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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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2
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Kim C, Roe DG, Lim DU, Choi YY, Kang MS, Kim DH, Cho JH. Toward human-like adaptability in robotics through a retention-engineered synaptic control system. SCIENCE ADVANCES 2024; 10:eadn6217. [PMID: 38924417 PMCID: PMC11204284 DOI: 10.1126/sciadv.adn6217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 05/21/2024] [Indexed: 06/28/2024]
Abstract
Although advanced robots can adeptly mimic human movement and aesthetics, they are still unable to adapt or evolve in response to external experiences. To address this limitation, we propose an innovative approach that uses parallel-processable retention-engineered synaptic devices in the control system. This approach aims to simulate a human-like learning system without necessitating complex computational systems. The retention properties of the synaptic devices were modulated by adjusting the amount of Ag/AgCl ink sprayed. This changed the voltage drop across the interface between the gate electrode and the electrolyte. Furthermore, the unrestricted movement of ions in the electrolyte enhanced the signal multiplexing capability of the ion gel, enabling device-level parallel processing. By integrating the unique characteristics of the synaptic devices with actuators, we successfully emulated a human-like workout process that includes feedback between acute and chronic responses. The proposed control system offers an innovative approach to reducing system complexity and achieving a human-like learning system in the field of biomimicry.
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Affiliation(s)
- Chan Kim
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Dong Gue Roe
- School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Dong Un Lim
- Hydrogen Energy Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon 305-600 Republic of Korea
| | - Yoon Young Choi
- Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Moon Sung Kang
- Department of Chemical and Biomolecular Engineering, Institute of Emergent Materials, Sogang University, Seoul 04107, Republic of Korea
| | - Dong-Hwan Kim
- School of Chemical Engineering, Biomedical Institute for Convergence at SKKU (BICS), Sungkyunkwan University (SKKU), Suwon 16419, Republic of Korea
| | - Jeong Ho Cho
- Department of Chemical and Biomolecular Engineering, Yonsei University, Seoul 03722, Republic of Korea
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3
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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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Lee H, Cho J, Jin M, Lee JH, Lee C, Kim J, Lee J, Shin JC, Yoo J, Lee E, Kim YS. Electrochemical Analysis of Ion Effects on Electrolyte-Gated Synaptic Transistor Characteristics. ACS NANO 2024. [PMID: 38324887 DOI: 10.1021/acsnano.3c10082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Electrolyte-gated transistors (EGTs) are promising candidates as artificial synapses owing to their precise conductance controllability, quick response times, and especially their low operating voltages resulting from ion-assisted signal transmission. However, it is still vague how ion-related physiochemical elements and working mechanisms impact synaptic performance. Here, to address the unclear correlations, we suggest a methodical approach based on electrochemical analysis using poly(ethylene oxide) EGTs with three alkali ions: Li+, Na+, and K+. Cyclic voltammetry is employed to identify the kind of electrochemical reactions taking place at the channel/electrolyte interface, which determines the nonvolatile memory functionality of the EGTs. Additionally, using electrochemical impedance spectroscopy and qualitative analysis of electrolytes, we confirm that the intrinsic properties of electrolytes (such as crystallinity, solubility, and ion conductivity) and ion dynamics ultimately define the linearity/symmetricity of conductance modulation. Through simple but systematic electrochemical analysis, these results offer useful insights for the selection of components for high-performing artificial synapses.
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Affiliation(s)
- Haeyeon Lee
- Department of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Jinil Cho
- Program in Nano Science and Technology, Graduate School of Convergence Science and Technology, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Minho Jin
- Program in Nano Science and Technology, Graduate School of Convergence Science and Technology, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Jae Hak Lee
- Program in Nano Science and Technology, Graduate School of Convergence Science and Technology, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
- Samsung Display Company, Ltd., 1 Samsung-ro, Giheung-gu, Yongin-si, Gyeonggi-do 17113, Republic of Korea
| | - Chan Lee
- Department of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Jiyeon Kim
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Jiho Lee
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Jong Chan Shin
- Department of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Jeeyoung Yoo
- School of Energy Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Eungkyu Lee
- Department of Electronic Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do 17104, Republic of Korea
| | - Youn Sang Kim
- Department of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
- Program in Nano Science and Technology, Graduate School of Convergence Science and Technology, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, Republic of Korea
- Advanced Institutes of Convergence Technology, 145 Gwanggyo-ro, Yeongtong-gu, Suwon 16229, Republic of Korea
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Abstract
Efforts to design devices emulating complex cognitive abilities and response processes of biological systems have long been a coveted goal. Recent advancements in flexible electronics, mirroring human tissue's mechanical properties, hold significant promise. Artificial neuron devices, hinging on flexible artificial synapses, bioinspired sensors, and actuators, are meticulously engineered to mimic the biological systems. However, this field is in its infancy, requiring substantial groundwork to achieve autonomous systems with intelligent feedback, adaptability, and tangible problem-solving capabilities. This review provides a comprehensive overview of recent advancements in artificial neuron devices. It starts with fundamental principles of artificial synaptic devices and explores artificial sensory systems, integrating artificial synapses and bioinspired sensors to replicate all five human senses. A systematic presentation of artificial nervous systems follows, designed to emulate fundamental human nervous system functions. The review also discusses potential applications and outlines existing challenges, offering insights into future prospects. We aim for this review to illuminate the burgeoning field of artificial neuron devices, inspiring further innovation in this captivating area of research.
