Influence of junction resistance on spatiotemporal dynamics and reservoir computing performance arising from an SWNT/POM 3D network formed <i>via</i> a scaffold template technique

Azhari, Saman; Banerjee, Deep; Kotooka, Takumi; Usami, Yuki; Tanaka, Hirofumi

doi:10.1039/d2nr04619a

Cited by 3 publications

(3 citation statements)

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“…Various physical reservoirs have been used in the reservoir layer, [11][12][13][14][15][16][17] and research into materials-based reservoir computing is currently accelerating. [18][19][20] For example, reservoir computing research exists using atomic switch technologies to control the growth and contraction of Ag filaments from Ag 2 S. 12,21,22) Ag 2 S reservoirs have also been used for benchmarking tasks such as STM, PC, and MNIST image recognition and optical pattern classification. 23,24) In terms of social implementation of artificial intelligence, AI robot development using machine learning, such as deep learning, has been conducted in recent years, [25][26][27] which will meet the increasing demand for care and assistance robots.…”

Section: Introductionmentioning

confidence: 99%

Research on tactile sensation by physical reservoir computing with a robot arm and a Ag₂S reservoir

Yoshimura,

Hasegawa

2024

Jpn. J. Appl. Phys.

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In recent years, physical reservoir computing has attracted much attention because of its low computational cost and low power consumption. In terms of social implementation of artificial intelligence, physical reservoir has a potential to meet the request, such as the need for AI robots to process information related to tactile sensation. It has been reported that a Ag2S polycrystalline thin film retains short-term memory and non-linearity when used as a physical reservoir. In this study, we applied the technique to tactile sensation by combining with a pressure sensor attached to a robot arm. In the object grasping task, a Ag2S physical reservoir enabled the objective recognition with the accuracy of 81.3%, although the task failed with linear regression of the direct output from the pressure sensor. We also demonstrate the potential of the system to detect anomalies in object grabbing.

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Section: Introductionmentioning

confidence: 99%

Research on tactile sensation by physical reservoir computing with a robot arm and a Ag₂S reservoir

Yoshimura,

Hasegawa

2024

Jpn. J. Appl. Phys.

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“…For example, the extension of the network topology inside the material reservoir to 3D has recently been reported to improve the performance of in materio RC with better nonlinear dynamics and memory capacity. [ 16 ] Based on these backgrounds, we aim to develop a 3D wiring technique in this study for CPWs composed of poly(3,4‐ethylenedioxy‐thiophene) doped with poly(styrene sulfonate) anions (PEDOT:PSS). PEDOT:PSS is one of the most widely used conductive polymers for manufacturing flexible and transparent electrodes, [ 17 ] electrochromic devices, [ 18 ] and thermoelectric devices [ 19 ] because of its high conductivity, transparency, flexibility, and stability.…”

Section: Introductionmentioning

confidence: 99%

Fabrication and Training of 3D Conductive Polymer Networks for Neuromorphic Wetware

Hagiwara

Asai

Ando

et al. 2023

Adv Funct Materials

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The human brain possesses an exceptional information processing capability owing to the 3D and dense network architecture of numerous neurons and synapses. Brain‐inspired neuromorphic hardware can also benefit from 3D architectures, such as high integration of circuits and acquisition of highly complex dynamical systems. In this study, for future 3D neuromorphic engineering, 3D conductive polymer networks consisting of poly(3,4‐ethylenedioxy‐thiophene) doped with poly(styrene sulfonate) anions (PEDOT:PSS) are successfully and stably fabricated between multiple electrodes from scratch in precursor solution by electropolymerization. The networks efficiently emulate the 3D local connections between neighboring neurons observed in the cortex. This novel technology, which allows 3D conductive wiring only between desired electrodes, is unprecedented and has potential as an underlying technology for 3D integration. Furthermore, the experimental results also conclusively prove that conductance modification can be performed by manipulating the physical and chemical properties of 3D branch‐wired conductive polymer wires, thus demonstrating for the first time the feasibility of neuromorphic wetware with enhanced biological plausibility in the subsequent post‐Moore era.

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“…This phenomenon is a frequently observed occurrence in diverse nonlinear systems that rely on physical reservoirs. 12,20,[38][39][40] In addition, we demonstrated the RC task of Boolean logic optimization-a common nonlinear operation utilized in practical computing 28,41 that cannot be solved without nonlinear data transformation. 41 The device was integrated with a measurement system controlled by LabVIEW software.…”

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confidence: 99%

Effect of nonlinearity induced by atomic switch in Ag/Ag2S nanoparticles on performance of in-materio reservoir computing

Dang,

Srikimkaew,

Banerjee

et al. 2024

Applied Physics Letters

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A random network of Ag/Ag2S nanoparticles (NPs) was used as a physical system in reservoir computing (RC) because the network has nonlinear and dynamical characteristics. Ag/Ag2S NPs were synthesized by the modified Brust–Schiffrin method. Atomic switching among the NPs caused nonlinear dynamical behavior of the random network. The Fourier transform of output signals indicated that the generated harmonics were far higher with a larger amplitude of the input sine wave because the atomic switching occurred only at high bias voltages. Higher accuracy was achieved in the Boolean logic RC task because of the nonlinearity originating from switching. These findings suggest that nonlinearity plays a fundamental role in the design and implementation of RC devices.

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Influence of junction resistance on spatiotemporal dynamics and reservoir computing performance arising from an SWNT/POM 3D network formed via a scaffold template technique

Abstract: For scientists in numerous fields, creating a physical device that can function like the human brain is an aspiration. It is believed that we may achieve brain-like spatiotemporal information processing...

Cited by 3 publications

References 79 publications

Research on tactile sensation by physical reservoir computing with a robot arm and a Ag₂S reservoir

Research on tactile sensation by physical reservoir computing with a robot arm and a Ag₂S reservoir

Fabrication and Training of 3D Conductive Polymer Networks for Neuromorphic Wetware

Effect of nonlinearity induced by atomic switch in Ag/Ag2S nanoparticles on performance of in-materio reservoir computing

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Influence of junction resistance on spatiotemporal dynamics and reservoir computing performance arising from an SWNT/POM 3D network formed via a scaffold template technique

Abstract: For scientists in numerous fields, creating a physical device that can function like the human brain is an aspiration. It is believed that we may achieve brain-like spatiotemporal information processing...

Cited by 3 publications

References 79 publications

Research on tactile sensation by physical reservoir computing with a robot arm and a Ag2S reservoir

Research on tactile sensation by physical reservoir computing with a robot arm and a Ag2S reservoir

Fabrication and Training of 3D Conductive Polymer Networks for Neuromorphic Wetware

Effect of nonlinearity induced by atomic switch in Ag/Ag2S nanoparticles on performance of in-materio reservoir computing

Contact Info

Product

Resources

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Research on tactile sensation by physical reservoir computing with a robot arm and a Ag₂S reservoir

Research on tactile sensation by physical reservoir computing with a robot arm and a Ag₂S reservoir