Towards Experimental Handbooks in Catalysis
Annette Trunschke, Giulia Bellini, Maxime Boniface, Spencer J. Carey, Jinhu Dong, Ezgi Erdem, Lucas Foppa, Wiebke Frandsen, Michael Geske, Luca M. Ghiringhelli, Frank Girgsdies, Rania Hanna, Maike Hashagen, Michael Hävecker, Gregory S. Huff, Axel Knop‐Gericke, Gregor Koch, Peter Kraus, Jutta Kröhnert, Pierre Kube, Stephen Lohr, Thomas Lunkenbein, Liudmyla Masliuk, Raoul Naumann d’Alnoncourt, Toyin Omojola, Christoph Pratsch, Sven C. Richter, Christian Rohner, Frank Rosowski, Frederik Rüther, Matthias Scheffler, Robert Schlögl, Andrey Tarasov, Detre Teschner, Olaf Timpe, Philipp Trunschke, Yuanqing Wang, Sabine Wrabetz
Abstract
Abstract The “Seven Pillars” of oxidation catalysis proposed by Robert K. Grasselli represent an early example of phenomenological descriptors in the field of heterogeneous catalysis. Major advances in the theoretical description of catalytic reactions have been achieved in recent years and new catalysts are predicted today by using computational methods. To tackle the immense complexity of high-performance systems in reactions where selectivity is a major issue, analysis of scientific data by artificial intelligence and data science provides new opportunities for achieving improved understanding. Modern data analytics require data of highest quality and sufficient diversity. Existing data, however, frequently do not comply with these constraints. Therefore, new concepts of data generation and management are needed. Herein we present a basic approach in defining best practice procedures of measuring consistent data sets in heterogeneous catalysis using “handbooks”. Selective oxidation of short-chain alkanes over mixed metal oxide catalysts was selected as an example.