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Liu X, Sun C, Ye X, Zhu X, Hu C, Tan H, He S, Shao M, Li RW. Neuromorphic Nanoionics for Human-Machine Interaction: From Materials to Applications. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2311472. [PMID: 38421081 DOI: 10.1002/adma.202311472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 02/06/2024] [Indexed: 03/02/2024]
Abstract
Human-machine interaction (HMI) technology has undergone significant advancements in recent years, enabling seamless communication between humans and machines. Its expansion has extended into various emerging domains, including human healthcare, machine perception, and biointerfaces, thereby magnifying the demand for advanced intelligent technologies. Neuromorphic computing, a paradigm rooted in nanoionic devices that emulate the operations and architecture of the human brain, has emerged as a powerful tool for highly efficient information processing. This paper delivers a comprehensive review of recent developments in nanoionic device-based neuromorphic computing technologies and their pivotal role in shaping the next-generation of HMI. Through a detailed examination of fundamental mechanisms and behaviors, the paper explores the ability of nanoionic memristors and ion-gated transistors to emulate the intricate functions of neurons and synapses. Crucial performance metrics, such as reliability, energy efficiency, flexibility, and biocompatibility, are rigorously evaluated. Potential applications, challenges, and opportunities of using the neuromorphic computing technologies in emerging HMI technologies, are discussed and outlooked, shedding light on the fusion of humans with machines.
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Affiliation(s)
- Xuerong Liu
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- College of Materials Sciences and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Cui Sun
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Xiaoyu Ye
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Xiaojian Zhu
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Cong Hu
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Hongwei Tan
- Department of Applied Physics, Aalto University, Aalto, FI-00076, Finland
| | - Shang He
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Mengjie Shao
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
| | - Run-Wei Li
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, 315201, China
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Chen L, Ren M, Zhou J, Zhou X, Liu F, Di J, Xue P, Li C, Li Q, Li Y, Wei L, Zhang Q. Bioinspired iontronic synapse fibers for ultralow-power multiplexing neuromorphic sensorimotor textiles. Proc Natl Acad Sci U S A 2024; 121:e2407971121. [PMID: 39110725 PMCID: PMC11331142 DOI: 10.1073/pnas.2407971121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2024] [Accepted: 06/27/2024] [Indexed: 08/21/2024] Open
Abstract
Artificial neuromorphic devices can emulate dendric integration, axonal parallel transmission, along with superior energy efficiency in facilitating efficient information processing, offering enormous potential for wearable electronics. However, integrating such circuits into textiles to achieve biomimetic information perception, processing, and control motion feedback remains a formidable challenge. Here, we engineer a quasi-solid-state iontronic synapse fiber (ISF) comprising photoresponsive TiO2, ion storage Co-MoS2, and an ion transport layer. The resulting ISF achieves inherent short-term synaptic plasticity, femtojoule-range energy consumption, and the ability to transduce chemical/optical signals. Multiple ISFs are interwoven into a synthetic neural fabric, allowing the simultaneous propagation of distinct optical signals for transmitting parallel information. Importantly, IFSs with multiple input electrodes exhibit spatiotemporal information integration. As a proof of concept, a textile-based multiplexing neuromorphic sensorimotor system is constructed to connect synaptic fibers with artificial fiber muscles, enabling preneuronal sensing information integration, parallel transmission, and postneuronal information output to control the coordinated motor of fiber muscles. The proposed fiber system holds enormous promise in wearable electronics, soft robotics, and biomedical engineering.
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Affiliation(s)
- Long Chen
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou215123, China
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore639798, Singapore
| | - Ming Ren
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou215123, China
| | - Jianxian Zhou
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou215123, China
| | - Xuhui Zhou
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore639798, Singapore
| | - Fan Liu
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore639798, Singapore
| | - Jiangtao Di
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou215123, China
| | - Pan Xue
- School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou225002, China
| | - Chunsheng Li
- School of Chemistry and Life Sciences, Suzhou University of Science and Technology, Suzhou215009, China
| | - Qingwen Li
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou215123, China
| | - Yang Li
- School of Microelectronics, Shandong University, Jinan250101, China
| | - Lei Wei
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore639798, Singapore
| | - Qichong Zhang
- Key Laboratory of Multifunctional Nanomaterials and Smart Systems, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou215123, China
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Ren S, Wang K, Jia X, Wang J, Xu J, Yang B, Tian Z, Xia R, Yu D, Jia Y, Yan X. Fibrous MXene Synapse-Based Biomimetic Tactile Nervous System for Multimodal Perception and Memory. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2400165. [PMID: 38329189 DOI: 10.1002/smll.202400165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 01/19/2024] [Indexed: 02/09/2024]
Abstract
Biomimetic tactile nervous system (BTNS) inspired by organisms has motivated extensive attention in wearable fields due to its biological similarity, low power consumption, and perception-memory integration. Though many works about planar-shape BTNS are developed, few researches could be found in the field of fibrous BTNS (FBTNS) which is superior in terms of strong flexibility, weavability, and high-density integration. Herein, a FBTNS with multimodal sensibility and memory is proposed, by fusing the fibrous poly lactic acid (PLA)/Ag/MXene/Pt artificial synapse and MXene/EMIMBF4 ionic conductive elastomer. The proposed FBTNS can successfully perceive external stimuli and generate synaptic responses. It also exhibits a short response time (23 ms) and low set power consumption (17 nW). Additionally, the proposed device demonstrates outstanding synaptic plasticity under both mechanical and electrical stimuli, which can simulate the memory function. Simultaneously, the fibrous devices are embedded into textiles to construct tactile arrays, by which biomimetic tactile perception and temporary memory functions are successfully implemented. This work demonstrates the as-prepared FBTNS can generate biomimetic synaptic signals to serve as artificial feeling signals, it is thought that it could offer a fabric electronic unit integrating with perception and memory for Human-Computer interaction, and has great potential to build lightweight and comfortable Brain-Computer interfaces.
