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RESEARCH PAPER · Sustainable materials and technologies · 2026

Machine learning toward electrochemical energy storage materials and devices: A review

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Machine learning toward electrochemical energy storage materials and devices: A reviewOriginalReview: recent advances in perovskite synthesis and their impact on energy storage technologies1Machine learning-driven prediction and validation for ionic conductivity of hydrogel electrolytes1Waste‐derived nanomaterials for energy storage and water remediation: Structure–property–performance relationships1Computational and ML methods in MOF based supercapacitors - from mechanistic understanding to future materials design0Preparation, Properties, and Applications of Smart Liquid Metal Hydrogel Composites: A Review0

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  1. Review: recent advances in perovskite synthesis and their impact on energy storage technologies

    Journal of Materials Science · 2026-05-30

    S. Shiphi Amirthakumari, H. Joy Prabu, A. Felix Sahayaraj, I. Johnson, S. Sudhagar

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  2. Machine learning-driven prediction and validation for ionic conductivity of hydrogel electrolytes

    Electrochimica Acta · 2026-06-04

    Ruilin Liu, Jing Xu, Yibing Xie

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  3. Waste‐derived nanomaterials for energy storage and water remediation: Structure–property–performance relationships

    Environmental Progress & Sustainable Energy · 2026-06-19

    Yuvarajan Devarajan, G. M. Lionus Leo, Ravikumar Jayabal, Sasmeeta Tripathy, Nirav Gandhi, M. Madhusudhan, Amit Kumar, H.D. Raghavendra Prasad

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  4. Computational and ML methods in MOF based supercapacitors - from mechanistic understanding to future materials design

    Journal of Materials Science Materials Theory · 2026-08-29

    Achal Siddharth Fulmali, Himanshu Sekhar Panda

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  5. Preparation, Properties, and Applications of Smart Liquid Metal Hydrogel Composites: A Review

    The Chemical Record · 2026-09-06

    Jiuya Zhai, Jing Xu, Yibing Xie

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