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Adaptive Synaptic Memory via Lithium Ion Modulation in RRAM Devices.
Lin, Chih-Yang; Chen, Jia; Chen, Po-Hsun; Chang, Ting-Chang; Wu, Yuting; Eshraghian, Jason K; Moon, John; Yoo, Sangmin; Wang, Yu-Hsun; Chen, Wen-Chung; Wang, Zhi-Yang; Huang, Hui-Chun; Li, Yi; Miao, Xiangshui; Lu, Wei D; Sze, Simon M.
Afiliação
  • Lin CY; Department of Physics, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan.
  • Chen J; Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information, Huazhong University of Science and Technology, No.1037 Luoyu Road, Wuhan, 430074, China.
  • Chen PH; Department of Applied Science, R.O.C. Naval Academy, No.669 Junxiao Road, Kaohsiung, 81345, Taiwan.
  • Chang TC; Center for Nanoscience and Nanotechnology, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan.
  • Wu Y; Department of Physics, The Center of Crystal Research, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan.
  • Eshraghian JK; Electrical Engineering and Computer Science, University of Michigan, No.1301 Beal Avenue, Ann Arbor, Michigan, 48109-2122, USA.
  • Moon J; Electrical Engineering and Computer Science, University of Michigan, No.1301 Beal Avenue, Ann Arbor, Michigan, 48109-2122, USA.
  • Yoo S; Electrical Engineering and Computer Science, University of Michigan, No.1301 Beal Avenue, Ann Arbor, Michigan, 48109-2122, USA.
  • Wang YH; Electrical Engineering and Computer Science, University of Michigan, No.1301 Beal Avenue, Ann Arbor, Michigan, 48109-2122, USA.
  • Chen WC; Department of Electronics Engineering and Institute of Electronics, National Chiao Tung University, No.1001 University Road, Hsinchu, 30010, Taiwan.
  • Wang ZY; Department of Materials and Optoelectronic Science, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan.
  • Huang HC; Department of Materials and Optoelectronic Science, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan.
  • Li Y; Department of Materials and Optoelectronic Science, National Sun Yat-sen University, No.70 Lien-hai Road, Kaohsiung, 80424, Taiwan.
  • Miao X; Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information, Huazhong University of Science and Technology, No.1037 Luoyu Road, Wuhan, 430074, China.
  • Lu WD; Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information, Huazhong University of Science and Technology, No.1037 Luoyu Road, Wuhan, 430074, China.
  • Sze SM; Electrical Engineering and Computer Science, University of Michigan, No.1301 Beal Avenue, Ann Arbor, Michigan, 48109-2122, USA.
Small ; 16(42): e2003964, 2020 10.
Article em En | MEDLINE | ID: mdl-32996256
ABSTRACT
Biologically plausible computing systems require fine-grain tuning of analog synaptic characteristics. In this study, lithium-doped silicate resistive random access memory with a titanium nitride (TiN) electrode mimicking biological synapses is demonstrated. Biological plausibility of this RRAM device is thought to occur due to the low ionization energy of lithium ions, which enables controllable forming and filamentary retraction spontaneously or under an applied voltage. The TiN electrode can effectively store lithium ions, a principle widely adopted from battery construction, and allows state-dependent decay to be reliably achieved. As a result, this device offers multi-bit functionality and synaptic plasticity for simulating various strengths in neuronal connections. Both short-term memory and long-term memory are emulated across dynamical timescales. Spike-timing-dependent plasticity and paired-pulse facilitation are also demonstrated. These mechanisms are capable of self-pruning to generate efficient neural networks. Time-dependent resistance decay is observed for different conductance values, which mimics both biological and artificial memory pruning and conforms to the trend of the biological brain that prunes weak synaptic connections. By faithfully emulating learning rules that exist in human's higher cortical areas from STDP to synaptic pruning, the device has the capacity to drive forward the development of highly efficient neuromorphic computing systems.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sinapses / Lítio Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sinapses / Lítio Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article