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RESEARCH PAPER · Chemistry of Materials · 2025

Utilizing Machine Learning to Advance Battery Materials Design: Challenges and Prospects

Souvik Manna, Poulami Paul, Surya Sekhar Manna, Sandeep Das, Biswarup Pathak

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Utilizing Machine Learning to Advance Battery Materials Design: Challenges and ProspectsOriginalArtificial Intelligence for Carbon Capture, Utilization and Storage: Technological Evolution and Systemic Integration Pathways2Exploring Hybrid Electrolytes for Zn Metal Batteries29Bayesian Optimization of the Experimental Parameters of Material Synthesis: Application to the Magnesioreduction of Rare-Earth-Free (Mn1–xFex)5Si3 Magnetocalorics2Adaptive multi-task learning for battery health prediction: A BiLSTM framework with Bayesian optimization and dynamic task weighting14Generative Deep Learning for Advanced Battery Materials3Real-time heavy metal detection in water using machine learning-augmented CNT sensors via truncated factorization nuclear norm-based SVD1Intelligent fault detection in battery systems: a machine learning approach with transformer-enhanced multi-modal Sensing14Covalent organic framework-based solid polymer electrolytes for metal-ion batteries: pioneering the future of DFT, MD, and ML techniques4Design optimization of electric-fish-inspired power sources using statistical and machine learning approaches2Topology optimization framework for 3D structural design based on micropolar elasticity and enhanced by machine learning4Multiscale Simulation Drives the Rational Design of Lithium‐Sulfur Batteries1Artificial Intelligence as a Materials-integrated Brain: Revolutionizing Organic Semiconductor Design and Aptamer-OFET Biosensing in the Post-silicon Era4Energy Materials: Synthesis and Characterizations0Convergence of Computational Materials Science and AI for Next-Generation Energy Storage Materials6Molecular dynamics and machine learning framework for predicting ion transport and mechanical properties of ionic liquid@polyvinylidene fluoride gel polymer electrolyte5Recent progress in data-driven approaches for single-atom catalysts in lithium-sulfur batteries2High-entropy alloy electrocatalysts for water splitting: A systematic review with perspectives on machine learning and future design strategies9AI-driven exploration and design of inorganic battery materials14Biodegradable and bioresorbable rechargeable batteries: chemistries, AI-driven material discovery, and emerging applications0Data-driven discovery of a zero-strain cathode with dynamic bond-switching for solid-state zinc-ion batteries0Energy Materials: Synthesis and Characterizations0Integrating Density Functional Theory with Deep Neural Networks for Accurate Voltage Prediction in Alkali‐Metal‐Ion Battery Materials4Interfacial design principles of two-dimensional graphene-based heterostructures for lithium- and sodium-ion battery anodes0Probing the composition space of V, Fe, and Ti substituted sodium manganese oxides for next-generation sodium-ion cathodes0Machine Learning‐Guided Design of a Flexible Highly Conductive Additive‐Free Polymer Cathode0Density Functional Theory–Machine Learning-Assisted Insightful Identification of Next-Generation High-Voltage Organic Dual-Ion Batteries3Deep learning-based battery health prediction for enhancing electric vehicle performance8Application of machine learning to rechargeable aqueous zinc-ion batteries: Advancements and prospects3Artificial intelligence–driven evolution and system integration for geological carbon capture, utilization, and storage0Emerging nanomaterials for next-generation automotive energy storage systems1Recent advances, challenges and future perspectives of polycyclic aromatic hydrocarbons as materials for metal-ion batteries – A comprehensive review1Stabilizing Electrode/Electrolyte interphases for Lithium-Ion batteries at High-Temperature through integrated electrolyte engineering and surface modification1A Perspective on Crystalline Cathode Materials for Aqueous Mn-Ion Batteries1Crystal Water Engineering in Electrode Materials: Decoding Structure‐Property Dynamics for Advanced Energy Storage Devices4Machine learning-based assessment technique of state-of-health, remaining useful life, and maximum operating temperature for lithium-ion battery for eVTOL aircraft0Rational design of MXene composites for high-performance potassium-ion batteries9Artificial intelligence in advanced polymer manufacturing1A Deep Learning Approach for OER Electrocatalyst Kinetics Prediction1Regulatory strategies for lithium-sulfur batteries: Integration of hollow porous carbon with single/dual-atom catalysts2Hollow Ti3C2Tx-MXene nanosphere electrochemical sensor coupled with LSTM time-series modeling for rapid detection of ascorbic acid in sweat1Electrolyte Engineering in Aqueous Zinc‐Ion Batteries: From Solvation Chemistry to Interface Stabilization0Transition metal halides for high-performance and sustainable solid-state batteries0Magnesium-ion battery cathode materials: Artificial intelligence applications, research advances, and industrialization0AI-driven sustainable supercapacitors for advanced renewable energy storage applications1Data-driven discovery and first-principles design of novel cathode materials for sodium-ion batteries0Computational and ML methods in MOF based supercapacitors - from mechanistic understanding to future materials design0Unlocking rechargeable battery materials with artificial intelligence: From data-descriptor-model workflows to closed-loop discovery0Protective interphases and safety enhancement in high-energy-density batteries: A critical review0Review of AI-driven discovery of cathode anode and electrolyte materials for advancing sodium-ion batteries0Tailoring Lithium‐Rich NMC Cathode Materials for High‐Energy Lithium‐Ion Batteries0Garnet-type LLZO solid electrolytes: Grain-boundary engineering, electro-chemo-mechanical failure, and manufacturability0

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