151
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van de Burgt Y, Lubberman E, Fuller EJ, Keene ST, Faria GC, Agarwal S, Marinella MJ, Alec Talin A, Salleo A. A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. NATURE MATERIALS 2017; 16:414-418. [PMID: 28218920 DOI: 10.1038/nmat4856] [Citation(s) in RCA: 566] [Impact Index Per Article: 80.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2016] [Accepted: 01/12/2017] [Indexed: 05/19/2023]
Abstract
The brain is capable of massively parallel information processing while consuming only ∼1-100 fJ per synaptic event. Inspired by the efficiency of the brain, CMOS-based neural architectures and memristors are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODe switches at low voltage and energy (<10 pJ for 103 μm2 devices), displays >500 distinct, non-volatile conductance states within a ∼1 V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODes are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems. Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.
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Affiliation(s)
- Yoeri van de Burgt
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA
| | - Ewout Lubberman
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA
- Zernike Institute for Advanced Materials, University of Groningen, 9747AG Gronigen, The Netherlands
| | - Elliot J Fuller
- Sandia National Laboratories, Livermore, California 94551, USA
| | - Scott T Keene
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA
| | - Grégorio C Faria
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA
- Instituto de Física de São Carlos, Universidade de São Paulo, 13566-590 São Carlos, SP, Brasil
| | - Sapan Agarwal
- Sandia National Laboratories, Livermore, California 94551, USA
| | | | - A Alec Talin
- Sandia National Laboratories, Livermore, California 94551, USA
| | - Alberto Salleo
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA
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152
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Nagareddy VK, Barnes MD, Zipoli F, Lai KT, Alexeev AM, Craciun MF, Wright CD. Multilevel Ultrafast Flexible Nanoscale Nonvolatile Hybrid Graphene Oxide-Titanium Oxide Memories. ACS NANO 2017; 11:3010-3021. [PMID: 28221755 DOI: 10.1021/acsnano.6b08668] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Graphene oxide (GO) resistive memories offer the promise of low-cost environmentally sustainable fabrication, high mechanical flexibility and high optical transparency, making them ideally suited to future flexible and transparent electronics applications. However, the dimensional and temporal scalability of GO memories, i.e., how small they can be made and how fast they can be switched, is an area that has received scant attention. Moreover, a plethora of GO resistive switching characteristics and mechanisms has been reported in the literature, sometimes leading to a confusing and conflicting picture. Consequently, the potential for graphene oxide to deliver high-performance memories operating on nanometer length and nanosecond time scales is currently unknown. Here we address such shortcomings, presenting not only the smallest (50 nm), fastest (sub-5 ns), thinnest (8 nm) GO-based memory devices produced to date, but also demonstrate that our approach provides easily accessible multilevel (4-level, 2-bit per cell) storage capabilities along with excellent endurance and retention performance-all on both rigid and flexible substrates. Via comprehensive experimental characterizations backed-up by detailed atomistic simulations, we also show that the resistive switching mechanism in our Pt/GO/Ti/Pt devices is driven by redox reactions in the interfacial region between the top (Ti) electrode and the GO layer.
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Affiliation(s)
- V Karthik Nagareddy
- Centre for Graphene Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter , Harrison Building, North Park Road, Exeter EX4 4QF, U.K
| | - Matthew D Barnes
- Centre for Graphene Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter , Harrison Building, North Park Road, Exeter EX4 4QF, U.K
| | - Federico Zipoli
- IBM Research-Zurich , Säumerstrasse 4, 8803 Rüuschlikon, Switzerland
| | - Khue T Lai
- Centre for Graphene Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter , Harrison Building, North Park Road, Exeter EX4 4QF, U.K
| | - Arseny M Alexeev
- Centre for Graphene Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter , Harrison Building, North Park Road, Exeter EX4 4QF, U.K
| | - Monica Felicia Craciun
- Centre for Graphene Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter , Harrison Building, North Park Road, Exeter EX4 4QF, U.K
| | - C David Wright
- Centre for Graphene Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter , Harrison Building, North Park Road, Exeter EX4 4QF, U.K
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153
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Kim S, Choi B, Lim M, Yoon J, Lee J, Kim HD, Choi SJ. Pattern Recognition Using Carbon Nanotube Synaptic Transistors with an Adjustable Weight Update Protocol. ACS NANO 2017; 11:2814-2822. [PMID: 28221756 DOI: 10.1021/acsnano.6b07894] [Citation(s) in RCA: 116] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Recent electronic applications require an efficient computing system that can perform data processing with limited energy consumption. Inspired by the massive parallelism of the human brain, a neuromorphic system (hardware neural network) may provide an efficient computing unit to perform such tasks as classification and recognition. However, the implementation of synaptic devices (i.e., the essential building blocks for emulating the functions of biological synapses) remains challenging due to their uncontrollable weight update protocol and corresponding uncertain effects on the operation of the system, which can lead to a bottleneck in the continuous design and optimization. Here, we demonstrate a synaptic transistor based on highly purified, preseparated 99% semiconducting carbon nanotubes, which can provide adjustable weight update linearity and variation margin. The pattern recognition efficacy is validated using a device-to-system level simulation framework. The enlarged margin rather than the linear weight update can enhance the fault tolerance of the recognition system, which improves the recognition accuracy.
