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Przyczyna D, Mech K, Kowalewska E, Marzec M, Mazur T, Zawal P, Szaciłowski K. The Memristive Properties and Spike Timing-Dependent Plasticity in Electrodeposited Copper Tungstates and Molybdates. MATERIALS (BASEL, SWITZERLAND) 2023; 16:6675. [PMID: 37895657 PMCID: PMC10608134 DOI: 10.3390/ma16206675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 09/28/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023]
Abstract
Memristors possess non-volatile memory, adjusting their electrical resistance to the current that flows through them and allowing switching between high and low conducting states. This technology could find applications in fields such as IT, consumer electronics, computing, sensors, and medicine. In this paper, we report successful electrodeposition of thin-film materials consisting of copper tungstate and copper molybdate (CuWO4 and Cu3Mo2O9), which showed notable memristive properties. Material characterisation was performed with techniques such as XRD, XPS, and SEM. The electrodeposited materials exhibited the ability to switch between low and high resistive states during varied cyclic scans and short-term impulses. The retention time of these switched states was also explored. Using these materials, the effects seen in biological systems, specifically spike timing-dependent plasticity, were simulated, being based on analogue operation of the memristors to achieve multiple conductivity states. Bio-inspired simulations performed directly on the material could possibly offer energy and time savings for classical computations. Memristors could be crucial for the advancement of high-efficiency, low-energy neuromorphic electronic devices and technologies in the future.
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Affiliation(s)
- Dawid Przyczyna
- Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland; (D.P.); (K.M.); (E.K.); (M.M.); (T.M.); (P.Z.)
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland
| | - Krzysztof Mech
- Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland; (D.P.); (K.M.); (E.K.); (M.M.); (T.M.); (P.Z.)
| | - Ewelina Kowalewska
- Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland; (D.P.); (K.M.); (E.K.); (M.M.); (T.M.); (P.Z.)
| | - Mateusz Marzec
- Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland; (D.P.); (K.M.); (E.K.); (M.M.); (T.M.); (P.Z.)
| | - Tomasz Mazur
- Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland; (D.P.); (K.M.); (E.K.); (M.M.); (T.M.); (P.Z.)
| | - Piotr Zawal
- Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland; (D.P.); (K.M.); (E.K.); (M.M.); (T.M.); (P.Z.)
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland
| | - Konrad Szaciłowski
- Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland; (D.P.); (K.M.); (E.K.); (M.M.); (T.M.); (P.Z.)
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Crepaldi M, Mohan C, Garofalo E, Adamatzky A, Szaciłowski K, Chiolerio A. Experimental Demonstration of In-Memory Computing in a Ferrofluid System. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2211406. [PMID: 36919899 DOI: 10.1002/adma.202211406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/27/2023] [Indexed: 06/09/2023]
Abstract
Magnetic fluids are excellent candidates for several important research fields including energy harvesting, biomedical applications, soft robotics, and exploration. However, notwithstanding relevant advancements such as shape reconfigurability, that have been demonstrated, there is no evidence for their computing capability, including the emulation of synaptic functions, which requires complex non-linear dynamics. Here, it is experimentally demonstrated that a Fe3 O4 water-based ferrofluid (FF) can perform electrical analogue computing and be programmed using quasi direct current (DC) signals and read at radio frequency (RF) mode. Features have been observed in all respects attributable to a memristive behavior, featuring both short and long-term information storage capacity and plasticity. The colloid is capable of classifying digits of a 8 × 8 pixel dataset using a custom in-memory signal processing scheme, and through physical reservoir computing by training a readout layer. These findings demonstrate the feasibility of in-memory computing using an amorphous FF system in a liquid aggregation state. This work poses the basis for the exploitation of a FF colloid as both an in-memory computing device and as a full-electric liquid computer thanks to its fluidity and the reported complex dynamics, via probing read-out and programming ports.
