JST Press Release: Best performance of organic material for lithium battery anode using: Materials Informatics:Combining empirical knowledge and machine learning with a small experimental dataset
GitHub - wanbin-song/BatteryMachineLearning: Machine learning based Lithium-Ion battery capacity estimation using multi-Channel charging Profiles
Honorable Mention Winnerʼs Article: High-Fidelity State-of-Charge Estimation of Li-Ion Batteries using Machine Learning - HORIBA
Applied Sciences | Free Full-Text | State-of-Health Identification of Lithium-Ion Batteries Based on Nonlinear Frequency Response Analysis: First Steps with Machine Learning
Machine learning assisted materials design and discovery for rechargeable batteries - ScienceDirect
Machine Learning for Advanced Batteries | Transportation and Mobility Research | NREL
Application of DFT-based machine learning for developing molecular electrode materials in Li-ion batteries - RSC Advances (RSC Publishing)
Predicting the state of charge and health of batteries using data-driven machine learning | Nature Machine Intelligence
Predicting the state of charge and health of batteries using data-driven machine learning | Nature Machine Intelligence
Machine learning prediction of coordination energies for alkali group elements in battery electrolyte solvents - Physical Chemistry Chemical Physics (RSC Publishing)
Multi-scale computation methods: Their applications in lithium-ion battery research and development
Multi-scale computation methods: Their applications in lithium-ion battery research and development
Application of machine learning methods for the prediction of crystal system of cathode materials in lithium-ion batteries - ScienceDirect
A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning - ScienceDirect
Closed-loop optimization of fast-charging protocols for batteries with machine learning | Nature
Applying Machine Learning to Rechargeable Batteries: From the Microscale to the Macroscale - Chen - 2021 - Angewandte Chemie International Edition - Wiley Online Library
Machine learning‐based model for lithium‐ion batteries in BMS of electric/hybrid electric aircraft - Hashemi - 2021 - International Journal of Energy Research - Wiley Online Library
One-shot battery degradation trajectory prediction with deep learning - ScienceDirect
Predicting the state of charge and health of batteries using data-driven machine learning | Nature Machine Intelligence
Energies | Free Full-Text | State-of-Charge Estimation of Battery Pack under Varying Ambient Temperature Using an Adaptive Sequential Extreme Learning Machine
Predicting battery life with early cyclic data by machine learning - Zhu - 2019 - Energy Storage - Wiley Online Library
Autonomous discovery of battery electrolytes with robotic experimentation and machine learning – Physics World
![PDF] A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/27b59d665ff60f9849e6182a8a09238a40c31fc0/24-Figure4-1.png "PDF] A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning | Semantic Scholar")
PDF] A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning | Semantic Scholar
Machine Learning Method to Improve Fast Charging Battery Development – Full-Stack Feed
