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.
Authors
- Deep Banerjee (ORCID: https://orcid.org/0000-0003-1726-1867)
- Takumi Kotooka (ORCID: https://orcid.org/0000-0002-4513-1878)
- Yuki Usami (ORCID: https://orcid.org/0000-0002-8583-325X)
- Hirofumi Tanaka (ORCID: https://orcid.org/0000-0002-4378-5747)
- Shuho Murazoe
Institutions
- Kyushu Institute of Technology (JP)
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
Funders
- Japan Society for the Promotion of Science
- Japan Science and Technology Agency
- Core Research for Evolutional Science and Technology
- ACT-X