Even for experienced catalysts, matchmaking is not always easy. Some partners bind too strong, others leave too early. A team of scientists including members of e-conversion observed how a copper electrode solves this problem by itself.
One year ago David Egger became professor for “Theory of Functional Energy Materials” at TU München and member of e-conversion. We asked him about his research, his ideas for the cluster and why he loves being a scientist.
Platinum is the common catalyst material for the oxygen reduction in fuel cells and its main cost factor. With a machine learning technique, scientists from e-conversion now can forecast and optimize the performance of catalysts with less platinum.