Applying machine learning to understand the properties of biomass carbon materials in supercapacitors-Reference-Cited by-同舟云学术

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Applying machine learning to understand the properties of biomass carbon materials in supercapacitors

Published:2023-11 Issue: Volume:10 Page:3125-3132
ISSN:2352-4847
Container-title:Energy Reports
language:en
Short-container-title:Energy Reports

Author:

Jamaluddin Anif^ORCID,Harjunowibowo Dewanto,Budiawanti Sri,Kurdhi Nughthoh Arfawi,Sutarsis ,Lai Daphne T.C.^ORCID,Ramesh S.

Publisher

Elsevier BV

Subject

General Energy

Reference35 articles.

1. Efficient hyperparameter-tuned machine learning approach for estimation of supercapacitor performance attributes;Ahmed;J. Phys. Commun.,2021

2. A novel visual approach for enhanced attribute analysis and selection;Artur;Comput. Graph.,2019

3. Design of supercapacitor electrodes using molecular dynamics simulations;Bo;Nanomicro. Lett.,2018

4. Carbon-based composite materials for supercapacitor electrodes: A review;Borenstein;J. Mater. Chem. A,2017

5. WEKA—Experiences with a Java open-source project;Bouckaert;J. Mach. Learn. Res.,2010

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1. Recent advances in artificial intelligence boosting materials design for electrochemical energy storage;Chemical Engineering Journal;2024-06

2. Activated of Waste Palm-Oil Based on Chemical-Assisted Microwave Radition for Supercapacitor Materials;2024-05-13

3. Data-Driven Optimization of Carbon Electrodes for Aqueous Supercapacitors;Journal of Chemical & Engineering Data;2024-05-02

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