1
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Xu G, Zhang M, Mei T, Liu W, Wang L, Xiao K. Nanofluidic Ionic Memristors. ACS NANO 2024. [PMID: 39022809 DOI: 10.1021/acsnano.4c06467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Living organisms use ions and small molecules as information carriers to communicate with the external environment at ultralow power consumption. Inspired by biological systems, artificial ion-based devices have emerged in recent years to try to realize efficient information-processing paradigms. Nanofluidic ionic memristors, memory resistors based on confined fluidic systems whose internal ionic conductance states depend on the historical voltage, have attracted broad attention and are used as neuromorphic devices for computing. Despite their high exposure, nanofluidic ionic memristors are still in the initial stage. Therefore, systematic guidance for developing and reasonably designing ionic memristors is necessary. This review systematically summarizes the history, mechanisms, and potential applications of nanofluidic ionic memristors. The essential challenges in the field and the outlook for the future potential applications of nanofluidic ionic memristors are also discussed.
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Affiliation(s)
- Guoheng Xu
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Institute of Innovative Materials, Southern University of Science and Technology (SUSTech), Shenzhen 518055, P. R. China
| | - Miliang Zhang
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Institute of Innovative Materials, Southern University of Science and Technology (SUSTech), Shenzhen 518055, P. R. China
| | - Tingting Mei
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Institute of Innovative Materials, Southern University of Science and Technology (SUSTech), Shenzhen 518055, P. R. China
| | - Wenchao Liu
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Institute of Innovative Materials, Southern University of Science and Technology (SUSTech), Shenzhen 518055, P. R. China
| | - Li Wang
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Institute of Innovative Materials, Southern University of Science and Technology (SUSTech), Shenzhen 518055, P. R. China
| | - Kai Xiao
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Institute of Innovative Materials, Southern University of Science and Technology (SUSTech), Shenzhen 518055, P. R. China
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2
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Wang W, Liang Y, Ma Y, Shi D, Xie Y. Memristive Characteristics in an Asymmetrically Charged Nanochannel. J Phys Chem Lett 2024; 15:6852-6858. [PMID: 38917304 DOI: 10.1021/acs.jpclett.4c00488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
The emergent nanofluidic memristor provides a promising way of emulating neuromorphic functions in the brain. The conical-shaped nanopore showed promising features for a nanofluidic memristor, inspiring us to investigate the memory effects in asymmetrically charged nanochannels due to their high current rectification, which may result in good memory effects. Here, the memory effects of an asymmetrically charged nanofluidic channel were numerically simulated by Poisson-Nernst-Planck equations. Our results showed that the I-V curves represented a diode in low scanning frequency and then became a memristor and finally a resistor as frequency increased. We successfully replicated the learning behavior in our system with history-dependent ion redistribution in the nanochannel. Some critical factors were quantitatively analyzed for the memory effects including voltage amplitude, optimal frequency, and Dukhin number. Experimental characterizations were also carried out. Our findings are useful for the design of nanofluidic memristors by the principle of enrichment and depletion as well as the determination of the best memory settings.
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Affiliation(s)
- Wei Wang
- School of Physical Science and Technology, Northwestern Polytechnical University, Xi'an, Shaanxi Province 710129, P. R. China
| | - Yizheng Liang
- School of Physical Science and Technology, Northwestern Polytechnical University, Xi'an, Shaanxi Province 710129, P. R. China
| | - Yu Ma
- School of Physical Science and Technology, Northwestern Polytechnical University, Xi'an, Shaanxi Province 710129, P. R. China
| | - Deli Shi
- School of Physical Science and Technology, Northwestern Polytechnical University, Xi'an, Shaanxi Province 710129, P. R. China
| | - Yanbo Xie
- School of Aeronautics and Institute of Extreme Mechanics, Northwestern Polytechnical University, Xi'an, Shaanxi Province 710072, P. R. China
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3
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Li P, Liu J, Yuan JH, Guo Y, Wang S, Zhang P, Wang W. Artificial Funnel Nanochannel Device Emulates Synaptic Behavior. NANO LETTERS 2024; 24:6192-6200. [PMID: 38666542 DOI: 10.1021/acs.nanolett.3c05079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2024]
Abstract
Creating artificial synapses that can interact with biological neural systems is critical for developing advanced intelligent systems. However, there are still many difficulties, including device morphology and fluid selection. Based on Micro-Electro-Mechanical System technologies, we utilized two immiscible electrolytes to form a liquid/liquid interface at the tip of a funnel nanochannel, effectively enabling a wafer-level fabrication, interactions between multiple information carriers, and electron-to-chemical signal transitions. The distinctive ionic transport properties successfully achieved a hysteresis in ionic transport, resulting in adjustable multistage conductance gradient and synaptic functions. Notably, the device is similar to biological systems in terms of structure and signal carriers, especially for the low operating voltage (200 mV), which matches the biological neural potential (∼110 mV). This work lays the foundation for realizing the function of iontronics neuromorphic computing at ultralow operating voltages and in-memory computing, which can break the limits of information barriers for brain-machine interfaces.
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Affiliation(s)
- Peiyue Li
- School of Integrated Circuits, Peking University, Beijing 100871, People's Republic of China
| | - Junjie Liu
- College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, People's Republic of China
| | - Jun-Hui Yuan
- School of Science, Wuhan University of Technology, Wuhan 430070, People's Republic of China
| | - Yechang Guo
- School of Integrated Circuits, Peking University, Beijing 100871, People's Republic of China
| | - Shaofeng Wang
- School of Engineering and Technology, China University of Geosciences (Beijing), Beijing 100083, People's Republic of China
| | - Pan Zhang
- School of Integrated Circuits, Peking University, Beijing 100871, People's Republic of China
- National Key Laboratory of Advanced Micro and Nano Manufacture Technology, Beijing 100871, People's Republic of China
| | - Wei Wang
- School of Integrated Circuits, Peking University, Beijing 100871, People's Republic of China
- National Key Laboratory of Advanced Micro and Nano Manufacture Technology, Beijing 100871, People's Republic of China
- Beijing Advanced Innovation Center for Integrated Circuits, Beijing 100871, People's Republic of China
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4
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Ramirez P, Portillo S, Cervera J, Bisquert J, Mafe S. Memristive arrangements of nanofluidic pores. Phys Rev E 2024; 109:044803. [PMID: 38755814 DOI: 10.1103/physreve.109.044803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 03/29/2024] [Indexed: 05/18/2024]
Abstract
We demonstrate that nanofluidic diodes in multipore membranes show a memristive behavior that can be controlled not only by the amplitude and frequency of the external signal but also by series and parallel arrangements of the membranes. Each memristor consists of a polymeric membrane with conical nanopores that allow current rectification due to the electrical interaction between the ionic solution and the pore surface charges. This surface charge-regulated ionic transport shows a rich nonlinear physics, including memory and inductive effects, which are characterized here by the current-voltage curves and electrical impedance spectroscopy. Also, neuromorphiclike potentiation of the membrane conductance following voltage pulses (spikes) is observed. The multipore membrane with nanofluidic diodes shows physical concepts that should have application for information processing and signal conversion in iontronics hybrid devices.
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Affiliation(s)
- Patricio Ramirez
- Departament de Física Aplicada, Universitat Politècnica de València, E-46022 València, Spain
| | - Sergio Portillo
- Departament de Física de la Terra i Termodinàmica, Universitat de València, E-46100 Burjassot, Spain
| | - Javier Cervera
- Departament de Física de la Terra i Termodinàmica, Universitat de València, E-46100 Burjassot, Spain
| | - Juan Bisquert
- Institute of Advanced Materials (INAM), Universitat Jaume I, 12006 Castelló, Spain
| | - Salvador Mafe
- Departament de Física de la Terra i Termodinàmica, Universitat de València, E-46100 Burjassot, Spain
- Allen Discovery Center at Tufts University, Medford, Massachusetts 02155, USA
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5
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Jeon JW, Park B, Jang YH, Lee SH, Jeon S, Han J, Ryoo SK, Kim KD, Shim SK, Cheong S, Choi W, Jeon G, Kim S, Yoo C, Han JK, Hwang CS. Vertically Stackable Ovonic Threshold Switch Oscillator Using Atomic Layer Deposited Ge 0.6Se 0.4 Film for High-Density Artificial Neural Networks. ACS APPLIED MATERIALS & INTERFACES 2024. [PMID: 38491936 DOI: 10.1021/acsami.3c18625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/18/2024]
Abstract
Nanodevice oscillators (nano-oscillators) have received considerable attention to implement in neuromorphic computing as hardware because they can significantly improve the device integration density and energy efficiency compared to complementary metal oxide semiconductor circuit-based oscillators. This work demonstrates vertically stackable nano-oscillators using an ovonic threshold switch (OTS) for high-density neuromorphic hardware. A vertically stackable Ge0.6Se0.4 OTS-oscillator (VOTS-OSC) is fabricated with a vertical crossbar array structure by growing Ge0.6Se0.4 film conformally on a contact hole structure using atomic layer deposition. The VOTS-OSC can be vertically integrated onto peripheral circuits without causing thermal damage because the fabrication temperature is <400 °C. The fabricated device exhibits oscillation characteristics, which can serve as leaky integrate-and-fire neurons in spiking neural networks (SNNs) and coupled oscillators in oscillatory neural networks (ONNs). For practical applications, pattern recognition and vertex coloring are demonstrated with SNNs and ONNs, respectively, using semiempirical simulations. This structure increases the oscillator integration density significantly, enabling complex tasks with a large number of oscillators. Moreover, it can enhance the computational speed of neural networks due to its rapid switching speed.
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Affiliation(s)
- Jeong Woo Jeon
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Byongwoo Park
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Yoon Ho Jang
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Soo Hyung Lee
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Sangmin Jeon
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Janguk Han
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Seung Kyu Ryoo
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Kyung Do Kim
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Sung Keun Shim
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Sunwoo Cheong
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Wonho Choi
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Gwangsik Jeon
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Sungjin Kim
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Chanyoung Yoo
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States
| | - Joon-Kyu Han
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Cheol Seong Hwang
- Department of Materials Science and Engineering and Inter-University Semiconductor Research Center, Seoul National University, Gwanak-ro 1, Daehagdong, Gwanak-gu, Seoul 08826, Republic of Korea
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6
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Guo J, Liu L, Wang J, Zhao X, Zhang Y, Yan Y. A Diffusive Artificial Synapse Based on Charged Metal Nanoparticles. NANO LETTERS 2024; 24:1951-1958. [PMID: 38315061 DOI: 10.1021/acs.nanolett.3c04224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
We show that a diffusive memristor with analogue switching characteristics can be achieved in a layer of gold nanoparticles (AuNPs) functionalized with charged self-assembled monolayers (deprotonated 11-mercaptoundecanoic acid). The nanoparticle core and the anchored stationary charges are jammed within the layer while the mobile counterions [N(CH3)4+] can respond to the electric field and spontaneously diffuse back to the initial positions upon removal of the field. This metal nanoparticle device is set-step free, energy consumption efficient, mechanically flexible, and analogous to bio-Ca2+ dynamics and has tunable conductance modulation capabilities at the counterion concentrations. The gradual resistive switching behavior enables us to implement several important synaptic functions such as potentiation/depression, spike voltage-dependent plasticity, spike duration-dependent plasticity, spike frequency-dependent plasticity, and paired-pulse facilitation. Finally, on the basis of the paired-pulse facilitation characteristics, the metal nanoparticle diffusive artificial synapse is used for edge extraction with exhibits excellent performance.
