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cond-mat.mtrl-sci2025
A literature-derived dataset of migration barriers for quantifying ionic transport in battery materials
Reshma Devi, Avaneesh Balasubramanian, Keith T. Butler +1
The rate performance of any electrode or solid electrolyte material used in a battery is critically dependent on the migration barrier () governing the motion of the intercala…
cond-mat.mtrl-sci2025
Leveraging transfer learning for accurate estimation of ionic migration barriers in solids
Reshma Devi, Keith T. Butler, Gopalakrishnan Sai Gautam
Ionic mobility determines the rate performance of several applications, such as batteries, fuel cells, and electrochemical sensors and is exponentially dependent on the migration b…
cond-mat.mtrl-sci2024
Optimal pre-train/fine-tune strategies for accurate material property predictions
Reshma Devi, Keith T. Butler, Gopalakrishnan Sai Gautam
Overcoming the challenge of limited data availability within materials science is crucial for the broad-based applicability of machine learning within materials science. One pathwa…