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Affiliation(s)
- Shuhui Ren
- College of Electronic Information and Optical Engineering, Nankai University, Tianjin, 300071, P. R. China
| | - Kaiyang Wang
- College of Electronic Information and Optical Engineering, Nankai University, Tianjin, 300071, P. R. China
| | - Xiaotong Jia
- College of Electronic Information and Optical Engineering, Nankai University, Tianjin, 300071, P. R. China
| | - Jiuyang Wang
- College of Electronic Information and Optical Engineering, Nankai University, Tianjin, 300071, P. R. China
| | - Jikang Xu
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding, 071002, P. R. China
| | - Biao Yang
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding, 071002, P. R. China
| | - Ziwei Tian
- College of Electronic Information and Optical Engineering, Nankai University, Tianjin, 300071, P. R. China
| | - Ruoxuan Xia
- College of Electronic Information and Optical Engineering, Nankai University, Tianjin, 300071, P. R. China
| | - Ding Yu
- College of Electronic Information and Optical Engineering, Nankai University, Tianjin, 300071, P. R. China
| | - Yunfang Jia
- College of Electronic Information and Optical Engineering, Nankai University, Tianjin, 300071, P. R. China
| | - Xiaobing Yan
- Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, Hebei University, Baoding, 071002, P. R. China
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Song J, Liu H, Zhao Z, Lin P, Yan F. Flexible Organic Transistors for Biosensing: Devices and Applications. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2300034. [PMID: 36853083 DOI: 10.1002/adma.202300034] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 02/20/2023] [Indexed: 06/18/2023]
Abstract
Flexible and stretchable biosensors can offer seamless and conformable biological-electronic interfaces for continuously acquiring high-fidelity signals, permitting numerous emerging applications. Organic thin film transistors (OTFTs) are ideal transducers for flexible and stretchable biosensing due to their soft nature, inherent amplification function, biocompatibility, ease of functionalization, low cost, and device diversity. In consideration of the rapid advances in flexible-OTFT-based biosensors and their broad applications, herein, a timely and comprehensive review is provided. It starts with a detailed introduction to the features of various OTFTs including organic field-effect transistors and organic electrochemical transistors, and the functionalization strategies for biosensing, with a highlight on the seminal work and up-to-date achievements. Then, the applications of flexible-OTFT-based biosensors in wearable, implantable, and portable electronics, as well as neuromorphic biointerfaces are detailed. Subsequently, special attention is paid to emerging stretchable organic transistors including planar and fibrous devices. The routes to impart stretchability, including structural engineering and material engineering, are discussed, and the implementations of stretchable organic transistors in e-skin and smart textiles are included. Finally, the remaining challenges and the future opportunities in this field are summarized.
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Affiliation(s)
- Jiajun Song
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China
| | - Hong Liu
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China
| | - Zeyu Zhao
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China
| | - Peng Lin
- Shenzhen Key Laboratory of Special Functional Materials and Guangdong Research Center for Interfacial Engineering of Functional Materials, College of Materials Science and Engineering, Shenzhen University, Shenzhen, 518060, P. R. China
| | - Feng Yan
- Department of Applied Physics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China
- Research Institute of Intelligent Wearable Systems, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, 999077, P. R. China
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5
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Cho KG, Lee KH, Frisbie CD. Tuning Gate Potential Profiles and Current-Voltage Characteristics of Polymer Electrolyte-Gated Transistors by Capacitance Engineering. ACS APPLIED MATERIALS & INTERFACES 2024; 16:19309-19317. [PMID: 38591355 DOI: 10.1021/acsami.4c00079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/10/2024]
Abstract
We demonstrate that the transfer characteristics of electrolyte-gated transistors (EGTs) with polythiophene semiconductor channels are a strong function of gate/electrolyte interfacial contact area, i.e., gate size. Polythiophene EGTs with gate/electrolyte areas much larger than the channel/electrolyte areas show a clear peak in the drain current vs gate voltage (ID-VG) behavior, as well as peak voltage hysteresis between the forward and reverse VG sweeps. Polythiophene EGTs with small gate/electrolyte areas, on the other hand, exhibit current plateaus in the ID-VG behavior and a gate-size-dependent hysteresis loop between turn on and off. The qualitatively different transport behaviors are attributed to the relative sizes of the gate/electrolyte and channel/electrolyte interface capacitances, which are proportional to interfacial area. These interfacial capacitances are in series with each other such that the total capacitance of the full gate/electrolyte/channel stack is dominated by the interface with the smallest capacitance or area. For EGTs with large gates, most of the applied VG is dropped at the channel/electrolyte interface, leading to very high charge accumulations, up to ∼0.3 holes per ring (hpr) in the case of polythiophene semiconductors. The large charge density results in sub-band-filling and a marked decrease in hole mobility, giving rise to the peak in ID-VG. For EGTs with small gates, hole accumulation saturates near 0.15 hpr, band-filling does not occur, and hole mobility is maintained at a fixed value, which leads to the ID plateau. Potential drops at the interfaces are confirmed by in situ potential measurements inside a gate/electrolyte/polymer semiconductor stack. Hole accumulations are measured with gate current-gate voltage (IG-VG) measurements acquired simultaneously with the ID-VG characteristics. Overall, our measurements demonstrate that remarkably different ID behavior can be obtained for polythiophene EGTs by controlling the magnitude of the gate-electrolyte interfacial capacitance.
