Emerging Iontronic Neural Devices for Neuromorphic Sensory Computing

被引:39
作者
Dai, Shilei [1 ,2 ,3 ]
Liu, Xu [2 ]
Liu, Youdi [4 ]
Xu, Yutong [2 ]
Zhang, Junyao [2 ]
Wu, Yue [2 ]
Cheng, Ping [5 ]
Xiong, Lize [1 ]
Huang, Jia [1 ,2 ]
机构
[1] Tongji Univ, Shanghai Peoples Hosp 4, Translat Res Inst Brain & Brain Like Intelligence, Shanghai Key Lab Anesthesiol & Brain Funct Modulat, Shanghai 200434, Peoples R China
[2] Tongji Univ, Interdisciplinary Mat Res Ctr, Sch Mat Sci & Engn, Shanghai 201804, Peoples R China
[3] Univ Hong Kong, Dept Elect & Elect Engn, Pokfulam, Hong Kong 999077, Peoples R China
[4] Penn State Univ, Dept Engn Sci & Mech, Univ Pk, State Coll, PA 16802 USA
[5] Univ Chicago, Pritzker Sch Mol Engn, Chicago, IL 60637 USA
基金
中国国家自然科学基金;
关键词
iontronics; neuromorphic computing; neuromorphic devices; neuromorphic sensing; ARTIFICIAL SYNAPSE; OXIDE MEMRISTORS; PHOTO-SYNAPSES; MEMORY ARRAY; TRANSISTORS; PLASTICITY; PEROVSKITE; NETWORK; NEURONS; VOLTAGE;
D O I
10.1002/adma.202300329
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Living organisms have a very mysterious and powerful sensory computing system based on ion activity. Interestingly, studies on iontronic devices in the past few years have proposed a promising platform for simulating the sensing and computing functions of living organisms, because: 1) iontronic devices can generate, store, and transmit a variety of signals by adjusting the concentration and spatiotemporal distribution of ions, which analogs to how the brain performs intelligent functions by alternating ion flux and polarization; 2) through ionic-electronic coupling, iontronic devices can bridge the biosystem with electronics and offer profound implications for soft electronics; 3) with the diversity of ions, iontronic devices can be designed to recognize specific ions or molecules by customizing the charge selectivity, and the ionic conductivity and capacitance can be adjusted to respond to external stimuli for a variety of sensing schemes, which can be more difficult for electron-based devices. This review provides a comprehensive overview of emerging neuromorphic sensory computing by iontronic devices, highlighting representative concepts of both low-level and high-level sensory computing and introducing important material and device breakthroughs. Moreover, iontronic devices as a means of neuromorphic sensing and computing are discussed regarding the pending challenges and future directions.
引用
收藏
页数:29
相关论文
共 267 条
[71]   A Carbon Nanotube Synapse with Dynamic Logic and Learning [J].
Kim, Kyunghyun ;
Chen, Chia-Ling ;
Quyen Truong ;
Shen, Alex M. ;
Chen, Yong .
ADVANCED MATERIALS, 2013, 25 (12) :1693-1698
[72]   Bio-Inspired Artificial Vision and Neuromorphic Image Processing Devices [J].
Kim, Min Sung ;
Kim, Min Seok ;
Lee, Gil Ju ;
Sunwoo, Sung-Hyuk ;
Chang, Sehui ;
Song, Young Min ;
Kim, Dae-Hyeong .
ADVANCED MATERIALS TECHNOLOGIES, 2022, 7 (02)
[73]   Emerging Materials for Neuromorphic Devices and Systems [J].
Kim, Min-Kyu ;
Park, Youngjun ;
Kim, Ik-Jyae ;
Lee, Jang-Sik .
ISCIENCE, 2020, 23 (12)
[74]   Dendritic Network Implementable Organic Neurofiber Transistors with Enhanced Memory Cyclic Endurance for Spatiotemporal Iterative Learning [J].
Kim, Soo Jin ;
Jeong, Jae-Seung ;
Jang, Ho Won ;
Yi, Hyunjung ;
Yang, Hoichang ;
Ju, Hyunsu ;
Lim, Jung Ah .
ADVANCED MATERIALS, 2021, 33 (26)
[75]   Deterministic Multimodal Perturbation Enables Neuromorphic-Compatible Signal Multiplexing [J].
Kim, Ui Jin ;
Ho, Dong Hae ;
Choi, Yoon Young ;
Choi, Yongsuk ;
Roe, Dong Gue ;
Kwon, Yonghyun Albert ;
Kim, Seongchan ;
Choi, Young Jin ;
Heo, Yejin ;
Jo, Sae Byeok ;
Bae, Geun Yeol ;
Lee, Taeyoon ;
Cho, Jeong Ho .
ACS MATERIALS LETTERS, 2022, 4 (01) :102-110
[76]   A bioinspired flexible organic artificial afferent nerve [J].
Kim, Yeongin ;
Chortos, Alex ;
Xu, Wentao ;
Liu, Yuxin ;
Oh, Jin Young ;
Son, Donghee ;
Kang, Jiheong ;
Foudeh, Amir M. ;
Zhu, Chenxin ;
Lee, Yeongjun ;
Niu, Simiao ;
Liu, Jia ;
Pfattner, Raphael ;
Bao, Zhenan ;
Lee, Tae-Woo .
SCIENCE, 2018, 360 (6392) :998-+
[77]   Metaplastic and energy-efficient biocompatible graphene artificial synaptic transistors for enhanced accuracy neuromorphic computing [J].
Kireev, Dmitry ;
Liu, Samuel ;
Jin, Harrison ;
Xiao, T. Patrick ;
Bennett, Christopher H. ;
Akinwande, Deji ;
Incorvia, Jean Anne C. .
NATURE COMMUNICATIONS, 2022, 13 (01)
[78]   Organic neuromorphic electronics for sensorimotor integration and learning in robotics [J].
Krauhausen, Imke ;
Koutsouras, Dimitrios A. ;
Melianas, Armantas ;
Keene, Scott T. ;
Lieberth, Katharina ;
Ledanseur, Hadrien ;
Sheelamanthula, Rajendar ;
Giovannitti, Alexander ;
Torricelli, Fabrizio ;
Mcculloch, Iain ;
Blom, Paul W. M. ;
Salleo, Alberto ;
van de Burgt, Yoeri ;
Gkoupidenis, Paschalis .
SCIENCE ADVANCES, 2021, 7 (50)
[79]   A Highly Transparent Artificial Photonic Nociceptor [J].
Kumar, Mohit ;
Kim, Hong-Sik ;
Kim, Joondong .
ADVANCED MATERIALS, 2019, 31 (19)
[80]   Dynamical memristors for higher-complexity neuromorphic computing [J].
Kumar, Suhas ;
Wang, Xinxin ;
Strachan, John Paul ;
Yang, Yuchao ;
Lu, Wei D. .
NATURE REVIEWS MATERIALS, 2022, 7 (07) :575-591