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RESEARCH PAPER · Chemical Science · 2022

Machine learning for flow batteries: opportunities and challenges

Tianyu Li, Changkun Zhang, Xianfeng Li

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Machine learning for flow batteries: opportunities and challengesOriginalMachine Learning for Battery Research4Machine learning-driven advanced development of carbon-based luminescent nanomaterials23Strategies for Improving Solubility of Redox‐Active Organic Species in Aqueous Redox Flow Batteries: A Review25Modelling and Estimation of Vanadium Redox Flow Batteries: A Review87Machine learning for battery research110High-Throughput Virtual Screening of Quinones for Aqueous Redox Flow Batteries: Status and Perspectives18Machine Learning for Flow Battery Systems0Machine learning models for predicting density of sodium-ion battery materials1Data-driven approaches enabling the screening and design of promising materials for energy storage batteries0Unlocking the Potential: Predicting Redox Behavior of Organic Molecules, from Linear Fits to Neural Networks27Artificial intelligence-driven rechargeable batteries in multiple fields of development and application towards energy storage34High-Throughput Electrochemical Characterization of Aqueous Organic Redox Flow Battery Active Material20Enhancing Sign Language Detection using Tensor Flow3Optimization of a Redox-Flow Battery Simulation Model Based on a Deep Reinforcement Learning Approach8Machine Learning Assisted Prediction of the Mass Activity of Platinum-Based Anode Catalysts Supported on a Variety of Carbon Nanostructures for Direct Methanol Fuel Cells0State-of-Health and State-of-Charge Estimation in Electric Vehicles Batteries: A Survey on Machine Learning Approaches73Data‐Driven Battery Characterization and Prognosis: Recent Progress, Challenges, and Prospects55Electrospun porous carbon nanofiber-based electrodes for redox flow batteries: Progress and opportunities32Alkaline zinc-based flow battery: chemical stability, morphological evolution, and performance of zinc electrode with ionic liquid1A Review of Capacity Decay Studies of All‐vanadium Redox Flow Batteries: Mechanism and State Estimation39Digitization of flow battery experimental process research and development9An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations84Physics-Guided Continual Learning for Predicting Emerging Aqueous Organic Redox Flow Battery Material Performance17Machine Learning Orchestrating the Materials Discovery and Performance Optimization of Redox Flow Battery29Redox-active molecules for aqueous electrolytes of energy storage devices: A review on fundamental aspects, current progress, and prospects32A critical review on operating parameter monitoring/estimation, battery management and control system for redox flow batteries15Machine learning applications in nanomaterials: Recent advances and future perspectives94Organic redox flow batteries in non-aqueous electrolyte solutions42Recent Advances in Machine Learning‐Assisted Multiscale Design of Energy Materials188Machine learning for the redox potential prediction of molecules in organic redox flow battery16Recent trends of machine learning on energy storage devices7Current status and future perspectives of low-temperature electrolytes for supercapacitors26Monitoring chemical processes in redox flow batteries employing in situ and in operando analyses31Unlocking new horizons, challenges of integrating machine learning to energy conversion and storage research9A Machine Learning Approach for Prediction of Faradaic Efficiency in Electrochemical CO2 Reduction on Nitrogen‐Doped Carbon4Artificial Intelligence in Computational and Materials Chemistry: Prospects and Limitations13Pathways to Realize High‐Energy Density Aqueous Redox Flow Batteries14Artificial intelligence-empowered modeling and management of flow batteries: A mini-review6A comprehensive review of vanadium redox flow batteries: Principles, benefits, and applications20Chinese tofu-inspired nanocuring: Rapid UV-assembled phase change composites with mechanical-thermal synergy11A Review on Battery and Energy Management for Redox Flow Batteries4PredPotS: web tool for predicting one-electron standard reduction potentials for organic molecules in aqueous phase1Data-Driven Performance Prediction of Lead–Carbon Batteries: Integrating Experimental Validation and Reduced-Order Model-Guided Neural Networks0Data-Driven Kinetic Decoupling and Hierarchical Control of Zinc-Air Batteries via XGBoost Modeling0Emerging deposition–dissolution chemistry for next-generation metal-based hybrid flow batteries: progress and perspectives4Optimization of porous electrode configuration for organic redox flow battery by machine learning based on back propagation neural network based on firefly4Integrating artificial intelligence with electrochemical science for advanced energy storage9Generative AI Driven Process Calculations for Fuel Cells and Flow Batteries1High-voltage organic molecules for nonaqueous redox flow batteries: Molecular design rules for stability and energy density2Recent advances in flow field of vanadium redox flow batteries: Structure, performance and prospect2Hybrid simulation–learning model for predicting degradation in lead–carbon batteries0Review: graphite felt electrodes in vanadium redox flow batteries-mechanistic insights and design strategies for high-performance energy storage1Design and screening of complex serpentine flow fields in redox flow batteries with expanded topological space0Artificial intelligence for energy storage systems: State of the art and future perspectives1Artificial intelligence for carbon materials in electrochemical energy storage: Methods, applications, and perspectives0Data-driven performance prediction and operational boundary mapping of zinc-air batteries via XGBoost modeling0Applications and prospects of machine learning in aqueous batteries0Scaling‐Up Vanadium Redox Flow Batteries: From Lab‐Scale Flow Cells to Application Stacks0

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  20. A Review of Capacity Decay Studies of All‐vanadium Redox Flow Batteries: Mechanism and State Estimation

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