Article Machine Learning—Guided Design of Biomass‐Based Porous Carbon for Aqueous Symmetric Supercapacitors

Manickam Minakshi ORCID ; Apsana Sharma ; Ferdous Sohel ; Almantas Pivrikas ORCID ; Pragati A. Shinde ORCID ; Katsuhiko Ariga SAMURAI ORCID ; Lok Kumar Shrestha SAMURAI ORCID

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Manickam Minakshi, Apsana Sharma, Ferdous Sohel, Almantas Pivrikas, Pragati A. Shinde, Katsuhiko Ariga, Lok Kumar Shrestha. Machine Learning—Guided Design of Biomass‐Based Porous Carbon for Aqueous Symmetric Supercapacitors. ChemPlusChem. 2025, 90 (10), e202500342. https://doi.org/10.1002/cplu.202500342

Description:

(abstract)

In this study, we employ a machine learning (ML) approach to analyze experimental data from previously reported sources, enabling the prediction of specific capacitance (F/g) based on various material characteristics and processing conditions. The trained ML model evaluates the influence of factors such as biomass type, electrolyte, activating agent, and key synthesis parameters, including activation and carbonization temperatures and durations, on supercapacitor performance.

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Keyword: biomass, carbon, dopant, energy, machine learning, storage

Date published: 2025-10-09

Publisher: Wiley

Journal:

  • ChemPlusChem (ISSN: 21926506) vol. 90 issue. 10 e202500342

Funding:

  • Japan Society for the Promotion of Science JP20H00392
  • Japan Society for the Promotion of Science JP23H05459

Manuscript type: Publisher's version (Version of record)

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First published URL: https://doi.org/10.1002/cplu.202500342

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Updated at: 2025-10-21 16:06:10 +0900

Published on MDR: 2025-10-21 15:43:24 +0900

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