Workflow from Scientific Research

Data acquisition in catalysis research provides the basis for understanding fundamental relationships between physical material properties and the performance of a catalytically active material to discover new catalysts based on this knowledge. Data analysis in catalysis requires coping with the complex entanglement of different data types resulting from the integration of experiment and theory, as well as the interdisciplinary nature of experimental catalysis research. Artificial intelligence and accelerated development (e.g., by design of experiment (DoE) methods) are playing an increasingly important role, which imposes high demands on the quality of the data and the documentation of metadata.

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