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Affiliation(s)
- Jiahui Guo
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- State Key Laboratory of Mesoscience and Engineering (State Key Laboratory of Multi-phase Complex Systems), Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
| | - Lin Liu
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jingyu Wang
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xing Zhao
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Yuchun Zhang
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
| | - Yong Yan
- CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China
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7
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Armendarez NX, Mohamed AS, Dhungel A, Hossain MR, Hasan MS, Najem JS. Brain-Inspired Reservoir Computing Using Memristors with Tunable Dynamics and Short-Term Plasticity. ACS APPLIED MATERIALS & INTERFACES 2024; 16:6176-6188. [PMID: 38271202 DOI: 10.1021/acsami.3c16003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2024]
Abstract
Recent advancements in reservoir computing (RC) research have created a demand for analogue devices with dynamics that can facilitate the physical implementation of reservoirs, promising faster information processing while consuming less energy and occupying a smaller area footprint. Studies have demonstrated that dynamic memristors, with nonlinear and short-term memory dynamics, are excellent candidates as information-processing devices or reservoirs for temporal classification and prediction tasks. Previous implementations relied on nominally identical memristors that applied the same nonlinear transformation to the input data, which is not enough to achieve a rich state space. To address this limitation, researchers either diversified the data encoding across multiple memristors or harnessed the stochastic device-to-device variability among the memristors. However, this approach requires additional preprocessing steps and leads to synchronization issues. Instead, it is preferable to encode the data once and pass them through a reservoir layer consisting of memristors with distinct dynamics. Here, we demonstrate that ion-channel-based memristors with voltage-dependent dynamics can be controllably and predictively tuned through the voltage or adjustment of the ion channel concentration to exhibit diverse dynamic properties. We show, through experiments and simulations, that reservoir layers constructed with a small number of distinct memristors exhibit significantly higher predictive and classification accuracies with a single data encoding. We found that for a second-order nonlinear dynamical system prediction task, the varied memristor reservoir experimentally achieved an impressive normalized mean square error of 1.5 × 10-3, using only five distinct memristors. Moreover, in a neural activity classification task, a reservoir of just three distinct memristors experimentally attained an accuracy of 96.5%. This work lays the foundation for next-generation physical RC systems that can exploit the complex dynamics of their diverse building blocks to achieve increased signal processing capabilities.
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Affiliation(s)
- Nicholas X Armendarez
- Department of Mechanical Engineering, The Pennsylvania State University, 336 Reber Building, University Park, Pennsylvania 16802, United States
| | - Ahmed S Mohamed
- Department of Mechanical Engineering, The Pennsylvania State University, 336 Reber Building, University Park, Pennsylvania 16802, United States
| | - Anurag Dhungel
- Department of Electrical and Computer Engineering, The University of Mississippi, 310 Anderson Hall, University, Mississippi 38677, United States
| | - Md Razuan Hossain
- Department of Electrical and Computer Engineering, The University of Mississippi, 310 Anderson Hall, University, Mississippi 38677, United States
| | - Md Sakib Hasan
- Department of Electrical and Computer Engineering, The University of Mississippi, 310 Anderson Hall, University, Mississippi 38677, United States
| | - Joseph S Najem
- Department of Mechanical Engineering, The Pennsylvania State University, 336 Reber Building, University Park, Pennsylvania 16802, United States
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8
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Ramirez P, Portillo S, Cervera J, Nasir S, Ali M, Ensinger W, Mafe S. Neuromorphic responses of nanofluidic memristors in symmetric and asymmetric ionic solutions. J Chem Phys 2024; 160:044701. [PMID: 38258920 DOI: 10.1063/5.0188940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 01/02/2024] [Indexed: 01/24/2024] Open
Abstract
We show that ionic conduction properties of a multipore nanofluidic memristor can be controlled not only by the amplitude and frequency of an external driving signal but also by chemical gating based on the electrolyte concentration, presence of divalent and trivalent cations, and multi-ionic systems in single and mixed electrolytes. In addition, we describe the modulation of current rectification and hysteresis phenomena, together with neuromorphic conductance responses to voltage pulses, in symmetric and asymmetric external solutions. In our case, memristor conical pores act as nanofluidic diodes modulated by ionic solution characteristics due to the surface charge-regulated ionic transport. The above facts suggest potential sensing and actuating applications based on the conversion between ionic and electronic signals in bioelectrochemical hybrid circuits.
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Affiliation(s)
- Patricio Ramirez
- Dept. de Física Aplicada, Universitat Politècnica de València, E-46022 València, Spain
| | - Sergio Portillo
- Dept. de Física de la Terra i Termodinàmica, Universitat de València, E-46100 Burjassot, Spain
| | - Javier Cervera
- Dept. de Física de la Terra i Termodinàmica, Universitat de València, E-46100 Burjassot, Spain
| | - Saima Nasir
- Dept. of Material- and Geo-Sciences, Technische Universität Darmstadt, D-64287 Darmstadt, Germany
- Materials Research Dept., GSI Helmholtzzentrum für Schwerionenforschung, D-64291 Darmstadt, Germany
| | - Mubarak Ali
- Dept. of Material- and Geo-Sciences, Technische Universität Darmstadt, D-64287 Darmstadt, Germany
- Materials Research Dept., GSI Helmholtzzentrum für Schwerionenforschung, D-64291 Darmstadt, Germany
| | - Wolfgang Ensinger
- Materials Research Dept., GSI Helmholtzzentrum für Schwerionenforschung, D-64291 Darmstadt, Germany
| | - Salvador Mafe
- Dept. de Física de la Terra i Termodinàmica, Universitat de València, E-46100 Burjassot, Spain
- Allen Discovery Center at Tufts University, Medford, Massachusetts 02155, USA
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9
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Paulo G, Sun K, Di Muccio G, Gubbiotti A, Morozzo Della Rocca B, Geng J, Maglia G, Chinappi M, Giacomello A. Hydrophobically gated memristive nanopores for neuromorphic applications. Nat Commun 2023; 14:8390. [PMID: 38110352 PMCID: PMC10728163 DOI: 10.1038/s41467-023-44019-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 11/27/2023] [Indexed: 12/20/2023] Open
Abstract
Signal transmission in the brain relies on voltage-gated ion channels, which exhibit the electrical behaviour of memristors, resistors with memory. State-of-the-art technologies currently employ semiconductor-based neuromorphic approaches, which have already demonstrated their efficacy in machine learning systems. However, these approaches still cannot match performance achieved by biological neurons in terms of energy efficiency and size. In this study, we utilise molecular dynamics simulations, continuum models, and electrophysiological experiments to propose and realise a bioinspired hydrophobically gated memristive nanopore. Our findings indicate that hydrophobic gating enables memory through an electrowetting mechanism, and we establish simple design rules accordingly. Through the engineering of a biological nanopore, we successfully replicate the characteristic hysteresis cycles of a memristor and construct a synaptic device capable of learning and forgetting. This advancement offers a promising pathway for the realization of nanoscale, cost- and energy-effective, and adaptable bioinspired memristors.
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Affiliation(s)
- Gonçalo Paulo
- Department of Mechanics and Aerospace Engineering, Sapienza University of Rome, Rome, 00184, Italy
| | - Ke Sun
- Chemical Biology Department, Groningen Biomolecular Sciences & Biotechnology Institute, Groningen, 9700 CC, The Netherlands
- Department of Laboratory Medicine, State Key Laboratory of Biotherapy and Cancer Center, Med+X Center for Manufacturing, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, 610041, China
| | - Giovanni Di Muccio
- Department of Mechanics and Aerospace Engineering, Sapienza University of Rome, Rome, 00184, Italy
| | - Alberto Gubbiotti
- Department of Mechanics and Aerospace Engineering, Sapienza University of Rome, Rome, 00184, Italy
| | | | - Jia Geng
- Department of Laboratory Medicine, State Key Laboratory of Biotherapy and Cancer Center, Med+X Center for Manufacturing, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, 610041, China
| | - Giovanni Maglia
- Chemical Biology Department, Groningen Biomolecular Sciences & Biotechnology Institute, Groningen, 9700 CC, The Netherlands
| | - Mauro Chinappi
- Department of Industrial Engineering, Tor Vergata University of Rome, Rome, 00133, Italy
| | - Alberto Giacomello
- Department of Mechanics and Aerospace Engineering, Sapienza University of Rome, Rome, 00184, Italy.
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10
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Ramirez P, Gómez V, Cervera J, Mafe S, Bisquert J. Synaptical Tunability of Multipore Nanofluidic Memristors. J Phys Chem Lett 2023:10930-10934. [PMID: 38033300 DOI: 10.1021/acs.jpclett.3c02796] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2023]
Abstract
We demonstrate a multipore nanofluidic memristor with conical pores showcasing a wide range of hysteresis and memristor properties that provide functionalities for brainlike computation in neuromorphic applications. Leveraging the interplay between the charged functional groups on the pore surfaces and the confined ionic solution, the memristor characteristics are modulated through the electrolyte type, ionic concentrations, and pH levels of the aqueous solution. The multipore membrane mimics the functional characteristics of biological ion channels and displays synaptical potentiation and depression. Furthermore, this property can be inverted in polarity by chemically varying the pH level. The ability to modulate memory effects by ionic conductivity holds promise for enhancing signal information processing capabilities.
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Affiliation(s)
- Patricio Ramirez
- Dept. de Física Aplicada, Universitat Politècnica de València, E-46022 València, Spain
| | - Vicente Gómez
- Dept. de Física Aplicada, Universitat Politècnica de València, E-46022 València, Spain
| | - Javier Cervera
- Dept. de Física de la Terra i Termodinàmica, Universitat de València, E-46100 Burjassot, Spain
| | - Salvador Mafe
- Dept. de Física Aplicada, Universitat Politècnica de València, E-46022 València, Spain
- Dept. de Física de la Terra i Termodinàmica, Universitat de València, E-46100 Burjassot, Spain
| | - Juan Bisquert
- Institute of Advanced Materials (INAM), Universitat Jaume I, 12006 Castelló, Spain
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11
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Chen W, Zhai L, Zhang S, Zhao Z, Hu Y, Xiang Y, Liu H, Xu Z, Jiang L, Wen L. Cascade-heterogated biphasic gel iontronics for electronic-to-multi-ionic signal transmission. Science 2023; 382:559-565. [PMID: 37917701 DOI: 10.1126/science.adg0059] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Accepted: 09/22/2023] [Indexed: 11/04/2023]
Abstract
Currently, electronics and iontronics in abiotic-biotic systems can only use electrons and single-species ions as unitary signal carriers. Thus, a mechanism of gating transmission for multiple biosignals in such devices is needed to match and modulate complex aqueous-phase biological systems. Here we report the use of cascade-heterogated biphasic gel iontronics to achieve diverse electronic-to-multi-ionic signal transmission. The cascade-heterogated property determined the transfer free energy barriers experienced by ions and ionic hydration-dehydration states under an electric potential field, fundamentally enhancing the distinction of cross-interface transmission between different ions by several orders of magnitude. Such heterogated or chemical-heterogated iontronics with programmable features can be coupled with multi-ion cross-interface mobilities for hierarchical and selective cross-stage signal transmission. We expect that such iontronics would be ideal candidates for a variety of biotechnology applications.
