as supported by our theoretical simulations of radiation-induced changes in the diffusion process. Our findings propose a new opportunity to engineer the required characteristics of diffusive memristors in order to emulate biological neurons and develop bio-inspired computational technology.
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Affiliation(s)
- D P Pattnaik
- Department of Physics, Loughborough University, Loughborough, LE11 3TU, UK.
| | - C Andrews
- University of Manchester, Dalton Cumbrian Facility, Westlakes Science Park, Moor Row, CA24 3HA, UK
| | - M D Cropper
- Department of Physics, Loughborough University, Loughborough, LE11 3TU, UK.
| | - A Gabbitas
- Department of Physics, Loughborough University, Loughborough, LE11 3TU, UK.
| | - A G Balanov
- Department of Physics, Loughborough University, Loughborough, LE11 3TU, UK.
| | - S Savel'ev
- Department of Physics, Loughborough University, Loughborough, LE11 3TU, UK.
| | - P Borisov
- Department of Physics, Loughborough University, Loughborough, LE11 3TU, UK.
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17
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Zhang T, Wang L, Ding W, Zhu Y, Qian H, Zhou J, Chen Y, Li J, Li W, Huang L, Song C, Yi M, Huang W. Rationally Designing High-Performance Versatile Organic Memristors through Molecule-Mediated Ion Movements. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2302863. [PMID: 37392013 DOI: 10.1002/adma.202302863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 06/23/2023] [Accepted: 06/25/2023] [Indexed: 07/02/2023]
Abstract
Organic memory has attracted tremendous attention for next-generation electronic elements for the molecules' striking ease of structural design. However, due to them being hardly controllable and their low ion transport, it is always essential and challenge to effectively control their random migration, pathway, and duration. There are very few effective strategies, and specific platforms with a view to molecules with specific coordination-groups-regulating ions have been rarely reported. In this work, as a generalized rational design strategy, the well-known tetracyanoquinodimethane (TCNQ) is introduced with multiple coordination groups and small plane structure into a stable polymers framework to modulate Ag migration and then achieve high-performance devices with ideal productivity, low operation voltage and power, stable switching cycles, and state retention. Raman mapping demonstrates that the migrated Ag can specially coordinate with the embedded TCNQ molecules. Notably, the TCNQ molecule distribution can be modulated inside the polymer framework and regulate the memristive behaviors through controlling the formed Ag conductive filaments (CFs) as demonstrated by Raman mapping, in situ conductive atomic force microscopy (C-AFM), X-ray diffraction (XRD) and depth-profiling X-ray photoelectron spectroscopy (XPS). Thus the controllable molecule-mediated Ag movements show its potential in rationally designing high-performance devices and versatile functions and is enlightening in constructing memristors with molecule-mediated ion movements.
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Affiliation(s)
- Tao Zhang
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
| | - Laiyuan Wang
- Department of Materials Science and Engineering, California NanoSystems Institute (CNSI), University of California, Los Angeles, 607 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Weiwei Ding
- School of Biological Science and Medical Engineering, Beihang University, 37 Xueyuan Road, Beijing, 100083, China
| | - Yunfeng Zhu
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
| | - Haowen Qian
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
| | - Jia Zhou
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
| | - Ye Chen
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
| | - Jiayu Li
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
| | - Wen Li
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
| | - Liya Huang
- College of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
| | - Chunyuan Song
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
| | - Mingdong Yi
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
| | - Wei Huang
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing, 210023, China
- Frontiers Science Center for Flexible Electronics, Xi'an Institute of Flexible Electronics (IFE) and Xi'an Institute of Biomedical Materials & Engineering, Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, 710072, China
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18
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Kim DS, Suh HW, Cho SW, Oh SY, Lee HH, Lee KW, Choi JH, Cho HK. Intensive harmonized synapses with amorphous Cu 2O-based memristors using ultrafine Cu nanoparticle sublayers formed via atomically controlled electrochemical pulse deposition. MATERIALS HORIZONS 2023; 10:3382-3392. [PMID: 37439537 DOI: 10.1039/d3mh00508a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/14/2023]
Abstract
Resistive random-access memory (RRAM) devices have significant advantages for neuromorphic computing but have fatal problems of uncontrollability and abrupt resistive switching behaviors degrading their synaptic performance. In this paper, we propose the electrochemical design of an active Cu2O layer containing a strategic sublayer of ultrafine Cu nanoparticles (U-Cu NPs) to form uniformly dispersed conducting filaments, which can effectively improve the reliability for analog switching of RRAM-based neuromorphic computing. The electrochemical pulse deposited (EPD) U-Cu NPs are linked to the bottom electrode through a semi-conductive path within the bottom Cu2O layer, since the EPD is preferentially carried out on the conductive sites. All Cu2O films with U-Cu NPs are developed in situ in the single electrolyte bath without any pause. The proposed U-Cu NPs can concentrate the external electric field and can generate conductive filament paths for analog resistive switching. The applied electric field was uniformly spread to U-Cu NPs at the center of the active layer and displays resistive switching behavior via multiple conductive filaments. This shows a strong harmony between the resistance-switching characteristics and the analog operation of the active layer. This RRAM device shows outstanding gradual analog switching, great linearity, dynamic range, endurance, precision, speed, and retention characteristics simultaneously and adequately for neuromorphic computing by realizing multiple weak filament-type operation.
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Affiliation(s)
- Dong Su Kim
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, 16419, Republic of Korea.
| | - Hee Won Suh
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, 16419, Republic of Korea.
| | - Sung Woon Cho
- Department of Advanced Components and Materials Engineering, Sunchon National University, 255, Jungang-ro, Sunchon-si, Jeollanam-do, Republic of Korea
| | - Shin Young Oh
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, 16419, Republic of Korea.
| | - Hak Hyeon Lee
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, 16419, Republic of Korea.
| | - Kun Woong Lee
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, 16419, Republic of Korea.
| | - Ji Hoon Choi
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, 16419, Republic of Korea.
| | - Hyung Koun Cho
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, 16419, Republic of Korea.
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19
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Ma Z, Chen W, Cao X, Diao S, Liu Z, Ge J, Pan S. Criticality and Neuromorphic Sensing in a Single Memristor. NANO LETTERS 2023. [PMID: 37326403 DOI: 10.1021/acs.nanolett.3c00389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Resistive random access memory (RRAM) is an important technology for both data storage and neuromorphic computation, where the dynamics of nanoscale conductive filaments lies at the core of the technology. Here, we analyze the current noise of various silicon-based memristors that involves the creation of a percolation path at the intermediate phase of filament growth. Remarkably, we find that these atomic switching events follow scale-free avalanche dynamics with exponents satisfying the criteria for criticality. We further prove that the switching dynamics are universal and show little dependence on device sizes or material features. Utilizing criticality in memristors, we simulate the functionality of hair cells in auditory sensory systems by observing the frequency selectivity of input stimuli with tunable characteristic frequency. We further demonstrate a single-memristor-based sensing primitive for representation of input stimuli that exceeds the theoretical limits dictated by the Nyquist-Shannon theorem.