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Affiliation(s)
- Kyung Gook Cho
- Department of Chemical Engineering and Materials Science, University of Minnesota-Twin Cities, Minneapolis, Minnesota 55455, United States
| | - Keun Hyung Lee
- Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials Inha University, Incheon 22212, Republic of Korea
| | - C Daniel Frisbie
- Department of Chemical Engineering and Materials Science, University of Minnesota-Twin Cities, Minneapolis, Minnesota 55455, United States
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Liu P, Kong XY, Jiang L, Wen L. Ion transport in nanofluidics under external fields. Chem Soc Rev 2024; 53:2972-3001. [PMID: 38345093 DOI: 10.1039/d3cs00367a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Nanofluidic channels with tailored ion transport dynamics are usually used as channels for ion transport, to enable high-performance ion regulation behaviors. The rational construction of nanofluidics and the introduction of external fields are of vital significance to the advancement and development of these ion transport properties. Focusing on the recent advances of nanofluidics, in this review, various dimensional nanomaterials and their derived homogeneous/heterogeneous nanofluidics are first briefly introduced. Then we discuss the basic principles and properties of ion transport in nanofluidics. As the major part of this review, we focus on recent progress in ion transport in nanofluidics regulated by external physical fields (electric field, light, heat, pressure, etc.) and chemical fields (pH, concentration gradient, chemical reaction, etc.), and reveal the advantages and ion regulation mechanisms of each type. Moreover, the representative applications of these nanofluidic channels in sensing, ionic devices, energy conversion, and other areas are summarized. Finally, the major challenges that need to be addressed in this research field and the future perspective of nanofluidics development and practical applications are briefly illustrated.
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Affiliation(s)
- Pei Liu
- Henan Institute of Advanced Technology, Zhengzhou University, Zhengzhou 450052, P. R. China
- College of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450052, P. R. China
| | - Xiang-Yu Kong
- 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
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230026, P. R. China
- Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu 215123, 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
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230026, P. R. China
- Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu 215123, P. R. China
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 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
- School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230026, P. R. China
- Suzhou Institute for Advanced Research, University of Science and Technology of China, Suzhou, Jiangsu 215123, P. R. China
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, P. R. China
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Wang J, Ma S, Jeong SY, Yang W, Li J, Han YW, Feng K, Guo X. High-performance n-type organic thermoelectrics enabled by modulating cyano-functionalized polythiophene backbones. Faraday Discuss 2024; 250:335-347. [PMID: 37965681 DOI: 10.1039/d3fd00135k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
The scarcity of n-type polymers with high electrical conductivity (σ) and power factor (PF) is the major challenge for organic thermoelectrics (OTEs). By integrating cyano functionalities and an intramolecular conformation lock, we herein synthesize a new electron-deficient building block, CNg4T2, bearing long 1,4,7,10-tetraoxahendecyl side chains, and then further develop two n-type polythiophene derivatives, CNg4T2-2FT and CNg4T2-CNT2, with 3,4-difluorothiophene and 3,3'-dicyano-2,2'-bithiophene as co-units, respectively. Compared with CNg4T2-2FT, CNg4T2-CNT2 features a deeper-positioned lowest unoccupied molecular orbital (LUMO) while maintaining a high degree of backbone coplanarity. As a consequence, the CNg4T2-CNT2 film with molecular dopant N-DMBI delivered an impressive σ of 13.2 S cm-1 and a high PF of up to 10.84 μW m-1 K-2, significantly outperforming CNg4T2-2FT and benchmark n-type polymer N2200 films. To the best of our knowledge, this PF of CNg4T2-CNT2 devices is the highest value for n-type polythiophenes in OTEs. Further characterizations indicate that the high performance of CNg4T2-CNT2-based devices is attributed to the high doping efficiency and ordered packing of polymer chains. Our study demonstrates that CNg4T2 is a highly appealing electron-deficient building block for n-type OTE polymers and also suggests that fine-tuning of the polymer backbone is a powerful approach to accessing high-performance n-type polymers for OTE devices.
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Affiliation(s)
- Junwei Wang
- Department of Materials Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, Guangdong 518055, China.
| | - Suxiang Ma
- Department of Materials Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, Guangdong 518055, China.
| | - Sang Young Jeong
- Department of Chemistry, Korea University, Anamro 145, Seoul 02841, Republic of Korea
| | - Wanli Yang
- Department of Materials Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, Guangdong 518055, China.
| | - Jianfeng Li
- Department of Materials Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, Guangdong 518055, China.
| | - Young Woo Han
- Department of Chemistry, Korea University, Anamro 145, Seoul 02841, Republic of Korea
| | - Kui Feng
- Department of Materials Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, Guangdong 518055, China.
- Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology (SUSTech), Shenzhen, Guangdong 518055, China
| | - Xugang Guo
- Department of Materials Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, Guangdong 518055, China.