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Affiliation(s)
- Weipeng Chen
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Linxin Zhai
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P. R. China
| | - Suli Zhang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, P. R. China
- Beijing Key Laboratory of Metabolic Disorder Related Cardiovascular Disease, Capital Medical University, Beijing 100069, P. R. China
| | - Ziguang Zhao
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Yuhao Hu
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Yun Xiang
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
| | - Huirong Liu
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, P. R. China
- Beijing Key Laboratory of Metabolic Disorder Related Cardiovascular Disease, Capital Medical University, Beijing 100069, P. R. China
| | - Zhiping Xu
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, P. R. China
| | - Lei Jiang
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Liping Wen
- CAS Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
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12
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Scott HL, Bolmatov D, Premadasa UI, Doughty B, Carrillo JMY, Sacci RL, Lavrentovich M, Katsaras J, Collier CP. Cations Control Lipid Bilayer Memcapacitance Associated with Long-Term Potentiation. ACS APPLIED MATERIALS & INTERFACES 2023; 15:44533-44540. [PMID: 37696028 DOI: 10.1021/acsami.3c09056] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/13/2023]
Abstract
Phospholipid bilayers can be described as capacitors whose capacitance per unit area (specific capacitance, Cm) is determined by their thickness and dielectric constant─independent of applied voltage. It is also widely assumed that the Cm of membranes can be treated as a "biological constant". Recently, using droplet interface bilayers (DIBs), it was shown that zwitterionic phosphatidylcholine (PC) lipid bilayers can act as voltage-dependent, nonlinear memory capacitors, or memcapacitors. When exposed to an electrical "training" stimulation protocol, capacitive energy storage in lipid membranes was enhanced in the form of long-term potentiation (LTP), which enables biological learning and long-term memory. LTP was the result of membrane restructuring and the progressive asymmetric distribution of ions across the lipid bilayer during training, which is analogous, for example, to exponential capacitive energy harvesting from self-powered nanogenerators. Here, we describe how LTP could be produced from a membrane that is continuously pumped into a nonequilibrium steady state, altering its dielectric properties. During this time, the membrane undergoes static and dynamic changes that are fed back to the system's potential energy, ultimately resulting in a membrane whose modified molecular structure supports long-term memory storage and LTP. We also show that LTP is very sensitive to different salts (KCl, NaCl, LiCl, and TmCl3), with LiCl and TmCl3 having the most profound effect in depressing LTP, relative to KCl. This effect is related to how the different cations interact with the bilayer zwitterionic PC lipid headgroups primarily through electric-field-induced changes to the statistically averaged orientations of water dipoles at the bilayer headgroup interface.
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Affiliation(s)
- Haden L Scott
- Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Dima Bolmatov
- Department of Physics and Astronomy, The University of Tennessee, Knoxville, Tennessee 37996, United States
- Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Uvinduni I Premadasa
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Benjamin Doughty
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Jan-Michael Y Carrillo
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Robert L Sacci
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Maxim Lavrentovich
- Department of Physics and Astronomy, The University of Tennessee, Knoxville, Tennessee 37996, United States
| | - John Katsaras
- Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
- Department of Physics and Astronomy, The University of Tennessee, Knoxville, Tennessee 37996, United States
- Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Charles P Collier
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
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13
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Bogard A, Finn PW, Smith AR, Flacau IM, Whiting R, Fologea D. Modulation of Voltage-Gating and Hysteresis of Lysenin Channels by Cu 2+ Ions. Int J Mol Sci 2023; 24:12996. [PMID: 37629177 PMCID: PMC10455686 DOI: 10.3390/ijms241612996] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 08/12/2023] [Accepted: 08/18/2023] [Indexed: 08/27/2023] Open
Abstract
The intricate voltage regulation presented by lysenin channels reconstituted in artificial lipid membranes leads to a strong hysteresis in conductance, bistability, and memory. Prior investigations on lysenin channels indicate that the hysteresis is modulated by multivalent cations which are also capable of eliciting single-step conformational changes and transitions to stable closed or sub-conducting states. However, the influence on voltage regulation of Cu2+ ions, capable of completely closing the lysenin channels in a two-step process, was not sufficiently addressed. In this respect, we employed electrophysiology approaches to investigate the response of lysenin channels to variable voltage stimuli in the presence of small concentrations of Cu2+ ions. Our experimental results showed that the hysteretic behavior, recorded in response to variable voltage ramps, is accentuated in the presence of Cu2+ ions. Using simultaneous AC/DC stimulation, we were able to determine that Cu2+ prevents the reopening of channels previously closed by depolarizing potentials and the channels remain in the closed state even in the absence of a transmembrane voltage. In addition, we showed that Cu2+ addition reinstates the voltage gating and hysteretic behavior of lysenin channels reconstituted in neutral lipid membranes in which lysenin channels lose their voltage-regulating properties. In the presence of Cu2+ ions, lysenin not only regained the voltage gating but also behaved like a long-term molecular memory controlled by electrical potentials.
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Affiliation(s)
- Andrew Bogard
- Department of Physics, Boise State University, Boise, ID 83725, USA
- Biomolecular Sciences Graduate Program, State University, Boise, ID 83725, USA
| | - Pangaea W. Finn
- Department of Physics, Boise State University, Boise, ID 83725, USA
| | - Aviana R. Smith
- Department of Physics, Boise State University, Boise, ID 83725, USA
| | - Ilinca M. Flacau
- Department of Physics, Boise State University, Boise, ID 83725, USA
| | - Rose Whiting
- Department of Physics, Boise State University, Boise, ID 83725, USA
- Biomolecular Sciences Graduate Program, State University, Boise, ID 83725, USA
| | - Daniel Fologea
- Department of Physics, Boise State University, Boise, ID 83725, USA
- Biomolecular Sciences Graduate Program, State University, Boise, ID 83725, USA
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14
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Biolek Z, Biolek D, Biolková V, Kolka Z. Extended Higher-Order Elements with Frequency-Doubled Parameters: The Hysteresis Loops Are Always of Type II. SENSORS (BASEL, SWITZERLAND) 2023; 23:7179. [PMID: 37631716 PMCID: PMC10458208 DOI: 10.3390/s23167179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 08/07/2023] [Accepted: 08/14/2023] [Indexed: 08/27/2023]
Abstract
Current MEMS (Micro Electro Mechanical Systems) can be modeled by state-dependent elements that exhibit hysteretic behavior. Examples include capacitors and inductors whose capacitances and inductances are dependent on the instantaneous state of the electromechanical system, resistors whose resistances exhibit temperature changes when the elements are actually heated, etc. Regardless of the physical background, such hysteresis manifestations can be studied uniformly in the broader framework of generic and extended higher-order elements, in which a classification of hysteretic loops into types I and II is established. The loop type is an important dynamical parameter of an element, having the potential to indicate, for example, its (in)volatility. Thus far, there is no reliable criterion to determine the type of steady loop from the defining relations of an element. This work reports on one special class of extended elements that produces type II loops under all circumstances. The paper presents hitherto unpublished connections between the frequency-doubling parameters of an element and the type of its hysteresis loop. The new findings are expressed by several theorems that allow the type of hysteresis to be inferred from the frequency behavior of the element parameter or state, and vice versa. These procedures are demonstrated with examples and verified by computer simulations.
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Affiliation(s)
- Zdeněk Biolek
- Department of Electrical Engineering, University of Defence, 662 10 Brno, Czech Republic;
| | - Dalibor Biolek
- Department of Electrical Engineering, University of Defence, 662 10 Brno, Czech Republic;
- Department of Microelectronics, Brno University of Technology, 616 00 Brno, Czech Republic
| | - Viera Biolková
- Department of Radio Electronics, Brno University of Technology, 616 00 Brno, Czech Republic; (V.B.); (Z.K.)
| | - Zdeněk Kolka
- Department of Radio Electronics, Brno University of Technology, 616 00 Brno, Czech Republic; (V.B.); (Z.K.)
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15
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Kim H, Kim M, Lee A, Park HL, Jang J, Bae JH, Kang IM, Kim ES, Lee SH. Organic Memristor-Based Flexible Neural Networks with Bio-Realistic Synaptic Plasticity for Complex Combinatorial Optimization. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023:e2300659. [PMID: 37189211 DOI: 10.1002/advs.202300659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 04/19/2023] [Indexed: 05/17/2023]
Abstract
Hardware neural networks with mechanical flexibility are promising next-generation computing systems for smart wearable electronics. Several studies have been conducted on flexible neural networks for practical applications; however, developing systems with complete synaptic plasticity for combinatorial optimization remains challenging. In this study, the metal-ion injection density is explored as a diffusive parameter of the conductive filament in organic memristors. Additionally, a flexible artificial synapse with bio-realistic synaptic plasticity is developed using organic memristors that have systematically engineered metal-ion injections, for the first time. In the proposed artificial synapse, short-term plasticity (STP), long-term plasticity, and homeostatic plasticity are independently achieved and are analogous to their biological counterparts. The time windows of the STP and homeostatic plasticity are controlled by the ion-injection density and electric-signal conditions, respectively. Moreover, stable capabilities for complex combinatorial optimization in the developed synapse arrays are demonstrated under spike-dependent operations. This effective concept for realizing flexible neuromorphic systems for complex combinatorial optimization is an essential building block for achieving a new paradigm of wearable smart electronics associated with artificial intelligent systems.
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Affiliation(s)
- Hyeongwook Kim
- School of Electronics Engineering, and School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 702-701, Republic of Korea
| | - Miseong Kim
- School of Electronics Engineering, and School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 702-701, Republic of Korea
| | - Aejin Lee
- School of Electronics Engineering, and School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 702-701, Republic of Korea
| | - Hea-Lim Park
- Department of Materials Science and Engineering, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea
| | - Jaewon Jang
- School of Electronics Engineering, and School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 702-701, Republic of Korea
| | - Jin-Hyuk Bae
- School of Electronics Engineering, and School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 702-701, Republic of Korea
| | - In Man Kang
- School of Electronics Engineering, and School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 702-701, Republic of Korea
| | - Eun-Sol Kim
- Department of Computer Science, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea
| | - Sin-Hyung Lee
- School of Electronics Engineering, and School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 702-701, Republic of Korea
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16
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El-Beyrouthy J, Makhoul-Mansour M, Gulle J, Freeman E. Morphogenesis-inspired two-dimensional electrowetting in droplet networks. BIOINSPIRATION & BIOMIMETICS 2023; 18. [PMID: 37074106 DOI: 10.1088/1748-3190/acc779] [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: 10/21/2022] [Accepted: 03/24/2023] [Indexed: 05/03/2023]
Abstract
Living tissues dynamically reshape their internal cellular structures through carefully regulated cell-to-cell interactions during morphogenesis. These cellular rearrangement events, such as cell sorting and mutual tissue spreading, have been explained using the differential adhesion hypothesis, which describes the sorting of cells through their adhesive interactions with their neighbors. In this manuscript we explore a simplified form of differential adhesion within a bioinspired lipid-stabilized emulsion approximating cellular tissues. The artificial cellular tissues are created as a collection of aqueous droplets adhered together in a network of lipid membranes. Since this abstraction of the tissue does not retain the ability to locally vary the adhesion of the interfaces through biological mechanisms, instead we employ electrowetting with offsets generated by spatial variations in lipid compositions to capture a simple form of bioelectric control over the tissue characteristics. This is accomplished by first conducting experiments on electrowetting in droplet networks, next creating a model for describing electrowetting in collections of adhered droplets, then validating the model against the experimental measurements. This work demonstrates how the distribution of voltage within a droplet network may be tuned through lipid composition then used to shape directional contraction of the adhered structure using two-dimensional electrowetting events. Predictions from this model were used to explore the governing mechanics for complex electrowetting events in networks, including directional contraction and the formation of new interfaces.
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Affiliation(s)
- Joyce El-Beyrouthy
- School of Environmental, Civil, Agricultural, and Mechanical Engineering, University of Georgia, Athens, GA, United States of America
| | - Michelle Makhoul-Mansour
- School of Environmental, Civil, Agricultural, and Mechanical Engineering, University of Georgia, Athens, GA, United States of America
- College of Engineering, University of Tennessee Knoxville, Knoxville, TN, United States of America
| | - Jesse Gulle
- School of Environmental, Civil, Agricultural, and Mechanical Engineering, University of Georgia, Athens, GA, United States of America
| | - Eric Freeman
- School of Environmental, Civil, Agricultural, and Mechanical Engineering, University of Georgia, Athens, GA, United States of America
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17
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Hou Y, Ling Y, Wang Y, Wang M, Chen Y, Li X, Hou X. Learning from the Brain: Bioinspired Nanofluidics. J Phys Chem Lett 2023; 14:2891-2900. [PMID: 36927003 DOI: 10.1021/acs.jpclett.2c03930] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
The human brain completes intelligent behaviors such as the generation, transmission, and storage of neural signals by regulating the ionic conductivity of ion channels in neuron cells, which provides new inspiration for the development of ion-based brain-like intelligence. Against the backdrop of the gradual maturity of neuroscience, computer science, and micronano materials science, bioinspired nanofluidic iontronics, as an emerging interdisciplinary subject that focuses on the regulation of ionic conductivity of nanofluidic systems to realize brain-like functionalities, has attracted the attention of many researchers. This Perspective provides brief background information and the state-of-the-art progress of nanofluidic intelligent systems. Two main categories are included: nanofluidic transistors and nanofluidic memristors. The prospects of nanofluidic iontronics' interdisciplinary progress in future artificial intelligence fields such as neuromorphic computing or brain-computer interfaces are discussed. This Perspective aims to give readers a clear understanding of the concepts and prospects of this emerging interdisciplinary field.
