研究者詳細 - 宇佐美　雄生

論文 - 宇佐美　雄生

分割表示31 件中 1 - 20 件目／全件表示 >>

Effect of electronic state for in-materio physical reservoir computing performance with a porphyrin-polyoxometalate/single-walled carbon nanotube network 査読有り国際誌

Usami Y., Murazoe S., Banerjee D., Kotooka T., Tanaka H.

Applied Physics Letters 126 ( 8 ) 2025年02月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（学術雑誌）

Semiconducting single-walled carbon nanotube (SWNT)/porphyrin-polyoxometalate (por-POM) networks were fabricated using [H4tBuTPP]2[SV2W10O40] (tBu H4TPP-POM) and [H4TPP]2[SV2W10O40] (H4TPP-POM) to compare their reservoir computing (RC) performances. Nonlinear electrical properties, phase shifts, and higher harmonics, which are required for superior RC performances, were generated in SWNT/por-POM networks. Lissajous plots show various phase shifts as the input frequency decreases, reflecting the relaxation time of the dynamics in the por-POMs. The SWNT/H4TPP-POM network exhibits the best performance of the RC benchmark task, indicating that H4TPP-POM generates rich chemical dynamics based on different charge accumulation with different electronic state in por-POM.

DOI： 10.1063/5.0245122

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85218881331&origin=inward

In-Materio Reservoir Computing in a Sulfonated Polyaniline Network 査読有り

Usami Y., van de Ven B., Mathew D.G., Chen T., Kotooka T., Kawashima Y., Tanaka Y., Otsuka Y., Ohoyama H., Tamukoh H., Tanaka H., van der Wiel W.G., Matsumoto T.

Advanced Materials 33 ( 48 ) 2102688 2021年09月

担当区分：筆頭著者記述言語：英語掲載種別：研究論文（学術雑誌）

A sulfonated polyaniline (SPAN) organic electrochemical network device (OEND) is fabricated using a simple drop-casting method on multiple Au electrodes for use in reservoir computing (RC). The SPAN network has humidity-dependent electrical properties. Under high humidity, the SPAN OEND exhibits mainly ionic conduction, including charging of an electric double layer and ionic diffusion. The nonlinearity and hysteresis of the current–voltage characteristics progressively increase with increasing humidity. The rich dynamic output behavior indicates wide variations for each electrode, which improves the RC performance because of the disordered network. For RC, waveform generation and short-term memory tasks are realized by a linear combination of outputs. The waveform task accuracy and memory capacity calculated from a short-term memory task reach 90% and 33.9, respectively. Improved spoken-digit classification is realized with 60% accuracy by only 12 outputs, demonstrating that the SPAN OEND can manage time series dynamic data operation in RC owing to a combination of rich dynamic and nonlinear electronic properties. The results suggest that SPAN-based electrochemical systems can be applied for material-based computing, by exploiting their intrinsic physicochemical behavior.

DOI： 10.1002/adma.202102688

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85114995164&origin=inward

導電性高分子ネットワークを用いたマテリアルリザバー演算招待有り査読有り

宇佐美雄生, 琴岡匠, 松本卓也, 田中啓文

表面と真空 ( 公益社団法人日本表面真空学会 ) 67 ( 11 ) 527 - 532 2024年11月

担当区分：筆頭著者記述言語：日本語掲載種別：研究論文（学術雑誌）

<p>Artificial intelligence (AI) has rapidly advanced and is being utilized across a wide range of fields by developing artificial neural network (ANN). However, constructing large-scale ANNs requires significant power consumption. In the field of materials and device engineering, “physical reservoir computing (physical RC)” is gaining attention to perform ANN computations with low power consumption. Unlike traditional ANNs, physical RC leverages physical properties for computation, resulting in energy efficiency. Conductive polymers such as polyaniline are expected to exhibit excellent performance in in-materio physical reservoir computing (IMRC) due to their superior environmental stability and reversible doping behavior. This paper introduces about utilizing the mixed polaron-ion conductivity of sulfonated polyaniline (SPAN), evaluating changes in electrical properties with humidity adjustments, and exploring its potential application in IMRC by investigating the correlation between the electrical properties and computational ability.</p>

