AI and automation: democratizing automation and the evolution towards true AI-autonomous robotics

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Chem. Sci., 2025, 16, 15769
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Exchanging interlayer anions in NiFe-LDHs nanosphere enables superior battery-type storage for high-rate aqueous hybrid supercapacitors

Harishchandra S. Nishad, Vishal Kotha, Pradip Sarawade, Atul C. Chaskar, Sagar Mane, Jaewoong Lee and Pravin S. Walke

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A mixed-ligand approach to a cobalt-based electroactive framework for superior supercapacitor performance

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Data-driven finding of organic anode active materials for lithium-ion batteries from natural flower scent products using capacity predictors

Haruka Tobita, Kosuke Sakano, Hiroaki Imai, Yusuke Yamashita and Yuya Oaki

J. Mater. Chem. A, 2025, 13, 36116
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Leveraging machine learning in porous media

Mostafa Delpisheh, Benyamin Ebrahimpour, Abolfazl Fattahi, Majid Siavashi, Hamed Mir, Hossein Mashhadimoslem, Mohammad Ali Abdol, Mina Ghorbani, Javad Shokri, Daniel Niblett, Khabat Khosravi, Shayan Rahimi, Seyed Mojtaba Alirahmi, Haoshui Yu, Ali Elkamel, Vahid Niasar and Mohamed Mamlouk

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A comprehensive review on MoSe2 nanostructures with an overview of machine learning techniques for supercapacitor applications

Robertson B, Sapna R, Vinod Hegde and Hareesh K

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In-depth understanding of electrochemical energy storage efficiency in a series of new 3d–4d mixed metal polyoxometalates: experimental and theoretical investigations

Kalyankumar S. Morla, Dewendra Thakre, Tushar Balasaheb Deshmukh, Sunanda Malo, Subuhan Ahamed, Ravari Kandy Aparna, Subham Sahoo, Debajit Sarma, Kartik Chandra Mondal, Babasaheb R. Sankapal and Abhishek Banerjee

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Insights on the rate performance of polyaniline supercapacitors by integrated mathematical modeling and machine learning

Elham Rahmanian, Rasoul Malekfar and Ali Sajedi-Moghaddam

J. Mater. Chem. A, 2024, 12, 32318
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Nickel cobalt phosphate/phosphide as a promising electrode material for extrinsic supercapacitors: machine learning analysis

C. D. Chavare, D. S. Sawant, S. V. Gaikwad, A. V. Fulari, H. R. Kulkarni, D. P. Dubal and G. M. Lohar

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Recent advances in carbon-based materials for supercapacitors: synthesis, electrochemical properties, and impact of machine learning

Anik Sahoo, Sumanta Sahoo and Rajesh Kumar

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A Novel Supercapacitor Degradation Prediction Using a 1D Convolutional Neural Network and Improved Informer Model

Hao Zhang, Zhenxiao Yi, Le Kang, Yi Zhang and Kai Wang

Prot. Control Mod. Power Syst., 2024, 9, 51
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Machine Learning Enhanced Self‐Charging Power Sources

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

Adv Funct Materials, 2025, 35
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Evaluating machine learning models for predicting the storage performance of polypyrrole-based supercapacitor electrodes

A.E. Abd-elnaby, Khaled E. El-Kelany, F. Selim, Mostafa A. Ebied and A.M. Elshaer

Journal of Energy Storage, 2025, 140, 118943
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Hybrid MXenes for supercapacitors: Advances, mechanisms, and outlook

Sonika and Narinder Singh

Materials Today Physics, 2025, 59, 101947
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Machine Learning-Assisted Electrode Material Fabrication and Electrochemical Efficiency Prediction and Validation of PANI-Ni/Co Hydroxide Nanocomposites

Arpit Mendhe and Himanshu Sekhar Panda

ACS Sustainable Chem. Eng., 2023, 11, 17262
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Synthesis and applications of self-supported porous polymetallic tungstates heterostructure electrodes for high-performance asymmetric supercapacitors

Bin Gao, Ruiyuan Hu, Zhifang Feng, Xiao-Feng Wang, Yulan Meng, Xue-Zhi Song and Zhenquan Tan

Journal of Alloys and Compounds, 2024, 979, 173562
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Progress in flexible supercapacitors for wearable electronics using graphene-based organic frameworks

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Efficient structure-informed featurization and property prediction of ordered, dilute, and random atomic structures

Adam M. Krajewski, Jonathan W. Siegel and Zi-Kui Liu

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Capacitance Classification for Supercapacitors Using Machine Learning

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IEEE Access, 2025, 13, 53116
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Advancements on the synthesis and modification of metal-organic framework derivatives for supercapacitors

Geping He, Xueting Li, Wenbo Zhou, Zhong Huang, Huijun HuangFu, Lang Jv, Yuxia Qiao, Zhilei Li, Donghai Ding, Zongmo Shi and Quan Yang

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Recent advances in the high entropy materials for advanced energy storage with machine learning

Xin Tong, Kaifang Sun, Hao Ye, Lin Cao, Jinliang Zhuang, Juan Tian and Xinxing Zhan

Materials Reports: Energy, 2025, 5, 100379
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Machine-learning interatomic potentials for interfaces in all-solid-state batteries: Perspectives on training data, model selection, and validation