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Affiliation(s)
- Yaqi Hou
- State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
- The Institute of Flexible Electronics (IFE, Future Technologies), Xiamen University, Xiamen 361005, China
| | - Yixin Ling
- State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Yanqiong Wang
- The Institute of Flexible Electronics (IFE, Future Technologies), Xiamen University, Xiamen 361005, China
| | - Miao Wang
- Institute of Artificial Intelligence, Xiamen University, Xiamen 361005, China
- College of Materials, Xiamen University, Xiamen 361005, China
| | - Yeyun Chen
- Institute of Artificial Intelligence, Xiamen University, Xiamen 361005, China
| | - Xipeng Li
- State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
- Binzhou Institute of Technology, Binzhou, 256600, China
| | - Xu Hou
- State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
- Department of Physics, Research Institute for Biomimetics and Soft Matter, Fujian Provincial Key Laboratory for Soft Functional Materials Research, Jiujiang Research Institute, College of Physical Science and Technology, Xiamen University, Xiamen 361005, China
- Institute of Artificial Intelligence, Xiamen University, Xiamen 361005, China
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen 361102, China
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18
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Fu T, Fu S, Yao J. Recent progress in bio-voltage memristors working with ultralow voltage of biological amplitude. NANOSCALE 2023; 15:4669-4681. [PMID: 36779566 DOI: 10.1039/d2nr06773k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Neuromorphic systems built from memristors that emulate bioelectrical information processing in the brain may overcome the limitations of traditional computing architectures. However, functional emulation alone may still not attain all the merits of bio-computation, which uses action potentials of 50-120 mV at least 10 times lower than signal amplitude in conventional electronics to achieve extraordinary power efficiency and effective functional integration. Reducing the functional voltage in memristors to this biological amplitude can thus advance neuromorphic engineering and bio-emulated integration. This review aims to provide a timely update on the effort and progress in this burgeoning research direction, covering the aspects of device material composition, performance, working mechanism, and potential application.
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Affiliation(s)
- Tianda Fu
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA 01003, USA.
| | - Shuai Fu
- Institute for Applied Life Sciences (IALS), University of Massachusetts, Amherst, MA 01003, USA
| | - Jun Yao
- Department of Electrical Computer and Engineering, University of Massachusetts, Amherst, MA 01003, USA.
- Institute for Applied Life Sciences (IALS), University of Massachusetts, Amherst, MA 01003, USA
- Department of Biomedical Engineering, University of Massachusetts, Amherst, MA 01003, USA
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19
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Khan R, Rehman NU, Ilyas N, Sfina N, Barhoumi M, Khan A, Althubeiti K, Otaibi SA, Iqbal S, Rahman N, Sohail M, Ullah A, Del Rosso T, Zaman Q, Ali Khan A, Abdullaev SS, Khan A. Threshold switching in nickel-doped zinc oxide based memristor for artificial sensory applications. NANOSCALE 2023; 15:1900-1913. [PMID: 36607270 DOI: 10.1039/d2nr05257a] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Electronic devices featuring biomimetic behaviour as electronic synapses and neurons have motivated the emergence of a new era in information and humanoid robotics technologies. In the human body, a nociceptor is a unique sensory neuron receptor that is capable of detecting harmful signals, leading to the central nervous system initiating a motor response. Herein, a nickel-doped zinc oxide (NZO)/Au based memristor is fabricated for the first time and characterized for artificial nociceptor application. For this, the introduction of a nickel-doped zinc oxide (NZO) layer between P++-Si and Au electrodes is used to eliminate the surface effects of the NZO layer, resulting in improved volatile threshold switching performance. Depending on the intensity, duration, and repetition rate of the external stimuli, this newly created memristor exhibits various critical nociceptive functions, including threshold, relaxation, allodynia, and hyperalgesia. The electron trapping/detrapping to/from the traps in the NZO layer is responsible for these nociceptive properties. This kind of NZO-based device produces a multifunctional nociceptor performance that is essential for applications in artificial intelligence systems, such as neural integrated devices with nanometer-sized features.
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Affiliation(s)
- Rajwali Khan
- School of Physics and Optoelectronic Engineering, Shenzhen University, Nanshan, 518000 Shenzhen Guangdong, China.
- Department of Physics, University of Lakki Marwat, 28420, Lakki Marwat, KP Pakistan.
| | - Naveed Ur Rehman
- Department of Physics, University of Lakki Marwat, 28420, Lakki Marwat, KP Pakistan.
| | - Nasir Ilyas
- School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, P.R. China
| | - Nourreddine Sfina
- College of Sciences and Arts in Mahayel Asir, Department of Physics, King Khalid University, Abha, Saudi Arabia
- Laboratoire de la Matière Condensée et des Nanosciences (LMCN), Université de Monastir, Département de Physique, Faculté des Sciences de Monastir, Avenue de l'Environnement, 5019 Monastir, Tunisia
| | - Mohamed Barhoumi
- Laboratoire de la Matière Condensée et des Nanosciences (LMCN), Université de Monastir, Département de Physique, Faculté des Sciences de Monastir, Avenue de l'Environnement, 5019 Monastir, Tunisia
| | - Alamzeb Khan
- Department of pediatrics, Yale School of Medicine, Yale University, New Haven, CT, 0651, USA
| | - Khaled Althubeiti
- Department of Chemistry, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
| | - Sattam Al Otaibi
- Department of Electrical Engineering, Collage of Engineering, Taif University, P.O. Box11099, Taif 21944, Saudi Arabia
| | - Shahid Iqbal
- Department of Physics, Albion College, Albion, Michigan, 49224, USA
| | - Nasir Rahman
- Department of Physics, University of Lakki Marwat, 28420, Lakki Marwat, KP Pakistan.
| | - Mohammad Sohail
- Department of Physics, University of Lakki Marwat, 28420, Lakki Marwat, KP Pakistan.
| | - Asad Ullah
- Department of Mathematics, University of Lakki Marwat, 28420, Lakki Marwat, KP Pakistan
| | - Tommaso Del Rosso
- Department of Physics, Pontifícia Universidade Católica do Rio de Janeiro, Rua Marques de São Vicente, 22451-900, Rio de janeiro, Brazil
| | - Quaid Zaman
- Department of Physic, University of Buner, Pakistan
| | - Abid Ali Khan
- Department of Chemical Sciences, University of Lakki Marwat, 28420, Lakki Marwat, KP Pakistan
| | - Sherzod Sh Abdullaev
- Independent Researcher of Andijan Machine-Building Institute, Uzbekistan/CEO of the company of "Editory" LLC, Uzbekistan
| | - Aurangzeb Khan
- Department of Physics, Abdul Wali Khan University Mardan, 23200, KP Pakistan
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20
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Xiong T, Li C, He X, Xie B, Zong J, Jiang Y, Ma W, Wu F, Fei J, Yu P, Mao L. Neuromorphic functions with a polyelectrolyte-confined fluidic memristor. Science 2023; 379:156-161. [PMID: 36634194 DOI: 10.1126/science.adc9150] [Citation(s) in RCA: 67] [Impact Index Per Article: 67.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Reproducing ion channel-based neural functions with artificial fluidic systems has long been an aspirational goal for both neuromorphic computing and biomedical applications. In this study, neuromorphic functions were successfully accomplished with a polyelectrolyte-confined fluidic memristor (PFM), in which confined polyelectrolyte-ion interactions contributed to hysteretic ion transport, resulting in ion memory effects. Various electric pulse patterns were emulated by PFM with ultralow energy consumption. The fluidic property of PFM enabled the mimicking of chemical-regulated electric pulses. More importantly, chemical-electric signal transduction was implemented with a single PFM. With its structural similarity to ion channels, PFM is versatile and easily interfaces with biological systems, paving a way to building neuromorphic devices with advanced functions by introducing rich chemical designs.
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Affiliation(s)
- Tianyi Xiong
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences (CAS), Beijing 100190, China.,School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Changwei Li
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences (CAS), Beijing 100190, China.,Key Laboratory of Environmentally Friendly Chemistry and Applications of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan 411105, China
| | - Xiulan He
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences (CAS), Beijing 100190, China
| | - Boyang Xie
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences (CAS), Beijing 100190, China.,School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jianwei Zong
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences (CAS), Beijing 100190, China.,School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanan Jiang
- College of Chemistry, Beijing Normal University, Beijing 100875, China
| | - Wenjie Ma
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences (CAS), Beijing 100190, China
| | - Fei Wu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences (CAS), Beijing 100190, China
| | - Junjie Fei
- Key Laboratory of Environmentally Friendly Chemistry and Applications of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan 411105, China
| | - Ping Yu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences (CAS), Beijing 100190, China.,School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lanqun Mao
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences (CAS), Beijing 100190, China.,College of Chemistry, Beijing Normal University, Beijing 100875, China
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21
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Biophysical quantification of unitary solute and solvent permeabilities to enable translation to membrane science. J Memb Sci 2022. [DOI: 10.1016/j.memsci.2022.121308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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22
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Lin L, Liu Z, Premadasa UI, Li T, Ma YZ, Sacci RL, Katsaras J, Hong K, Collier CP, Carrillo JMY, Doughty B. The Unexpected Role of Cations in the Self-Assembly of Positively Charged Amphiphiles at Liquid/Liquid Interfaces. J Phys Chem Lett 2022; 13:10889-10896. [PMID: 36394318 DOI: 10.1021/acs.jpclett.2c02921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Conventional wisdom suggests that cations play a minimal role in the assembly of cationic amphiphiles. Here, we show that at liquid/liquid (L/L) interfaces, specific cation effects can modulate the assemblies of hydrophobic tails in an oil phase despite being attached to cationic headgroups in the aqueous phase. We used oligo-dimethylsiloxane (ODMS) methyl imidazolium amphiphiles to identify these specific interactions at hexadecane/aqueous interfaces. Small cations, such as Li+, bind to the O atoms in the ODMS tail and pin it to the interface, thereby imposing a kinked conformation─as evidenced by vibrational sum frequency generation spectroscopy and molecular dynamics simulations. While larger Cs+ ions more readily partition to the interface, they do not form analogous complexes. Our data not only point to ways for controlling amphiphile structure at L/L interfaces but also suggest a means for the separation of Li+, or related applications, in soft-matter electronics.
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Affiliation(s)
- Lu Lin
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
| | - Zening Liu
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
| | - Uvinduni I Premadasa
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
| | - Tianyu Li
- Department of Materials Science and Engineering, University of Tennessee, Knoxville, Tennessee37996, United States
| | - Ying-Zhong Ma
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
| | - Robert L Sacci
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
| | - John Katsaras
- Laboratories and Soft Matter Group, Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
- Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
| | - Kunlun Hong
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
| | - C Patrick Collier
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
| | - Jan-Michael Y Carrillo
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
| | - Benjamin Doughty
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831, United States
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23
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Biolek Z, Biolková V, Biolek D, Kolka Z. Extended and Generic Higher-Order Elements for MEMS Modeling. SENSORS (BASEL, SWITZERLAND) 2022; 22:8007. [PMID: 36298355 PMCID: PMC9607103 DOI: 10.3390/s22208007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 10/10/2022] [Accepted: 10/18/2022] [Indexed: 06/16/2023]
Abstract
State-dependent resistors, capacitors, and inductors are a common part of many smart engineering solutions, e.g., in MEMS (Micro-Electro-Mechanical Systems) sensors and actuators, Micro/NanoMachines, or biomimetic systems. These memory elements are today modeled as generic and extended memristors (MR), memcapacitors (MC), and meminductors (ML), which are more general versions of classical MR, MC, and ML from the infinite set of the fundamental elements of electrical engineering, known as Higher-Order Elements (HOEs). It turns out that models of many complex phenomena in MEMS cannot be constructed only from classical and state-dependent elements such as R, L, and C, but that other HOEs with generalized behavior should also be used. Thus, in this paper, generic and extended versions of HOEs are introduced, overcoming the existing limitation to MR, MC, and ML elements. The relevant circuit theorems are formulated, which generalize the well-known theorems of classical memory elements, and their application to model complex processes of various physical natures in MEMS is shown.