DOI： 10.1380/vss.67.527

その他リンク： http://id.ndl.go.jp/bib/033827434

ナノマテリアルランダムネットワークを利用した物理リザバー演算素子とそのセンシング応用招待有り

田中啓文, アズハリサマン, バナジーディープ, 君塚紘喜, 田中悠一朗, 宇佐美雄生

表面と真空 ( 公益社団法人日本表面真空学会 ) 67 ( 9 ) 428 - 432 2024年09月

記述言語：日本語掲載種別：記事・総説・解説・論説等（学術雑誌）

<p>The rapid advancement of software-based deep learning has led to a surge in AI applications, yet hardware limitations in silicon CMOS technology hinder performance. Consequently, interest is growing in hardware technologies and new materials for artificial neural networks (ANNs) and neuromorphic systems. Exploiting nanomaterials nonlinearity caused by spontaneous physical phenomena holds promise of reducing power consumption in AI hardware. Reservoir computing devices, derived from recurrent neural networks, play a crucial role, with material reservoir devices showcasing “material intelligence.” Tailored nanomaterials for reservoir devices hold potential for revolutionizing AI, especially in robotics. As research progresses, focusing on device functionalization and applications, recent findings underline the significance of integrating nanomaterials into AI hardware for enhanced computational capabilities and energy efficiency.</p>

DOI： 10.1380/vss.67.428

その他リンク： https://www.jstage.jst.go.jp/article/vss/67/9/67_20181334/_pdf

A new physical reservoir using the complex dynamics of electric fields in type-II superconductors containing pinning centers interacting with quantized magnetic flux lines 査読有り国際誌

Arita K., Ueda T., Otabe E.S., Usami Y., Tanaka H., Matsuno T.

Physica C: Superconductivity and its Applications 622 2024年07月

記述言語：英語掲載種別：研究論文（学術雑誌）

Reservoir computing, which takes advantage of physical phenomena with nonlinearities, is attracting a lot of attention. Therefore, it is expected to focus on superconductivity, a physical phenomenon with nonlinearities between the output electric field and the input current density. Compared to other physical phenomena used in reservoirs, it is considered that with superconductivity, the nonlinearity can easily be adjusted spatially by pin placement to produce dynamics suitable for reservoirs. The nonlinearity between the electric field generated by the motion of the quantized magnetic flux lines and the input current density was used to perform a reservoir computing task. Three waveform generation tasks, a NARMA2 task and a nonlinear-memory task were performed, and all tasks were generally successful. It was found that the electromagnetic phenomenon in superconductors can be used as a physical reservoir.

DOI： 10.1016/j.physc.2024.1354522

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85194199384&origin=inward

High Performance of an In-Material Reservoir Computing Device Achieved by Complex Dynamics in a Nanoparticle Random Network Memristor 査読有り国際誌

Srikimkaew O., Banerjee D., Azhari S., Usami Y., Tanaka H.

ACS Applied Electronic Materials 6 ( 2 ) 688 - 695 2024年02月

記述言語：英語掲載種別：研究論文（学術雑誌）

An in-material reservoir computing (RC) device with an Ag-Ag2S core-shell nanoparticle (NP) network is proposed. Network-wide nonlinear sine-wave outputs of higher frequencies and varying phases were produced from the different Ag+ ion diffusion rates and filament formation caused by the heterogeneous NP size in the thiol layer. Such emergent dynamics of multiple information regimes enabled the reconstruction of Fourier waves, with a maximum accuracy of 99% achieved only for trained outputs with mixed spatiotemporal complexities. Additionally, the device showed stable retrieval of past information with a two-times-step delay and successfully computed a two-step time-series prediction task with 87% accuracy.