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Affiliation(s)
- Sungho Kim
- Department of Electrical Engineering, Sejong University , Seoul 05006, Korea
| | - Bongsik Choi
- School of Electrical Engineering, Kookmin University , Seoul 02707, Korea
| | - Meehyun Lim
- Mechatronics R&D Center, Samsung Electronics , Gyonggi-do 18448, Korea
| | - Jinsu Yoon
- School of Electrical Engineering, Kookmin University , Seoul 02707, Korea
| | - Juhee Lee
- School of Electrical Engineering, Kookmin University , Seoul 02707, Korea
| | - Hee-Dong Kim
- Department of Electrical Engineering, Sejong University , Seoul 05006, Korea
| | - Sung-Jin Choi
- School of Electrical Engineering, Kookmin University , Seoul 02707, Korea
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154
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Chiolerio A, Chiappalone M, Ariano P, Bocchini S. Coupling Resistive Switching Devices with Neurons: State of the Art and Perspectives. Front Neurosci 2017; 11:70. [PMID: 28261048 PMCID: PMC5309244 DOI: 10.3389/fnins.2017.00070] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Accepted: 01/31/2017] [Indexed: 11/13/2022] Open
Abstract
Here we provide the state-of-the-art of bioelectronic interfacing between biological neuronal systems and artificial components, focusing the attention on the potentiality offered by intrinsically neuromorphic synthetic devices based on Resistive Switching (RS). Neuromorphic engineering is outside the scopes of this Perspective. Instead, our focus is on those materials and devices featuring genuine physical effects that could be sought as non-linearity, plasticity, excitation, and extinction which could be directly and more naturally coupled with living biological systems. In view of important applications, such as prosthetics and future life augmentation, a cybernetic parallelism is traced, between biological and artificial systems. We will discuss how such intrinsic features could reduce the complexity of conditioning networks for a more natural direct connection between biological and synthetic worlds. Putting together living systems with RS devices could represent a feasible though innovative perspective for the future of bionics.
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Affiliation(s)
- Alessandro Chiolerio
- Center for Sustainable Future Technologies, Istituto Italiano di Tecnologia Torino, Italy
| | - Michela Chiappalone
- Neuroscience and Brain Technologies Department, Istituto Italiano di Tecnologia Genova, Italy
| | - Paolo Ariano
- Center for Sustainable Future Technologies, Istituto Italiano di Tecnologia Torino, Italy
| | - Sergio Bocchini
- Center for Sustainable Future Technologies, Istituto Italiano di Tecnologia Torino, Italy
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155
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Lee J, Lu WD, Kioupakis E. Electronic and optical properties of oxygen vacancies in amorphous Ta 2O 5 from first principles. NANOSCALE 2017; 9:1120-1127. [PMID: 28009928 DOI: 10.1039/c6nr07892c] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Oxygen vacancies are important defects considered to play a central role in the electronic and optical properties of tantalum pentoxide (Ta2O5) films and devices. Despite extensive experimental studies on oxygen vacancies in Ta2O5, the reported defect states are ambiguously identified due to the absence of accurate and conclusive theoretical evidence. Here we investigate the thermodynamic, electronic, and optical properties of oxygen vacancies in amorphous Ta2O5 by first-principles calculations based on hybrid-functional density functional theory (DFT). The calculated thermodynamic and optical transition levels are in good agreement with a broad range of diverse measured properties with various experimental methods, providing conclusive evidence for the identification of the defect states observed in experiments as originating from oxygen vacancies. Our calculations also predict the formation of spin-polarized polarons. Our results elucidate the fundamental atomistic properties of oxygen vacancies in various oxidation states as a function of growth conditions and provide guidance to control the properties of Ta2O5 films/devices.
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Affiliation(s)
- Jihang Lee
- Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109, USA. and Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109, USA.
| | - Wei D Lu
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109, USA.
| | - Emmanouil Kioupakis
- Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI 48109, USA.