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Affiliation(s)
- Zdeněk Biolek
- Department of Electrical Engineering, University of Defence, 662 10 Brno, Czech Republic
- Department of Microelectronics, Brno University of Technology, 616 00 Brno, Czech Republic
| | - Viera Biolková
- Department of Radio Electronics, Brno University of Technology, 616 00 Brno, Czech Republic
| | - Dalibor Biolek
- Department of Electrical Engineering, University of Defence, 662 10 Brno, Czech Republic
- Department of Microelectronics, Brno University of Technology, 616 00 Brno, Czech Republic
| | - Zdeněk Kolka
- Department of Radio Electronics, Brno University of Technology, 616 00 Brno, Czech Republic
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24
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Koner S, Tawfik J, Mashali F, Kennison KB, McClintic WT, Heberle FA, Tu YM, Kumar M, Sarles SA. Homogeneous hybrid droplet interface bilayers assembled from binary mixtures of DPhPC phospholipids and PB-b-PEO diblock copolymers. BIOCHIMICA ET BIOPHYSICA ACTA. BIOMEMBRANES 2022; 1864:183997. [PMID: 35718208 DOI: 10.1016/j.bbamem.2022.183997] [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: 12/28/2021] [Revised: 06/09/2022] [Accepted: 06/14/2022] [Indexed: 06/15/2023]
Abstract
Hybrid membranes built from phospholipids and amphiphilic block copolymers seek to capitalize on the benefits of both constituents for constructing biomimetic interfaces with improved performance. However, hybrid membranes have not been formed or studied using the droplet interface bilayer (DIB) method, an approach that offers advantages for revealing nanoscale changes in membrane structure and mechanics and offers a path toward assembling higher-order tissues. We report on hybrid droplet interface bilayers (hDIBs) formed in hexadecane from binary mixtures of synthetic diphytanoyl phosphatidylcholine (DPhPC) lipids and low molecular weight 1,2 polybutadiene-b-polyethylene oxide (PBPEO) amphiphilic block copolymers and use electrophysiology measurements and imaging to assess the effects of PBPEO in the membrane. This work reveals that hDIBs containing up to 15 mol% PBPEO plus DPhPC are homogeneously mixtures of lipids and polymers, remain highly resistive to ion transport, and are stable-including under applied voltage. Moreover, they exhibit hydrophobic thicknesses similar to DPhPC-only bilayers, but also have significantly lower values of membrane tension. These characteristics coincide with reduced energy of adhesion between droplets and the formation of alamethicin ion channels at significantly lower threshold voltages, demonstrating that even moderate amounts of amphiphilic block copolymers in a lipid bilayer provide a route for tuning the physical properties of a biomimetic membrane.
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Affiliation(s)
- Subhadeep Koner
- Department of Mechanical Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA
| | - Joseph Tawfik
- Department of Mechanical Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA
| | - Farzin Mashali
- Department of Mechanical Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA
| | - Kristen B Kennison
- Department of Chemistry, University of Tennessee, Knoxville, TN 37996, USA
| | | | | | - Yu-Ming Tu
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Manish Kumar
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78712, USA; Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX 78712, USA
| | - Stephen A Sarles
- Department of Mechanical Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, USA.
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25
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McClintic WT, Scott HL, Moore N, Farahat M, Maxwell M, Schuman CD, Bolmatov D, Barrera FN, Katsaras J, Collier CP. Heterosynaptic plasticity in biomembrane memristors controlled by pH. MRS BULLETIN 2022; 48:13-21. [PMID: 36908998 PMCID: PMC9988737 DOI: 10.1557/s43577-022-00344-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/02/2022] [Indexed: 05/12/2023]
Abstract
Abstract In biology, heterosynaptic plasticity maintains homeostasis in synaptic inputs during associative learning and memory, and initiates long-term changes in synaptic strengths that nonspecifically modulate different synapse types. In bioinspired neuromorphic circuits, heterosynaptic plasticity may be used to extend the functionality of two-terminal, biomimetic memristors. In this article, we explore how changes in the pH of droplet interface bilayer aqueous solutions modulate the memristive responses of a lipid bilayer membrane in the pH range 4.97-7.40. Surprisingly, we did not find conclusive evidence for pH-dependent shifts in the voltage thresholds (V*) needed for alamethicin ion channel formation in the membrane. However, we did observe a clear modulation in the dynamics of pore formation with pH in time-dependent, pulsed voltage experiments. Moreover, at the same voltage, lowering the pH resulted in higher steady-state currents because of increased numbers of conductive peptide ion channels in the membrane. This was due to increased partitioning of alamethicin monomers into the membrane at pH 4.97, which is below the pKa (~5.3-5.7) of carboxylate groups on the glutamate residues of the peptide, making the monomers more hydrophobic. Neutralization of the negative charges on these residues, under acidic conditions, increased the concentration of peptide monomers in the membrane, shifting the equilibrium concentrations of peptide aggregate assemblies in the membrane to favor greater numbers of larger, increasingly more conductive pores. It also increased the relaxation time constants for pore formation and decay, and enhanced short-term facilitation and depression of the switching characteristics of the device. Modulating these thresholds globally and independently of alamethicin concentration and applied voltage will enable the assembly of neuromorphic computational circuitry with enhanced functionality. Impact statement We describe how to use pH as a modulatory "interneuron" that changes the voltage-dependent memristance of alamethicin ion channels in lipid bilayers by changing the structure and dynamical properties of the bilayer. Having the ability to independently control the threshold levels for pore conduction from voltage or ion channel concentration enables additional levels of programmability in a neuromorphic system. In this article, we note that barriers to conduction from membrane-bound ion channels can be lowered by reducing solution pH, resulting in higher currents, and enhanced short-term learning behavior in the form of paired-pulse facilitation. Tuning threshold values with environmental variables, such as pH, provide additional training and learning algorithms that can be used to elicit complex functionality within spiking neural networks. Graphical abstract Supplementary information The online version contains supplementary material available at 10.1557/s43577-022-00344-z.
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Affiliation(s)
- William T. McClintic
- Bredesen Center for Interdisciplinary Research, The University of Tennessee, Knoxville, USA
| | - Haden L. Scott
- Large Scale Structures Group, Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, USA
| | - Nick Moore
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, USA
| | - Mustafa Farahat
- Department of Chemical and Biomolecular Engineering, The University of Tennessee, Knoxville, USA
| | - Mikayla Maxwell
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, USA
| | - Catherine D. Schuman
- Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, USA
| | - Dima Bolmatov
- Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, USA
| | - Francisco N. Barrera
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, USA
| | - John Katsaras
- Large Scale Structures Group, Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, USA
- Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, USA
| | - C. Patrick Collier
- Bredesen Center for Interdisciplinary Research, The University of Tennessee, Knoxville, USA
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, USA
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26
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Xu J, Zhao X, Zhao X, Wang Z, Tang Q, Xu H, Liu Y. Memristors with Biomaterials for Biorealistic Neuromorphic Applications. SMALL SCIENCE 2022. [DOI: 10.1002/smsc.202200028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Affiliation(s)
- Jiaqi Xu
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Xiaoning Zhao
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Xiaoli Zhao
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Zhongqiang Wang
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Qingxin Tang
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Haiyang Xu
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
| | - Yichun Liu
- Key Laboratory of UV Light-Emitting Materials and Technology of Ministry of Education Northeast Normal University Changchun 130024 China
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27
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Xie B, Xiong T, Li W, Gao T, Zong J, Liu Y, Yu P. Perspective on Nanofluidic Memristors: from Mechanism to Application. Chem Asian J 2022; 17:e202200682. [PMID: 35994236 DOI: 10.1002/asia.202200682] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/19/2022] [Indexed: 11/11/2022]
Abstract
Nanofluidic memristors are memory resistors based on nanoconfined fluidic systems exhibiting history-dependent ion conductivity. Toward establishing powerful computing systems beyond the Harvard architecture, these ion-based neuromorphic devices attracted enormous research attention owing to the unique characteristics of ion-based conductors. However, the design of nanofluidic memristor is still at a primary state and a systematic guidance on the rational design of nanofluidic system is desperately required for the development of nanofluidic-based neuromorphic devices. Herein, we proposed a systematic review on the history, main mechanism and potential application of nanofluidic memristors in order to give a prospective view on the design principle of memristors based on nanofluidic systems. Furthermore, based on the present status of these devices, some fundamental challenges for this promising area were further discussed to show the possible application of these ion-based devices.
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Affiliation(s)
- Boyang Xie
- Chinese Academy of Sciences, Institute of Chemistry, No.2, 1st North Street, Zhongguancun, Beijing, China, 100190, Beijing, CHINA
| | - Tianyi Xiong
- Chinese Academy of Sciences, Institute of Chemistry, No.2, 1st North Street, Zhongguancun, Beijing, China, 100190, Beijing, CHINA
| | - Weiqi Li
- Chinese Academy of Sciences, Institute of Chemistry, No.2, 1st North Street Zhongguancun, Beijing, China, 100190, Beijing, CHINA
| | - Tienan Gao
- Chinese Academy of Sciences, Institute of Chemistry, No.2, 1st North Street Zhongguancun, Beijing, China, 100190, Beijing, CHINA
| | - Jianwei Zong
- Chinese Academy of Sciences, Institute of Chemistry, No.2, 1st North Street Zhongguancun, Beijing, 100190, Beijing, CHINA
| | - Ying Liu
- Chinese Academy of Sciences, Institute of Chemistry, No.2, 1st North Street Zhongguancun, Beijing, China, 100190, CHINA
| | - Ping Yu
- Chinese Academy of Sciences, Institute of Chemistry, North first street No. 2, zhonguancun, 100190, Beijing, CHINA
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28
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Challenges and opportunities in achieving the full potential of droplet interface bilayers. Nat Chem 2022; 14:862-870. [PMID: 35879442 DOI: 10.1038/s41557-022-00989-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 05/27/2022] [Indexed: 12/27/2022]
Abstract
Model membranes can be used to elucidate the intricacies of the chemical processes that occur in cell membranes, but the perfectly biomimetic, yet bespoke, model membrane has yet to be built. Droplet interface bilayers are a new type of model membrane able to mimic some features of real cell membranes better than traditional models, such as liposomes and black lipid membranes. In this Perspective, we discuss recent work in the field that is starting to showcase the potential of these model membranes to enable the quantification of membrane processes, such as the behaviour of protein transporters and the prediction of in vivo drug movement, and their use as scaffolds for electrophysiological measurements. We also highlight the challenges that remain to enable droplet interface bilayers to achieve their full potential as artificial cells, and as biological analytical platforms to quantify molecular transport.
