FAIRDI

FAIR Data Infrastructure
for Physics, Chemistry,
Materials Science,
and Astronomy e.V.

Pillar D: Heterogenous catalysis

Heterogeneous catalysis is a key interdisciplinary field that provides solutions to ensure society’s future energy supply, environmental protection, and sustainable chemistry by closing chemical cycles. 

It has proven impossible to infer simple relations between process conditions, catalyst properties and performance as they generally depend on each other in a highly non-linear fashion. In the past 150 years, the invention of new catalysts was therefore mainly guided by chemical intuition and based on empirical approaches and serendipity. The development of high-throughput experimentation and computational techniques did not change this substantially, but led to the accumulation of a tremendous amount of catalysis-related data in the literature and in local laboratories. Generally, only the smallest part of these data meets the criteria for data-science applications. To this end, the definition of standards and clear procedures is necessary, which will enable quality control and the collection of reliable and balanced datasets that are then amenable to modern data analytics. In view of the dynamic and adaptive nature of working catalysts, it is imperative to implement direct connections between the chemical and physical properties of the material, process conditions, time-resolved properties, and functional studies under operando conditions. The heterogeneous catalysis pillar within FAIR-DI will act as an important platform for collecting existing and future data and making these data accessible to the community. By making these data available, we will ultimately change the way how catalysts will be discovered and designed in the future.

Within this pillar, research data from computational and experimental research in the broader field of heterogeneous catalysis will be made accessible according to the FAIR principles. Key people within this pillar are Annette Trunschke, Robert Schlögl, Roger Gläser, Carsten Baldauf, Matthias Scheffler, and Karsten Reuter.