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156
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Khiat A, Cortese S, Serb A, Prodromakis T. Resistive switching of Pt/TiO x /Pt devices fabricated on flexible Parylene-C substrates. NANOTECHNOLOGY 2017; 28:025303. [PMID: 27924782 DOI: 10.1088/1361-6528/28/2/025303] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Pt/TiO x /Pt resistive switching (RS) devices are considered to be amongst the most promising candidates in memristor family and the technology transfer to flexible substrates could open the way to new opportunities for flexible memory implementations. Hence, an important goal is to achieve a fully flexible RS memory technology. Nonetheless, several fabrication challenges are present and must be solved prior to achieving reliable device fabrication and good electronic performances. Here, we propose a fabrication method for the successful transfer of Pt/TiO x /Pt stack onto flexible Parylene-C substrates. The devices were electrically characterised, exhibiting both digital and analogue memory characteristics, which are obtained by proper adjustment of pulsing schemes during tests. This approach could open new application possibilities of these devices in neuromorphic computing, data processing, implantable sensors and bio-compatible neural interfaces.
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Affiliation(s)
- Ali Khiat
- Nanoelectronics and Nanotechnology Research Group, Department of Electronics and Computer Science, University of Southampton, University Road, SO17 1BJ, Southampton, UK. Southampton Nanofabrication Centre, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK
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157
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Zhu X, Du C, Jeong Y, Lu WD. Emulation of synaptic metaplasticity in memristors. NANOSCALE 2017; 9:45-51. [PMID: 27906389 DOI: 10.1039/c6nr08024c] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Recent studies have shown that nanoionic-based memristors can offer rich internal dynamics during ion movement that enables these solid-state devices to emulate various synaptic functions in biological systems naturally. The experimental observations can be explained within the 2nd-order memristor theoretical framework, which states that the device conductance (weight) can be determined by multiple internal state variables that can be modulated at different time scales and lead to different activity-dependent synaptic behaviors. Here, we show experimentally that not only the synaptic weight, but also synaptic plasticity (i.e. polarity and the rate of weight change) depends on the history of the input activities. This "plasticity of plasticity" resembles metaplasticity effects observed in biological systems, which have been found to facilitate neuron competition and stability. Specifically, we show that the memristor device may exhibit the same apparent weight (conductance) after experiencing different history of activities, but when subjected to additional, identical stimulation conditions, the device will however exhibit very different responses including the polarity and rate of weight (conductance) change. These findings serve to further our knowledge of fundamental physical mechanisms in memristors, and help advance adaptive artificial neuromorphic systems based on these emerging devices.
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Affiliation(s)
- Xiaojian Zhu
- Department of Electrical Engineering and Computer Science, the University of Michigan, Ann Arbor, Michigan 48109, USA.
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158
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Li J, Duan Q, Zhang T, Yin M, Sun X, Cai Y, Li L, Yang Y, Huang R. Tuning analog resistive switching and plasticity in bilayer transition metal oxide based memristive synapses. RSC Adv 2017. [DOI: 10.1039/c7ra07522g] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The existence of rich suboxide phases is favorable for increasing the number of weight states in transition metal oxide synapses.
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Affiliation(s)
- Jingxian Li
- Key Laboratory of Microelectronic Devices and Circuits (MOE)
- Institute of Microelectronics
- Peking University
- Beijing 100871
- China
| | - Qingxi Duan
- Key Laboratory of Microelectronic Devices and Circuits (MOE)
- Institute of Microelectronics
- Peking University
- Beijing 100871
- China
| | - Teng Zhang
- Key Laboratory of Microelectronic Devices and Circuits (MOE)
- Institute of Microelectronics
- Peking University
- Beijing 100871
- China
| | - Minghui Yin
- Key Laboratory of Microelectronic Devices and Circuits (MOE)
- Institute of Microelectronics
- Peking University
- Beijing 100871
- China
| | - Xinhao Sun
- Key Laboratory of Microelectronic Devices and Circuits (MOE)
- Institute of Microelectronics
- Peking University
- Beijing 100871
- China
| | - Yimao Cai
- Key Laboratory of Microelectronic Devices and Circuits (MOE)
- Institute of Microelectronics
- Peking University
- Beijing 100871
- China
| | - Lidong Li
- State Key Lab for Advanced Metals and Materials
- School of Materials Science and Engineering
- University of Science and Technology Beijing
- Beijing 100083
- China
| | - Yuchao Yang
- Key Laboratory of Microelectronic Devices and Circuits (MOE)
- Institute of Microelectronics
- Peking University
- Beijing 100871
- China
| | - Ru Huang
- Key Laboratory of Microelectronic Devices and Circuits (MOE)
- Institute of Microelectronics
- Peking University
- Beijing 100871
- China
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159
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Wang Z, Joshi S, Savel'ev SE, Jiang H, Midya R, Lin P, Hu M, Ge N, Strachan JP, Li Z, Wu Q, Barnell M, Li GL, Xin HL, Williams RS, Xia Q, Yang JJ. Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing. NATURE MATERIALS 2017; 16:101-108. [PMID: 27669052 DOI: 10.1038/nmat4756] [Citation(s) in RCA: 614] [Impact Index Per Article: 87.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Accepted: 08/17/2016] [Indexed: 05/20/2023]
Abstract
The accumulation and extrusion of Ca2+ in the pre- and postsynaptic compartments play a critical role in initiating plastic changes in biological synapses. To emulate this fundamental process in electronic devices, we developed diffusive Ag-in-oxide memristors with a temporal response during and after stimulation similar to that of the synaptic Ca2+ dynamics. In situ high-resolution transmission electron microscopy and nanoparticle dynamics simulations both demonstrate that Ag atoms disperse under electrical bias and regroup spontaneously under zero bias because of interfacial energy minimization, closely resembling synaptic influx and extrusion of Ca2+, respectively. The diffusive memristor and its dynamics enable a direct emulation of both short- and long-term plasticity of biological synapses, representing an advance in hardware implementation of neuromorphic functionalities.
