journal article·2021-08

Grain‐Boundary Engineering of Monolayer MoS2 for Energy‐Efficient Lateral Synaptic Devices

Xuewen Wang, Bolun Wang, Qinghua Zhang, Yufei Sun, Enze Wang, Hao Luo, Yonghuang Wu, Lin Gu, Huanglong Li, Kai Liu

Advanced Materials· Volume 33· Issue 32
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Abstract

Abstract Synaptic devices based on 2D‐layered materials have emerged as high‐efficiency electronic synapses and neurons for neuromorphic computing. Lateral 2D synaptic devices have the advantages of multiple functionalities by responding to diverse stimuli, but they consume large amounts of energy, far more than the human brain. Moreover, current lateral devices employ several mechanisms based on conductive filaments and grain boundaries (GBs), but their formation is random and difficult to control, also hindering their practical applications. Here, four‐terminal, lateral synaptic devices with artificially engineered GBs are reported, which are made from monolayer MoS2. With lithography‐free, direct‐laser‐writing‐controlled MoS2/MoS2−xOδ GBs, such synaptic devices exhibit short‐term and long‐term plasticity characteristics that are responsive to electric and light stimulation simultaneously. This enables detailed simulations of biological learning and cognitive processes as well as image perception and processing. In particular, the device exhibits low energy consumption, similar to that of the human brain and much lower than those of other lateral 2D synaptic devices. This work provides an effective way to fabricate lateral synaptic devices for practical application development and sheds light on controllable electrical state switching for neuromorphic computing.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Transition Metal Oxide Nanomaterials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing 100084 China

Institute of Physics Chinese Academy of Sciences Beijing 100190 China

Department of Precision Instrument Center for Brain Inspired Computing Research Tsinghua University Beijing 100084 China

Funding

National Natural Science Foundation of China · National Basic Research Program of China

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