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Affiliation(s)
- Ke He
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Cong Wang
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Yongli He
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Jiangtao Su
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Xiaodong Chen
- Innovative Centre for Flexible Devices (iFLEX), Max Planck-NTU Joint Lab for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
- Institute for Digital Molecular Analytics and Science (IDMxS), Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore
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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: 14] [Impact Index Per Article: 14.0] [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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Yang J, Chen Y, Liu S, Liu C, Ma T, Luo Z, Ge G. Single-Line Multi-Channel Flexible Stress Sensor Arrays. MICROMACHINES 2023; 14:1554. [PMID: 37630090 PMCID: PMC10456942 DOI: 10.3390/mi14081554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/01/2023] [Accepted: 08/01/2023] [Indexed: 08/27/2023]
Abstract
Flexible stress sensor arrays, comprising multiple flexible stress sensor units, enable accurate quantification and analysis of spatial stress distribution. Nevertheless, the current implementation of flexible stress sensor arrays faces the challenge of excessive signal wires, resulting in reduced deformability, stability, reliability, and increased costs. The primary obstacle lies in the electric amplitude modulation nature of the sensor unit's signal (e.g., resistance and capacitance), allowing only one signal per wire. To overcome this challenge, the single-line multi-channel signal (SLMC) measurement has been developed, enabling simultaneous detection of multiple sensor signals through one or two signal wires, which effectively reduces the number of signal wires, thereby enhancing stability, deformability, and reliability. This review offers a general knowledge of SLMC measurement beginning with flexible stress sensors and their piezoresistive, capacitive, piezoelectric, and triboelectric sensing mechanisms. A further discussion is given on different arraying methods and their corresponding advantages and disadvantages. Finally, this review categorizes existing SLMC measurement methods into RLC series resonant sensing, transmission line sensing, ionic conductor sensing, triboelectric sensing, piezoresistive sensing, and distributed fiber optic sensing based on their mechanisms, describes the mechanisms and characteristics of each method and summarizes the research status of SLMC measurement.
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Affiliation(s)
- Jiayi Yang
- College of Computer Science and Technology, Xi’an University of Science and Technology, Xi’an 710054, China
- College of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
| | - Yuanyuan Chen
- College of Computer Science and Technology, Xi’an University of Science and Technology, Xi’an 710054, China
| | - Shuoyan Liu
- Department of Materials Science and Engineering, National University of Singapore, Singapore 117583, Singapore
| | - Chang Liu
- Department of Materials Science and Engineering, National University of Singapore, Singapore 117583, Singapore
| | - Tian Ma
- College of Computer Science and Technology, Xi’an University of Science and Technology, Xi’an 710054, China
- College of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
| | - Zhenmin Luo
- College of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
| | - Gang Ge
- Department of Materials Science and Engineering, National University of Singapore, Singapore 117583, Singapore
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Choi YJ, Roe DG, Choi YY, Kim S, Jo SB, Lee HS, Kim DH, Cho JH. Multiplexed Complementary Signal Transmission for a Self-Regulating Artificial Nervous System. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2205155. [PMID: 36437048 PMCID: PMC9875628 DOI: 10.1002/advs.202205155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Indexed: 06/16/2023]
Abstract
Neuromorphic engineering has emerged as a promising research field that can enable efficient and sophisticated signal transmission by mimicking the biological nervous system. This paper presents an artificial nervous system capable of facile self-regulation via multiplexed complementary signals. Based on the tunable nature of the Schottky barrier of a complementary signal integration circuit, a pair of complementary signals is successfully integrated to realize efficient signal transmission. As a proof of concept, a feedback-based blood glucose level control system is constructed by incorporating a glucose/insulin sensor, a complementary signal integration circuit, an artificial synapse, and an artificial neuron circuit. Certain amounts of glucose and insulin in the initial state are detected by each sensor and reflected as positive and negative amplitudes of the multiplexed presynaptic pulses, respectively. Subsequently, the pulses are converted to postsynaptic current, which triggered the injection of glucose or insulin in a way that confined the glucose level to a desirable range. The proposed artificial nervous system demonstrates the notable potential of practical advances in complementary control engineering.
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Affiliation(s)
- Young Jin Choi
- Department of Chemical and Biomolecular EngineeringYonsei UniversitySeoul03722Republic of Korea
| | - Dong Gue Roe
- School of Electrical and Electronic EngineeringYonsei UniversitySeoul03722Republic of Korea
| | - Yoon Young Choi
- Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana−ChampaignUrbanaIL61801USA
| | - Seongchan Kim
- SKKU Advanced Institute of Nanotechnology (SAINT)Sungkyunkwan UniversitySuwon16419Republic of Korea
| | - Sae Byeok Jo
- School of Chemical EngineeringSKKU Institute of Energy Science and Technology (SIEST)Sungkyunkwan University (SKKU)Suwon16419Republic of Korea
| | - Hwa Sung Lee
- Department of Materials Science and Chemical EngineeringHanyang UniversityAnsan15588Republic of Korea
| | - Do Hwan Kim
- Department of Chemical EngineeringHanyang UniversitySeoul04763Republic of Korea
| | - Jeong Ho Cho
- Department of Chemical and Biomolecular EngineeringYonsei UniversitySeoul03722Republic of Korea
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