Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

DS: Fachverband Dünne Schichten

DS 21: Thin Film Characterisation: Structure Analysis and Composition II

DS 21.5: Vortrag

Dienstag, 21. März 2017, 10:30–10:45, CHE 91

Structure-property relationships in catalysts identified by combining data science and high-throughput experimentation — •Helge S. Stein¹, Jinjang Li^2,3, Ramona Gutkowski⁴, Christina Eberling¹, Sally Jiao⁵, Kirill Sliozberg⁴, Christoph Schwanke⁶, Karin M. Aziz-Lange⁶, Lifei Xi⁶, Andre D. Taylor^2,3, Wolfgang Schuhmann^4,7, and Alfred Ludwig^1,7 — ¹Institute for Materials, Ruhr-Universität Bochum — ²Department of Chemical and Environmental Engineering, Yale University — ³Center for Research on Interface Structures and Phenomena, Yale University — ⁴Analytical Chemistry-Center for Electrochemical Sciences (CES), Ruhr-Universität Bochum — ⁵Department of Chemical and Biological Engineering, Princeton University — ⁶Operando Characterization of Solar Fuel Materials, Helmholtz-Zentrum Berlin für Materialien und Energie — ⁷ZGH & MRD, Ruhr-Universität Bochum

The transition towards a zero-CO2-emission economy requires clean and renewably produced fuels such as hydrogen. In this contribution, catalysts for the efficient production of hydrogen through water reduction (HER) and oxidation (OER), as well as catalysts for the reverse reaction, namely oxygen reduction (ORR), will be shown. Through the implementation of versatile machine learning and statistical methods, novel structure-property correlations were discovered from a total of over 1500 synthesized compositions. These findings offer possible search strategies for the discovery of new and improved catalysts. As an outlook, high-throughput XPS analysis on Co-Fe-Mn-O will be demonstrated.