Yang Rong, De Yu, Xin Zhang, Tao Wang, Jie Wang, Yuheng Li, Tongpeng Zhao, Ruiqin He, Yuxin Gao, Can Huang, Shumin Xiao, Jingkai Qin, Sai Bai, Huihui Zhu, Ao Liu, Yimu Chen, Qinghai Song
{"title":"Perovskite Thin-Film Transistors for Ultra-Low-Voltage Neuromorphic Visions.","authors":"Yang Rong, De Yu, Xin Zhang, Tao Wang, Jie Wang, Yuheng Li, Tongpeng Zhao, Ruiqin He, Yuxin Gao, Can Huang, Shumin Xiao, Jingkai Qin, Sai Bai, Huihui Zhu, Ao Liu, Yimu Chen, Qinghai Song","doi":"10.1002/advs.202410015","DOIUrl":null,"url":null,"abstract":"<p><p>Perovskite thin-film transistors (TFTs) simultaneously possessing exceptional carrier transport capabilities, nonvolatile memory effects, and photosensitivity have recently attracted attention in fields of both complementary circuits and neuromorphic computing. Despite continuous performance improvements through additive and composition engineering of the channel materials, the equally crucial dielectric/channel interfaces of perovskite TFTs have remained underexplored. Here, it is demonstrated that engineering the dielectric/channel interface in 2D tin perovskite TFTs not only enhances the performance and operational stability for their utilization in complementary circuits but also enables efficient synaptic behaviors (optical information sensing and storage) under an extremely low operating voltage of -1 mV at the same time. The interface-engineered TFT arrays operating at -1 mV are then demonstrated as the preprocessing hardware for neuromorphic visions with pattern recognition accuracy of 92.2% and long-term memory capability. Such a low operating voltage provides operational feasibility to the design of large-scale-integrated and wearable/implantable neuromorphic hardware.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":null,"pages":null},"PeriodicalIF":14.3000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Science","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/advs.202410015","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Perovskite thin-film transistors (TFTs) simultaneously possessing exceptional carrier transport capabilities, nonvolatile memory effects, and photosensitivity have recently attracted attention in fields of both complementary circuits and neuromorphic computing. Despite continuous performance improvements through additive and composition engineering of the channel materials, the equally crucial dielectric/channel interfaces of perovskite TFTs have remained underexplored. Here, it is demonstrated that engineering the dielectric/channel interface in 2D tin perovskite TFTs not only enhances the performance and operational stability for their utilization in complementary circuits but also enables efficient synaptic behaviors (optical information sensing and storage) under an extremely low operating voltage of -1 mV at the same time. The interface-engineered TFT arrays operating at -1 mV are then demonstrated as the preprocessing hardware for neuromorphic visions with pattern recognition accuracy of 92.2% and long-term memory capability. Such a low operating voltage provides operational feasibility to the design of large-scale-integrated and wearable/implantable neuromorphic hardware.
期刊介绍:
Advanced Science is a prestigious open access journal that focuses on interdisciplinary research in materials science, physics, chemistry, medical and life sciences, and engineering. The journal aims to promote cutting-edge research by employing a rigorous and impartial review process. It is committed to presenting research articles with the highest quality production standards, ensuring maximum accessibility of top scientific findings. With its vibrant and innovative publication platform, Advanced Science seeks to revolutionize the dissemination and organization of scientific knowledge.