- Guangdong Provincial Key Laboratory of Functional Oxide Materials and Devices, Southern University of Science and Technology (SUSTech), Shenzhen, Guangdong 518055, China
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Liu R, Zhu X, Duan J, Chen J, Xie Z, Chen C, Xie X, Zhang Y, Yue W. Versatile Neuromorphic Modulation and Biosensing based on N-type Small-molecule Organic Mixed Ionic-Electronic Conductors. Angew Chem Int Ed Engl 2023:e202315537. [PMID: 38081781 DOI: 10.1002/anie.202315537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Indexed: 12/23/2023]
Abstract
The ion/chemical-based modulation feature of organic mixed ionic-electronic conductors (OMIECs) are critical to advancing next generation bio-integrated neuromorphic hardware. Despite achievements with polymeric OMIECs in organic electrochemical neuronal synapse (OENS). However, small molecule OMIECs based OENS has not yet been realized. Here, for the first time, we demonstrate an effective materials design concept of combining n-type fused all-acceptor small molecule OMIECs with subtle side chain optimization that enables robustly and flexibly modulating versatile synaptic behavior and sensing neurotransmitter in solid or aqueous electrolyte, operating in accumulation modes. By judicious tuning the ending side chains, the linear oligoether and butyl chain derivative gNR-Bu exhibits higher recognition accuracy for a model artificial neural network (ANN) simulation, higher steady conductance states and more outstanding ambient stability, which is superior to the state-of-art n-type OMIECs based OENS. These superior artificial synapse characteristics of gNR-Bu can be attributed to its higher crystallinity with stronger ion bonding capacities. More impressively, we unprecedentedly realized n-type small-molecule OMIECs based OENS as a neuromorphic biosensor enabling to respond synaptic communication signals of dopamine even at sub-μM level in aqueous electrolyte. This work may open a new path of small-molecule ion-electron conductors for next-generation ANN and bioelectronics.
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Affiliation(s)
- Riping Liu
- Guangzhou Key Laboratory of Flexible Electronic Materials and Wearable Devices, Key Laboratory for Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, State Key Laboratory of Optoelectronic Materials and Technologies, Sun Yat-sen University, 510275, Guangzhou, P. R. China
| | - Xiuyuan Zhu
- Guangzhou Key Laboratory of Flexible Electronic Materials and Wearable Devices, Key Laboratory for Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, State Key Laboratory of Optoelectronic Materials and Technologies, Sun Yat-sen University, 510275, Guangzhou, P. R. China
| | - Jiayao Duan
- Guangzhou Key Laboratory of Flexible Electronic Materials and Wearable Devices, Key Laboratory for Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, State Key Laboratory of Optoelectronic Materials and Technologies, Sun Yat-sen University, 510275, Guangzhou, P. R. China
| | - Junxin Chen
- Guangzhou Key Laboratory of Flexible Electronic Materials and Wearable Devices, Key Laboratory for Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, State Key Laboratory of Optoelectronic Materials and Technologies, Sun Yat-sen University, 510275, Guangzhou, P. R. China
| | - Zhuang Xie
- Guangzhou Key Laboratory of Flexible Electronic Materials and Wearable Devices, Key Laboratory for Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, State Key Laboratory of Optoelectronic Materials and Technologies, Sun Yat-sen University, 510275, Guangzhou, P. R. China
| | - Chaoyue Chen
- Guangzhou Key Laboratory of Flexible Electronic Materials and Wearable Devices, Key Laboratory for Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, State Key Laboratory of Optoelectronic Materials and Technologies, Sun Yat-sen University, 510275, Guangzhou, P. R. China
| | - Xi Xie
- Institute of Precision Medicine, The First Affiliated Hospital Sun Yat-sen University, State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, 510006, Guangzhou, P. R. China
| | - Yanxi Zhang
- The Institute of Flexible Electronics (IFE, Future Technologies), Xiamen University, 361005, Xiamen, Fujian, China
| | - Wan Yue
- Guangzhou Key Laboratory of Flexible Electronic Materials and Wearable Devices, Key Laboratory for Polymeric Composite and Functional Materials of Ministry of Education, School of Materials Science and Engineering, State Key Laboratory of Optoelectronic Materials and Technologies, Sun Yat-sen University, 510275, Guangzhou, P. R. China
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Wu S, Zeng L, Zhai Y, Shin C, Eedugurala N, Azoulay JD, Ng TN. Retinomorphic Motion Detector Fabricated with Organic Infrared Semiconductors. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2304688. [PMID: 37672884 PMCID: PMC10625071 DOI: 10.1002/advs.202304688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Indexed: 09/08/2023]
Abstract
Organic retinomorphic sensors offer the advantage of in-sensor processing to filter out redundant static backgrounds and are well suited for motion detection. To improve this promising structure, here, the key role of interfacial energetics in promoting charge accumulation to raise the inherent photoresponse of the light-sensitive capacitor is studied. Specifically, incorporating appropriate interfacial layers around the photoactive layer is crucial to extend the carrier lifetime, as confirmed by intensity-modulated photovoltage spectroscopy. Compared to its photodiode counterpart, the retinomorphic sensor shows better detectivity and response speed due to the additional insulating layer, which reduces the dark current and the RC time constant. Lastly, three retinomorphic sensors are integrated into a line array to demonstrate the detection of movement speed and direction, showing the potential of retinomorphic designs for efficient motion tracking.
