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RESEARCH PAPER · Journal of Energy Storage · 2024

Machine learning assisted prediction in the discharge capacities of novel MXene cathodes for aluminum ion batteries

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42 direct citing works

Machine learning assisted prediction in the discharge capacities of novel MXene cathodes for aluminum ion batteriesOriginalMXenes and its composite structures: synthesis, properties, applications, 3D/4D printing, and artificial intelligence; machine learning integration78Investigating lithium-ion battery discharge capacity under variable operating conditions using nature-inspired hybrid algorithms with minimal descriptors6Review: MXenes—properties, synthesis, hydrogen storage, catalytic performance, and future prospects12Application of MXene-based hydrogel in biomedical technologies7Few-shot learning of initial coulombic efficiency using adaptive combination kernel deep Gaussian process regression5Recent advances in machine learning applications for MXene materials: Design, synthesis, characterization, and commercialization for energy and environmental applications22Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives53Novel core-shell structure Co2P/Fe2P@C@NC as advanced cathode for aluminum batteries8MXenes for advanced energy storage: A computational perspective0Dual-modified NiCoP cathode with amorphous carbon and nitrogen-doped carbon shell: Towards superior performance of aluminum battery7MXene-based hybrid architectures for potassium-ion and aluminium-ion battery systems: Design strategies and mechanism insights0A Lightweight, Low-Label Framework Towards Autonomous Morphology-Resolved SEM–EDS Analysis in Material Microscopy0Rational Design of MXene‐Based Heterostructures for Potassium‐Ion and Aluminum‐Ion Batteries: From Structure Engineering to Charge‐Storage Mechanisms0Transfer learning framework for SEM-based degraded lithium-ion battery diagnostics under domain shift and data scarcity0Aluminum-ion batteries: materials, charge storage mechanisms, and future challenges0

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  1. MXenes and its composite structures: synthesis, properties, applications, 3D/4D printing, and artificial intelligence; machine learning integration

    Progress in Materials Science · 2025-01-20

    Vimukthi Dananjaya, Nethmi Hansika, Sathish Marimuthu, Venkata S. Chevali, Yogendra Kumar Mishra, Andrews Nirmala Grace, Nisa V. Salim, Chamil Abeykoon

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  2. Investigating lithium-ion battery discharge capacity under variable operating conditions using nature-inspired hybrid algorithms with minimal descriptors

    Journal of Energy Storage · 2025-03-19

    Yakubu Sani Wudil, M.A. Gondal, Mohammed Ali Al-Osta

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  3. Review: MXenes—properties, synthesis, hydrogen storage, catalytic performance, and future prospects

    Journal of Materials Science · 2025-05-01

    Runze Hou, Wei Jiang

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  4. Application of MXene-based hydrogel in biomedical technologies

    Microchemical Journal · 2025-05-27

    Ping-Ping He, Zhaosheng Fan, Keke Xue, Wenjun Sun, Xinyu Wang, Xin Ju, Qingyu Yan, Xiaoxue Du, Enxiang Zhang

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  5. Few-shot learning of initial coulombic efficiency using adaptive combination kernel deep Gaussian process regression

    Journal of Energy Storage · 2025-05-28

    Hai Guo, Hongcheng Zhang, Xiaofeng Lv, Xiaoxu Liu, Tianyi Ji

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  6. Recent advances in machine learning applications for MXene materials: Design, synthesis, characterization, and commercialization for energy and environmental applications

    Next Materials · 2025-06-25

    Sodiq Abiodun Kareem, Makinde Akindeji Ibrahim, Justus Uchenna Anaele, Olajesu Favor Olanrewaju, Emmanuel Omosegunfunmi Aikulola, Michael Oluwatosin Bodunrin

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  7. Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

    Advanced Functional Materials · 2025-07-06

    Qingyun Hu, Junyuan Lu, Jian Hui, Ziyuan Rao, Yang Ren, Hong Wang

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  8. Novel core-shell structure Co2P/Fe2P@C@NC as advanced cathode for aluminum batteries

    Acta Materialia · 2025-12-05

    Wenbin Luo, Jian Li, Yi Yu, Dingrui Xiao, Zi‐Sheng Chao, Jincheng Fan

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  9. MXenes for advanced energy storage: A computational perspective

    Frontiers of Physics · 2026-01-01

    Hejing Wang, Beibei Shi, Yixiao Zhang, Yongzheng Fang, Xu Zhang, Menggai Jiao, Zhen Zhou

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  10. Dual-modified NiCoP cathode with amorphous carbon and nitrogen-doped carbon shell: Towards superior performance of aluminum battery

    Carbon · 2026-04-06

    Jian Li, Wenbin Luo, Jiang Liang, Dingrui Xiao, Yi Yu, Ruichen Xu, Zisheng Chao, Jincheng Fan

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  11. MXene-based hybrid architectures for potassium-ion and aluminium-ion battery systems: Design strategies and mechanism insights

    Advanced Composites and Hybrid Materials · 2026-05-01

    K. Karuppasamy, Ganesh Kumar Veerasubramani, Palanivel Molaiyan, Eswaravara Prasadarao Komarala, Vasanth Rajendiran Jothi, Dhanasekaran Vikraman, Dr. Hossein Rostami, Hari Vignesh Ramasamy, Georgios N. Karanikolos, Min Jae Ko, Ali AbdulKareem AlHammadi, Hyun‐Seok Kim, Mohit Saraf, Ulla Lassi, Akram AlFantazi

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  12. A Lightweight, Low-Label Framework Towards Autonomous Morphology-Resolved SEM–EDS Analysis in Material Microscopy

    Research Square · 2026-08-04

    Siraprapha Deebansok, Bannapol Limanond, Patricia Moraille, Kajiana Boonpalit, Kanakorn Suk-ieam, Visarut Nganpipatmongkon, Pasit Pakawatpanurut, Antonella Badia, Takayuki Okatani

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  13. Rational Design of MXene‐Based Heterostructures for Potassium‐Ion and Aluminum‐Ion Batteries: From Structure Engineering to Charge‐Storage Mechanisms

    Small · 2026-08-11

    Narasimharao Kitchamsetti, A. L. F. de Barros, Sungwook Mhin, HyukSu Han

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  14. Transfer learning framework for SEM-based degraded lithium-ion battery diagnostics under domain shift and data scarcity

    Journal of Power Sources · 2026-08-20

    Haein Jeon, Donghun Lee, Bo‐Yeong Kang, Jimin Oh

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  15. Aluminum-ion batteries: materials, charge storage mechanisms, and future challenges

    Journal of Energy Storage · 2026-08-28

    Anita K. Tawade, Shivaji N. Tayade, Ruoyu Hong, David Hui, Minglin Li

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