DOI： 10.1021/acsaelm.3c01046

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85181823293&origin=inward

Effect of nonlinearity induced by atomic switch in Ag/Ag<inf>2</inf>S nanoparticles on performance of in-materio reservoir computing 査読有り国際誌

Dang T.T., Srikimkaew O., Banerjee D., Azhari S., Usami Y., Tanaka H.

Applied Physics Letters 124 ( 9 ) 2024年02月

記述言語：英語掲載種別：研究論文（学術雑誌）

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.

DOI： 10.1063/5.0169067

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85186372242&origin=inward

Visualizing Ribbon-to-Ribbon Heterogeneity of Chemically Unzipped Wide Graphene Nanoribbons by Silver Nanowire-Based Tip-Enhanced Raman Scattering Microscopy 査読有り国際誌

Inose T., Toyouchi S., Hara S., Sugioka S., Walke P., Oyabu R., Fortuni B., Peeters W., Usami Y., Hirai K., De Feyter S., Uji-i H., Fujita Y., Tanaka H.

Small 20 ( 3 ) 2024年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

Graphene nanoribbons (GNRs), a quasi-one-dimensional form of graphene, have gained tremendous attention due to their potential for next-generation nanoelectronic devices. The chemical unzipping of carbon nanotubes is one of the attractive fabrication methods to obtain single-layered GNRs (sGNRs) with simple and large-scale production. The authors recently found that unzipping from double-walled carbon nanotubes (DWNTs), rather than single- or multi-walled, results in high-yield production of crystalline sGNRs. However, details of the resultant GNR structure, as well as the reaction mechanism, are not fully understood due to the necessity of nanoscale spectroscopy. In this regard, silver nanowire-based tip-enhanced Raman spectroscopy (TERS) is applied for single GNR analysis and investigated ribbon-to-ribbon heterogeneity in terms of defect density and edge structure generated through the unzipping process. The authors found that sGNRs originated from the inner walls of DWNTs showed lower defect densities than those from the outer walls. Furthermore, TERS spectra of sGNRs exhibit a large variety in graphitic Raman parameters, indicating a large variation in edge structures. This work at the single GNR level reveals, for the first time, ribbon-to-ribbon heterogeneity that can never be observed by diffraction-limited techniques and provides deeper insights into unzipped GNR structure as well as the DWNT unzipping reaction mechanism.

DOI： 10.1002/smll.202301841

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85169170888&origin=inward

Short-Term and Long-Term Memory Functionality of a Brain-Like Device Built from Nanoparticle Atomic Switch Networks 招待有り査読有り国際誌

Srikimkaew O., Azhari S., Banerjee D., Usami Y., Tanaka H.

Advanced Electronic Materials 10 ( 12 ) 2024年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

The synaptic plasticity of the Ag-Ag2S nanoparticle-based volatile memristor system is demonstrated. The nanoparticles self-assemble into a network with over 103 interconnected atomic switch interfaces. Short-term plasticity is identified by spontaneous conductance relaxation, attributed to the memristor's volatility. The conductance of the network is enhanced when a subsequent stimulus pulse arrives shortly after the previous one, analogous to the paired-pulse facilitation in biological synapses. Furthermore, repeated pulse stimulation is used to achieve the transition from short-term plasticity to long-term potentiation, a process related to learning and memory formation. Remarkably, the result reveals that the lifetime of long-term potentiation for 100-pulse stimulation is 40 min, indicating that the device can forget newly acquired information after prolonged storage, akin to human memories. The findings provide insight into the the learning and memory abilities of atomic switch network memristors, facilitating the development of hardware-implemented artificial neural networks.

DOI： 10.1002/aelm.202400360

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85203194268&origin=inward

Volatile and Nonvolatile Dual-Mode Switching Operations in an Ag-Ag<inf>2</inf>S Core-Shell Nanoparticle Atomic Switch Network 査読有り国際誌

Srikimkaew O., Ricci S., Porzani M., Dang T.T., Nakaoka Y., Usami Y., Ielmini D., Tanaka H.