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29
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He K, Liu Y, Yu J, Guo X, Wang M, Zhang L, Wan C, Wang T, Zhou C, Chen X. Artificial Neural Pathway Based on a Memristor Synapse for Optically Mediated Motion Learning. ACS NANO 2022; 16:9691-9700. [PMID: 35587990 DOI: 10.1021/acsnano.2c03100] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Animals execute intelligent and efficient interactions with their surroundings through neural pathways, exhibiting learning, memory, and cognition. Artificial autonomous devices that generate self-optimizing feedback mimicking biological systems are essential in pursuing future intelligent robots. Here, we report an artificial neural pathway (ANP) based on a memristor synapse to emulate neuromorphic learning behaviors. In our ANP, optical stimulations are detected and converted into electrical signals through a flexible perovskite photoreceptor. The acquired electrical signals are further processed in a zeolitic imidazolate frameworks-8 (ZIF-8)-based memristor device. By controlling the growth of the ZIF-8 nanoparticles, the conductance of the memristor can be finely modulated with electrical stimulations to mimic the modulation of synaptic plasticity. The device is employed in the ANP to implement synaptic functions of learning and memory. Subsequently, the synaptic feedbacks are used to direct a robotic arm to perform responding motions. Upon repeatedly "reviewing" the optical stimulation, the ANP is able to learn, memorize, and complete the specific motions. This work provides a promising strategy toward the design of intelligent autonomous devices and bioinspired robots through memristor-based systems.
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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
| | - Yaqing Liu
- Key Laboratory of Colloid and Interface Chemistry of the Ministry of Education, School of Chemistry and Chemical Engineering, Shandong University, Jinan, Shandong 250100, China
| | - Jiancan Yu
- 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
| | - Xintong Guo
- 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
| | - Ming 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
| | - Liandong Zhang
- Advanced Robotics and Intelligent Control Centre, Singapore Polytechnic, 500 Dover Road, Singapore 139651, Singapore
| | - Changjin Wan
- 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
| | - Ting 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
| | - Changjiu Zhou
- Advanced Robotics and Intelligent Control Centre, Singapore Polytechnic, 500 Dover Road, Singapore 139651, 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 of Materials Research and Engineering, Agency for Science, Technology and Research, 2 Fusionopolis Way, Innovis, #08-03, Singapore 138634, Singapore
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30
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Liu Z, Lin L, Li T, Kinnun J, Hong K, Ma YZ, Sacci RL, Katsaras J, Carrillo JM, Doughty B, Collier CP. Squeezing Out Interfacial Solvation: The Role of Hydrogen-Bonding in the Structural and Orientational Freedom of Molecular Self-Assembly. J Phys Chem Lett 2022; 13:2273-2280. [PMID: 35239358 DOI: 10.1021/acs.jpclett.1c03941] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Bioinspired membrane molecules with improved physical properties and enhanced stability can serve as functional models for conventional lipid or amphiphilic species. Importantly, these molecules can also provide new insights into emergent phenomena that manifest during self-assembly at interfaces. Here, we elucidate the structural response and mechanistic steps underlying the self-assembly of the amphiphilic, charged oligodimethylsiloxane imidazolium cation (ODMS-MIM+) at the air-aqueous interface using Langmuir trough methods with coincident surface-specific vibrational sum-frequency generation (SFG) spectroscopy. We find evidence for a new compression-induced desolvation step that precedes commonly known disordered-to-ordered phase transitions to form nanoscopic assemblies. The experimental data was supported by atomistic molecular dynamics (MD) simulations to provide a detailed mechanistic picture underlying the assembly and the role of water in these phase transitions. The sensitivity of the hydrophobic ODMS tail conformations to compression─owing to distinct water-ODMS interactions and tail-tail solvation properties─offers new strategies for the design of interfaces that can be further used to develop soft-matter electronics and low-dimensional materials using physical and chemical controls.
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Affiliation(s)
- Zening Liu
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Lu Lin
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Tianyu Li
- Department of Materials Science and Engineering, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Jacob Kinnun
- Neutron Scattering Division and Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Kunlun Hong
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Ying-Zhong Ma
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Robert L Sacci
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - John Katsaras
- Neutron Scattering Division and Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Jan-Michael Carrillo
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Benjamin Doughty
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Charles Patrick Collier
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
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31
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Lin L, Chowdhury AU, Ma YZ, Sacci RL, Katsaras J, Hong K, Collier CP, Carrillo JMY, Doughty B. Ion Pairing and Molecular Orientation at Liquid/Liquid Interfaces: Self-Assembly and Function. J Phys Chem B 2022; 126:2316-2323. [PMID: 35289625 DOI: 10.1021/acs.jpcb.2c01148] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Molecular orientation plays a pivotal role in defining the functionality and chemistry of interfaces, yet accurate measurements probing this important feature are few, due, in part, to technical and analytical limitations in extracting information from molecular monolayers. For example, buried liquid/liquid interfaces, where a complex and poorly understood balance of inter- and intramolecular interactions impart structural constraints that facilitate the formation of supramolecular assemblies capable of new functions, are difficult to probe experimentally. Here, we use vibrational sum-frequency generation spectroscopy, numerical polarization analysis, and atomistic molecular dynamics simulations to probe molecular orientations at buried oil/aqueous interfaces decorated with amphiphilic oligomers. We show that the orientation of self-assembled oligomers changes upon the addition of salts in the aqueous phase. The evolution of these structures can be described by competitive ion effects in the aqueous phase altering the orientations of the tails extending into the oil phase. These specific anionic effects occur via interfacial ion pairing and associated changes in interfacial solvation and hydrogen-bonding networks. These findings provide more quantitative insight into orientational changes encountered during self-assembly and pave the way for the design of functional interfaces for chemical separations, neuromorphic computing applications, and related biomimetic systems.
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Affiliation(s)
- Lu Lin
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Azhad U Chowdhury
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Ying-Zhong Ma
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Robert L Sacci
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - John Katsaras
- Labs and Soft Matter Group, Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States.,Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Kunlun Hong
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - C Patrick Collier
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Jan-Michael Y Carrillo
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Benjamin Doughty
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
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32
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Schuman CD, Kulkarni SR, Parsa M, Mitchell JP, Date P, Kay B. Opportunities for neuromorphic computing algorithms and applications. NATURE COMPUTATIONAL SCIENCE 2022; 2:10-19. [PMID: 38177712 DOI: 10.1038/s43588-021-00184-y] [Citation(s) in RCA: 111] [Impact Index Per Article: 55.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 12/07/2021] [Indexed: 01/06/2024]
Abstract
Neuromorphic computing technologies will be important for the future of computing, but much of the work in neuromorphic computing has focused on hardware development. Here, we review recent results in neuromorphic computing algorithms and applications. We highlight characteristics of neuromorphic computing technologies that make them attractive for the future of computing and we discuss opportunities for future development of algorithms and applications on these systems.
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Affiliation(s)
- Catherine D Schuman
- Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA.
| | - Shruti R Kulkarni
- Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Maryam Parsa
- Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA
| | - J Parker Mitchell
- Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Prasanna Date
- Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Bill Kay
- Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
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33
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Guo J, Xu H, Zhao J, Gao Z, Wu ZQ, Song YY. Locally superengineered cascade recognition–quantification zones in nanochannels for sensitive enantiomer identification. Chem Sci 2022; 13:9993-10002. [PMID: 36128237 PMCID: PMC9430310 DOI: 10.1039/d2sc03198a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 08/08/2022] [Indexed: 11/23/2022] Open
Abstract
As an intriguing and intrinsic feature of life, chirality is highly associated with many significant biological processes. Simultaneous recognition and quantification of enantiomers remains a major challenge. Here, a sensitive enantiomer identification device is developed on TiO2 nanochannels via the design of cascade recognition–quantification zones along the nanochannels. In this system, β-cyclodextrin (β-CD) is self-assembled on one side of the nanochannels for the selective recognition of enantiomers; CuMOFs are designed as the target-responsive partners on the other side of the nanochannels for the quantification of enantiomers that pass through the nanochannels. As a proof-of-principle of the cascade design, arginine (Arg) enantiomers are tested as the identification targets. The l-Arg molecules selectively bind in the recognition zone; d-Arg molecules pass through the recognition zone and then interact with the quantification zone via a specialized reduction reaction. As verified by nanofluidic simulations, because of the confinement effect of nanoscale channels combined with the condensation effect of porous structure, the in situ reaction in the quantification zone contributes to an unprecedented variation in transmembrane K+ flux, leading to an improved identification signal. This novel cascade-zone nanochannel membrane provides a smart strategy to design multifunctional nanofluidic devices. A design of the cascade recognition–quantification zone is developed along TiO2 nanochannels. The asymmetric nanochannels exhibit a predominant sensitivity and selectivity for enantiomer discrimination.![]()
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Affiliation(s)
- Junli Guo
- College of Sciences, Northeastern University, Shenyang 110819, China
| | - Huijie Xu
- College of Sciences, Northeastern University, Shenyang 110819, China
| | - Junjian Zhao
- College of Sciences, Northeastern University, Shenyang 110819, China
| | - Zhida Gao
- College of Sciences, Northeastern University, Shenyang 110819, China
| | - Zeng-Qiang Wu
- School of Public Health, Nantong University, Nantong, 226019, China
| | - Yan-Yan Song
- College of Sciences, Northeastern University, Shenyang 110819, China
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Abstract
Bio-memristors constitute candidates for the next generation of non-volatile storage and bionic synapses due to their biocompatibility, environmental benignity, sustainability, flexibility, degradability, and impressive memristive performance. Silk fibroin (SF), a natural and abundant biomaterial with excellent mechanical, optical, electrical, and structure-adjustable properties as well as being easy to process, has been utilized and shown to have potential in the construction of bio-memristors. Here, we first summarize the fundamental mechanisms of bio-memristors based on SF. Then, the latest achievements and developments of pristine and composited SF-based memristors are highlighted, followed by the integration of memristive devices. Finally, the challenges and insights associated with SF-based bio-memristors are presented. Advances in SF-based bio-memristors will open new avenues in the design and integration of high-performance bio-integrated systems and facilitate their application in logic operations, complex circuits, and neural networks.
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Affiliation(s)
- Yi Zhang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, P. R. China.
| | - Suna Fan
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, P. R. China.
| | - Yaopeng Zhang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, P. R. China.
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35
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Meng D, Hao C, Cai J, Ma W, Chen C, Xu C, Xu L, Kuang H. Tailored Chiral Copper Selenide Nanochannels for Ultrasensitive Enantioselective Recognition and Detection. Angew Chem Int Ed Engl 2021; 60:24997-25004. [PMID: 34463011 DOI: 10.1002/anie.202109920] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 08/21/2021] [Indexed: 11/07/2022]
Abstract
We constructed a tailorable membrane channel system consisting of penicillamine molecules intercalated in copper selenide nanoparticles (Cu2-x Se NPs), which exhibited circular dichroism (CD) bands in the near infrared region (CD, 800-1600 nm) with a maximum intensity of 164.5 mdeg at 1440 nm. The chiral ligand hybridized to the surface of achiral Cu2-x Se NPs by breaking the intrinsic symmetry of Cu2-x Se NPs and further large-scale assembly induced strong optical activity. The fabricated multilayer chiral membrane achieved an increased rectification ratio (RR) up to 114. The integration of penicillamine allowed for high enantioselective recognition against naproxen,which displayed high sensitivity with a limit of detection (LOD) as low as 0.027 nM.
