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Sun B, Chen Y, Zhou G, Cao Z, Yang C, Du J, Chen X, Shao J. Memristor-Based Artificial Chips. ACS NANO 2024; 18:14-27. [PMID: 38153841 DOI: 10.1021/acsnano.3c07384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2023]
Abstract
Memristors, promising nanoelectronic devices with in-memory resistive switching behavior that is assembled with a physically integrated core processing unit (CPU) and memory unit and even possesses highly possible multistate electrical behavior, could avoid the von Neumann bottleneck of traditional computing devices and show a highly efficient ability of parallel computation and high information storage. These advantages position them as potential candidates for future data-centric computing requirements and add remarkable vigor to the research of next-generation artificial intelligence (AI) systems, particularly those that involve brain-like intelligence applications. This work provides an overview of the evolution of memristor-based devices, from their initial use in creating artificial synapses and neural networks to their application in developing advanced AI systems and brain-like chips. It offers a broad perspective of the key device primitives enabling their special applications from the view of materials, nanostructure, and mechanism models. We highlight these demonstrations of memristor-based nanoelectronic devices that have potential for use in the field of brain-like AI, point out the existing challenges of memristor-based nanodevices toward brain-like chips, and propose the guiding principle and promising outlook for future device promotion and system optimization in the biomedical AI field.
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Affiliation(s)
- Bai Sun
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Yuanzheng Chen
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China
| | - Guangdong Zhou
- College of Artificial Intelligence, Brain-inspired Computing & Intelligent Control of Chongqing Key Lab, Southwest University, Chongqing 400715, People's Republic of China
| | - Zelin Cao
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Chuan Yang
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China
| | - Junmei Du
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials, Southwest Jiaotong University, Chengdu, Sichuan 610031, People's Republic of China
| | - Xiaoliang Chen
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Jinyou Shao
- Micro-and Nano-technology Research Center, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
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Chen W, Zhai L, Zhang S, Zhao Z, Hu Y, Xiang Y, Liu H, Xu Z, Jiang L, Wen L. Cascade-heterogated biphasic gel iontronics for electronic-to-multi-ionic signal transmission. Science 2023; 382:559-565. [PMID: 37917701 DOI: 10.1126/science.adg0059] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Accepted: 09/22/2023] [Indexed: 11/04/2023]
Abstract
Currently, electronics and iontronics in abiotic-biotic systems can only use electrons and single-species ions as unitary signal carriers. Thus, a mechanism of gating transmission for multiple biosignals in such devices is needed to match and modulate complex aqueous-phase biological systems. Here we report the use of cascade-heterogated biphasic gel iontronics to achieve diverse electronic-to-multi-ionic signal transmission. The cascade-heterogated property determined the transfer free energy barriers experienced by ions and ionic hydration-dehydration states under an electric potential field, fundamentally enhancing the distinction of cross-interface transmission between different ions by several orders of magnitude. Such heterogated or chemical-heterogated iontronics with programmable features can be coupled with multi-ion cross-interface mobilities for hierarchical and selective cross-stage signal transmission. We expect that such iontronics would be ideal candidates for a variety of biotechnology applications.
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Affiliation(s)
- Weipeng Chen
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Linxin Zhai
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P. R. China
| | - Suli Zhang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, P. R. China
- Beijing Key Laboratory of Metabolic Disorder Related Cardiovascular Disease, Capital Medical University, Beijing 100069, P. R. China
| | - Ziguang Zhao
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Yuhao Hu
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Yun Xiang
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
| | - Huirong Liu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, P. R. China
- Beijing Key Laboratory of Metabolic Disorder Related Cardiovascular Disease, Capital Medical University, Beijing 100069, P. R. China
| | - Zhiping Xu
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P. R. China
| | - Lei Jiang
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Liping Wen
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
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Fu T, Fu S, Yao J. Recent progress in bio-voltage memristors working with ultralow voltage of biological amplitude. NANOSCALE 2023; 15:4669-4681. [PMID: 36779566 DOI: 10.1039/d2nr06773k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Neuromorphic systems built from memristors that emulate bioelectrical information processing in the brain may overcome the limitations of traditional computing architectures. However, functional emulation alone may still not attain all the merits of bio-computation, which uses action potentials of 50-120 mV at least 10 times lower than signal amplitude in conventional electronics to achieve extraordinary power efficiency and effective functional integration. Reducing the functional voltage in memristors to this biological amplitude can thus advance neuromorphic engineering and bio-emulated integration. This review aims to provide a timely update on the effort and progress in this burgeoning research direction, covering the aspects of device material composition, performance, working mechanism, and potential application.
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Affiliation(s)
- Tianda Fu
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA 01003, USA.
| | - Shuai Fu
- Institute for Applied Life Sciences (IALS), University of Massachusetts, Amherst, MA 01003, USA
| | - Jun Yao
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA 01003, USA.
- Institute for Applied Life Sciences (IALS), University of Massachusetts, Amherst, MA 01003, USA
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA 01003, USA
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