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Affiliation(s)
- Zelin Ma
- Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China
- Solid State Physics & Material Research Laboratory, School of Physics and Material Science, Guangzhou University, Guangzhou 510006, China
| | - Wanjun Chen
- Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China
- Solid State Physics & Material Research Laboratory, School of Physics and Material Science, Guangzhou University, Guangzhou 510006, China
| | - Xucheng Cao
- Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China
- Solid State Physics & Material Research Laboratory, School of Physics and Material Science, Guangzhou University, Guangzhou 510006, China
| | - Shanqing Diao
- Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China
- Solid State Physics & Material Research Laboratory, School of Physics and Material Science, Guangzhou University, Guangzhou 510006, China
| | - Zhiyu Liu
- Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China
- Solid State Physics & Material Research Laboratory, School of Physics and Material Science, Guangzhou University, Guangzhou 510006, China
| | - Jun Ge
- Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China
- Solid State Physics & Material Research Laboratory, School of Physics and Material Science, Guangzhou University, Guangzhou 510006, China
- Key Lab of Si-based Information Materials & Devices and Integrated Circuits Design, Department of Education of Guangdong Province, Guangzhou 510006, China
| | - Shusheng Pan
- Research Center for Advanced Information Materials (CAIM), Huangpu Research & Graduate School of Guangzhou University, Guangzhou 510555, China
- Solid State Physics & Material Research Laboratory, School of Physics and Material Science, Guangzhou University, Guangzhou 510006, China
- Key Lab of Si-based Information Materials & Devices and Integrated Circuits Design, Department of Education of Guangdong Province, Guangzhou 510006, China
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20
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Wang X, Chen C, Zhu L, Shi K, Peng B, Zhu Y, Mao H, Long H, Ke S, Fu C, Zhu Y, Wan C, Wan Q. Vertically integrated spiking cone photoreceptor arrays for color perception. Nat Commun 2023; 14:3444. [PMID: 37301894 PMCID: PMC10257685 DOI: 10.1038/s41467-023-39143-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 05/31/2023] [Indexed: 06/12/2023] Open
Abstract
The cone photoreceptors in our eyes selectively transduce the natural light into spiking representations, which endows the brain with high energy-efficiency color vision. However, the cone-like device with color-selectivity and spike-encoding capability remains challenging. Here, we propose a metal oxide-based vertically integrated spiking cone photoreceptor array, which can directly transduce persistent lights into spike trains at a certain rate according to the input wavelengths. Such spiking cone photoreceptors have an ultralow power consumption of less than 400 picowatts per spike in visible light, which is very close to biological cones. In this work, lights with three wavelengths were exploited as pseudo-three-primary colors to form 'colorful' images for recognition tasks, and the device with the ability to discriminate mixed colors shows better accuracy. Our results would enable hardware spiking neural networks with biologically plausible visual perception and provide great potential for the development of dynamic vision sensors.
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Affiliation(s)
- Xiangjing Wang
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
| | - Chunsheng Chen
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
| | - Li Zhu
- College of Integrated Circuit Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China
| | - Kailu Shi
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
| | - Baocheng Peng
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
| | - Yixin Zhu
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
| | - Huiwu Mao
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
| | - Haotian Long
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
| | - Shuo Ke
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
| | - Chuanyu Fu
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
| | - Ying Zhu
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China
| | - Changjin Wan
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China.
| | - Qing Wan
- School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210093, China.
- School of Micro Nanoelectronics, Zhejiang University, ZJU-Hangzhou Global Scientific and Technological Innovation Centre, 310027, Hangzhou, PR China.
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21
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Wang L, Zuo Z, Wen D. Realization of Artificial Nerve Synapses Based on Biological Threshold Resistive Random Access Memory. Adv Biol (Weinh) 2023; 7:e2200298. [PMID: 36650948 DOI: 10.1002/adbi.202200298] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/09/2022] [Indexed: 01/19/2023]
Abstract
A one-selector one resistor (1S1R) array formed of a selector and resistive random access memory (RRAM) is an important way to achieve high-density storage and neuromorphic computing. However, the low durability and poor consistency of the selector limit its practical application. The fabrication of a selector based on egg albumen (EA) is reported in this paper. The device exhibits excellent bidirectional threshold switching characteristics, including a low leakage current (10-7 A), a high ON/OFF current ratio (106 ), and good endurance (>700 days). It is used as a selector to form a 1S1R unit in combination with an EA-based RRAM to effectively solve the leakage current in a crossbar array. A feasible solution is provided for the realization of a protein-based 1S1R array to achieve high-density storage. The 1S1R unit shows characteristics similar to those of synapses in the human brain under impulse excitation and has great potential in simulating the human brain for neuromorphic calculations.).
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Affiliation(s)
- Lu Wang
- School of Electronic Engineering, Heilongjiang University, Harbin, 150080, P. R. China
| | - Ze Zuo
- School of Electronic Engineering, Heilongjiang University, Harbin, 150080, P. R. China
| | - Dianzhong Wen
- School of Electronic Engineering, Heilongjiang University, Harbin, 150080, P. R. China
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22
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Oh J, Kim S, Lee C, Cha JH, Yang SY, Im SG, Park C, Jang BC, Choi SY. Preventing Vanishing Gradient Problem of Hardware Neuromorphic System by Implementing Imidazole-Based Memristive ReLU Activation Neuron. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2300023. [PMID: 36938884 DOI: 10.1002/adma.202300023] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 03/05/2023] [Indexed: 06/16/2023]
Abstract
With advances in artificial intelligent services, brain-inspired neuromorphic systems with synaptic devices are recently attracting significant interest to circumvent the von Neumann bottleneck. However, the increasing trend of deep neural network parameters causes huge power consumption and large area overhead of a nonlinear neuron electronic circuit, and it incurs a vanishing gradient problem. Here, a memristor-based compact and energy-efficient neuron device is presented to implement a rectifying linear unit (ReLU) activation function. To emulate the volatile and gradual switching of the ReLU function, a copolymer memristor with a hybrid structure is proposed using a copolymer/inorganic bilayer. The functional copolymer film developed by introducing imidazole functional groups enables the formation of nanocluster-type pseudo-conductive filaments by boosting the nucleation of Cu nanoclusters, causing gradual switching. The ReLU neuron device is successfully demonstrated by integrating the memristor with amorphous InGaZnO thin-film transistors, and achieves 0.5 pJ of energy consumption based on sub-10 µA operation current and high-speed switching of 650 ns. Furthermore, device-to-system-level simulation using neuron devices on the MNIST dataset demonstrates that the vanishing gradient problem is effectively resolved by five-layer deep neural networks. The proposed neuron device will enable the implementation of high-density and energy-efficient hardware neuromorphic systems.
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Affiliation(s)
- Jungyeop Oh
- School of Electrical Engineering, Graphene/2D Materials Research Center, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
| | - Sungkyu Kim
- Department of Nanotechnology and Advanced Materials Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, 05006, Republic of Korea
| | - Changhyeon Lee
- Department of Chemical and Biomolecular Engineering, Graphene/2D Materials Research Center, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
| | - Jun-Hwe Cha
- School of Electrical Engineering, Graphene/2D Materials Research Center, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
| | - Sang Yoon Yang
- School of Electrical Engineering, Graphene/2D Materials Research Center, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
| | - Sung Gap Im
- Department of Chemical and Biomolecular Engineering, Graphene/2D Materials Research Center, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
| | - Cheolmin Park
- School of Electrical Engineering, Graphene/2D Materials Research Center, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
| | - Byung Chul Jang
- School of Electronics and Electrical Engineering, Kyungpook National University, 41566, 80 Daehakro, Bukgu, Daegu, Republic of Korea
| | - Sung-Yool Choi
- School of Electrical Engineering, Graphene/2D Materials Research Center, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
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23
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Li C, Zhang X, Chen P, Zhou K, Yu J, Wu G, Xiang D, Jiang H, Wang M, Liu Q. Short-term synaptic plasticity in emerging devices for neuromorphic computing. iScience 2023; 26:106315. [PMID: 36950108 PMCID: PMC10025973 DOI: 10.1016/j.isci.2023.106315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023] Open
Abstract
Neuromorphic computing is a promising computing paradigm toward building next-generation artificial intelligence machines, in which diverse types of synaptic plasticity play an active role in information processing. Compared to long-term plasticity (LTP) forming the foundation of learning and memory, short-term plasticity (STP) is essential for critical computational functions. So far, the practical applications of LTP have been widely investigated, whereas the implementation of STP in hardware is still elusive. Here, we review the development of STP by bridging the physics in emerging devices and biological behaviors. We explore the computational functions of various STP in biology and review their recent progress. Finally, we discuss the main challenges of introducing STP into synaptic devices and offer the potential approaches to utilize STP to enrich systems' capabilities. This review is expected to provide prospective ideas for implementing STP in emerging devices and may promote the construction of high-level neuromorphic machines.