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Affiliation(s)
- Shuo‐En Wu
- Materials Science and Engineering ProgramUniversity of California San DiegoLa JollaCA92093USA
| | - Longhui Zeng
- Department of Electrical and Computer EngineeringUniversity of California San DiegoLa JollaCA92093USA
| | - Yichen Zhai
- Department of Mechanical EngineeringUniversity of California San DiegoLa JollaCA92093USA
| | - Chanho Shin
- Materials Science and Engineering ProgramUniversity of California San DiegoLa JollaCA92093USA
| | - Naresh Eedugurala
- School of Chemistry and Biochemistry and School of Materials Science and EngineeringGeorgia Institute of TechnologyAtlantaGA30332USA
| | - Jason D. Azoulay
- School of Chemistry and Biochemistry and School of Materials Science and EngineeringGeorgia Institute of TechnologyAtlantaGA30332USA
| | - Tse Nga Ng
- Materials Science and Engineering ProgramUniversity of California San DiegoLa JollaCA92093USA
- Department of Electrical and Computer EngineeringUniversity of California San DiegoLa JollaCA92093USA
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10
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Chen X, Sun YF, Wu X, Shi S, Wang Z, Zhang J, Fang WH, Huang W. Breaking the Trade-Off Between Polymer Dielectric Constant and Loss via Aluminum Oxo Macrocycle Dopants for High-Performance Neuromorphic Electronics. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023:e2306260. [PMID: 37660306 DOI: 10.1002/adma.202306260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 08/24/2023] [Indexed: 09/05/2023]
Abstract
The dielectric layer is crucial in regulating the overall performance of field-effect transistors (FETs), the key component in central processing units, sensors, and displays. Despite considerable efforts being devoted to developing high-permittivity (k) dielectrics, limited progress is made due to the inherent trade-off between dielectric constant and loss. Here, a solution is presented by designing a monodispersed disk-shaped Ce-Al-O-macrocycle as a dopant in polymer dielectrics. The molecule features a central Ce(III) core connected with eight Al atoms through sixteen bridging hydroxyls and eight 3-aminophenyl peripheries. The incorporation of this macrocycle in polymer dielectrics results in an up to sevenfold increase in dielectric constants and up to 89% reduction in dielectric loss at low frequencies. Moreover, the leakage-current densities decrease, and the breakdown strengths are improved by 63%. Relying on the above merits, FETs bearing cluster-doped polymer dielectrics give near three-orders source-drain current increments while maintaining low-level leakage/off currents, resulting in much higher charge-carrier mobilities (up to 2.45 cm2 V-1 s-1 ) and on/off ratios. This cluster-doping strategy is generalizable and shows great promise for ultralow-power photoelectric synapses and neuromorphic retinas. This work successfully breaks the trade-off between dielectric constant and loss and offers a unique design for polymer composite dielectrics.
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Affiliation(s)
- Xiaowei Chen
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, P. R. China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, P. R. China
| | - Yi-Fan Sun
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, P. R. China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, P. R. China
| | - Xiaosong Wu
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, P. R. China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, P. R. China
| | - Shuhui Shi
- Department of Electrical and Electronic Engineering, University of Hong Kong, Pokfulam Road, Hong Kong SAR, Hong Kong
| | - Zhongrui Wang
- Department of Electrical and Electronic Engineering, University of Hong Kong, Pokfulam Road, Hong Kong SAR, Hong Kong
| | - Jian Zhang
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, P. R. China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, P. R. China
| | - Wei-Hui Fang
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, P. R. China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, P. R. China
| | - Weiguo Huang
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, P. R. China
- University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing, 100049, P. R. China
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11
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Dai S, Liu X, Liu Y, Xu Y, Zhang J, Wu Y, Cheng P, Xiong L, Huang J. Emerging Iontronic Neural Devices for Neuromorphic Sensory Computing. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2300329. [PMID: 36891745 DOI: 10.1002/adma.202300329] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/22/2023] [Indexed: 06/18/2023]
Abstract
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.
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Affiliation(s)
- Shilei Dai
- Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, Tongji University, Shanghai, 200434, P. R. China
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong, 999077, China
| | - Xu Liu
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
| | - Youdi Liu
- Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, State College, PA, 16802, USA
| | - Yutong Xu
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
| | - Junyao Zhang
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
| | - Yue Wu
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
| | - Ping Cheng
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA
| | - Lize Xiong
- Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, Tongji University, Shanghai, 200434, P. R. China
| | - Jia Huang
- Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, Tongji University, Shanghai, 200434, P. R. China
- Interdisciplinary Materials Research Center, School of Materials Science and Engineering, Tongji University, Shanghai, 201804, P. R. China
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12
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Wang X, Ran Y, Li X, Qin X, Lu W, Zhu Y, Lu G. Bio-inspired artificial synaptic transistors: evolution from innovative basic units to system integration. MATERIALS HORIZONS 2023; 10:3269-3292. [PMID: 37312536 DOI: 10.1039/d3mh00216k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The investigation of transistor-based artificial synapses in bioinspired information processing is undergoing booming exploration, and is the stable building block for brain-like computing. Given that the storage and computing separation architecture of von Neumann construction is not conducive to the current explosive information processing, it is critical to accelerate the connection between hardware systems and software simulations of intelligent synapses. So far, various works based on a transistor-based synaptic system successfully simulated functions similar to biological nerves in the human brain. However, the influence of the semiconductor and the device structural design on synaptic properties is still poorly linked. This review concretely emphasizes the recent advances in the novel structure design of semiconductor materials and devices used in synaptic transistors, not only from a single multifunction synaptic device but also to system application with various connected routes and related working mechanisms. Finally, crises and opportunities in transistor-based synaptic interconnection are discussed and predicted.
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Affiliation(s)
- Xin Wang
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| | - Yixin Ran
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| | - Xiaoqian Li
- Shandong Technology Center of Nanodevices and Integration, School of Microelectronics, Shandong University, Jinan, Shandong Province, 250100, P. R. China
| | - Xinsu Qin
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| | - Wanlong Lu
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| | - Yuanwei Zhu
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
| | - Guanghao Lu
- Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710054, P. R. China.