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Affiliation(s)
- Zhongrui Wang
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, Massachusetts 01003, USA
| | - Saumil Joshi
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, Massachusetts 01003, USA
| | - Sergey E Savel'ev
- Department of Physics, Loughborough University, Loughborough LE11 3TU, UK
| | - Hao Jiang
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, Massachusetts 01003, USA
| | - Rivu Midya
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, Massachusetts 01003, USA
| | - Peng Lin
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, Massachusetts 01003, USA
| | - Miao Hu
- Hewlett Packard Labs, Palo Alto, California 94304, USA
| | - Ning Ge
- Hewlett Packard Labs, Palo Alto, California 94304, USA
| | | | - Zhiyong Li
- Hewlett Packard Labs, Palo Alto, California 94304, USA
| | - Qing Wu
- Air Force Research Lab, Information Directorate, Rome, New York 13441, USA
| | - Mark Barnell
- Air Force Research Lab, Information Directorate, Rome, New York 13441, USA
| | - Geng-Lin Li
- Biology Department, University of Massachusetts, Amherst, Massachusetts 01003, USA
| | - Huolin L Xin
- Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, New York 11973, USA
| | | | - Qiangfei Xia
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, Massachusetts 01003, USA
| | - J Joshua Yang
- Department of Electrical and Computer Engineering, University of Massachusetts, Amherst, Massachusetts 01003, USA
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160
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Campbell KA, Drake KT, Barney Smith EH. Pulse Shape and Timing Dependence on the Spike-Timing Dependent Plasticity Response of Ion-Conducting Memristors as Synapses. Front Bioeng Biotechnol 2016; 4:97. [PMID: 28083531 PMCID: PMC5183647 DOI: 10.3389/fbioe.2016.00097] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Accepted: 12/14/2016] [Indexed: 11/13/2022] Open
Abstract
Ion-conducting memristors comprised of the layered materials Ge2Se3/SnSe/Ag are promising candidates for neuromorphic computing applications. Here, the spike-timing dependent plasticity (STDP) application is demonstrated for the first time with a single memristor type operating as a synapse over a timescale of 10 orders of magnitude, from nanoseconds through seconds. This large dynamic range allows the memristors to be useful in applications that require slow biological times, as well as fast times such as needed in neuromorphic computing, thus allowing multiple functions in one design for one memristor type-a "one size fits all" approach. This work also investigated the effects of varying the spike pulse shapes on the STDP response of the memristors. These results showed that small changes in the pre- and postsynaptic pulse shape can have a significant impact on the STDP. These results may provide circuit designers with insights into how pulse shape affects the actual memristor STDP response and aid them in the design of neuromorphic circuits and systems that can take advantage of certain features in the memristor STDP response that are programmable via the pre- and postsynaptic pulse shapes. In addition, the energy requirement per memristor is approximated based on the pulse shape and timing responses. The energy requirement estimated per memristor operating on slower biological timescales (milliseconds to seconds) is larger (nanojoules range), as expected, than the faster (nanoseconds) operating times (~0.1 pJ in some cases). Lastly, the memristors responded in a similar manner under normal STDP conditions (pre- and post-spikes applied to opposite memristor terminals) as they did to the case where a waveform corresponding to the difference between pre- and post-spikes was applied to only one electrode, with the other electrode held at ground potential. By applying the difference signal to only one terminal, testing of the memristor in various applications can be achieved with a simplified test set-up, and thus be easier to accomplish in most laboratories.