Advanced Electronic Materials 10 ( 10 ) 2024年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

This paper proposes a nanoparticle-based atomic switch network memristive device, capable of both volatile and nonvolatile switching operations, which have not been previously reported for this material. The operational modes can be determined by altering the compliance current, demonstrating high stability over 100 cycles. Analysis of the conduction mechanism using I–V curves reveals switching characteristics consistent with space-charge-limited current conduction during the set process and ohmic behavior in the reset state. Furthermore, this study analyzes these dual-operational modes in devices with varying electrode spacings. The results indicate that a wider spacing necessitated a higher compliance current for the volatile-to-nonvolatile transition, underscoring the significance of interconnection. These findings facilitate the integration of neuron and synapse functions within a single atomic switch network device, thereby advancing neuromorphic systems.

DOI： 10.1002/aelm.202300709

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85197746392&origin=inward

Object recognition and grasping point detection using carbon nanotube - polydimethylsiloxane nanocomposite sensor 招待有り査読有り国際誌

Tokuno Shoshi, Kimizuka Kouki, Tanaka Yuichiro, Usami Yuki, Tanaka Hirofumi, Tamukoh Hakaru

Nonlinear Theory and Its Applications, IEICE ( 一般社団法人電子情報通信学会 ) 15 ( 4 ) 883 - 898 2024年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

<p>This paper presents a system for processing tactile information using a carbon nanotube (CNT)-polydimethylsiloxane (PDMS) nanocomposite sensor designed for robotic applications. This study introduces an approach for recognizing objects and detecting optimal grasping points using tactile data from a sensor-equipped robotic hand. The sensor is expected to be more efficient than a computerized implementation using sensor dynamics directly in the computation. The experiments demonstrated the system's ability to classify nine types of objects with an accuracy of 83.56% and to discern two grasping points on four object types, achieving a 71.7% success rate.</p>

DOI： 10.1587/nolta.15.883

その他リンク： https://www.jstage.jst.go.jp/article/nolta/15/4/15_883/_pdf

Mel-frequency cepstral coefficients feature extracted voice recognition task using atomic switch Ag/Ag<sub>2</sub>S device-based time-delayed reservoir computing 招待有り査読有り国際誌

Karacali Ahmet, Nakao Yusuke, Srikimkaew Oradee, Abdi Gisya, Szacilowski Konrad, Usami Yuki, Tanaka Hirofumi

Nonlinear Theory and Its Applications, IEICE ( 一般社団法人電子情報通信学会 ) 15 ( 4 ) 871 - 882 2024年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

<p>Neuromorphic devices have diverse potential applications, such as brain-inspired computers and promising high-performance arithmetic systems with power saving. Reservoir computing (RC), a type of recurrent neural network (RNN), achieves learning by adjusting the weights between the intermediate and output layers. Time-delay reservoir computing introduces a delay and creates virtual nodes within the middle layer. The Ag/Ag<sub>2</sub>S nanoparticles function as nonlinear electrical devices, following the atomic switch principles of the time-delay system. Voice recognition was performed with 87.81% accuracy when six different people pronounced the same number, and 80.18% when the same person pronounced ten different numbers.</p>

DOI： 10.1587/nolta.15.871

その他リンク： https://www.jstage.jst.go.jp/article/nolta/15/4/15_871/_pdf

Performance improvement of in-materio reservoir computing by noise injection 招待有り査読有り国際誌

Hakoshima M., Usami Y., Kotooka T., Tanaka H.

Japanese Journal of Applied Physics 62 2023年06月

担当区分：責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

Computation performance of in-materio reservoir device was evaluated by varying intensity of noise injection. Materials for the reservoir device was synthesized using a α-Fe2O3/titanium bismuth oxide composite by using the sol-gel method. The prepared samples were characterized by conducting X-ray diffractmetry, transmission electron microscopy, and energy dispersive X-ray spectroscopy to confirm presence of α-Fe2O3, TiO2, and Bi4Ti3O12 nanoparticles. The I-V and V-t curves show nonlinearity, and phase differences between input and output signals, and the fast Fourier transform of the V-t curve showed high harmonics at the input sine wave with 11 Hz of frequency. In the waveform prediction task, the prediction accuracy was improved only when a small intensity of white noise voltage was superimposed to the input information signal.

