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All-in-one perovskite memristor with tunable photoresponsivity

  • Guan Hua Dun*
  • , Yuan Yuan Li
  • , Hai Nan Zhang
  • , Fan Wu
  • , Xi Chao Tan
  • , Ken Qin
  • , Yi Chu He
  • , Ze Shu Wang
  • , Yu Hao Wang
  • , Tian Lu
  • , Shi Wei Tian
  • , Dan Xie*
  • , Jia Li Peng
  • , Xiang Shun Geng
  • , Xiao Tong Zhao
  • , Jia He Zhang
  • , Yu Han Zhao
  • , Xiaoyu Wu*
  • , Ning Qin Deng
  • , Zheng Qiang Zhu
  • Yan Li, Xian Zhu Liu, Xing Wu, Weida Hu, Peng Zhou, Yang Chai, Mario Lanza, He Tian*, Yi Yang*, Tian Ling Ren*
*此作品的通讯作者
  • Tsinghua University
  • Xi'an Jiaotong University
  • National Institute of Metrology China
  • Beijing Institute of Aerospace Control Devices
  • China University of Mining & Technology, Beijing
  • Changchun University of Science and Technology
  • CAS - Shanghai Institute of Technical Physics
  • Fudan University
  • Hong Kong Polytechnic University
  • King Abdullah University of Science and Technology

科研成果: 期刊稿件文章同行评审

摘要

Photoelectric memristors have shown great potential for future machine visions, via integrating sensing, memory, and computing (namely “all-in-one”) functions in a single device. However, their hard-to-tune photoresponse behavior necessitates extra function modules for signal encoding and modality conversion, impeding such integration. Here, we report an all-in-one memristor with Cs2AgBiBr6 perovskite, where the Br vacancy doping-endowed tunable energy band enables tunable photoresponsivity (TPR) behavior. As a result, the memristor showed a large tunable ratio of 35.9 dB, while its photoresponsivity presented a maximum of 2.7 × 103 mA W−1 and a long-term memory behavior with over 104 s, making it suitable for realizing all-in-one processing tasks. By mapping the algorithm parameters onto the photoresponsivity, we successfully performed both recognition and processing tasks based on the TPR memristor array. Remarkably, compared with conventional complementary metal–oxide–semiconductor counterparts, our demonstrations provided comparable performance but had ~133-fold and ~299-fold reductions in energy consumption, respectively. Our work could facilitate the development of all-in-one smart devices for next-generation machine visions. (Figure presented.).

源语言英语
文章编号e12619
期刊InfoMat
7
3
DOI
出版状态已出版 - 3月 2025

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

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    可持续发展目标 7 经济适用的清洁能源

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