Laura M. Bies

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

The growing availability of structured battery databases opens new opportunities for data‐driven quality control in battery manufacturing. Efficient identification of anomalous cells is critical for ensuring safety, performance, and longevity. In this work, we present a machine‐l...