Effect of electronic state for in-materio physical reservoir computing performance with a porphyrin-polyoxometalate/single-walled carbon nanotube network

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.

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Publication Details

Journal
Applied Physics Letters
Published
2025-02-01
DOI
https://doi.org/10.1063/5.0245122
Citations
4
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
9.92

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article

Effect of electronic state for in-materio physical reservoir computing performance with a porphyrin-polyoxometalate/single-walled carbon nanotube network

Deep Banerjee, Takumi Kotooka, Yuki Usami, Hirofumi Tanaka et al.
4 citations
Applied Physics Letters
Neural Networks and Reservoir Computing
9.92
article

Effect of electronic state for in-materio physical reservoir computing performance with a porphyrin-polyoxometalate/single-walled carbon nanotube network

Deep Banerjee, Takumi Kotooka, Yuki Usami, Hirofumi Tanaka, Shuho Murazoe
article en
4 citations

Abstract

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.

Applied Physics LettersVol. 126(8)
Kyushu Institute of Technology (JP)
Japan Society for the Promotion of Science, Japan Science and Technology Agency, Core Research for Evolutional Science and Technology, ACT-X
Openalex Percentile: Top 3%
Neural Networks and Reservoir Computing
9.92
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