DOI： 10.35848/1347-4065/acbd5b

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85152129564&origin=inward

Integration of Wireless Power Transfer Technology With Hierarchical Multiwalled Carbon Nanotubes-Polydimethylsiloxane Piezo-Responsive Pressure Sensor for Remote Force Measurement 査読有り国際誌

Azhari S., Kimizuka K., Mehes G., Usami Y., Hayashi Y., Tanaka H., Miyake T.

IEEE Sensors Journal 23 ( 7 ) 7902 - 7909 2023年04月

記述言語：英語掲載種別：研究論文（学術雑誌）

Integrating sensory devices with wireless power transfer technology for remote sensing (RS) requires the implementation of complex electronic circuitry and communication protocols. To overcome this challenge and remotely monitor mechanical force, we directly integrated piezo-responsive porous multiwalled carbon nanotubes (MWCNTs)/polydimethylsiloxane (PDMS) nanocomposites with a near-field wireless power transfer system. The wireless system transfers power bidirectionally between the transmitter and the sensing receiver at the resonant frequency of 13.56 MHz. The detection principle is based on the mechanical force-induced impedance changes in the receiver circuit. The modulated impedance signal is detected wirelessly at the transmitter circuit via a full-bridge rectifier and a smoothing capacitor. Furthermore, we demonstrate the wireless monitoring of finger bending and applied force using our flexible and disposable sensor without using any energy storage devices. The results suggest a response and recovery time of 400 ± 50 ms, strain sensitivity of 24.73, and pressure sensitivity of 0.98. Our approach adds a new path for disposable haptic-based sensory applications that do not require complex communication protocols in medical, robotics, and other fields.

DOI： 10.1109/JSEN.2023.3248021

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85149370379&origin=inward

分子が学ぶ画像認識招待有り

宇佐美雄生

化学 ( 株式会社化学同人 ) 78 ( 4 ) 59 - 60 2023年03月

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

Azhari S., Banerjee D., Kotooka T., Usami Y., Tanaka H.

Nanoscale 15 ( 18 ) 8169 - 8180 2023年02月

記述言語：英語掲載種別：研究論文（学術雑誌）

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 by fabricating an in materio reservoir computing (RC) device because of a complex random network topology with nonlinear dynamics. One of the significant drawbacks of a two-dimensional physical reservoir system is the difficulty in controlling the network density. This work reports the use of a 3D porous template as a scaffold to fabricate a three-dimensional network of a single-walled carbon nanotube polyoxometalate nanocomposite. Although the three-dimensional system exhibits better nonlinear dynamics and spatiotemporal dynamics, and higher harmonics generation than a two-dimensional system, the results suggest a correlation between a higher number of resistive junctions and reservoir performance. We show that by increasing the spatial dimension of the device, the memory capacity improves, while the scale-free network exponent (γ) remains nearly unchanged. The three-dimensional device also displays improved performance in the well-known RC benchmark task of waveform generation. This study demonstrates the impact of an additional spatial dimension, network distribution and network density on in materio RC device performance and tries to shed some light on the reason behind such behavior.

DOI： 10.1039/d2nr04619a

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85150509508&origin=inward

Random network device fabricated using Ag2Se nanowires for data augmentation with binarized convolutional neural network 査読有り国際誌

Kotooka T., Tanaka Y., Tamukoh H., Usami Y., Tanaka H.

Applied Physics Express 16 ( 1 ) 2023年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

An Ag2Se nanowire random network was fabricated for application as a data augmentation device and combined with a binary convolutional neural network (BCNN) to achieve high accuracy in voice classification tasks. Due to the nonlinear high-dimensional characteristics resulting from the formation of the conductive filament at the cross junction, the Ag2Se device could transform input data into higher-order multiple signals, thereby enhancing the accuracy of the classification task by augmenting input signals. The results indicate that materials can realize data augmentation with the same performance as software, suggesting that material-based hardware can be used as an elemental technology for information processing.