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Affiliation(s)
- Kristy A. Campbell
- Department of Electrical and Computer Engineering, Boise State University, Boise, ID, USA
| | - Kolton T. Drake
- Department of Electrical and Computer Engineering, Boise State University, Boise, ID, USA
| | - Elisa H. Barney Smith
- Department of Electrical and Computer Engineering, Boise State University, Boise, ID, USA
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161
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La Barbera S, Vincent AF, Vuillaume D, Querlioz D, Alibart F. Interplay of multiple synaptic plasticity features in filamentary memristive devices for neuromorphic computing. Sci Rep 2016; 6:39216. [PMID: 27982093 PMCID: PMC5159796 DOI: 10.1038/srep39216] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 11/21/2016] [Indexed: 11/29/2022] Open
Abstract
Bio-inspired computing represents today a major challenge at different levels ranging from material science for the design of innovative devices and circuits to computer science for the understanding of the key features required for processing of natural data. In this paper, we propose a detail analysis of resistive switching dynamics in electrochemical metallization cells for synaptic plasticity implementation. We show how filament stability associated to joule effect during switching can be used to emulate key synaptic features such as short term to long term plasticity transition and spike timing dependent plasticity. Furthermore, an interplay between these different synaptic features is demonstrated for object motion detection in a spike-based neuromorphic circuit. System level simulation presents robust learning and promising synaptic operation paving the way to complex bio-inspired computing systems composed of innovative memory devices.
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Affiliation(s)
- Selina La Barbera
- Institut of Electronic, Microelectronic and Nanoelectronic, CNRS, boulevard Poincarré CS 60069, 59652 Villeneuve d’Ascq, France
| | - Adrien F. Vincent
- Centre de Nanosciences et de Nanotechnologies, CNRS, Univ. Paris-Sud, Université Paris-Saclay, C2N - Orsay, 91405 Orsay cedex, France
| | - Dominique Vuillaume
- Institut of Electronic, Microelectronic and Nanoelectronic, CNRS, boulevard Poincarré CS 60069, 59652 Villeneuve d’Ascq, France
| | - Damien Querlioz
- Centre de Nanosciences et de Nanotechnologies, CNRS, Univ. Paris-Sud, Université Paris-Saclay, C2N - Orsay, 91405 Orsay cedex, France
| | - Fabien Alibart
- Institut of Electronic, Microelectronic and Nanoelectronic, CNRS, boulevard Poincarré CS 60069, 59652 Villeneuve d’Ascq, France
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162
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Nili H, Ahmed T, Walia S, Ramanathan R, Kandjani AE, Rubanov S, Kim J, Kavehei O, Bansal V, Bhaskaran M, Sriram S. Microstructure and dynamics of vacancy-induced nanofilamentary switching network in donor doped SrTiO 3-x memristors. NANOTECHNOLOGY 2016; 27:505210. [PMID: 27861164 DOI: 10.1088/0957-4484/27/50/505210] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Donor doping of perovskite oxides has emerged as an attractive technique to create high performance and low energy non-volatile analog memories. Here, we examine the origins of improved switching performance and stable multi-state resistive switching in Nb-doped oxygen-deficient amorphous SrTiO3 (Nb:a-STO x ) metal-insulator-metal (MIM) devices. We probe the impact of substitutional dopants (i.e., Nb) in modulating the electronic structure and subsequent switching performance. Temperature stability and bias/time dependence of the switching behavior are used to ascertain the role of substitutional dopants and highlight their utility to modulate volatile and non-volatile behavior in a-STO x devices for adaptive and neuromorphic applications. We utilized a combination of transmission electron microscopy, photoluminescence emission properties, interfacial compositional evaluation, and activation energy measurements to investigate the microstructure of the nanofilamentary network responsible for switching. These results provide important insights into understanding mechanisms that govern the performance of donor-doped perovskite oxide-based memristive devices.
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Affiliation(s)
- Hussein Nili
- Functional Materials and Microsystems Research Group and Micro Nano Research Facility, RMIT University, VIC 3001, Australia
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163
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Yang X, Fang Y, Yu Z, Wang Z, Zhang T, Yin M, Lin M, Yang Y, Cai Y, Huang R. Nonassociative learning implementation by a single memristor-based multi-terminal synaptic device. NANOSCALE 2016; 8:18897-18904. [PMID: 27714050 DOI: 10.1039/c6nr04142f] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Animals' survival is dependent on their abilities to adapt to the changing environment by adjusting their behaviours, which is related to the ubiquitous learning behaviour, nonassociative learning. Thus mimicking the indispensable learning behaviour in organisms based on electronic devices is vital to better achieve artificial neural networks and neuromorphic computing. Here a three terminal device consisting of an oxide-based memristor and a NMOS transistor is proposed. The memristor with gradual conductance tuning inherently functions as the synapse between sensor neurons and motor neurons and presents adjustable synaptic plasticity, while the NMOS transistor attached to the memristor is utilized to mimic the modulatory effect of the neuromodulator released by inter neurons. Such a memristor-based multi-terminal device allows the practical implementation of significant nonassociative learning based on a single electronic device. In this study, the experience-induced modification behaviour, both habituation and sensitization, was successfully achieved. The dependence of the nonassociative behavioural response on the strength and interval of presented stimuli was also discussed. The implementation of nonassociative learning offers feasible and experimental advantages for further study on neuromorphic systems based on electronic devices.
