Predicting Battery Lifetimes With Machine Learning

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Predicting Battery Lifetimes With Machine Learning
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U.S. Department of Energy’s (DOE) Argonne National Laboratory have turned to the power of machine learning to predict the battery lifetimes

Argonne National LaboratoryImagine a psychic telling your parents, on the day you were born, how long you would live. A similar experience is possible for battery chemists who are using new computational models to calculate battery lifetimes based on as little as a single cycle of experimental data.

In a machine learning algorithm, scientists train a computer program to make inferences on an initial set of data, and then take what it has learned from that training to make decisions on another set of data.For every different kind of battery application, from cell phones to electric vehicles to grid storage, battery lifetime is of fundamental importance for every consumer,” said Argonne computational scientist Noah Paulson, an author of the study.

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