Machine learning accelerates identification of lithiated phases in X-ray images of battery hosts.

Mistry, Aashutosh; Srinivasan, Venkat · Patterns (N Y) · 2022

basic_science · Level V

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Abstract

Santos et al. (2022) propose a machine learning-based approach to identify various lithiated phases across lengthscales in X-ray images of battery particles, thus enabling automatic interpretation of such information in much bigger datasets and creating opportunities to unravel previously inaccessible scientific understanding.