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

https://mdr.nims.go.jp/datasets/8d976e81-304b-4f26-b331-a96a48adb478

## File

- [ChemPlusChem25_90_e202500342.pdf](https://mdr.nims.go.jp/filesets/7d89d933-1fcc-4e5f-8c67-a3a933267340/download) ([Detail](https://mdr.nims.go.jp/filesets/7d89d933-1fcc-4e5f-8c67-a3a933267340.md))

## Id

8d976e81-304b-4f26-b331-a96a48adb478

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2025-10-11T09:01:01.376354Z

## Updated at

2025-10-21T07:06:10.012198Z

## Published at

2025-10-21T06:43:24.882518Z

## Doi



## First published url

https://doi.org/10.1002/cplu.202500342

## Date published

2025-10-09

## Recorded date published

2025-10-9

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Machine Learning—Guided Design of Biomass‐Based Porous Carbon for Aqueous
    Symmetric Supercapacitors
  title_type: original
  lang: en

## Description

- description: '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. '
  description_type: abstract
  lang: und

## Creator

- name: Manickam Minakshi
  role: author
  orcid: https://orcid.org/0000-0001-6558-8317
- name: Apsana Sharma
  role: author
- name: Ferdous Sohel
  role: author
- name: Almantas Pivrikas
  role: author
  orcid: https://orcid.org/0000-0002-7713-2154
- name: Pragati A. Shinde
  role: author
  orcid: https://orcid.org/0000-0003-1730-2374
- name: Katsuhiko Ariga
  role: author
  orcid: https://orcid.org/0000-0002-2445-2955
- name: Lok Kumar Shrestha
  role: author
  orcid: https://orcid.org/0000-0003-2680-6291

## Contact agent



## Publisher

organization: Wiley

## Managing organization



## Keyword

- subject: biomass
  schema: not_defined
- subject: carbon
  schema: not_defined
- subject: dopant
  schema: not_defined
- subject: energy
  schema: not_defined
- subject: machine learning
  schema: not_defined
- subject: storage
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by-nc-nd/4.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: ChemPlusChem
  issn: '21926506'
  volume: '90'
  issue: '10'
  article_number: e202500342

## Conference



## Related item



## Funding

- identifier: JP20H00392
  funder_name: Japan Society for the Promotion of Science
- identifier: JP23H05459
  funder_name: Japan Society for the Promotion of Science

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



## Energy level/transition state



## Software



## Custom property



## Fileset

- id: 7d89d933-1fcc-4e5f-8c67-a3a933267340
  filename: ChemPlusChem25_90_e202500342.pdf
  content_type: application/pdf
  size: 3700393
  md5: c4f71b9c0c8116fb4c207ee7090e761a

## Thumbnail

fileset_id: 7d89d933-1fcc-4e5f-8c67-a3a933267340
filename: ChemPlusChem25_90_e202500342.pdf