Adaptive Synaptic Memory via Lithium Ion Modulation in RRAM Devices. Issue 42 (29th September 2020)

• Record Type: Journal Article
• Authors: 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.
• Is Part Of: Small. Volume 16:Issue 42(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-29
• Subjects: lithium -- neuromorphic computing -- paired pulse facilitation (PPF) -- resistive random access memory (RRAM) -- spike‐timing‐dependent plasticity (STDP) -- synaptic plasticity; Nanotechnology -- Periodicals; Nanoparticles -- Periodicals; Microtechnology -- Periodicals; 620.5
• DOI: 10.1002/smll.202003964
• Languages: English
• ISSNs: 1613-6810

Abstract

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. Abstract : In this study, lithium‐doped silicate resistive random access memory with a titanium nitride (TiN) electrode is shown to mimic biological synapses. The TiN electrode effectively stores lithium ions, a principle widely adopted from battery construction, and enables reliable state‐dependent decay. This device offers multi‐bit functionality and synaptic plasticity, short‐term memory and long‐term memory, spike‐timing‐dependent plasticity and paired‐pulse facilitation.