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Affiliation(s)
- Marco Crepaldi
- Electronic Design Laboratory, Istituto Italiano di Tecnologia, Via Melen 83, Genova, Liguria, 16152, Italy
| | - Charanraj Mohan
- Electronic Design Laboratory, Istituto Italiano di Tecnologia, Via Melen 83, Genova, Liguria, 16152, Italy
| | - Erik Garofalo
- Bioinspired Soft Robotics, Istituto Italiano di Tecnologia, Via Morego 30, Genova, Liguria, 16163, Italy
| | - Andrew Adamatzky
- Unconventional Computing Laboratory, University of West England, Frenchay Campus, Coldharbour Ln, Bristol, Bristol, BS16 1QY, UK
| | - Konrad Szaciłowski
- Academic Centre for Materials and Nanotechnology, AGH University of Technology, 30 Mickiewicza Avenue, Kraków, 30-059, Poland
| | - Alessandro Chiolerio
- Bioinspired Soft Robotics, Istituto Italiano di Tecnologia, Via Morego 30, Genova, Liguria, 16163, Italy
- Unconventional Computing Laboratory, University of West England, Frenchay Campus, Coldharbour Ln, Bristol, Bristol, BS16 1QY, UK
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Kheirabadi NR, Chiolerio A, Szaciłowski K, Adamatzky A. Neuromorphic Liquids, Colloids, and Gels: A Review. Chemphyschem 2023; 24:e202200390. [PMID: 36002385 PMCID: PMC10092099 DOI: 10.1002/cphc.202200390] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 08/23/2022] [Indexed: 01/07/2023]
Abstract
Advances in flexible electronic devices and robotic software require that sensors and controllers be virtually devoid of traditional electronic components, be deformable and stretch-resistant. Liquid electronic devices that mimic biological synapses would make an ideal core component for flexible liquid circuits. This is due to their unbeatable features such as flexibility, reconfiguration, fault tolerance. To mimic synaptic functions in fluids we need to imitate dynamics and complexity similar to those that occurring in living systems. Mimicking ionic movements are considered as the simplest platform for implementation of neuromorphic in material computing systems. We overview a series of experimental laboratory prototypes where neuromorphic systems are implemented in liquids, colloids and gels.
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Affiliation(s)
| | - Alessandro Chiolerio
- Unconventional Computing Laboratory, UWE, Bristol, UK.,Center for Bioinspired Soft Robotics, Istituto Italiano di Tecnologia, Genova, Italy
| | - Konrad Szaciłowski
- Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Krakow, Poland
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Huang W, Xia X, Zhu C, Steichen P, Quan W, Mao W, Yang J, Chu L, Li X. Memristive Artificial Synapses for Neuromorphic Computing. NANO-MICRO LETTERS 2021; 13:85. [PMID: 34138298 PMCID: PMC8006524 DOI: 10.1007/s40820-021-00618-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 01/29/2021] [Indexed: 05/06/2023]
Abstract
Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the von Neumann architecture. This computing is realized based on memristive hardware neural networks in which synaptic devices that mimic biological synapses of the brain are the primary units. Mimicking synaptic functions with these devices is critical in neuromorphic systems. In the last decade, electrical and optical signals have been incorporated into the synaptic devices and promoted the simulation of various synaptic functions. In this review, these devices are discussed by categorizing them into electrically stimulated, optically stimulated, and photoelectric synergetic synaptic devices based on stimulation of electrical and optical signals. The working mechanisms of the devices are analyzed in detail. This is followed by a discussion of the progress in mimicking synaptic functions. In addition, existing application scenarios of various synaptic devices are outlined. Furthermore, the performances and future development of the synaptic devices that could be significant for building efficient neuromorphic systems are prospected.
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Affiliation(s)
- Wen Huang
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China.
| | - Xuwen Xia
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Chen Zhu
- College of Electronic and Optical Engineering and College of Microelectronics, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Parker Steichen
- Department of Materials Science and Engineering, University of Washington, Seattle, WA, 98195-2120, USA
| | - Weidong Quan
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Weiwei Mao
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Jianping Yang
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China
| | - Liang Chu
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China.
| | - Xing'ao Li
- New Energy Technology Engineering Laboratory of Jiangsu Province and School of Science, Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, 210023, People's Republic of China.
- Key Laboratory for Organic Electronics and Information Displays and Institute of Advanced Materials, Jiangsu National Synergistic Innovation Center for Advanced Materials, School of Materials Science and Engineering, Nanjing University of Posts and Telecommunications (NUPT), 9 Wenyuan Road, Nanjing, 210023, People's Republic of China.
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The Fuzziness in Molecular, Supramolecular, and Systems Chemistry. MOLECULES (BASEL, SWITZERLAND) 2020; 25:molecules25163634. [PMID: 32785069 PMCID: PMC7463983 DOI: 10.3390/molecules25163634] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 08/07/2020] [Indexed: 12/31/2022]
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