{"title":"CuInP2S6 Heterojunction Based Visible Range Optoelectronic Synapse With Femtojoule Energy Consumption","authors":"Zichen Wang, Jialin Li, Xinyi Fan, Wei Tang, Huanfeng Zhu, Linjun Li","doi":"10.1002/admt.202401589","DOIUrl":null,"url":null,"abstract":"<p>The 2D van der Waals material CuInP<sub>2</sub>S<sub>6</sub>, characterized by its memory behavior arising from room-temperature ferroelectricity and Cu<sup>+</sup> ions migration, has emerged as a promising candidate material for artificial synaptic devices. Nevertheless, with a bandgap of 2.7 eV, CIPS-based devices are generally limited to operating in pure electrical mode or under ultraviolet light, making them unsuitable for applications across the entire visible light spectrum. Here, a two-terminal artificial synapse based on CIPS/MoS<sub>2</sub>/graphene heterojunction is constructed. Compared to ion migration or ferroelectricity under high bias voltage, photogating due to charge trapping is identified as the working mechanism under low bias voltage (< 1.5 V), which can respond to the shortest pulse (∼5 ms) and least energy consumption of 1.7 / 6.3 fJ per pulse up to date for CIPS-based synapses. Benefiting from the fading memory effect and nonlinear characteristics in visible light range, handwritten digit recognition based on reservoir computing has achieved an accuracy of 90.43% with four times higher efficiency than directly using an artificial neuron network. This work thus paves the way for constructing CIPS heterostructure for artificial vision and neuromorphic computing systems.</p>","PeriodicalId":7292,"journal":{"name":"Advanced Materials Technologies","volume":"10 9","pages":""},"PeriodicalIF":6.4000,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Materials Technologies","FirstCategoryId":"88","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/admt.202401589","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The 2D van der Waals material CuInP2S6, characterized by its memory behavior arising from room-temperature ferroelectricity and Cu+ ions migration, has emerged as a promising candidate material for artificial synaptic devices. Nevertheless, with a bandgap of 2.7 eV, CIPS-based devices are generally limited to operating in pure electrical mode or under ultraviolet light, making them unsuitable for applications across the entire visible light spectrum. Here, a two-terminal artificial synapse based on CIPS/MoS2/graphene heterojunction is constructed. Compared to ion migration or ferroelectricity under high bias voltage, photogating due to charge trapping is identified as the working mechanism under low bias voltage (< 1.5 V), which can respond to the shortest pulse (∼5 ms) and least energy consumption of 1.7 / 6.3 fJ per pulse up to date for CIPS-based synapses. Benefiting from the fading memory effect and nonlinear characteristics in visible light range, handwritten digit recognition based on reservoir computing has achieved an accuracy of 90.43% with four times higher efficiency than directly using an artificial neuron network. This work thus paves the way for constructing CIPS heterostructure for artificial vision and neuromorphic computing systems.
期刊介绍:
Advanced Materials Technologies Advanced Materials Technologies is the new home for all technology-related materials applications research, with particular focus on advanced device design, fabrication and integration, as well as new technologies based on novel materials. It bridges the gap between fundamental laboratory research and industry.