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13
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Chen H, Li H, Ma T, Han S, Zhao Q. Biological function simulation in neuromorphic devices: from synapse and neuron to behavior. SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS 2023; 24:2183712. [PMID: 36926202 PMCID: PMC10013381 DOI: 10.1080/14686996.2023.2183712] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/06/2023] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
Abstract
As the boom of data storage and processing, brain-inspired computing provides an effective approach to solve the current problem. Various emerging materials and devices have been reported to promote the development of neuromorphic computing. Thereinto, the neuromorphic device represented by memristor has attracted extensive research due to its outstanding property to emulate the brain's functions from synaptic plasticity, sensory-memory neurons to some intelligent behaviors of living creatures. Herein, we mainly review the progress of these brain functions mimicked by neuromorphic devices, concentrating on synapse (i.e. various synaptic plasticity trigger by electricity and/or light), neurons (including the various sensory nervous system) and intelligent behaviors (such as conditioned reflex represented by Pavlov's dog experiment). Finally, some challenges and prospects related to neuromorphic devices are presented.
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Affiliation(s)
- Hui Chen
- Heart Center of Henan Provincial People’s Hospital, Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, P. R. China
| | - Huilin Li
- Henan Key Laboratory of Photovoltaic Materials, Henan University, Kaifeng, P. R. China
| | - Ting Ma
- Henan Key Laboratory of Photovoltaic Materials, Henan University, Kaifeng, P. R. China
| | - Shuangshuang Han
- Henan Key Laboratory of Photovoltaic Materials, Henan University, Kaifeng, P. R. China
| | - Qiuping Zhao
- Heart Center of Henan Provincial People’s Hospital, Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, P. R. China
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14
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Sun F, Jiang H, Wang H, Zhong Y, Xu Y, Xing Y, Yu M, Feng LW, Tang Z, Liu J, Sun H, Wang H, Wang G, Zhu M. Soft Fiber Electronics Based on Semiconducting Polymer. Chem Rev 2023; 123:4693-4763. [PMID: 36753731 DOI: 10.1021/acs.chemrev.2c00720] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Fibers, originating from nature and mastered by human, have woven their way throughout the entire history of human civilization. Recent developments in semiconducting polymer materials have further endowed fibers and textiles with various electronic functions, which are attractive in applications such as information interfacing, personalized medicine, and clean energy. Owing to their ability to be easily integrated into daily life, soft fiber electronics based on semiconducting polymers have gained popularity recently for wearable and implantable applications. Herein, we present a review of the previous and current progress in semiconducting polymer-based fiber electronics, particularly focusing on smart-wearable and implantable areas. First, we provide a brief overview of semiconducting polymers from the viewpoint of materials based on the basic concepts and functionality requirements of different devices. Then we analyze the existing applications and associated devices such as information interfaces, healthcare and medicine, and energy conversion and storage. The working principle and performance of semiconducting polymer-based fiber devices are summarized. Furthermore, we focus on the fabrication techniques of fiber devices. Based on the continuous fabrication of one-dimensional fiber and yarn, we introduce two- and three-dimensional fabric fabricating methods. Finally, we review challenges and relevant perspectives and potential solutions to address the related problems.
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Affiliation(s)
- Fengqiang Sun
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
- Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
| | - Hao Jiang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Haoyu Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Yueheng Zhong
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Yiman Xu
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Yi Xing
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Muhuo Yu
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
- Shanghai Key Laboratory of Lightweight Structural Composites, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Liang-Wen Feng
- Key Laboratory of Green Chemistry & Technology, Ministry of Education, College of Chemistry, Sichuan University, Chengdu 610065, China
| | - Zheng Tang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
- Center for Advanced Low-dimension Materials, Donghua University, Shanghai 201620, China
| | - Jun Liu
- National Key Laboratory on Electromagnetic Environment Effects and Electro-Optical Engineering, Nanjing 210007, China
| | - Hengda Sun
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Hongzhi Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Gang Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Meifang Zhu
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
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15
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Wearable in-sensor reservoir computing using optoelectronic polymers with through-space charge-transport characteristics for multi-task learning. Nat Commun 2023; 14:468. [PMID: 36709349 PMCID: PMC9884246 DOI: 10.1038/s41467-023-36205-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 01/17/2023] [Indexed: 01/30/2023] Open
Abstract
In-sensor multi-task learning is not only the key merit of biological visions but also a primary goal of artificial-general-intelligence. However, traditional silicon-vision-chips suffer from large time/energy overheads. Further, training conventional deep-learning models is neither scalable nor affordable on edge-devices. Here, a material-algorithm co-design is proposed to emulate human retina and the affordable learning paradigm. Relying on a bottle-brush-shaped semiconducting p-NDI with efficient exciton-dissociations and through-space charge-transport characteristics, a wearable transistor-based dynamic in-sensor Reservoir-Computing system manifesting excellent separability, fading memory, and echo state property on different tasks is developed. Paired with a 'readout function' on memristive organic diodes, the RC recognizes handwritten letters and numbers, and classifies diverse costumes with accuracies of 98.04%, 88.18%, and 91.76%, respectively (higher than all reported organic semiconductors). In addition to 2D images, the spatiotemporal dynamics of RC naturally extract features of event-based videos, classifying 3 types of hand gestures at an accuracy of 98.62%. Further, the computing cost is significantly lower than that of the conventional artificial-neural-networks. This work provides a promising material-algorithm co-design for affordable and highly efficient photonic neuromorphic systems.
