Veit Königer

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...

Supporting AI Readiness Through Digital Workflows in Materials Science

Materials science produces heterogeneous data across experiments, simulations, and industrial processes that often remain bound to local formats, manual procedures, and project‐specific software. Digital workflows address this fragmentation through explicit, repeatable, and machi...