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Affiliation(s)
- Dan Meng
- State Key Lab of Food Science and Technology, International Joint Research Laboratory for Biointerface and Biodetection, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China
| | - Changlong Hao
- State Key Lab of Food Science and Technology, International Joint Research Laboratory for Biointerface and Biodetection, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China
| | - Jiarong Cai
- State Key Lab of Food Science and Technology, International Joint Research Laboratory for Biointerface and Biodetection, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China
| | - Wei Ma
- State Key Lab of Food Science and Technology, International Joint Research Laboratory for Biointerface and Biodetection, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China
| | - Chen Chen
- State Key Lab of Food Science and Technology, International Joint Research Laboratory for Biointerface and Biodetection, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China
| | - Chuanlai Xu
- State Key Lab of Food Science and Technology, International Joint Research Laboratory for Biointerface and Biodetection, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China
| | - Liguang Xu
- State Key Lab of Food Science and Technology, International Joint Research Laboratory for Biointerface and Biodetection, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China
| | - Hua Kuang
- State Key Lab of Food Science and Technology, International Joint Research Laboratory for Biointerface and Biodetection, School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China
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36
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Meng D, Hao C, Cai J, Ma W, Chen C, Xu C, Xu L, Kuang H. Tailored Chiral Copper Selenide Nanochannels for Ultrasensitive Enantioselective Recognition and Detection. Angew Chem Int Ed Engl 2021. [DOI: 10.1002/ange.202109920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Dan Meng
- State Key Lab of Food Science and Technology International Joint Research Laboratory for Biointerface and Biodetection School of Food Science and Technology Jiangnan University Wuxi Jiangsu 214122 P. R. China
| | - Changlong Hao
- State Key Lab of Food Science and Technology International Joint Research Laboratory for Biointerface and Biodetection School of Food Science and Technology Jiangnan University Wuxi Jiangsu 214122 P. R. China
| | - Jiarong Cai
- State Key Lab of Food Science and Technology International Joint Research Laboratory for Biointerface and Biodetection School of Food Science and Technology Jiangnan University Wuxi Jiangsu 214122 P. R. China
| | - Wei Ma
- State Key Lab of Food Science and Technology International Joint Research Laboratory for Biointerface and Biodetection School of Food Science and Technology Jiangnan University Wuxi Jiangsu 214122 P. R. China
| | - Chen Chen
- State Key Lab of Food Science and Technology International Joint Research Laboratory for Biointerface and Biodetection School of Food Science and Technology Jiangnan University Wuxi Jiangsu 214122 P. R. China
| | - Chuanlai Xu
- State Key Lab of Food Science and Technology International Joint Research Laboratory for Biointerface and Biodetection School of Food Science and Technology Jiangnan University Wuxi Jiangsu 214122 P. R. China
| | - Liguang Xu
- State Key Lab of Food Science and Technology International Joint Research Laboratory for Biointerface and Biodetection School of Food Science and Technology Jiangnan University Wuxi Jiangsu 214122 P. R. China
| | - Hua Kuang
- State Key Lab of Food Science and Technology International Joint Research Laboratory for Biointerface and Biodetection School of Food Science and Technology Jiangnan University Wuxi Jiangsu 214122 P. R. China
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37
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Korner JL, Elvira KS. The role of temperature in the formation of human-mimetic artificial cell membranes using droplet interface bilayers (DIBs). SOFT MATTER 2021; 17:8891-8901. [PMID: 34543370 DOI: 10.1039/d1sm00668a] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Droplet interface bilayers (DIBs) have recently started to be used as human-mimetic artificial cell membranes. DIBs are bilayer sections created at the interface of two aqueous droplets, such that one droplet can be used as a donor compartment and the other as an acceptor compartment for the quantification of molecular transport across the artificial cell membrane. However, synthetic phospholipids are overwhelmingly used to create DIBs instead of naturally derived phospholipids, even though the diverse distribution of phospholipids in the latter is more biomimetic. We present the first systematic study of the role of temperature in DIB formation, which shows that the temperature at which DIBs are formed is a key parameter for the formation of DIBs using naturally derived phospholipids in a microfluidic platform. The phospholipids that are most abundant in mammalian cell membranes (phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), and phosphatidylinositol (PI)) only form DIBs when the temperature is above the phase transition temperature (Tm). Similarly, DIB formation usually only occurs above the highest Tm of a single phospholipid in a bespoke formulation. In addition, we show a new phenomenon wherein the DIB "melts" without disintegrating for bilayers formed predominantly of phospholipids that occupy cylindrical spaces. We also demonstrate differences in DIB formation rates as well as permeability of these biomimetic membranes. Given the difficulties associated with making DIBs using naturally derived phospholipids, we anticipate this work will illuminate the role of phospholipid phase transition in mono- and bilayer formation and lay the foundation for DIBs to be used as human-mimetic artificial cell membranes.
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Affiliation(s)
- Jaime L Korner
- Department of Chemistry, University of Victoria, Victoria, BC, Canada.
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38
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Lin L, Chowdhury AU, Ma YZ, Sacci RL, Katsaras J, Hong K, Collier CP, Carrillo JMY, Doughty B. Ion Pairing Mediates Molecular Organization Across Liquid/Liquid Interfaces. ACS APPLIED MATERIALS & INTERFACES 2021; 13:33734-33743. [PMID: 34235915 DOI: 10.1021/acsami.1c09763] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Liquid/liquid interfaces play a central role in scientific fields ranging from nanomaterial synthesis and soft matter electronics to nuclear waste remediation and chemical separations. This diversity of functions arises from an interface's ability to respond to changing conditions in its neighboring bulk phases. Understanding what drives this interfacial flexibility can provide novel avenues for designing new functional interfaces. However, limiting this progress is an inadequate understanding of the subtle intermolecular and interphase interactions taking place at the molecular level. Here, we use surface-specific vibrational sum frequency generation spectroscopy combined with atomistic molecular dynamics simulations to investigate the self-assembly and structure of model ionic oligomers consisting of an oligodimethylsiloxane (ODMS) tail covalently attached to a positively charged methyl imidazolium (MIM+) head group at buried oil/aqueous interfaces. We show how the presence of seemingly innocuous salts can impart dramatic changes to the ODMS tail conformations in the oil phase via specific ion effects and ion-pairing interactions taking place in the aqueous phase. These specific ion interactions are shown to drive enhanced amphiphile adsorption, induce morphological changes, and disrupt emergent hydrogen-bonding structures at the interface. Tuning these interactions allows for independent control over the oligomer structure in the oil phase versus interfacial population changes and represents key mechanistic insight that is needed to control chemical reactions at liquid/liquid interfaces.
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Affiliation(s)
- Lu Lin
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Azhad U Chowdhury
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Ying-Zhong Ma
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Robert L Sacci
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - John Katsaras
- Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
- Shull Wollan Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Kunlun Hong
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - C Patrick Collier
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Jan-Michael Y Carrillo
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Benjamin Doughty
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
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39
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Zhang Y, Han F, Fan S, Zhang Y. Low-Power and Tunable-Performance Biomemristor Based on Silk Fibroin. ACS Biomater Sci Eng 2021; 7:3459-3468. [PMID: 34165975 DOI: 10.1021/acsbiomaterials.1c00513] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Biomemristors have attracted significant attention because of their potential applications in logic operations, nonvolatile memory, and synaptic emulators, thus leading to the urgent need to improve memristive performance. In this work, a silk fibroin (SF)-based memristor, integrated with both low power and low operating current simultaneously, has been reported. Doping the SF with Ag and an ethanol-based post-treatment promote microcrystal formation in the bulk of the SF. This induces carrier transport along fixed, short paths and results in a low set voltage, low operating current, and high memristive stability. Such performances can greatly reduce power consumption and heat generation, beneficial for the accuracy and durability of memristor devices. The memristive mechanism of SF-based memristors with different Ag contents is the space-charge-limited conduction (SCLC) mechanism. In addition, the nonlinear transmission property of SF-based memristors suggests useful applications in bioelectronics.
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Affiliation(s)
- Yi Zhang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, P. R. China
| | - Fang Han
- College of Information Science and Technology, Donghua University, Shanghai 201620, P. R. China
| | - Suna Fan
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, P. R. China
| | - Yaopeng Zhang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, P. R. China
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40
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Sun J, Han J, Wang Y, Liu P. Memristor-Based Neural Network Circuit of Emotion Congruent Memory With Mental Fatigue and Emotion Inhibition. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2021; 15:606-616. [PMID: 34156947 DOI: 10.1109/tbcas.2021.3090786] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Most memristor-based neural networks only consider a single mode of memory or emotion, but ignore the relationship between emotion and memory. In this paper, a memristor-based neural network circuit of emotion congruent memory is proposed and verified by the simulation results. The designed circuit consists of a memory module, an emotion module and an association neuron module. Varieties of memory and emotion functions are considered. The functions such as learning, forgetting, variable rate and emotion generation are implemented by the circuit. Furthermore, mental fatigue and emotion inhibition which are two important self-protective measures of the brain are realized in this paper on the basis of emotion congruent memory. Finally, the paper also considers the congruence between emotion and memory materials and the regulation of emotion on memory. The neural network circuit of emotion congruent memory can provide more references for the application of memristor.
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41
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Wang K, Hu Q, Gao B, Lin Q, Zhuge FW, Zhang DY, Wang L, He YH, Scheicher RH, Tong H, Miao XS. Threshold switching memristor-based stochastic neurons for probabilistic computing. MATERIALS HORIZONS 2021; 8:619-629. [PMID: 34821279 DOI: 10.1039/d0mh01759k] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Biological neurons exhibit dynamic excitation behavior in the form of stochastic firing, rather than stiffly giving out spikes upon reaching a fixed threshold voltage, which empowers the brain to perform probabilistic inference in the face of uncertainty. However, owing to the complexity of the stochastic firing process in biological neurons, the challenge of fabricating and applying stochastic neurons with bio-realistic dynamics to probabilistic scenarios remains to be fully addressed. In this work, a novel CuS/GeSe conductive-bridge threshold switching memristor is fabricated and singled out to realize electronic stochastic neurons, which is ascribed to the similarity between the stochastic switching behavior observed in the device and that of biological ion channels. The corresponding electric circuit of a stochastic neuron is then constructed and the probabilistic firing capacity of the neuron is utilized to implement Bayesian inference in a spiking neural network (SNN). The application prospects are demonstrated on the example of a tumor diagnosis task, where common fatal diagnostic errors of a conventional artificial neural network are successfully circumvented. Moreover, in comparison to deterministic neuron-based SNNs, the stochastic neurons enable SNNs to deliver an estimate of the uncertainty in their predictions, and the fidelity of the judgement is drastically improved by 81.2%.
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Affiliation(s)
- Kuan Wang
- Wuhan National Laboratory for Optoelectronics, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
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42
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Li C, Xiong T, Yu P, Fei J, Mao L. Synaptic Iontronic Devices for Brain-Mimicking Functions: Fundamentals and Applications. ACS APPLIED BIO MATERIALS 2021; 4:71-84. [PMID: 35014277 DOI: 10.1021/acsabm.0c00806] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Inspired by the information transmission mechanism in the central nervous systems of life, synapse-mimicking devices have been designed and fabricated for the purpose of breaking the bottleneck of von Neumann architecture and realizing the construction of effective hardware-based artificial intelligence. In this case, synaptic iontronic devices, dealing with current information with ions instead of electrons, have attracted enormous scientific interests owing to their unique characteristics provided by ions, such as the designability of charge carriers and the diversity of chemical regulation. Herein, the basic conception, working mechanism, performance metrics, and advanced applications of synaptic iontronic devices based on three-terminal transistors and two-terminal memristors are systematically reviewed and comprehensively discussed. This Review provides a prospect on how to realize artificial synaptic functions based on the regulation of ions and raises a series of further challenges unsolved in this area.
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Affiliation(s)
- Changwei Li
- Key Laboratory of Environmentally Friendly Chemistry and Applications of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan 411105, China.,Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, the Chinese Academy of Sciences (CAS), Beijing 100190, China
| | - Tianyi Xiong
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, the Chinese Academy of Sciences (CAS), Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ping Yu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, the Chinese Academy of Sciences (CAS), Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Junjie Fei
- Key Laboratory of Environmentally Friendly Chemistry and Applications of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan 411105, China
| | - Lanqun Mao
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, the Chinese Academy of Sciences (CAS), Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
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43
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Park HL, Kim MH, Kim MH, Lee SH. Reliable organic memristors for neuromorphic computing by predefining a localized ion-migration path in crosslinkable polymer. NANOSCALE 2020; 12:22502-22510. [PMID: 33174583 DOI: 10.1039/d0nr06964g] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
In flexible neuromorphic systems for realizing artificial intelligence, organic memristors are essential building blocks as artificial synapses to perform information processing and memory. Despite much effort to implement artificial neural networks (ANNs) using organic memristors, the reliability of these devices is inherently hampered by global ion transportation and arbitrary growth of conductive filaments (CFs). As a result, the performance of ANNs is restricted. Herein, a novel concept for confining CF growth in organic memristors is demonstrated by exploiting the unique functionality of crosslinkable polymers. This can be achieved by predefining the localized ion-migration path (LIP) in crosslinkable polymers. In the proposed organic memristor, metal cations are locally transported along the LIP. Thus, CF growth is achieved only in a confined region. A flexible memristor with an LIP exhibits a vastly improved reliability and uniformity, and it is capable of operating with high mechanical and electrical endurance. Moreover, neuromorphic arrays based on the proposed memristor exhibit 96.3% learning accuracy, which is comparable to the ideal software baseline. The proposed concept of predefining the LIP in organic memristors is expected to provide novel platforms for the advance of flexible electronics and to realize a variety of practical neural networks for artificial intelligence applications.
