Ultra‐Low Power Consumption Artificial Photoelectric Synapses Based on Lewis Acid Doped WSe 2 for Neuromorphic Computing
Year: 2024
Type: article
Abstract: Capitalizing on the extensive spectral capacity and minimal crosstalk properties inherent in optical signals, photoelectric synapses are poised to assume a pivotal stance in the realm of neuromorphic computation. Herein, a photoelectric synapse based on Lewis acid‐doped semiconducting tungsten diselenide (WSe 2 ) is introduced, exhibiting tunable short‐term and long‐term plasticity. The device consumes a mere 0.1 fJ per synaptic operation, which is lower than the energy required by a single synaptic event observed in the human brain. Furthermore, these devices demonstrate high‐pass filtering capabilities, highlighting their potential in image‐sharpening applications. In particular, by synergistically modulating the photoconductivity and electrical gate bias, versatile logic capabilities are demonstrated within a single device, enabling it to flexibly perform both Boolean AND and OR gate operations. This work demonstrates a viable approach for Lewis acid‐treated TMDs to realize multifunctional photoelectric synapses for neuromorphic computing.
Source: Small
Authors: Mingjun Ma, Chaoning Huang, Mingyu Yang, Dong He, Yongfeng Pei, Yufan Kang, Wenqing Li, Cheng Lei, Xiangheng Xiao
Institution: Wuhan University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4403658463
