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RESEARCH PAPER · Carbon · 2023

Machine learning assisted chemical characterization to investigate the temperature-dependent supercapacitance using Co-rGO electrodes

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13 direct citing papers in this saved network. Explore the next layer with second-order citations.

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Machine learning assisted chemical characterization to investigate the temperature-dependent supercapacitance using Co-rGO electrodesOriginalReduced graphene oxide-wrapped ZnS–SnS 2 heterojunction bimetallic hollow cubic boxes as high-magnification and long lifespan supercapacitor anode materials12Machine learning-assisted prediction, screen, and interpretation of porous carbon materials for high-performance supercapacitors20Machine learning framework for selective and sensitive metal ion sensing with nitrogen-doped graphene quantum dots heterostructure26Harnessing Nano & AI for Sustainable Energy Application1Efficient activation of peroxymonosulfate by sulfur-coordinated iron-based two-dimensional composite membrane (S–Fe@G) via sulfur doping and nanoconfined catalysis10Incorporation of silver and cobalt in zinc oxide using sol–gel route1Machine Learning Enhanced Self‐Charging Power Sources21Data-driven machine learning modeling reveals the impact of micro/nanoplastics on microalgae and their key underlying mechanisms4MXene/NiCo2S4 2D/3D Heterostructure as a High-Performance Pt-Free Counter Electrode for DSSCs2Advances in machine learning (ML)-driven design of two-dimensional materials for energy and environmental applications4Machine learning toward electrochemical energy storage materials and devices: A review5Machine learning-assisted materials design, mechanistic insights, and predictive modeling for high performance lithium-sulfur batteries2Advancing Cobalt-Based Supercapacitor Electrodes via Machine Learning: A Review of Predictive and Optimization Strategies0

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  1. Reduced graphene oxide-wrapped ZnS–SnS 2 heterojunction bimetallic hollow cubic boxes as high-magnification and long lifespan supercapacitor anode materials

    Nanoscale · 2024-01-01

    Xiaoqin Li, Guoqing Feng, Lingling Zhou, Tiewei Zhao, Feng Jiang, Huiyu Li, Yongsheng Liu, Qing Lei Yu, Hao Ding, Tian Zou, Shanhai Zhao, Jun Cao, Yanyan Zhu, Haijing Cao

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  2. Machine learning-assisted prediction, screen, and interpretation of porous carbon materials for high-performance supercapacitors

    Journal of Materials Informatics · 2024-10-24

    Hongwei Liu, Zhenming Cui, Zhennan Qiao, Xiaokang An, Yongzhen Wang

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  3. Machine learning framework for selective and sensitive metal ion sensing with nitrogen-doped graphene quantum dots heterostructure

    Carbon · 2024-11-05

    Ruma Das, Abhirup Paria, Pratibha Kiran Giri

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  4. Harnessing Nano & AI for Sustainable Energy Application

    Information systems engineering and management · 2025-01-01

    Ruma Das, Abhirup Paria

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  5. Efficient activation of peroxymonosulfate by sulfur-coordinated iron-based two-dimensional composite membrane (S–Fe@G) via sulfur doping and nanoconfined catalysis

    Journal of Membrane Science · 2025-03-17

    Wenwa Weng, Jiawei Hou, Nigel Graham, Xinyu Yu, Wenzheng Yu, Kening Sun, Ting Liu

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  6. Incorporation of silver and cobalt in zinc oxide using sol–gel route

    Indian Chemical Engineer · 2025-03-24

    Karishma Jain, Sushil Kumar Jain, Balram Tripathi

    Read original paper ↗ ·
  7. Machine Learning Enhanced Self‐Charging Power Sources

    Advanced Functional Materials · 2025-05-05

    Rui Gu, Wei Ping Liang, Nuo Xu, Yao Xiong, Qijun Sun, Zhong Lin Wang

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  8. Data-driven machine learning modeling reveals the impact of micro/nanoplastics on microalgae and their key underlying mechanisms

    Journal of Hazardous Materials · 2025-07-25

    Houyu Li, Yaxu Pang, Yinuo Ding, Zhengzhe Fan, Yan Xu, Wei Liu

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  9. MXene/NiCo2S4 2D/3D Heterostructure as a High-Performance Pt-Free Counter Electrode for DSSCs

    Journal of Science Advanced Materials and Devices · 2025-08-09

    Kumar Subalakshmi, Anshika Gupta, Youngmin Lee, Sejoon Lee

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  10. Advances in machine learning (ML)-driven design of two-dimensional materials for energy and environmental applications

    Nano Energy · 2026-03-02

    Tao Jian, Zengjian Zhao, Wangyang Ye, Xiang Cai, Hongjun Lin, Jiaheng Teng, Bisheng Li, Leihong Zhao, Banglin Chen

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

    Sustainable materials and technologies · 2026-04-06

    Chong Ma, Chen Yao, Jing Xu, Yibing Xie

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  12. Machine learning-assisted materials design, mechanistic insights, and predictive modeling for high performance lithium-sulfur batteries

    Energy storage materials · 2026-06-21

    Kaijie Miao, Chengwei Ma, Jiangqi Zhou

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  13. Advancing Cobalt-Based Supercapacitor Electrodes via Machine Learning: A Review of Predictive and Optimization Strategies

    International Conference on Applying New Technology in Green Buildings (ATiGB) · 2026-07-01

    Arsh Sardana, Chhavi Sharma, Kunal, Anugya Agarwal, Pooja Sharma

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