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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 ...
Frontiers

Physics-Grounded Machine Learning Force Fields for Biomolecular Modelling: Variational, Renormalization and Effective Field Theory Approaches

Machine learning is rapidly reshaping how we model molecules, and a growing body of work suggests that neural networks are not merely statistical ...
EurekAlert!

First principles calculations informing machine learning framework and visualization system for rapid and generalized gas response prediction in black phosphorus sensors (IMAGE)

An integrated framework combining first-principles calculations and machine learning was developed to predict gas-sensing performance. Key descriptors such as adsorption energy, adsorption distance, ...