With machine learning, researchers embrace the atomic-scale complexity of batteries

For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National Laboratory (LLNL) scientists are tackling that challenge in many ways, but one approach is making a significant impact: physics-informed machine learning.

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