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RESEARCH PAPER · Batteries · 2024

AI-Based Nano-Scale Material Property Prediction for Li-Ion Batteries

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AI-Based Nano-Scale Material Property Prediction for Li-Ion BatteriesOriginalMachine learning in advancing anode materials for Lithium-Ion batteries – A review17AI-based Nanotechnology: Breakthroughs, Applications, Challenges, and the Road Ahead3Enhanced Nano-Scale Material Property Prediction in Li-Ion Batteries with Stacked Ensemble Machine Learning Models1Application of in-situ characterization techniques and artificial intelligence-assisted analysis in studying electrode/electrolyte interface of batteries28

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  1. Machine learning in advancing anode materials for Lithium-Ion batteries – A review

    Inorganic Chemistry Communications · 2024-11-19

    Mohammad Aminul Islam, Zahid Ahsan, Mustafizur Rahman, Md. Ibrahim Abdullah, Masud Rana, Nayem Hossain, Mohammad Assaduzzaman Chowdhury

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  2. AI-based Nanotechnology: Breakthroughs, Applications, Challenges, and the Road Ahead

    Recent Patents on Nanotechnology · 2025-07-01

    Ji‐Huan He

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  3. Enhanced Nano-Scale Material Property Prediction in Li-Ion Batteries with Stacked Ensemble Machine Learning Models

    Lecture notes in networks and systems · 2025-10-01

    Navid T. Zaman, Mohammad Asif Khan, Shahriar Sadman Dihan, Farid Ishraqe Zarif, Md. Adnan Morshed, Ahmed Wasif Reza

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  4. Application of in-situ characterization techniques and artificial intelligence-assisted analysis in studying electrode/electrolyte interface of batteries

    Materials Science and Engineering R Reports · 2025-12-08

    Peng Wang, Huanhuan Yang, Hao Ding, Ningshuang Zhang, Dongni Zhao, Shiyou Li

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