Flexible neuromorphic transistors for neuromorphic computing and perception application

doi:10.1007/s44275-024-00009-w

Moore and More ›› 2025, Vol. 1 ›› Issue (2): 147-170.DOI: 10.1007/s44275-024-00009-w

• REVIEWS • 上一篇

Flexible neuromorphic transistors for neuromorphic computing and perception application

Shuo Ke^1,2, Yixin Zhu^1,2, Chuanyu Fu^1,2, Huiwu Mao^1,2, Kailu Shi², Lesheng Qiao², Qing Wan¹

1. Yongjiang Laboratory, Ningbo, 315202, China;
2. School of Electronic Science & Engineering, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210023, China

收稿日期:2024-05-09 修回日期:2024-07-09 接受日期:2024-07-15 出版日期:2024-09-29 发布日期:2024-09-29
通讯作者: Qing Wan,E-mail:qing-wan@ylab.ac.cn
Shuo Ke is currently a Ph.D. candidate at the School of Electronic Science and Engineering, Nanjing University, Nanjing, China. His research interests include neuromorphic photoelectric transistors and applications.
Yixin Zhu received his master’s degree in Physics from Qingdao University in 2020. He is currently a Ph.D. candidate at the School of Electronic Science and Engineering, Nanjing University, Nanjing, China. His research interests include neuromorphic devices and applications.
Chuanyu Fu received his master’s degree in Physics from Qingdao University in 2020. He is currently a Ph.D. candidate at the School of Electronic Science and Engineering, Nanjing University, Nanjing, China. His research interests include neuromorphic photoelectronic devices and applications.
Huiwu Mao received his master’s degree in Engineering from Nanjing Tech University in 2020. He is currently a Ph.D. candidate at the School of Electronic Science and Engineering, Nanjing University, Nanjing, China. His research interests include artificial neuron devices and applications.
Kailu Shi received her bachelor’s degree in Engineering from Shandong University in 2021. She is currently a Ph.D. candidate at the School of Electronic Science and Engineering, Nanjing University, Nanjing, China. Her research interests include artificial neuron devices and applications.
Lesheng Qiao received his master’s degree in Engineering from Anhui University in 2022. He is currently a Ph.D. candidate at the School of Electronic Science and Engineering, Nanjing University, Nanjing, China. His research interests include neuromorphic devices and applications.
Qing Wan is the Director of the Yongjiang Laboratory Heterogeneous Integration Research Center. He obtained his undergraduate degree in the Department of Materials at Zhejiang University and earned a Ph.D. in Microelectronics from the Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences in 2004. After completing his Ph.D., he conducted postdoctoral and visiting professor research at the University of Cambridge, the University of Michigan, and Stanford University. Upon returning to China, he held positions at Hunan University, the Ningbo Institute of Materials Technology, Chinese Academy of Sciences, and Nanjing University. In 2014, he was supported by the National Science Foundation for Distinguished Young Scholars of China. Currently, his primary research activities are carried out at the Yongjiang Laboratory.
基金资助:
This study was supported by National Natural Science Foundation of China (Grant no. 62074075).

Flexible neuromorphic transistors for neuromorphic computing and perception application

Shuo Ke^1,2, Yixin Zhu^1,2, Chuanyu Fu^1,2, Huiwu Mao^1,2, Kailu Shi², Lesheng Qiao², Qing Wan¹

1. Yongjiang Laboratory, Ningbo, 315202, China;
2. School of Electronic Science & Engineering, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, 210023, China

Received:2024-05-09 Revised:2024-07-09 Accepted:2024-07-15 Online:2024-09-29 Published:2024-09-29
Contact: Qing Wan,E-mail:qing-wan@ylab.ac.cn
Supported by:
This study was supported by National Natural Science Foundation of China (Grant no. 62074075).

摘要/Abstract

摘要： Emulating brain functionality with neuromorphic devices is an emerging field of research. It is extensively considered as the first step to overcome the limitations of conventional von Neumann systems and build artificial intelligent systems. Currently, most neuromorphic transistors are manufactured on rigid substrates, which are difficult to bend and cannot closely fit soft human skin, limiting their appliction scope. The emergence and evolution of flexible electronic devices address a plethora of application and scenario demands. Particularly, the introduction of flexible neuromorphic transistors injects fresh vitality into neuromorphic computing and perception, symbolizing a significant step towards overcoming the limitations of conventional computational models and fostering the development of more intelligent wearable devices. Herein, the recent developments in felxible neuromorphic transistors are summarized and their applications in neuromorphic computing and artificial perception systems are highlighted. The future prospects and challenges of felxible neuromorphic transistors are also discussed. We believe developments in felxible neuromorphic transistors will shed light on future advances in wearable artificial intelligent systems, humanoid robotics and neural repair technology.

关键词: Neuromorphic device, Flexible neuromorphic transistor, Neuromorphic computing, Artificial perception system

Abstract: Emulating brain functionality with neuromorphic devices is an emerging field of research. It is extensively considered as the first step to overcome the limitations of conventional von Neumann systems and build artificial intelligent systems. Currently, most neuromorphic transistors are manufactured on rigid substrates, which are difficult to bend and cannot closely fit soft human skin, limiting their appliction scope. The emergence and evolution of flexible electronic devices address a plethora of application and scenario demands. Particularly, the introduction of flexible neuromorphic transistors injects fresh vitality into neuromorphic computing and perception, symbolizing a significant step towards overcoming the limitations of conventional computational models and fostering the development of more intelligent wearable devices. Herein, the recent developments in felxible neuromorphic transistors are summarized and their applications in neuromorphic computing and artificial perception systems are highlighted. The future prospects and challenges of felxible neuromorphic transistors are also discussed. We believe developments in felxible neuromorphic transistors will shed light on future advances in wearable artificial intelligent systems, humanoid robotics and neural repair technology.

Key words: Neuromorphic device, Flexible neuromorphic transistor, Neuromorphic computing, Artificial perception system

Shuo Ke, Yixin Zhu, Chuanyu Fu, Huiwu Mao, Kailu Shi, Lesheng Qiao, Qing Wan. Flexible neuromorphic transistors for neuromorphic computing and perception application[J]. Moore and More, 2025, 1(2): 147-170.

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Flexible neuromorphic transistors for neuromorphic computing and perception application

Flexible neuromorphic transistors for neuromorphic computing and perception application

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