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16
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Sun C, Liu X, Jiang Q, Ye X, Zhu X, Li RW. Emerging electrolyte-gated transistors for neuromorphic perception. SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS 2023; 24:2162325. [PMID: 36684849 PMCID: PMC9848240 DOI: 10.1080/14686996.2022.2162325] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/18/2022] [Accepted: 12/21/2022] [Indexed: 05/31/2023]
Abstract
With the rapid development of intelligent robotics, the Internet of Things, and smart sensor technologies, great enthusiasm has been devoted to developing next-generation intelligent systems for the emulation of advanced perception functions of humans. Neuromorphic devices, capable of emulating the learning, memory, analysis, and recognition functions of biological neural systems, offer solutions to intelligently process sensory information. As one of the most important neuromorphic devices, Electrolyte-gated transistors (EGTs) have shown great promise in implementing various vital neural functions and good compatibility with sensors. This review introduces the materials, operating principle, and performances of EGTs, followed by discussing the recent progress of EGTs for synapse and neuron emulation. Integrating EGTs with sensors that faithfully emulate diverse perception functions of humans such as tactile and visual perception is discussed. The challenges of EGTs for further development are given.
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Affiliation(s)
- Cui Sun
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
| | - Xuerong Liu
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
| | - Qian Jiang
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- College of Materials Sciences and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoyu Ye
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- College of Materials Sciences and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Xiaojian Zhu
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- College of Materials Sciences and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Run-Wei Li
- CAS Key Laboratory of Magnetic Materials and Devices, and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- College of Materials Sciences and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing, China
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17
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Li Q, Wang T, Fang Y, Hu X, Tang C, Wu X, Zhu H, Ji L, Sun QQ, Zhang DW, Chen L. Ultralow Power Wearable Organic Ferroelectric Device for Optoelectronic Neuromorphic Computing. NANO LETTERS 2022; 22:6435-6443. [PMID: 35737934 DOI: 10.1021/acs.nanolett.2c01768] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In order to imitate brain-inspired biological information processing systems, various neuromorphic computing devices have been proposed, most of which were prepared on rigid substrates and have energy consumption levels several orders of magnitude higher than those of biological synapses (∼10 fJ per spike). Herein, a new type of wearable organic ferroelectric artificial synapse is proposed, which has two modulation modes (optical and electrical modulation). Because of the high photosensitivity of organic semiconductors and the ultrafast polarization switching of ferroelectric materials, the synaptic device has an ultrafast operation speed of 30 ns and an ultralow power consumption of 0.0675 aJ per synaptic event. Under combined photoelectric modulation, the artificial synapse realizes associative learning. The proposed artificial synapse with ultralow power consumption demonstrates good synaptic plasticity under different bending strains. This provides new avenues for the construction of ultralow power artificial intelligence system and the development of future wearable devices.
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Affiliation(s)
- Qingxuan Li
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
| | - Tianyu Wang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Yuqing Fang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
| | - Xuemeng Hu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
| | - Chengkang Tang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
| | - Xiaohan Wu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Hao Zhu
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Li Ji
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - Qing-Qing Sun
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
| | - David Wei Zhang
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
- National Integrated Circuit Innovation Center, Shanghai 201203, China
| | - Lin Chen
- State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China
- Zhangjiang Fudan International Innovation Center, Shanghai 201203, China
- National Integrated Circuit Innovation Center, Shanghai 201203, China
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18
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Yoon J, Kim HW, Shin M, Lim J, Lee JY, Lee SN, Choi JW. 3D Neural Network Composed of Neurospheroid and Bionanohybrid on Microelectrode Array to Realize the Spatial Input Signal Recognition in Neurospheroid. SMALL METHODS 2022; 6:e2200127. [PMID: 35595685 DOI: 10.1002/smtd.202200127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 05/03/2022] [Indexed: 06/15/2023]
Abstract
There have been several studies for demonstration of 2D neural network using living cells or organic/inorganic molecules, but to date, there is no report of development of a 3D neural network in vitro. Based on developed bionanohybrid composed of protein, DNA, molybdenum disulfide nanoparticles, and peptides for controlling electrophysiological states of living cells, here, the in vitro 3D neural network composed of the bionanohybrid, 3D neurospheroid and the microelectrode array (MEA) is developed. After production of the 3D neurospheroid derived from human neural stem cells, the bionanohybrid developed on the MEA successfully semi-penetrates the neurites of the 3D neurospheroid and forms the 3D neural network. The developed 3D neural network successfully exhibited the electrophysiological output signals of the 3D neurospheroid by transmitting the input signal applied by the bionanohybrid. Moreover, by using the selectively immobilized bionanohybrid on the MEA, the spatial input signal recognition in the neurospheroid of 3D neural network is realized for the first time. This newly developed in vitro 3D neural network provides a promising strategy to be applied in brain-on-a-chip, brain disease-related drug efficacy evaluation, bioelectronics, and bioelectronic medicine.