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Affiliation(s)
- Chao Li
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Key Laboratory of Microelectronics Device & Integrated Technology, Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xumeng Zhang
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Pei Chen
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
| | - Keji Zhou
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Jie Yu
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
| | - Guangjian Wu
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Du Xiang
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Hao Jiang
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Ming Wang
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Qi Liu
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
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24
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Seok H, Son S, Jathar SB, Lee J, Kim T. Synapse-Mimetic Hardware-Implemented Resistive Random-Access Memory for Artificial Neural Network. SENSORS (BASEL, SWITZERLAND) 2023; 23:3118. [PMID: 36991829 PMCID: PMC10058286 DOI: 10.3390/s23063118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/11/2023] [Accepted: 03/13/2023] [Indexed: 06/19/2023]
Abstract
Memristors mimic synaptic functions in advanced electronics and image sensors, thereby enabling brain-inspired neuromorphic computing to overcome the limitations of the von Neumann architecture. As computing operations based on von Neumann hardware rely on continuous memory transport between processing units and memory, fundamental limitations arise in terms of power consumption and integration density. In biological synapses, chemical stimulation induces information transfer from the pre- to the post-neuron. The memristor operates as resistive random-access memory (RRAM) and is incorporated into the hardware for neuromorphic computing. Hardware composed of synaptic memristor arrays is expected to lead to further breakthroughs owing to their biomimetic in-memory processing capabilities, low power consumption, and amenability to integration; these aspects satisfy the upcoming demands of artificial intelligence for higher computational loads. Among the tremendous efforts toward achieving human-brain-like electronics, layered 2D materials have demonstrated significant potential owing to their outstanding electronic and physical properties, facile integration with other materials, and low-power computing. This review discusses the memristive characteristics of various 2D materials (heterostructures, defect-engineered materials, and alloy materials) used in neuromorphic computing for image segregation or pattern recognition. Neuromorphic computing, the most powerful artificial networks for complicated image processing and recognition, represent a breakthrough in artificial intelligence owing to their enhanced performance and lower power consumption compared with von Neumann architectures. A hardware-implemented CNN with weight control based on synaptic memristor arrays is expected to be a promising candidate for future electronics in society, offering a solution based on non-von Neumann hardware. This emerging paradigm changes the computing algorithm using entirely hardware-connected edge computing and deep neural networks.
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Affiliation(s)
- Hyunho Seok
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Shihoon Son
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Sagar Bhaurao Jathar
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Jaewon Lee
- School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Taesung Kim
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
- School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
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25
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Chopin C, de Wergifosse S, Marchal N, Van Velthem P, Piraux L, Abreu Araujo F. Memristive and Tunneling Effects in 3D Interconnected Silver Nanowires. ACS OMEGA 2023; 8:6663-6668. [PMID: 36844586 PMCID: PMC9948158 DOI: 10.1021/acsomega.2c07171] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
A network of silver nanowires (Ag-NWs) is grown by electrodeposition in a nanoporous membrane with interconnected nanopores. This bottom-up approach fabrication method gives a conducting network with a 3D architecture and a high density of Ag-NWs. The network is then functionalized during the etching process, which leads to a high initial resistance as well as memristive behavior. The latter is expected to arise from the creation and the destruction of conducting silver filaments in the functionalized Ag-NW network. Moreover, after several cycles of measurement, the resistance of the network switches from a high-resistance regime in the GΩ range with tunnel conduction to a low-resistance regime presenting negative differential resistance in the kΩ range.
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26
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Guo H, Hu Q, Zhang C, Fan Z, Liu H, Wu R, Liu Z, Pan S. Resonance Coupling in Si@WS 2Core-Ω Shell Nanostructure. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:462. [PMID: 36770423 PMCID: PMC9920409 DOI: 10.3390/nano13030462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 01/21/2023] [Accepted: 01/21/2023] [Indexed: 06/18/2023]
Abstract
Realizing strong laser-matter interaction in a heterostructure consisting of two-dimensional transition metal dichalcogenides (TMDCs) and an optical nanocavity is a potential strategy for novel photonic devices. In this paper, two core-Ω shell nanostructures, Si@WS2 core-Ω shell nanostructure on glass/Si substrates, are briefly introduced. A strong laser-matter interaction occurred in the Si@WS2 core-Ω shell nanostructure when it was excited by femtosecond (fs) laser in the near-infrared-1 region (NIR-1, 650 nm-950 nm), resulting in a resonance coupling between the electric dipole resonance (EDR) of the Si nanosphere (NS) and the exciton resonance of the WS2 nanomembrane (NMB). The generation of resonance coupling regulates the resonant mode of the nanostructure to realize the multi-dimensional nonlinear optical response, which can be utilized in the fields of biological imaging and nanoscale light source.
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Affiliation(s)
- Haomin Guo
- School of Physics and Materials Science, Guangzhou University, Guangzhou 510006, China
| | - Qi Hu
- School of Physics and Materials Science, Guangzhou University, Guangzhou 510006, China
- Research Center for Advanced Information Materials (CAIM), Huangpu Research and Graduate School of Guangzhou University, Guangzhou 510555, China
| | - Chengyun Zhang
- School of Physics and Materials Science, Guangzhou University, Guangzhou 510006, China
- Research Center for Advanced Information Materials (CAIM), Huangpu Research and Graduate School of Guangzhou University, Guangzhou 510555, China
| | - Zihao Fan
- School of Physics and Materials Science, Guangzhou University, Guangzhou 510006, China
| | - Haiwen Liu
- School of Physics and Materials Science, Guangzhou University, Guangzhou 510006, China
| | - Runmin Wu
- School of Physics and Materials Science, Guangzhou University, Guangzhou 510006, China
| | - Zhiyu Liu
- School of Physics and Materials Science, Guangzhou University, Guangzhou 510006, China
- Research Center for Advanced Information Materials (CAIM), Huangpu Research and Graduate School of Guangzhou University, Guangzhou 510555, China
| | - Shusheng Pan
- School of Physics and Materials Science, Guangzhou University, Guangzhou 510006, China
- Research Center for Advanced Information Materials (CAIM), Huangpu Research and Graduate School of Guangzhou University, Guangzhou 510555, China
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27
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Fu T, Fu S, Sun L, Gao H, Yao J. An Effective Sneak-Path Solution Based on a Transient-Relaxation Device. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2207133. [PMID: 36222395 DOI: 10.1002/adma.202207133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/26/2022] [Indexed: 06/16/2023]
Abstract
An efficient strategy for addressing individual devices is required to unveil the full potential of memristors for high-density memory and computing applications. Existing strategies using two-terminal selectors that are preferable for compact integration have trade-offs in reduced generality or functional window. A strategy that applies to broad memristors and maintains their full-range functional window is proposed. This strategy uses a type of unipolar switch featuring a transient relaxation or retention as the selector. The unidirectional current flow in the switch suppresses the sneak-path current, whereas the transient-relaxation window is exploited for bidirectional programming. A unipolar volatile memristor with ultralow switching voltage (e.g., <100 mV), constructed from a protein nanowire dielectric harvested from Geobacter sulfurreducens, is specifically employed as the example switch to highlight the advantages and scalability in the strategy for array integration.
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Affiliation(s)
- Tianda Fu
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Shuai Fu
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Lu Sun
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Hongyan Gao
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA, 01003, USA
| | - Jun Yao
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA, 01003, USA
- Institute for Applied Life Sciences (IALS), University of Massachusetts, Amherst, MA, 01003, USA
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA, 01003, USA
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28
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Milano G, Miranda E, Fretto M, Valov I, Ricciardi C. Experimental and Modeling Study of Metal-Insulator Interfaces to Control the Electronic Transport in Single Nanowire Memristive Devices. ACS APPLIED MATERIALS & INTERFACES 2022; 14:53027-53037. [PMID: 36396122 PMCID: PMC9716557 DOI: 10.1021/acsami.2c11022] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 08/25/2022] [Indexed: 06/16/2023]
Abstract
Memristive devices relying on redox-based resistive switching mechanisms represent promising candidates for the development of novel computing paradigms beyond von Neumann architecture. Recent advancements in understanding physicochemical phenomena underlying resistive switching have shed new light on the importance of an appropriate selection of material properties required to optimize the performance of devices. However, despite great attention has been devoted to unveiling the role of doping concentration, impurity type, adsorbed moisture, and catalytic activity at the interfaces, specific studies concerning the effect of the counter electrode in regulating the electronic flow in memristive cells are scarce. In this work, the influence of the metal-insulator Schottky interfaces in electrochemical metallization memory (ECM) memristive cell model systems based on single-crystalline ZnO nanowires (NWs) is investigated following a combined experimental and modeling approach. By comparing and simulating the electrical characteristics of single NW devices with different contact configurations and by considering Ag and Pt electrodes as representative of electrochemically active and inert electrodes, respectively, we highlight the importance of an appropriate choice of electrode materials by taking into account the Schottky barrier height and interface chemistry at the metal-insulator interfaces. In particular, we show that a clever choice of metal-insulator interfaces allows to reshape the hysteretic conduction characteristics of the device and to increase the device performance by tuning its resistance window. These results obtained from single NW-based devices provide new insights into the selection criteria for materials and interfaces in connection with the design of advanced ECM cells.