DOI： 10.35848/1882-0786/acae6a

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85146494177&origin=inward

In-material reservoir implementation of reservoir-based convolution 査読有り国際誌

Tanaka Y., Usami Y., Tanaka H., Tamukoh H.

Proceedings - IEEE International Symposium on Circuits and Systems 2023-May 2023年01月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

This study aims to implement a reservoir-based convolutional neural network (CNN) on physical reservoir computing (RC) to develop an efficient image recognition system for edge AI. Therefore, we propose a novel reservoir-based convolution circuit system that uses in-material reservoir computing, a type of physical RC made from a sulfonated polyaniline network. The experimental results demonstrate that the proposed circuit system extracts image features in the same way as the original CNN and that a reservoir-based CNN on the in-material RC achieves an accuracy rate of 81.7% in an image classification task while an echo state network-based CNN achieves 87.7%.

DOI： 10.1109/ISCAS46773.2023.10181436

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85167720431&origin=inward

In-materio computing in random networks of carbon nanotubes complexed with chemically dynamic molecules: a review 招待有り査読有り国際誌

Hirofumi Tanaka, Saman Azhari, Yuki Usami, Deep Banerjee, Takumi Kotooka, Oradee Srikimkaew, Thien-Tan Dang, S Murazoe, R Oyabu, Kouki Kimizuka, Masaya Hakoshima

Neuromorphic Computing and Engineering ( IOP publishing ) 2 ( 2 ) 022002 2022年05月

記述言語：英語掲載種別：研究論文（学術雑誌）

The need for highly energy-efficient information processing has sparked a new age of material-based computational devices. Among these, random networks (RNWs) of carbon nanotubes (CNTs) complexed with other materials have been extensively investigated owing to their extraordinary characteristics. However, the heterogeneity of CNT research has made it quite challenging to comprehend the necessary features of in-materio computing in a RNW of CNTs. Herein, we systematically tackle the topic by reviewing the progress of CNT applications, from the discovery of individual CNT conduction to their recent uses in neuromorphic and unconventional (reservoir) computing. This review catalogues the extraordinary abilities of random CNT networks and their complexes used to conduct nonlinear in-materio computing tasks as well as classification tasks that may replace current energy-inefficient systems.

DOI： 10.1088/2634-4386/ac676a

DOI： 10.1088/2634-4386/ac676a

その他リンク： https://iopscience.iop.org/article/10.1088/2634-4386/ac676a

In-materio Reservoir Working at Low Frequencies in a Ag 2 S-island Network 招待有り査読有り国際誌

Motoharu Nakajima, Kazuki Minegishi, Yosuke Shimizu, Yuki Usami, Hirofumi Tanaka, Tsuyoshi Hasegawa

Nanoscale ( Royal Society of Chemistry ) 14 ( 20 ) 7634 - 7640 2022年05月

記述言語：英語掲載種別：研究論文（学術雑誌）

A Ag2S-island network is fabricated with surrounding electrodes to enable it to be used as a reservoir for unconventional computing. Local conductance change occurs due to the growth/shrinkage of Ag filaments from/into each Ag2S island in the reservoir. The growth/shrinkage of Ag filaments is caused by the drift of Ag+ cations in each Ag2S island, which results in a unique non-linear response as a reservoir, especially at lower frequencies. The response of the reservoir is shown to depend on the frequency and amplitude of the input signals. So as to evaluate its capability as a reservoir, logical operations were performed using the subject Ag2S-island network, with the results showing an accuracy of greater than 99%.

DOI： 10.1039/D2NR01439D

DOI： 10.1039/D2NR01439D

その他リンク： https://pubs.rsc.org/en/content/articlelanding/2022/NR/D2NR01439D

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