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Affiliation(s)
- Xue Yang
- Institute of Microelectronics, Peking University, 100871, Beijing, China
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164
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Effect of surfactants on the data directionality and learning behaviour of Al/TiO2/FTO thin film memristor-based electronic synapse. J Solid State Electrochem 2016. [DOI: 10.1007/s10008-016-3459-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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165
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Vassanelli S, Mahmud M. Trends and Challenges in Neuroengineering: Toward "Intelligent" Neuroprostheses through Brain-"Brain Inspired Systems" Communication. Front Neurosci 2016; 10:438. [PMID: 27721741 PMCID: PMC5034009 DOI: 10.3389/fnins.2016.00438] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Accepted: 09/09/2016] [Indexed: 11/30/2022] Open
Abstract
Future technologies aiming at restoring and enhancing organs function will intimately rely on near-physiological and energy-efficient communication between living and artificial biomimetic systems. Interfacing brain-inspired devices with the real brain is at the forefront of such emerging field, with the term "neurobiohybrids" indicating all those systems where such interaction is established. We argue that achieving a "high-level" communication and functional synergy between natural and artificial neuronal networks in vivo, will allow the development of a heterogeneous world of neurobiohybrids, which will include "living robots" but will also embrace "intelligent" neuroprostheses for augmentation of brain function. The societal and economical impact of intelligent neuroprostheses is likely to be potentially strong, as they will offer novel therapeutic perspectives for a number of diseases, and going beyond classical pharmaceutical schemes. However, they will unavoidably raise fundamental ethical questions on the intermingling between man and machine and more specifically, on how deeply it should be allowed that brain processing is affected by implanted "intelligent" artificial systems. Following this perspective, we provide the reader with insights on ongoing developments and trends in the field of neurobiohybrids. We address the topic also from a "community building" perspective, showing through a quantitative bibliographic analysis, how scientists working on the engineering of brain-inspired devices and brain-machine interfaces are increasing their interactions. We foresee that such trend preludes to a formidable technological and scientific revolution in brain-machine communication and to the opening of new avenues for restoring or even augmenting brain function for therapeutic purposes.
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Affiliation(s)
- Stefano Vassanelli
- NeuroChip Laboratory, Department of Biomedical Sciences, University of PadovaPadova, Italy
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166
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Zhang R, Pang W, Zhang Q, Chen Y, Chen X, Feng Z, Yang J, Zhang D. Enhanced non-volatile resistive switching in suspended single-crystalline ZnO nanowire with controllable multiple states. NANOTECHNOLOGY 2016; 27:315203. [PMID: 27346884 DOI: 10.1088/0957-4484/27/31/315203] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Resistive switching nanostructures are a promising candidate for next-generation non-volatile memories. In this report, we investigate the switching behaviors of single-crystalline ZnO nanowires suspended in air. They exhibit significantly higher current density, lower switching voltage, and more pronounced multiple conductance states compared to nanowires in direct contact with substrate. We attribute the effect to enhanced Joule heating efficiency, reduced surface scattering, and more significantly, the positive feedback established between the current density and local temperature in the suspended nanowires. The proposed mechanism has been quantitatively examined by finite element simulations. We have also demonstrated an innovative approach to initiating the current-temperature mutual enhancement through illumination by ultraviolet light, which further confirmed our hypothesis and enabled even greater enhancement. Our work provides further insight into the resistive switching mechanism of single-crystalline one-dimensional nanostructures, and suggests an effective means of performance enhancement and device optimization.
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Affiliation(s)
- Rui Zhang
- State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, People's Republic of China
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167
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Li X, Wu H, Wu W, Wu D, Deng N, Cai J, Qian H. Electrode-induced digital-to-analog resistive switching in TaO x -based RRAM devices. NANOTECHNOLOGY 2016; 27:305201. [PMID: 27302281 DOI: 10.1088/0957-4484/27/30/305201] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
In RRAM devices, electrodes play a significant role during the switching process. In this paper, different top electrodes are used for TaO y /Ta2O5-x /AlO σ triple-oxide-layer devices. Top electrode-induced digital resistive switching to analog resistive switching was observed. For Pt top electrode (TE) devices, abrupt digital resistive switching behavior was observed, while Al TE devices showed gradual analog resistive switching behavior. Devices with various AlO σ thicknesses and sizes were fabricated and characterized to evaluate the reliability of the analog resistive switching. The physical mechanisms responsible for this electrode-induced resistive switching behavior were discussed.