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Affiliation(s)
- Gianluca Milano
- Advanced
Materials Metrology and Life Sciences Division, INRiM (Istituto Nazionale di Ricerca Metrologica), Strada delle Cacce 91, 10135Torino, Italy
| | - Enrique Miranda
- Departament
d’Enginyeria Electrònica, Universitat Autònoma de Barcelona (UAB), 08193Cerdanyola del Vallès, Spain
| | - Matteo Fretto
- Advanced
Materials Metrology and Life Sciences Division, INRiM (Istituto Nazionale di Ricerca Metrologica), Strada delle Cacce 91, 10135Torino, Italy
| | - Ilia Valov
- JARA—Fundamentals
for Future Information Technology, 52425Jülich, Germany
- Peter-Grünberg-Institut
(PGI 7), Forschungszentrum Jülich, Wilhelm-Johnen-Straße, 52425Jülich, Germany
| | - Carlo Ricciardi
- Department
of Applied Science and Technology, Politecnico
di Torino, C.so Duca degli Abruzzi 24, 10129Torino, Italy
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29
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Woo KS, Kim J, Han J, Kim W, Jang YH, Hwang CS. Probabilistic computing using Cu 0.1Te 0.9/HfO 2/Pt diffusive memristors. Nat Commun 2022; 13:5762. [PMID: 36180426 PMCID: PMC9525628 DOI: 10.1038/s41467-022-33455-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 09/19/2022] [Indexed: 11/17/2022] Open
Abstract
A computing scheme that can solve complex tasks is necessary as the big data field proliferates. Probabilistic computing (p-computing) paves the way to efficiently handle problems based on stochastic units called probabilistic bits (p-bits). This study proposes p-computing based on the threshold switching (TS) behavior of a Cu0.1Te0.9/HfO2/Pt (CTHP) diffusive memristor. The theoretical background of the p-computing resembling the Hopfield network structure is introduced to explain the p-computing system. P-bits are realized by the stochastic TS behavior of CTHP diffusive memristors, and they are connected to form the p-computing network. The memristor-based p-bit is likely to be ‘0’ and ‘1’, of which probability is controlled by an input voltage. The memristor-based p-computing enables all 16 Boolean logic operations in both forward and inverted operations, showing the possibility of expanding its uses for complex operations, such as full adder and factorization. Designing a computing scheme to solve complex tasks as the big data field proliferates remains a challenge. Here, the authors present a probabilistic bit generation hardware built using the random nature of CuxTe1−x/HfO2/Pt memristors capable of performing logic gates with invertible mode, showing the expandability to complex logic circuits.
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Affiliation(s)
- Kyung Seok Woo
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Jaehyun Kim
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Janguk Han
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Woohyun Kim
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Yoon Ho Jang
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Cheol Seong Hwang
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehag-dong, Gwanak-gu, Seoul, 08826, Republic of Korea.
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30
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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: 5] [Impact Index Per Article: 2.5] [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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Li D, Li C, Wang J, Xu M, Ma J, Gu D, Liu F, Jiang Y, Li W. Multifunctional Analog Resistance Switching of Si 3N 4-Based Memristors through Migration of Ag + Ions and Formation of Si-Dangling Bonds. J Phys Chem Lett 2022; 13:5101-5108. [PMID: 35657147 DOI: 10.1021/acs.jpclett.2c00893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
With forming-free, self-rectifying, and self-compliant properties, memristors can effectively prevent themselves from experiencing leakage currents and overshoot voltages without any additional circuitry. However, the implementation of all these features in a single memristor remains a challenge. Herein, a multifunctional Si3N4-based memristor with a structure of Ag/a-SiNx/p++-Si has been fabricated, and it was demonstrated, for the first time, that the device exhibits novel analog resistance switching behaviors, such as being forming-free, self-rectifying, and self-compliant, presenting well a coexistence of volatile and nonvolatile performance of resistance switching. The multifunctional analog resistance switching could be attributed to the formation of the Si-dangling bond channel and the migration of Ag+ ions inside the a-SiNx layer. Our current results might provide an insightful understanding of the resistance switching mechanism of Si3N4-based memristors, and the device with a large on/off ratio (>103) and robust retention (>103 s) and endurance (>103 cycles) shows potential for application in crossbar synaptic array devices.
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Affiliation(s)
- Dongyang Li
- Key Laboratory of Information Materials of Sichuan Province, Southwest Minzu University, Chengdu 610041, P.R. China
| | - Chunmei Li
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, P.R. China
| | - Jinyong Wang
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, P.R. China
| | - Ming Xu
- Key Laboratory of Information Materials of Sichuan Province, Southwest Minzu University, Chengdu 610041, P.R. China
| | - Jian Ma
- Key Laboratory of Information Materials of Sichuan Province, Southwest Minzu University, Chengdu 610041, 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
| | - Fucai Liu
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, P.R. China
| | - Yadong Jiang
- 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
| | - Wei Li
- 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
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Banerjee W, Kashir A, Kamba S. Hafnium Oxide (HfO 2 ) - A Multifunctional Oxide: A Review on the Prospect and Challenges of Hafnium Oxide in Resistive Switching and Ferroelectric Memories. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2022; 18:e2107575. [PMID: 35510954 DOI: 10.1002/smll.202107575] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 03/24/2022] [Indexed: 06/14/2023]
Abstract
Hafnium oxide (HfO2 ) is one of the mature high-k dielectrics that has been standing strong in the memory arena over the last two decades. Its dielectric properties have been researched rigorously for the development of flash memory devices. In this review, the application of HfO2 in two main emerging nonvolatile memory technologies is surveyed, namely resistive random access memory and ferroelectric memory. How the properties of HfO2 equip the former to achieve superlative performance with high-speed reliable switching, excellent endurance, and retention is discussed. The parameters to control HfO2 domains are further discussed, which can unleash the ferroelectric properties in memory applications. Finally, the prospect of HfO2 materials in emerging applications, such as high-density memory and neuromorphic devices are examined, and the various challenges of HfO2 -based resistive random access memory and ferroelectric memory devices are addressed with a future outlook.
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Affiliation(s)
- Writam Banerjee
- Center for Single Atom-based Semiconductor Device, Department of Material Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea
| | - Alireza Kashir
- Institute of Physics of the Czech Academy of Sciences, Na Slovance 2, Prague 8, 182 21, Czech Republic
| | - Stanislav Kamba
- Institute of Physics of the Czech Academy of Sciences, Na Slovance 2, Prague 8, 182 21, Czech Republic
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Milano G, Miranda E, Ricciardi C. Connectome of memristive nanowire networks through graph theory. Neural Netw 2022; 150:137-148. [DOI: 10.1016/j.neunet.2022.02.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 01/26/2022] [Accepted: 02/24/2022] [Indexed: 12/27/2022]
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Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse. Nat Commun 2022; 13:2811. [PMID: 35589710 PMCID: PMC9120471 DOI: 10.1038/s41467-022-30432-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 04/25/2022] [Indexed: 12/02/2022] Open
Abstract
Neuromorphic computing targets the hardware embodiment of neural network, and device implementation of individual neuron and synapse has attracted considerable attention. The emulation of synaptic plasticity has shown promising results after the advent of memristors. However, neuronal intrinsic plasticity, which involves in learning process through interactions with synaptic plasticity, has been rarely demonstrated. Synaptic and intrinsic plasticity occur concomitantly in learning process, suggesting the need of the simultaneous implementation. Here, we report a neurosynaptic device that mimics synaptic and intrinsic plasticity concomitantly in a single cell. Threshold switch and phase change memory are merged in threshold switch-phase change memory device. Neuronal intrinsic plasticity is demonstrated based on bottom threshold switch layer, which resembles the modulation of firing frequency in biological neuron. Synaptic plasticity is also introduced through the nonvolatile switching of top phase change layer. Intrinsic and synaptic plasticity are simultaneously emulated in a single cell to establish the positive feedback between them. A positive feedback learning loop which mimics the retraining process in biological system is implemented in threshold switch-phase change memory array for accelerated training. Synaptic plasticity and neuronal intrinsic plasticity are both involved in the learning process of hardware artificial neural network. Here, Lee et al. integrate a threshold switch and a phase change memory in a single device, which emulates biological synaptic and intrinsic plasticity simultaneously.