Kwangnam Kim, Suyue Yuan, Brandon C. Wood and Liwen F. Wan

MRS Commun., 2026
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Synergistic design and synthesis of O, N Co-doped hierarchical porous carbon for enhanced supercapacitor performance

Hongwei Liu, Zhenming Cui, Yan Sun, Zhennan Qiao, Yanlan Zhang, Qiang Bai and Yongzhen Wang

Energy Mater, 2025, 5
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Machine learning-guided optimization, predictive modeling, and experimental validation of MXene-based supercapacitors

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Journal of Power Sources, 2026, 663, 238863
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Attention towards chemistry agnostic and explainable battery lifetime prediction

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npj Comput Mater, 2024, 10
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AI‐Driven Optimization of Waste‐Derived Nanocomposites for High‐Performance Microbial Fuel Cells

Darshita Valde, Lakeswer Dadsena, Chandrasekhar Kuppam, Monalisha Mohanta, Tungabidya Maharana and Satya Eswari Jujjavarapu

Energy Tech, 2026, 14
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Machine learning-assisted prediction, screen, and interpretation of porous carbon materials for high-performance supercapacitors

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

J Mater Inf, 2024, 4
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Engineering novel sea urchin-like bimetallic cu co selenide nanostructures for high-performance asymmetric supercapacitors

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Journal of Energy Storage, 2025, 137, 118602
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Machine Learning Validation via Rational Dataset Sampling with astartes

Jackson W. Burns, Kevin A. Spiekermann, Himaghna Bhattacharjee, Dionisios G. Vlachos and William H. Green

JOSS, 2023, 8, 5996
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Architectural engineering of nanocomposite electrodes for energy storage

Kara A. Randall, Mirina E. Enderlin and Paraskevi Flouda

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Energy storage in supercapacitor researches: Interdisciplinary applications from molecular simulations to machine learning

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Applied Energy, 2025, 393, 126074
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A review on nano-structured electrodes for high-performance supercapacitors: panoramic insights across dimensional spectra

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Discov Electron, 2025, 2
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Transition Metal Molybdates Emerging Materials for High‐Performance Supercapacitors: A Machine Learning Analysis

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Battery Energy, 2025, 4
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Predicting the Remaining Useful Life of Supercapacitors under Different Operating Conditions

Guangheng Qi, Ning Ma and Kai Wang

Energies, 2024, 17, 2585
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Recent progress in supercapacitors: A critical review of energy storage mechanisms, electrode design strategies and future perspectives

Chenyu Du, Jia Lei Chen-Qiu, Zengying Zhao, Felix Zamora and Hao Liu

Journal of Alloys and Compounds, 2026, 1054, 186363
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From data to device: Machine learning-driven optimization, predictions, and experimental insights for engineering high-performance MnO2 supercapacitors

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Accelerating supercapacitor lifetime optimization using quantum machine learning surrogates

Mojtaba Khakpour Komarsofla and Amirkianoosh Kiani

Energy and AI, 2026, 24, 100745
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Estimating state of charge of cylindrical lithium-ion cells using multiple random convolutional kernel transform and low-frequency stress waves

Jian Chen, Thomas Hannan, Yan Yao and Gangbing Song

Energy Storage Materials, 2024, 72, 103730
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Convergence of Computational Materials Science and AI for Next-Generation Energy Storage Materials

Xuexue Pan, Yuanlin Xie, Chujun Li, Yingyin He, Yitong Zhang, Yilin Wang, Ziman Li, Peiyu Peng and Jun Wang

J. Electron. Mater., 2026, 55, 45
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Artificial Intelligence in Predicting Performance of Sustainable Marine Materials

Ghanasham Chandrakant Sarode, Arvind Jagtap, Truti Pawase, Swati Jaiswal, Neha Joshi, Kasiprasad Mannepalli and Anant Sidhappa Kurhade

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Ion beam engineering of nanostructured materials for superior performance in supercapacitor applications: Recent progress and future perspectives

Basudeba Maharana and Shyamal Chatterjee

Journal of Energy Storage, 2025, 109, 115039
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Toward efficient dielectric material discovery: a comparative evaluation of Transformer and AutoML-based inverse learning

Murad Ali Khan, Hyejeong Song, Syed Shehryar Ali Naqvi, Muhammad Faseeh, Hyunseok Ko and Do-Hyeun Kim

Journal of Asian Ceramic Societies, 2026, 14, 1
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Temperature-dependent performance prediction for cerium oxynitride solid-state symmetric supercapacitor using machine learning

Sourav Ghosh, Ashwath Sibi, G. Sudha Priyanga, Zaineb Chelly Dagdia and Tiju Thomas

Journal of Energy Storage, 2025, 113, 115562
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Electrode Materials and Prediction of Cycle Stability and Remaining Service Life of Supercapacitors

Wen Jiang, Jingchen Wang, Rui Guo, Jinwei Wang, Jilong Song and Kai Wang

Coatings, 2026, 16, 41
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Calculated solvation and ionization energies for thousands of organic molecules relevant to battery design

Jan Weinreich, Konstantin Karandashev, Daniel Jose Arismendi Arrieta, Kersti Hermansson and O Anatole von Lilienfeld

Mach. Learn.: Sci. Technol., 2025, 6, 030602
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