Two-Terminal Lithium-Mediated Artificial Synapses with Enhanced Weight Modulation for Feasible Hardware Neural Networks

Recently,artificial synapses involving an electrochemical reaction of Li-ion have been attributed to have remarkable synaptic properties.Three-terminal synaptic transistors utilizing Li-ion intercalation exhibits reliable synaptic characteristics by exploiting the advantage of nondistributed weight updates owing to stable ion migrations.However,the three-terminal configurations with large and complex structures impede the crossbar array implementation required for hardware neuromorphic systems.Meanwhile,achieving adequate synaptic performances through effective Li-ion intercalation in vertical two-terminal synaptic devices for array integration remains challenging.Here,two-terminal Au/LixCoO_(2)/Pt artificial synapses are proposed with the potential for practical implementation of hardware neural networks.The Au/LixCoO_(2)/Pt devices demonstrated extraordinary neuromorphic behaviors based on a progressive dearth of Li in LixCoO_(2)films.The intercalation and deintercalation of Li-ion inside the films are precisely controlled over the weight control spike,resulting in improved weight control functionality.Various types of synaptic plasticity were imitated and assessed in terms of key factors such as nonlinearity,symmetricity,and dynamic range.Notably,the LixCoO_(2)-based neuromorphic system outperformed three-terminal synaptic transistors in simulations of convolutional neural networks and multilayer perceptrons due to the high linearity and low programming error.These impressive performances suggest the vertical two-terminal Au/LixCoO_(2)/Pt artificial synapses as promising candidates for hardware neural networks.

Enabling dendrite-free charging for lithium batteries based on transport-reaction competition mechanism in CHAIN framework

Worldwide trends in mobile electrification will skyrocket demands for lithium-based battery production,driven by the popularity of electric vehicles.However,both lithium metal batteries and lithium ion batteries face severe safety issues due to dendrite nucleation and growth process.Li deposition is significantly influenced by interfacial factors and charging conditions.In this paper,an electrochemical model considering the internal and external factors is proposed based on Monte Carlo method.The influence of internal solid electrolyte interphase(SEI)porosity,thickness and the external conditions on dendrite growth process is systematically described.The simulation results support that the three factors investigated in this model could synergistically regulate the dendrite growth process.Three competition mechanisms are proposed to tailor lithium deposition for Li-based batteries and numerical solutions for variation pattern of dendrite growth with time are fitted.A three-step process describing kinetic process of lithium deposition is proposed.To achieve dendrite-free charging process,charging strategies and emerging materials design should be considered,including physicochemical materials engineering,artificial SEI,and design for dynamic safety boundary.This work could contribute to the foundation for insights of Li deposition mechanism,which is promising to provide guidelines for next-generation high-energy-density and safe batteries in CHAIN framework.