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Wu W, Pavloudis T, Verkhovtsev AV, Solov'yov AV, Palmer RE. Molecular dynamics simulation of nanofilament breakage in neuromorphic nanoparticle networks. NANOTECHNOLOGY 2022; 33:275602. [PMID: 35412471 DOI: 10.1088/1361-6528/ac5e6d] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 03/15/2022] [Indexed: 06/14/2023]
Abstract
Neuromorphic computing systems may be the future of computing and cluster-based networks are a promising architecture for the realization of these systems. The creation and dissolution of synapses between the clusters are of great importance for their function. In this work, we model the thermal breakage of a gold nanofilament located between two gold nanoparticles via molecular dynamics simulations to study on the mechanisms of neuromorphic nanoparticle-based devices. We employ simulations of Au nanowires of different lengths (20-80 Å), widths (4-8 Å) and shapes connecting two Au1415nanoparticles (NPs) and monitor the evolution of the system via a detailed structural identification analysis. We found that atoms of the nanofilament gradually aggregate towards the clusters, causing the middle of wire to gradually thin and then break. Most of the system remains crystalline during this process but the center is molten. The terminal NPs increase the melting point of the NWs by fixing the middle wire and act as recrystallization areas. We report a strong dependence on the width of the NWs, but also their length and structure. These results may serve as guidelines for the realization of cluster-based neuromorphic computing systems.
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Affiliation(s)
- Wenkai Wu
- Nanomaterials Lab, College of Engineering, Swansea University, Fabian Way, SA1 8EN, Swansea, United Kingdom
| | - Theodoros Pavloudis
- Nanomaterials Lab, College of Engineering, Swansea University, Fabian Way, SA1 8EN, Swansea, United Kingdom
- School of Physics, Faculty of Sciences, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece
| | - Alexey V Verkhovtsev
- MBN Research Center gGmbH, Frankfurter Innovationszentrum Biotechnologie, Altenhöferallee 3, D-60438 Frankfurt am Main, Germany
| | - Andrey V Solov'yov
- MBN Research Center gGmbH, Frankfurter Innovationszentrum Biotechnologie, Altenhöferallee 3, D-60438 Frankfurt am Main, Germany
| | - Richard E Palmer
- Nanomaterials Lab, College of Engineering, Swansea University, Fabian Way, SA1 8EN, Swansea, United Kingdom
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Sparse CNT networks with implanted AgAu nanoparticles: A novel memristor with short-term memory bordering between diffusive and bipolar switching. PLoS One 2022; 17:e0264846. [PMID: 35358187 PMCID: PMC8970472 DOI: 10.1371/journal.pone.0264846] [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: 09/14/2021] [Accepted: 02/17/2022] [Indexed: 11/19/2022] Open
Abstract
With this work we introduce a novel memristor in a lateral geometry whose resistive switching behaviour unifies the capabilities of bipolar switching with decelerated diffusive switching showing a biologically plausible short-term memory. A new fabrication route is presented for achieving lateral nano-scaled distances by depositing a sparse network of carbon nanotubes (CNTs) via spin-coating of a custom-made CNT dispersion. Electrochemical metallization-type (ECM) resistive switching is obtained by implanting AgAu nanoparticles with a Haberland-type gas aggregation cluster source into the nanogaps between the CNTs and shows a hybrid behaviour of both diffusive and bipolar switching. The resistance state resets to a high resistive state (HRS) either if the voltage is removed with a retention time in the second- to sub-minute scale (diffusive) or by applying a reverse voltage (bipolar). Furthermore, the retention time is positively correlated to the duration of the Set voltage pulse. The potential for low-voltage operation makes this approach a promising candidate for short-term memory applications in neuromorphic circuits. In addition, the lateral fabrication approach opens the pathway towards integrating sensor-functionality and offers a general starting point for the scalable fabrication of nanoscaled devices.
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Shvetsov BS, Minnekhanov AA, Emelyanov AV, Ilyasov AI, Grishchenko YV, Zanaveskin ML, Nesmelov AA, Streltsov DR, Patsaev TD, Vasiliev AL, Rylkov VV, Demin VA. Parylene-based memristive crossbar structures with multilevel resistive switching for neuromorphic computing. NANOTECHNOLOGY 2022; 33:255201. [PMID: 35276689 DOI: 10.1088/1361-6528/ac5cfe] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 03/11/2022] [Indexed: 06/14/2023]
Abstract
Currently, there is growing interest in wearable and biocompatible smart computing and information processing systems that are safe for the human body. Memristive devices are promising for solving such problems due to a number of their attractive properties, such as low power consumption, scalability, and the multilevel nature of resistive switching (plasticity). The multilevel plasticity allows memristors to emulate synapses in hardware neuromorphic computing systems (NCSs). The aim of this work was to study Cu/poly-p-xylylene(PPX)/Au memristive elements fabricated in the crossbar geometry. In developing the technology for manufacturing such samples, we took into account their characteristics, in particular stable and multilevel resistive switching (at least 10 different states) and low operating voltage (<2 V), suitable for NCSs. Experiments on cycle to cycle (C2C) switching of a single memristor and device to device (D2D) switching of several memristors have shown high reproducibility of resistive switching (RS) voltages. Based on the obtained memristors, a formal hardware neuromorphic network was created that can be trained to classify simple patterns.
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Affiliation(s)
- Boris S Shvetsov
- National Research Centre 'Kurchatov Institute', 123182, Moscow, Russia
| | | | - Andrey V Emelyanov
- National Research Centre 'Kurchatov Institute', 123182, Moscow, Russia
- Moscow Institute of Physics and Technology, 141700, Dolgoprudny, Moscow Region, Russia
| | - Aleksandr I Ilyasov
- National Research Centre 'Kurchatov Institute', 123182, Moscow, Russia
- Lomonosov Moscow State University, 119991, Moscow, Russia
| | | | | | | | | | - Timofey D Patsaev
- National Research Centre 'Kurchatov Institute', 123182, Moscow, Russia
| | - Alexander L Vasiliev
- National Research Centre 'Kurchatov Institute', 123182, Moscow, Russia
- Moscow Institute of Physics and Technology, 141700, Dolgoprudny, Moscow Region, Russia
- Federal Research Center 'Crystallography and Photonics' of the Russian Academy of Sciences, 117342, Moscow, Russia
| | - Vladimir V Rylkov
- National Research Centre 'Kurchatov Institute', 123182, Moscow, Russia
- Kotel'nikov Institute of Radio Engineering and Electronics RAS, 141190, Fryazino, Moscow Region, Russia
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Zhou Y, Zhao X, Chen J, Gao M, He Z, Wang S, Wang C. Ternary Flash Memory with a Carbazole-Based Conjugated Copolymer: WS 2 Composites as Active Layers. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2022; 38:3113-3121. [PMID: 35239348 DOI: 10.1021/acs.langmuir.1c03089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
For nonvolatile memory devices, the design and synthesis of their substrate materials are very important. Due to the versatility and large-area fabrication of the low-temperature spin coating process, organic/inorganic nanomaterials as active layers of memory devices have been deeply studied. Inorganic nanoparticles can engage in interactions with polymers via external voltage. WS2 NPs have a large specific surface area and good conductivity. They can be used as the charge trap center in the active layer, which is conducive to the charge transfer in the active layer. Poly[2,7-9-(9-heptadecanyl)-9H-carbazole-co-benzo[4,5] imidazole[2,1-α] isoindol-11-one] (PIIO) was synthesized via the Suzuki coupling reaction. ITO/PIIO/Al and ITO/PIIO:WS2 NP/Al devices were prepared by the spin coating method and vacuum evaporation technology. All devices showed tristable switching behavior. The influence of the WS2 mass fraction on memory performance was studied. The device composite with 6 wt % WS2 NPs showed the best storage features. The OFF/ON1/ON2 current ratio was 1: 1.11 × 101: 2.03 × 104, and the threshold voltage Vth1/Vth2 was -0.60 V/-1.05 V. The device is steady for 12,000 s in three states-high-resistance state (HRS), intermediate state (IRS), and low-resistance state (LRS). After reading 3500 times, the switch-state current displayed no obvious attenuation. This work shows that the polymer and its composites have broad prospects in next-generation nonvolatile storage.