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Affiliation(s)
- Xinyi Li
- Institute of Microelectronics, Tsinghua University, Beijing 100084, People's Republic of China
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168
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Tian H, Guo Q, Xie Y, Zhao H, Li C, Cha JJ, Xia F, Wang H. Anisotropic Black Phosphorus Synaptic Device for Neuromorphic Applications. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2016; 28:4991-7. [PMID: 27119423 DOI: 10.1002/adma.201600166] [Citation(s) in RCA: 116] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Revised: 02/21/2016] [Indexed: 05/08/2023]
Abstract
The first black-phosphorus synaptic device is demonstrated, which offers intrinsic anisotropy in its synaptic characteristics directly resulting from its low crystalline symmetry. Key features of biological synapses, such as long-term plasticity with heterogeneity, including long-term potentiation/depression and spike-timing-dependent plasticity, are mimicked. This demonstration represents an important step toward introducing intrinsic heterogeneity to artificial neuromorphic systems.
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Affiliation(s)
- He Tian
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Qiushi Guo
- Department of Electrical Engineering, Yale University, New Haven, Connecticut, CT, 06511, USA
| | - Yujun Xie
- Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut, CT, 06511, USA
| | - Huan Zhao
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
| | - Cheng Li
- Department of Electrical Engineering, Yale University, New Haven, Connecticut, CT, 06511, USA
| | - Judy J Cha
- Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut, CT, 06511, USA
| | - Fengnian Xia
- Department of Electrical Engineering, Yale University, New Haven, Connecticut, CT, 06511, USA
| | - Han Wang
- Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089, USA
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169
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Kim S, Kim HD, Choi SJ. Compact Two-State-Variable Second-Order Memristor Model. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2016; 12:3320-3326. [PMID: 27152649 DOI: 10.1002/smll.201600088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Revised: 03/31/2016] [Indexed: 06/05/2023]
Abstract
A key requirement for using memristors in functional circuits is a predictive physical model to capture the resistive switching behavior, which shall be compact enough to be implemented using a circuit simulator. Although a number of memristor models have been developed, most of these models (i.e., first-order memristor models) have utilized only a one-state-variable. However, such simplification is not adequate for accurate modeling because multiple mechanisms are involved in resistive switching. Here, a two-state-variable based second-order memristor model is presented, which considers the axial drift of the charged vacancies in an applied electric field and the radial vacancy motion caused by the thermophoresis and diffusion. In particular, this model emulates the details of the intrinsic short-term dynamics, such as decay and temporal heat summation, and therefore, it accurately predicts the resistive switching characteristics for both DC and AC input signals.
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Affiliation(s)
- Sungho Kim
- Department of Electrical Engineering, Sejong University, Seoul, 05006, South Korea
| | - Hee-Dong Kim
- Department of Electrical Engineering, Sejong University, Seoul, 05006, South Korea
| | - Sung-Jin Choi
- School of Electrical Engineering, Kookmin University, Seoul, 02707, South Korea
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170
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Wang C, He W, Tong Y, Zhao R. Investigation and Manipulation of Different Analog Behaviors of Memristor as Electronic Synapse for Neuromorphic Applications. Sci Rep 2016; 6:22970. [PMID: 26971394 PMCID: PMC4789640 DOI: 10.1038/srep22970] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Accepted: 02/22/2016] [Indexed: 11/30/2022] Open
Abstract
Low-power and high-density electronic synapse is an important building block of brain-inspired systems. The recent advancement in memristor has provided an opportunity to advance electronic synapse design. However, a guideline on designing and manipulating the memristor’s analog behaviors is still lacking. In this work, we reveal that compliance current (Icomp) of electroforming process played an important role in realizing a stable analog behavior, which is attributed to the generation of conical-type conductive filament. A proper Icomp could result in a large conductance window, good stability, and low voltage analog switching. We further reveal that different pulse conditions can lead to three analog behaviors, where the conductance changes in monotonic increase, plateau after initial jump, and impulse-like shape, respectively. These behaviors could benefit the design of electronic synapse with enriched learning capabilities. This work will provide a useful guideline for designing and manipulating memristor as electronic synapses for brain-inspired systems.