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Affiliation(s)
- Hea-Lim Park
- Department of Materials Science and Engineering, Gwanak-ku, Seoul National University, Seoul 151-600, Republic of Korea.
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44
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Lee SH, Park HL, Kim MH, Kim MH, Park BG, Lee SD. Realization of Biomimetic Synaptic Functions in a One-Cell Organic Resistive Switching Device Using the Diffusive Parameter of Conductive Filaments. ACS APPLIED MATERIALS & INTERFACES 2020; 12:51719-51728. [PMID: 33151051 DOI: 10.1021/acsami.0c15519] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Toward the successful development of artificial intelligence, artificial synapses based on resistive switching devices are essential ingredients to perform information processing in spiking neural networks. In neural processes, synaptic plasticity related to the history of neuron activity plays a critical role during learning. In resistive switching devices, it is barely possible to emulate both short-term plasticity and long-term plasticity due to the uncontrollable dynamics of the conductive filaments (CFs). Despite extensive effort to realize synaptic plasticity in such devices, it is still challenging to achieve reliable synaptic functions due to the overgrowth of CFs in a random fashion. Herein, we propose an organic resistive switching device with bio-realistic synaptic functions by adjusting the CF diffusive parameter. In the proposed device, complete synaptic plasticity provides the history-dependent change in the conductance. Moreover, the homeostatic feedback, which resembles the biological process, regulates CF growth in our device, which enhances the reliability of synaptic plasticity. This novel concept for realizing synaptic functions in organic resistive switching devices may provide a physical platform to advance the fundamental understanding of learning and memory mechanisms and develop a variety of neural circuits and neuromorphic systems that can be linked to artificial intelligence and next-generation computing paradigm.
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Affiliation(s)
- Sin-Hyung Lee
- School of Electronics Engineering, and School of Electronic and Electrical Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 702-701, Republic of Korea
| | - Hea-Lim Park
- Department of Materials Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Min-Hoi Kim
- Department of Creative Convergence Engineering, Hanbat National University, Yuseong-gu, Daejeon 305-719, Republic of Korea
| | - Min-Hwi Kim
- School of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Byung-Gook Park
- School of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Sin-Doo Lee
- School of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
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45
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George R, Chiappalone M, Giugliano M, Levi T, Vassanelli S, Partzsch J, Mayr C. Plasticity and Adaptation in Neuromorphic Biohybrid Systems. iScience 2020; 23:101589. [PMID: 33083749 PMCID: PMC7554028 DOI: 10.1016/j.isci.2020.101589] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Neuromorphic systems take inspiration from the principles of biological information processing to form hardware platforms that enable the large-scale implementation of neural networks. The recent years have seen both advances in the theoretical aspects of spiking neural networks for their use in classification and control tasks and a progress in electrophysiological methods that is pushing the frontiers of intelligent neural interfacing and signal processing technologies. At the forefront of these new technologies, artificial and biological neural networks are tightly coupled, offering a novel "biohybrid" experimental framework for engineers and neurophysiologists. Indeed, biohybrid systems can constitute a new class of neuroprostheses opening important perspectives in the treatment of neurological disorders. Moreover, the use of biologically plausible learning rules allows forming an overall fault-tolerant system of co-developing subsystems. To identify opportunities and challenges in neuromorphic biohybrid systems, we discuss the field from the perspectives of neurobiology, computational neuroscience, and neuromorphic engineering.
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Affiliation(s)
- Richard George
- Department of Electrical Engineering and Information Technology, Technical University of Dresden, Dresden, Germany
| | | | - Michele Giugliano
- Neuroscience Area, International School of Advanced Studies, Trieste, Italy
| | - Timothée Levi
- Laboratoire de l’Intégration du Matéeriau au Systéme, University of Bordeaux, Bordeaux, France
- LIMMS/CNRS, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
| | - Stefano Vassanelli
- Department of Biomedical Sciences and Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Johannes Partzsch
- Department of Electrical Engineering and Information Technology, Technical University of Dresden, Dresden, Germany
| | - Christian Mayr
- Department of Electrical Engineering and Information Technology, Technical University of Dresden, Dresden, Germany
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46
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Xiao K, Wan C, Jiang L, Chen X, Antonietti M. Bioinspired Ionic Sensory Systems: The Successor of Electronics. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2020; 32:e2000218. [PMID: 32500602 DOI: 10.1002/adma.202000218] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 03/30/2020] [Accepted: 03/30/2020] [Indexed: 06/11/2023]
Abstract
All biological systems, including animals and plants, communicate in a language of ions and small molecules, while the modern information infrastructures and technologies rely on a language of electrons. Although electronics and bioelectronics have made great progress in the past several decades, they still face the disadvantage of signal transformation when communicating with biology. To narrow the gap between biological systems and artificial-intelligence systems, bioinspired ion-transport-based sensory systems should be developed as successor of electronics, since they can emulate biological functionality more directly and communicate with biology seamlessly. Herein, the essential principles of (accurate) ion transport are introduced, and the recent progress in the development of three elements of an ionic sensory system is reviewed: ionic sensors, ionic processors, and ionic interfaces. The current challenges and future developments of ion-transport-based sensory systems are also discussed.
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Affiliation(s)
- Kai Xiao
- Max Planck Institute of Colloids and Interfaces, Department of Colloid Chemistry, Potsdam, 14476, Germany
| | - Changjin Wan
- Innovative Center 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
| | - Lei Jiang
- Key Key Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, 100190, P. R. China
| | - Xiaodong Chen
- Innovative Center 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
| | - Markus Antonietti
- Max Planck Institute of Colloids and Interfaces, Department of Colloid Chemistry, Potsdam, 14476, Germany
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47
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Ge J, Ma Z, Chen W, Cao X, Yan J, Fang H, Qin J, Liu Z, Pan S. Solution-processed inorganic δ-phase CsPbI 3 electronic synapses with short- and long-term plasticity in a crossbar array structure. NANOSCALE 2020; 12:13558-13566. [PMID: 32555883 DOI: 10.1039/d0nr03242e] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Electronic synapses based on memristive devices can potentially open a niche area for neuromorphic computing by replicating the function of biological synapses with high fidelity. Recently, two-terminal memristors based on halide perovskites have demonstrated outstanding memristive properties and a variety of synaptic characteristics, combining with their additional advantages such as a solution-processed fabrication method and low crystalline temperature. However, the concerns over the chemical and phase stability of halide perovskites greatly hinder their practical applications. In this study, by using a simple single-step spin-coating method, we report artificial synapses with superior ambient stability (>90 days under ambient conditions) based on fully inorganic nonperovskite δ-phase CsPbI3 in a cross-bar array architecture. The threshold switching memristive device exhibits a moderate ON/OFF ratio, a relatively low operation voltage (0.3 V) and high endurance (>5 × 105). More importantly, the electronic device can emulate synaptic characteristics such as short-term plasticity, paired-pulse facilitation, and the transition from short-term memory to long-term memory with a high output signal-to-noise ratio (>102). This work represents the first record for artificial synapses based on nonperovskite CsPbI3 and will be a step toward achieving low-cost and high-density practical synapse arrays.
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Affiliation(s)
- Jun Ge
- Solid State Physics & Material Research Laboratory, School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, 510006, China.
| | - Zelin Ma
- Solid State Physics & Material Research Laboratory, School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, 510006, China.
| | - Weilong Chen
- Solid State Physics & Material Research Laboratory, School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, 510006, China.
| | - Xucheng Cao
- Solid State Physics & Material Research Laboratory, School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, 510006, China.
| | - Jianfeng Yan
- Solid State Physics & Material Research Laboratory, School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, 510006, China.
| | - Huaheng Fang
- Solid State Physics & Material Research Laboratory, School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, 510006, China.
| | - Jieli Qin
- Solid State Physics & Material Research Laboratory, School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, 510006, China.
| | - Zhiyu Liu
- Solid State Physics & Material Research Laboratory, School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, 510006, China.
| | - Shusheng Pan
- Solid State Physics & Material Research Laboratory, School of Physics and Electronic Engineering, Guangzhou University, Guangzhou, 510006, China.
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48
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Arrabito G, Ferrara V, Bonasera A, Pignataro B. Artificial Biosystems by Printing Biology. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e1907691. [PMID: 32511894 DOI: 10.1002/smll.201907691] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 05/09/2020] [Indexed: 05/09/2023]
Abstract
The continuous progress of printing technologies over the past 20 years has fueled the development of a plethora of applications in materials sciences, flexible electronics, and biotechnologies. More recently, printing methodologies have started up to explore the world of Artificial Biology, offering new paradigms in the direct assembly of Artificial Biosystems (small condensates, compartments, networks, tissues, and organs) by mimicking the result of the evolution of living systems and also by redesigning natural biological systems, taking inspiration from them. This recent progress is reported in terms of a new field here defined as Printing Biology, resulting from the intersection between the field of printing and the bottom up Synthetic Biology. Printing Biology explores new approaches for the reconfigurable assembly of designed life-like or life-inspired structures. This work presents this emerging field, highlighting its main features, i.e., printing methodologies (from 2D to 3D), molecular ink properties, deposition mechanisms, and finally the applications and future challenges. Printing Biology is expected to show a growing impact on the development of biotechnology and life-inspired fabrication.
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Affiliation(s)
- Giuseppe Arrabito
- Department of Physics and Chemistry - Emilio Segrè, University of Palermo, Viale delle Scienze, Building 17, Palermo, 90128, Italy
| | - Vittorio Ferrara
- Department of Physics and Chemistry - Emilio Segrè, University of Palermo, Viale delle Scienze, Building 17, Palermo, 90128, Italy
- Department of Chemical Sciences, University of Catania, Viale Andrea Doria, 6, Catania, 95125, Italy
| | - Aurelio Bonasera
- Department of Physics and Chemistry - Emilio Segrè, University of Palermo, Viale delle Scienze, Building 17, Palermo, 90128, Italy
| | - Bruno Pignataro
- Department of Physics and Chemistry - Emilio Segrè, University of Palermo, Viale delle Scienze, Building 17, Palermo, 90128, Italy
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49
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McClintic WT, Taylor GJ, Simpson ML, Collier CP. Macromolecular Crowding Affects Voltage-Dependent Alamethicin Pore Formation in Lipid Bilayer Membranes. J Phys Chem B 2020; 124:5095-5102. [DOI: 10.1021/acs.jpcb.0c01650] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- William T. McClintic
- The Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Graham J. Taylor
- The Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Michael L. Simpson
- The Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, Tennessee 37996, United States
- Center for Nanophase Material Science, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - C. Patrick Collier
- The Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, Tennessee 37996, United States
- Center for Nanophase Material Science, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
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50
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Liu S, Chen X, Liu G. Conjugated polymers for information storage and neuromorphic computing. POLYM INT 2020. [DOI: 10.1002/pi.6017] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Shuzhi Liu
- School of Chemistry and Chemical Engineering Shanghai Jiao Tong University Shanghai China
| | - Xinhui Chen
- School of Chemistry and Chemical Engineering Shanghai Jiao Tong University Shanghai China
| | - Gang Liu
- School of Chemistry and Chemical Engineering Shanghai Jiao Tong University Shanghai China
- Green Catalysis Center and College of Chemistry Zhengzhou University Zhengzhou China
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