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Affiliation(s)
- Yijia Zhou
- School of Chemical Engineering and Materials, Heilongjiang University, Harbin 150080, P. R. China
| | - Xiaofeng Zhao
- School of Electronic Engineering, Heilongjiang University, Harbin 150080, P. R. China
| | - Jiangshan Chen
- Institute of Polymer Optoelectronic Materials and Devices, State Key Laboratory of Luminescent Materials and Devices, South China University of Technology, Guangzhou 510640, P. R. China
| | - Meng Gao
- School of Chemical Engineering and Materials, Heilongjiang University, Harbin 150080, P. R. China
| | - Zhaohua He
- School of Chemical Engineering and Materials, Heilongjiang University, Harbin 150080, P. R. China
| | - Shuhong Wang
- School of Chemical Engineering and Materials, Heilongjiang University, Harbin 150080, P. R. China
| | - Cheng Wang
- School of Chemical Engineering and Materials, Heilongjiang University, Harbin 150080, P. R. China
- South China Advanced Institute for Soft Matter Science and Technology, South China University of Technology, Guangzhou 510640, P. R. China
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Guo T, Pan K, Jiao Y, Sun B, Du C, Mills JP, Chen Z, Zhao X, Wei L, Zhou YN, Wu YA. Versatile memristor for memory and neuromorphic computing. NANOSCALE HORIZONS 2022; 7:299-310. [PMID: 35064257 DOI: 10.1039/d1nh00481f] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The memristor is a promising candidate to implement high-density memory and neuromorphic computing. Based on the characteristic retention time, memristors are classified into volatile and non-volatile types. However, a single memristor generally provides a specific function based on electronic performances, which poses roadblocks for further developing novel circuits. Versatile memristors exhibiting both volatile and non-volatile properties can provide multiple functions covering non-volatile memory and neuromorphic computing. In this work, a versatile memristor with volatile/non-volatile bifunctional properties was developed. Non-volatile functionality with a storage window of 4.0 × 105 was obtained. Meanwhile, the device can provide threshold volatile functionalities with a storage window of 7.0 × 104 and a rectification ratio of 4.0 × 104. The leaky integrate-and-fire (LIF) neuron model and artificial synapse based on the device have been studied. Such a versatile memristor enables non-volatile memory, selectors, artificial neurons, and artificial synapses, which will provide advantages regarding circuit simplification, fabrication processes, and manufacturing costs.
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Affiliation(s)
- Tao Guo
- Department of Mechanical and Mechatronics Engineering, Waterloo Institute of Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.
| | - Kangqiang Pan
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - Yixuan Jiao
- Department of Mechanical and Mechatronics Engineering, Waterloo Institute of Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.
| | - 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
| | - Cheng Du
- Department of Mechanical and Mechatronics Engineering, Waterloo Institute of Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.
| | - Joel P Mills
- Department of Mechanical and Mechatronics Engineering, Waterloo Institute of Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.
| | - Zuolong Chen
- Department of Mechanical and Mechatronics Engineering, Waterloo Institute of Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.
| | - Xiaoye Zhao
- Department of Mechanical and Mechatronics Engineering, Waterloo Institute of Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.
- State Key Laboratory of Advanced Welding and Joining, Harbin Institute of Technology, Harbin 150001, China
| | - Lan Wei
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - Y Norman Zhou
- Department of Mechanical and Mechatronics Engineering, Waterloo Institute of Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.
| | - Yimin A Wu
- Department of Mechanical and Mechatronics Engineering, Waterloo Institute of Nanotechnology, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada.
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Song YG, Suh JM, Park JY, Kim JE, Chun SY, Kwon JU, Lee H, Jang HW, Kim S, Kang C, Yoon JH. Artificial Adaptive and Maladaptive Sensory Receptors Based on a Surface-Dominated Diffusive Memristor. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2103484. [PMID: 34837480 PMCID: PMC8811822 DOI: 10.1002/advs.202103484] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 10/14/2021] [Indexed: 05/03/2023]
Abstract
A biological receptor serves as sensory transduction from an external stimulus to an electrical signal. It allows humans to better match the environment by filtering out repetitive innocuous information and recognize potentially damaging stimuli through key features, including adaptive and maladaptive behaviors. Herein, for the first time, the authors develop substantial artificial receptors involving both adaptive and maladaptive behaviors using diffusive memristor. Metal-oxide nanorods (NR) as a switching matrix enable the electromigration of an active metal along the surface of the NRs under electrical stimulation, resulting in unique surface-dominated switching dynamics with the advantage of fast Ag migration and fine controllability of the conductive filament. To experimentally demonstrate its potential application, a thermoreceptor system is constructed using memristive artificial receptors. The proposed surface-dominated diffusive memristor allows the direct emulation of the biological receptors, which represents an advance in the bioinspired technology adopted in creating artificial intelligence systems.
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Affiliation(s)
- Young Geun Song
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)Seoul02791Republic of Korea
| | - Jun Min Suh
- Department of Materials Science and EngineeringSeoul National UniversitySeoul08826Republic of Korea
| | - Jae Yeol Park
- Department of Materials Science & EngineeringKorea Advanced Institute of Science and Technology (KAIST)Daejeon34141Republic of Korea
| | - Ji Eun Kim
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)Seoul02791Republic of Korea
- Department of Materials Science and EngineeringKorea UniversitySeoul02841Republic of Korea
| | - Suk Yeop Chun
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)Seoul02791Republic of Korea
- KU‐KIST Graduate School of Converging Science and TechnologyKorea UniversitySeoul02841Republic of Korea
| | - Jae Uk Kwon
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)Seoul02791Republic of Korea
- Department of Materials Science and EngineeringKorea UniversitySeoul02841Republic of Korea
| | - Ho Lee
- Department of Nuclear EngineeringHanyang UniversitySeoul02841Republic of Korea
| | - Ho Won Jang
- Department of Materials Science and EngineeringSeoul National UniversitySeoul08826Republic of Korea
| | - Sangtae Kim
- Department of Nuclear EngineeringHanyang UniversitySeoul02841Republic of Korea
| | - Chong‐Yun Kang
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)Seoul02791Republic of Korea
- KU‐KIST Graduate School of Converging Science and TechnologyKorea UniversitySeoul02841Republic of Korea
| | - Jung Ho Yoon
- Electronic Materials Research CenterKorea Institute of Science and Technology (KIST)Seoul02791Republic of Korea
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Choi SH, Park SO, Seo S, Choi S. Reliable multilevel memristive neuromorphic devices based on amorphous matrix via quasi-1D filament confinement and buffer layer. SCIENCE ADVANCES 2022; 8:eabj7866. [PMID: 35061541 PMCID: PMC8782456 DOI: 10.1126/sciadv.abj7866] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 11/30/2021] [Indexed: 05/19/2023]
Abstract
Conductive-bridging random access memory (CBRAM) has garnered attention as a building block of non-von Neumann architectures because of scalability and parallel processing on the crossbar array. To integrate CBRAM into the back-end-of-line (BEOL) process, amorphous switching materials have been investigated for practical usage. However, both the inherent randomness of filaments and disorders of amorphous material lead to poor reliability. In this study, a highly reliable nanoporous-defective bottom layer (NP-DBL) structure based on amorphous TiO2 is demonstrated (Ag/a-TiO2/a-TiOx/p-Si). The stoichiometries of DBL and the pore size can be manipulated to achieve the analog conductance updates and multilevel conductance by 300 states with 1.3% variation, and 10 levels, respectively. Compared with nonporous TiO2 CBRAM, endurance, retention, and uniformity can be improved by 106 pulses, 28 days at 85°C, and 6.7 times, respectively. These results suggest even amorphous-based systems, elaborately tuned structural variables, can help design more reliable CBRAMs.