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Affiliation(s)
- Changhong Wang
- Engineering Product Development Singapore University of Technology and Design 8 Somapah Road, Singapore 487372
| | - Wei He
- Engineering Product Development Singapore University of Technology and Design 8 Somapah Road, Singapore 487372
| | - Yi Tong
- Engineering Product Development Singapore University of Technology and Design 8 Somapah Road, Singapore 487372
| | - Rong Zhao
- Engineering Product Development Singapore University of Technology and Design 8 Somapah Road, Singapore 487372
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171
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Li H, Jiang H, Hu C. Existence and global exponential stability of periodic solution of memristor-based BAM neural networks with time-varying delays. Neural Netw 2016; 75:97-109. [DOI: 10.1016/j.neunet.2015.12.006] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Revised: 10/02/2015] [Accepted: 12/11/2015] [Indexed: 11/30/2022]
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172
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Simulation of synaptic short-term plasticity using Ba(CF3SO3)2-doped polyethylene oxide electrolyte film. Sci Rep 2016; 6:18915. [PMID: 26739613 PMCID: PMC4703968 DOI: 10.1038/srep18915] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2015] [Accepted: 11/30/2015] [Indexed: 11/08/2022] Open
Abstract
The simulation of synaptic plasticity using new materials is critical in the study of brain-inspired computing. Devices composed of Ba(CF3SO3)2-doped polyethylene oxide (PEO) electrolyte film were fabricated and with pulse responses found to resemble the synaptic short-term plasticity (STP) of both short-term depression (STD) and short-term facilitation (STF) synapses. The values of the charge and discharge peaks of the pulse responses did not vary with input number when the pulse frequency was sufficiently low(~1 Hz). However, when the frequency was increased, the charge and discharge peaks decreased and increased, respectively, in gradual trends and approached stable values with respect to the input number. These stable values varied with the input frequency, which resulted in the depressed and potentiated weight modifications of the charge and discharge peaks, respectively. These electrical properties simulated the high and low band-pass filtering effects of STD and STF, respectively. The simulations were consistent with biological results and the corresponding biological parameters were successfully extracted. The study verified the feasibility of using organic electrolytes to mimic STP.
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173
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Yang Y, Chen B, Lu WD. Memristive Physically Evolving Networks Enabling the Emulation of Heterosynaptic Plasticity. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2015; 27:7720-7. [PMID: 26484746 DOI: 10.1002/adma.201503202] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Revised: 08/11/2015] [Indexed: 05/26/2023]
Abstract
A nanoscale, solid-state physically evolving network is experimentally demonstrated, based on the self-organization of Ag nanoclusters under an electric field. The adaptive nature of the network is determined by the collective inputs from multiple terminals and allows the emulation of heterosynaptic plasticity, an important learning rule in biological systems. These effects are universally observed in devices based on different switching materials.
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Affiliation(s)
- Yuchao Yang
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Bing Chen
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Wei D Lu
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109, USA
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174
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Dong WS, Zeng F, Lu SH, Liu A, Li XJ, Pan F. Frequency-dependent learning achieved using semiconducting polymer/electrolyte composite cells. NANOSCALE 2015; 7:16880-16889. [PMID: 26412715 DOI: 10.1039/c5nr02891d] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Frequency-dependent learning has been achieved using semiconducting polymer/electrolyte composite cells. The cells composed of polymer/electrolyte double layers realized the conventional spike-rate-dependent plasticity (SRDP) learning model. These cells responded to depression upon low-frequency stimulation and to potentiation upon high-frequency stimulation and presented long-term memory. The transition threshold θm from depression to potentiation varied depending on the previous stimulations. A nanostructure resembling a bio-synapse in its transport passages was demonstrated and a random channel model was proposed to describe the ionic kinetics at the polymer/electrolyte interface during and after stimulations with various frequencies, accounting for the observed SRDP.
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Affiliation(s)
- W S Dong
- Laboratory of Advanced Materials (MOE), School of Materials Science and Engineering, Tsinghua University, Beijing 100084, People's Republic of China.
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175
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Dong WS, Zeng F, Lu SH, Li XJ, Chang CT, Liu A, Pan F, Guo D. Effect of heavy-ion on frequency selectivity of semiconducting polymer/electrolyte heterojunction. RSC Adv 2015. [DOI: 10.1039/c5ra19938g] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Long-term bidirectional frequency selectivity has been achieved in MEH-PPV/PEO–Nd3+cells, which suggests spike-rate-dependent plasticity learning protocol. It depends on pulse shape due to variation of ionic type.
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Affiliation(s)
- W. S. Dong
- Key Laboratory of Advanced Materials (MOE)
- School of Materials Science and Engineering
- Tsinghua University
- Beijing
- China
| | - F. Zeng
- Key Laboratory of Advanced Materials (MOE)
- School of Materials Science and Engineering
- Tsinghua University
- Beijing
- China
| | - S. H. Lu
- Key Laboratory of Advanced Materials (MOE)
- School of Materials Science and Engineering
- Tsinghua University
- Beijing
- China
| | - X. J. Li
- Key Laboratory of Advanced Materials (MOE)
- School of Materials Science and Engineering
- Tsinghua University
- Beijing
- China
| | - C. T. Chang
- Key Laboratory of Advanced Materials (MOE)
- School of Materials Science and Engineering
- Tsinghua University
- Beijing
- China
| | - A. Liu
- Key Laboratory of Advanced Materials (MOE)
- School of Materials Science and Engineering
- Tsinghua University
- Beijing
- China
| | - F. Pan
- Key Laboratory of Advanced Materials (MOE)
- School of Materials Science and Engineering
- Tsinghua University
- Beijing
- China
| | - D. Guo
- School of Materials Science & Engineering
- Beihang University
- China
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