{"title":"Bio-Inspired P-type TeSeO<sub>x</sub> Synaptic Transistor Based on Multispectral Sensing for Neuromorphic Visual Multilevel Nociceptor.","authors":"Li Zhu, Sixian Li, Feng Zhang, Xiang Wan, Chee Leong Tan, Huabin Sun, Shancheng Yan, Yong Xu, Ao Liu, Zhihao Yu","doi":"10.1002/smtd.202401543","DOIUrl":null,"url":null,"abstract":"<p><p>The development of neuromorphic color vision has significant research implications in the fields of machine vision and artificial intelligence. By mimicking the processing mechanisms of energy-efficient biological visual systems, it offers a unique potential for real-time color environment perception and dynamic adaptability. This paper reports on a multispectral color sensing synaptic device based on a novel p-type TeSeO<sub>x</sub> transistor, applied to a neuromorphic visual multilevel nociceptor. Due to the intrinsic properties of TeSeO<sub>x</sub>, its narrow bandgap allows for multi-wavelength (405, 532, 655 nm) response, and its oxide semiconductor-based persistent photoconductivity converts optical signals into stored electrical signals, successfully emulating key synaptic characteristics such as excitatory postsynaptic current (EPSC), multi-pulse facilitation, and the transition from short-term to long-term memory. Additionally, it simulates learning, forgetting, and relearning behaviors, as well as image memory under tricolor light. Finally, using optical signals as a pain stimulus, the fundamental functions of a nociceptor are realized, including \"threshold,\" \"non-adaptation,\" \"relaxation,\" and \"nociceptive sensitization\". More importantly, by using tricolor light, multilevel pain perception is acheived. These results have the potential to advance fields such as autonomous driving, machine vision, and intelligent alert systems.</p>","PeriodicalId":229,"journal":{"name":"Small Methods","volume":" ","pages":"e2401543"},"PeriodicalIF":10.7000,"publicationDate":"2024-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Small Methods","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/smtd.202401543","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The development of neuromorphic color vision has significant research implications in the fields of machine vision and artificial intelligence. By mimicking the processing mechanisms of energy-efficient biological visual systems, it offers a unique potential for real-time color environment perception and dynamic adaptability. This paper reports on a multispectral color sensing synaptic device based on a novel p-type TeSeOx transistor, applied to a neuromorphic visual multilevel nociceptor. Due to the intrinsic properties of TeSeOx, its narrow bandgap allows for multi-wavelength (405, 532, 655 nm) response, and its oxide semiconductor-based persistent photoconductivity converts optical signals into stored electrical signals, successfully emulating key synaptic characteristics such as excitatory postsynaptic current (EPSC), multi-pulse facilitation, and the transition from short-term to long-term memory. Additionally, it simulates learning, forgetting, and relearning behaviors, as well as image memory under tricolor light. Finally, using optical signals as a pain stimulus, the fundamental functions of a nociceptor are realized, including "threshold," "non-adaptation," "relaxation," and "nociceptive sensitization". More importantly, by using tricolor light, multilevel pain perception is acheived. These results have the potential to advance fields such as autonomous driving, machine vision, and intelligent alert systems.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.