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Abstract
With the development of the Internet of things, artificial intelligence, and wearable devices, massive amounts of data are generated and need to be processed. High standards are required to store and analyze this information. In the face of the explosive growth of information, the memory used in data storage and processing faces great challenges. Among many types of memories, memristors have received extensive attentions due to their low energy consumption, strong tolerance, simple structure, and strong miniaturization. However, they still face many problems, especially in the application of artificial bionic synapses, which call for higher requirements in the mechanical properties of the device. The progress of integrated circuit and micro-processing manufacturing technology has greatly promoted development of the flexible memristor. The use of a flexible memristor to simulate nerve synapses will provide new methods for neural network computing and bionic sensing systems. In this paper, the materials and structure of the flexible memristor are summarized and discussed, and the latest configuration and new materials are described. In addition, this paper will focus on its application in artificial bionic synapses and discuss the challenges and development direction of flexible memristors from this perspective.
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Choi YJ, Bang S, Kim TH, Hong K, Kim S, Kim S, Cho S, Park BG. Analytically and empirically consistent characterization of the resistive switching mechanism in a Ag conducting-bridge random-access memory device through a pseudo-liquid interpretation approach. Phys Chem Chem Phys 2021; 23:27234-27243. [PMID: 34853837 DOI: 10.1039/d1cp04637c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A new physical analysis of the filament formation in a Ag conducting-bridge random-access memory (CBRAM) device in consideration of the existence of inter-atomic attractions caused by metal bonding is suggested. The movement of Ag atoms inside the switching layer is characterized hydrodynamically using the Young-Laplace equation during set and reset operations. Both meridional and azimuthal curvatures of the Ag filament protruding from the Ag electrode are accurately calculated to track down the exact shape of the Ag filament with change in the applied voltage. The second-order partial differential equation for the Ag filament geometry is derived from the equation of equilibrium between the electrostatic pressure and the Laplace one. The solution to the equation is numerically obtained, and furthermore, the abrupt set operation in the forming process, bipolar resistive-switching, and the threshold switching operation in the reset operations are successfully simulated in accordance with the numerical solutions. Also, it is demonstrated that the currents extracted from the suggested model show good agreement with the I-V characteristics measured from the fabricated Ag CBRAM device.
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Affiliation(s)
- Yeon-Joon Choi
- Inter-University Semiconductor Research Center (ISRC) and the Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, South Korea.
| | - Suhyun Bang
- Inter-University Semiconductor Research Center (ISRC) and the Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, South Korea.
| | - Tae-Hyeon Kim
- Inter-University Semiconductor Research Center (ISRC) and the Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, South Korea.
| | - Kyungho Hong
- Inter-University Semiconductor Research Center (ISRC) and the Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, South Korea.
| | - Sungjoon Kim
- Inter-University Semiconductor Research Center (ISRC) and the Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, South Korea.
| | - Sungjun Kim
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, South Korea
| | - Seongjae Cho
- Department of Electronics Engineering, Gachon University, Seongnam-si, Gyeonggi-do 13120, South Korea.
| | - Byung-Gook Park
- Inter-University Semiconductor Research Center (ISRC) and the Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, South Korea.
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Abstract
Bio-memristors constitute candidates for the next generation of non-volatile storage and bionic synapses due to their biocompatibility, environmental benignity, sustainability, flexibility, degradability, and impressive memristive performance. Silk fibroin (SF), a natural and abundant biomaterial with excellent mechanical, optical, electrical, and structure-adjustable properties as well as being easy to process, has been utilized and shown to have potential in the construction of bio-memristors. Here, we first summarize the fundamental mechanisms of bio-memristors based on SF. Then, the latest achievements and developments of pristine and composited SF-based memristors are highlighted, followed by the integration of memristive devices. Finally, the challenges and insights associated with SF-based bio-memristors are presented. Advances in SF-based bio-memristors will open new avenues in the design and integration of high-performance bio-integrated systems and facilitate their application in logic operations, complex circuits, and neural networks.
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Affiliation(s)
- Yi Zhang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, P. R. China.
| | - Suna Fan
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, P. R. China.
| | - Yaopeng Zhang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, P. R. China.
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Shih YC, Shen YC, Cheng YK, Chaudhary M, Yang TY, Yu YJ, Chueh YL. Rational Design on Controllable Cation Injection with Improved Conductive-Bridge Random Access Memory by Glancing Angle Deposition Technology toward Neuromorphic Application. ACS APPLIED MATERIALS & INTERFACES 2021; 13:55470-55480. [PMID: 34775743 DOI: 10.1021/acsami.1c18101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
A conductive-bridge random access memory (CBRAM) has been considered a promising candidate for the next-generation nonvolatile memory technology because of its excellent performance, for which the resistive switching behavior depends on the formation/dissolution of conducting filaments in an electrolyte layer originated by the cation injection from the active electrode with electrochemical reactions. Typically, the controllability of cations into the electrolyte layer is a main issue, leading to stable switching reliability. In this work, an architecture combining spike-shaped Ag electrodes created by Al2O3 nanopillar arrays as a physical diffusion barrier by glancing angle deposition technology was proposed to localize Ag cation injection for the formation of controllable filaments inside TiOx as the switching layer. Interestingly, the dimension of the Ag plugs defined by the topography of Al2O3 nanopillar arrays can control Ag cation injection to influence the dimensionality of conductive filaments. Compared to the typical planar-Ag/TiOx/Pt device, the spiked-Ag/Al2O3 nanopillar arrays/TiOx/Pt device shows improvement of endurance and voltage disturbance. With enhanced multilevel characteristics, the spiked active-metal-based CBRAM device can be expected to serve as an analogue synapse for neuromorphic applications.
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Affiliation(s)
- Yu-Chuan Shih
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
- Frontier Research Center on Fundamental and Applied Sciences of Matters, National Tsing Hua University, Hsinchu 30013, Taiwan
- Department of Physics, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan
| | - Ying-Chun Shen
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
- Frontier Research Center on Fundamental and Applied Sciences of Matters, National Tsing Hua University, Hsinchu 30013, Taiwan
- Department of Physics, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan
| | - Yen-Kai Cheng
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
- Frontier Research Center on Fundamental and Applied Sciences of Matters, National Tsing Hua University, Hsinchu 30013, Taiwan
- Department of Physics, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan
| | - Mayur Chaudhary
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
- Frontier Research Center on Fundamental and Applied Sciences of Matters, National Tsing Hua University, Hsinchu 30013, Taiwan
- Department of Physics, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan
| | - Tzu-Yi Yang
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
- Frontier Research Center on Fundamental and Applied Sciences of Matters, National Tsing Hua University, Hsinchu 30013, Taiwan
- Department of Physics, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan
| | - Yi-Jen Yu
- Instrument Center, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Yu-Lun Chueh
- Department of Materials Science and Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
- Frontier Research Center on Fundamental and Applied Sciences of Matters, National Tsing Hua University, Hsinchu 30013, Taiwan
- Department of Physics, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan
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47
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Valencia FJ, Ramírez M, Varas A, Rogan J. Thermal Sensitivity on Eccentric Gold Hollow Nanoparticles: A Perspective from Atomistic Simulations. J Chem Inf Model 2021; 61:5499-5507. [PMID: 34726404 DOI: 10.1021/acs.jcim.1c00849] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Eccentricity is a common feature consequence of several synthesis protocols of hollow nanoshells. Despite the crescent interest in these nanoparticles, it is still unclear how an irregular layer on the nanoparticle impacts the macroscopic properties. Here, we study the thermal stability of eccentric hollow nanoparticles (hNPs) for different sizes and eccentricity values by means of classical molecular dynamics simulations. Our results reveal that eccentricity displays a significant role in the thermal stability of hNPs. We attribute this behavior to the irregular shell contour, which collapses due to the thermal-activated diffusive process from the nanoparticle shell's most thin region. The mechanism is driven at low temperature by the nucleation of stacking faults until the amorphization for larger temperature values. Besides, for some particular eccentric hNPs, the shell suffers a surface reconstruction process, transforming the eccentric hNP into a concentric hNP. We believe that our study on thermal effects in eccentric hNPs has relevance because of their outstanding applications for plasmonic and sensing.