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Affiliation(s)
- Jinho Yoon
- Department of Chemical & Biomolecular Engineering, Sogang University, Seoul, 04107, Republic of Korea
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 123 Bevier Road, Piscataway, NJ, 08854, USA
| | - Hyun-Woong Kim
- Department of Chemical & Biomolecular Engineering, Sogang University, Seoul, 04107, Republic of Korea
| | - Minkyu Shin
- Department of Chemical & Biomolecular Engineering, Sogang University, Seoul, 04107, Republic of Korea
| | - Joungpyo Lim
- Department of Chemical & Biomolecular Engineering, Sogang University, Seoul, 04107, Republic of Korea
| | - Ji-Young Lee
- Department of Chemical & Biomolecular Engineering, Sogang University, Seoul, 04107, Republic of Korea
| | - Sang-Nam Lee
- Uniance Gene Inc., Seoul, 04107, Republic of Korea
| | - Jeong-Woo Choi
- Department of Chemical & Biomolecular Engineering, Sogang University, Seoul, 04107, Republic of Korea
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19
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Granelli R, Alessandri I, Gkoupidenis P, Vassalini I, Kovács-Vajna ZM, Blom PWM, Torricelli F. High-Performance Bioelectronic Circuits Integrated on Biodegradable and Compostable Substrates with Fully Printed Mask-Less Organic Electrochemical Transistors. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2022; 18:e2108077. [PMID: 35642950 DOI: 10.1002/smll.202108077] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 03/31/2022] [Indexed: 06/15/2023]
Abstract
Organic electrochemical transistors (OECTs) rely on volumetric ion-modulation of the electronic current to provide low-voltage operation, large signal amplification, enhanced sensing capabilities, and seamless integration with biology. The majority of current OECT technologies require multistep photolithographic microfabrication methods on glass or plastic substrates, which do not provide an ideal path toward ultralow cost ubiquitous and sustainable electronics and bioelectronics. At the same time, the development of advanced bioelectronic circuits combining bio-detection, amplification, and local processing functionalities urgently demand for OECT technology platforms with a monolithic integration of high-performance iontronic circuits and sensors. Here, fully printed mask-less OECTs fabricated on thin-film biodegradable and compostable substrates are proposed. The dispensing and capillary printing methods are used for depositing both high- and low-viscosity OECT materials. Fully printed OECT unipolar inverter circuits with a gain normalized to the supply voltage as high as 136.6 V-1 , and current-driven sensors for ion detection and real-time monitoring with a sensitivity of up to 506 mV dec-1 , are integrated on biodegradable and compostable substrates. These universal building blocks with the top-performance ever reported demonstrate the effectiveness of the proposed approach and can open opportunities for next-generation high-performance sustainable bioelectronics.
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Affiliation(s)
- Roberto Granelli
- Department of Information Engineering, University of Brescia, via Branze 38, Brescia, 25123, Italy
| | - Ivano Alessandri
- Department of Information Engineering, University of Brescia, via Branze 38, Brescia, 25123, Italy
| | | | - Irene Vassalini
- Department of Information Engineering, University of Brescia, via Branze 38, Brescia, 25123, Italy
| | - Zsolt M Kovács-Vajna
- Department of Information Engineering, University of Brescia, via Branze 38, Brescia, 25123, Italy
| | - Paul W M Blom
- Max Planck Institute for Polymer Research, Ackermannweg 10, 55128, Mainz, Germany
| | - Fabrizio Torricelli
- Department of Information Engineering, University of Brescia, via Branze 38, Brescia, 25123, Italy
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Lee J, Kim S, Park S, Lee J, Hwang W, Cho SW, Lee K, Kim SM, Seong TY, Park C, Lee S, Yi H. An Artificial Tactile Neuron Enabling Spiking Representation of Stiffness and Disease Diagnosis. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2201608. [PMID: 35436369 DOI: 10.1002/adma.202201608] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 04/11/2022] [Indexed: 06/14/2023]
Abstract
Mechanical properties of biological systems provide useful information about the biochemical status of cells and tissues. Here, an artificial tactile neuron enabling spiking representation of stiffness and spiking neural network (SNN)-based learning for disease diagnosis is reported. An artificial spiking tactile neuron based on an ovonic threshold switch serving as an artificial soma and a piezoresistive sensor as an artificial mechanoreceptor is developed and shown to encode the elastic stiffness of pressed materials into spike frequency evolution patterns. SNN-based learning of ultrasound elastography images abstracted by spike frequency evolution rate enables the classification of malignancy status of breast tumors with a recognition accuracy up to 95.8%. The stiffness-encoding artificial tactile neuron and learning of spiking-represented stiffness patterns hold a great promise for the identification and classification of tumors for disease diagnosis and robot-assisted surgery with low power consumption, low latency, and yet high accuracy.
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Affiliation(s)
- Junseok Lee
- Post-Silicon Semiconductor Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- YU-KIST, Yonsei University, Seoul, 03722, Republic of Korea
- Department of Materials Science and Engineering, Yonsei University, Seoul, 03722, Republic of Korea
| | - Seonjeong Kim
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- Department of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Seongjin Park
- Post-Silicon Semiconductor Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
| | - Jaesang Lee
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- Department of Materials Science and Engineering, Seoul National University, Seoul, 08826, Republic of Korea
| | - Wonseop Hwang
- Post-Silicon Semiconductor Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
| | - Seong Won Cho
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- Department of Materials Science and Engineering, Seoul National University, Seoul, 08826, Republic of Korea
| | - Kyuho Lee
- Department of Materials Science and Engineering, Yonsei University, Seoul, 03722, Republic of Korea
| | - Sun Mi Kim
- Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, 13620, Republic of Korea
| | - Tae-Yeon Seong
- Department of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Cheolmin Park
- YU-KIST, Yonsei University, Seoul, 03722, Republic of Korea
- Department of Materials Science and Engineering, Yonsei University, Seoul, 03722, Republic of Korea
| | - Suyoun Lee
- Center for Neuromorphic Engineering, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- Division of Nano & Information Technology, Korea University of Science and Technology, Daejeon, 34316, Republic of Korea
| | - Hyunjung Yi
- Post-Silicon Semiconductor Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- YU-KIST, Yonsei University, Seoul, 03722, Republic of Korea
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