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Affiliation(s)
- Felipe J Valencia
- Centro de Investigación DAiTA Lab, Facultad de Estudios Interdisciplinarios, Universidad Mayor, Santiago 7510041, Chile.,Centro para el Desarrollo de la Nanociencia y la Nanotecnología, CEDENNA, Avda. Ecuador 3493, Santiago 9170124, Chile
| | - Max Ramírez
- Departamento de Física, Facultad de Ciencias, Universidad de Chile, Casilla 653, Santiago 7800024, Chile.,Centro para el Desarrollo de la Nanociencia y la Nanotecnologí a, CEDENNA, Avda. Ecuador 3493, Santiago 9170124, Chile
| | - Alejandro Varas
- Departamento de Física, Facultad de Ciencias, Universidad de Chile, Casilla 653, Santiago 7800024, Chile.,Centro para el Desarrollo de la Nanociencia y la Nanotecnologí a, CEDENNA, Avda. Ecuador 3493, Santiago 9170124, Chile
| | - José Rogan
- Departamento de Física, Facultad de Ciencias, Universidad de Chile, Casilla 653, Santiago 7800024, Chile.,Centro para el Desarrollo de la Nanociencia y la Nanotecnologí a, CEDENNA, Avda. Ecuador 3493, Santiago 9170124, Chile
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48
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A new opportunity for the emerging tellurium semiconductor: making resistive switching devices. Nat Commun 2021; 12:6081. [PMID: 34667171 PMCID: PMC8526830 DOI: 10.1038/s41467-021-26399-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 10/04/2021] [Indexed: 12/03/2022] Open
Abstract
The development of the resistive switching cross-point array as the next-generation platform for high-density storage, in-memory computing and neuromorphic computing heavily relies on the improvement of the two component devices, volatile selector and nonvolatile memory, which have distinct operating current requirements. The perennial current-volatility dilemma that has been widely faced in various device implementations remains a major bottleneck. Here, we show that the device based on electrochemically active, low-thermal conductivity and low-melting temperature semiconducting tellurium filament can solve this dilemma, being able to function as either selector or memory in respective desired current ranges. Furthermore, we demonstrate one-selector-one-resistor behavior in a tandem of two identical Te-based devices, indicating the potential of Te-based device as a universal array building block. These nonconventional phenomena can be understood from a combination of unique electrical-thermal properties in Te. Preliminary device optimization efforts also indicate large and unique design space for Te-based resistive switching devices. Resistive switching devices have great promise for a wide variety of technological applications. Here, Yang et al demonstrate that electrochemically induced tellurium filament can give rise to resistive switching, and show that devices based on this can provide a number of advantages compared to metallic filament-based devices.
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49
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Wang Y, Gong Y, Huang S, Xing X, Lv Z, Wang J, Yang JQ, Zhang G, Zhou Y, Han ST. Memristor-based biomimetic compound eye for real-time collision detection. Nat Commun 2021; 12:5979. [PMID: 34645801 PMCID: PMC8514515 DOI: 10.1038/s41467-021-26314-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 09/29/2021] [Indexed: 11/18/2022] Open
Abstract
The lobula giant movement detector (LGMD) is the movement-sensitive, wide-field visual neuron positioned in the third visual neuropile of lobula. LGMD neuron can anticipate collision and trigger avoidance efficiently owing to the earlier occurring firing peak before collision. Vision chips inspired by the LGMD have been successfully implemented in very-large-scale-integration (VLSI) system. However, transistor-based chips and single devices to simulate LGMD neurons make them bulky, energy-inefficient and complicated. The devices with relatively compact structure and simple operation mode to mimic the escape response of LGMD neuron have not been realized yet. Here, the artificial LGMD visual neuron is implemented using light-mediated threshold switching memristor. The non-monotonic response to light flow field originated from the formation and break of Ag conductive filaments is analogue to the escape response of LGMD neuron. Furthermore, robot navigation with obstacle avoidance capability and biomimetic compound eyes with wide field-of-view (FoV) detection capability are demonstrated.
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Affiliation(s)
- Yan Wang
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
- Hefei Innovation Research Institute, School of Microelectronics, Beihang University, 230013, Hefei, P. R. China
| | - Yue Gong
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Shenming Huang
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Xuechao Xing
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Ziyu Lv
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Junjie Wang
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Jia-Qin Yang
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Guohua Zhang
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Ye Zhou
- Institute for Advanced Study, Shenzhen University, 518060, Shenzhen, P. R. China
| | - Su-Ting Han
- Institute of Microscale optoelectronics and College of Optoelectronic Engineering, Shenzhen University, 518060, Shenzhen, P. R. China.
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50
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Niu Y, Jiang K, Dong X, Zheng D, Liu B, Wang H. High performance and low power consumption resistive random access memory with Ag/Fe 2O 3/Pt structure. NANOTECHNOLOGY 2021; 32:505715. [PMID: 34525467 DOI: 10.1088/1361-6528/ac26fd] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 09/14/2021] [Indexed: 06/13/2023]
Abstract
Due to magnetic field tunability and the abundance of iron in the Earth's crust, iron oxide-based resistive random access memory (RRAM) is considered to be low cost and potential for multi-level storage. However, the relatively high operation voltage (>1 V) and small storage window (<100) limit its application. In this work, the devices with simple Ag/Fe2O3/Pt structure exhibit typical bipolar resistive switching with ultralow set voltage (Vset) of 0.16 V, ultralow reset voltage (Vreset) of -0.04 V, high OFF/ON resistance ratio of 103, excellent cycling endurance more than 104and good retention time longer than 104s. Each major parameter has about an order of magnitude improvement compared to the previous data. The devices demonstrate outstanding stable low power consumption quality. Based on the analysis of the experimental results, a percolation model of silver ion migration was established and confirmed that low operation voltage is attributed to the amorphous oxide layer with large porosity. During electrical testing, the compliance current (Ic) and maximum reset voltage (Vmax) can also affect the device performance. This discovery suggests Fe2O3memristor has significant potential for application and provides a new idea for the realization of high-performance low-power RRAM.
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Affiliation(s)
- Yiru Niu
- State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Physics and Astronomy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
- Key Laboratory for Thin Film and Microfabrication Technology of the Ministry of Education, Research Institute of Micro/Nano Science and Technology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
| | - Kang'an Jiang
- State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Physics and Astronomy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
- Key Laboratory for Thin Film and Microfabrication Technology of the Ministry of Education, Research Institute of Micro/Nano Science and Technology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
| | - Xinyuan Dong
- State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Physics and Astronomy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
- Key Laboratory for Thin Film and Microfabrication Technology of the Ministry of Education, Research Institute of Micro/Nano Science and Technology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
| | - Diyuan Zheng
- State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Physics and Astronomy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
- Key Laboratory for Thin Film and Microfabrication Technology of the Ministry of Education, Research Institute of Micro/Nano Science and Technology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
| | - Binbin Liu
- State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Physics and Astronomy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
- Key Laboratory for Thin Film and Microfabrication Technology of the Ministry of Education, Research Institute of Micro/Nano Science and Technology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
| | - Hui Wang
- State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Physics and Astronomy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
- Key Laboratory for Thin Film and Microfabrication Technology of the Ministry of Education, Research Institute of Micro/Nano Science and Technology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China
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