There is currently a great interest in finding new ways to control chemical reactions at catalytic surfaces. A key part of controlling the chemistry at these surfaces is understanding the dynamic nature of catalyst surfaces and local environments in the reaction medium. Both in operando and theoretical studies are key to understanding the dynamic environment under real-time reaction conditions and allowing in-depth studies of reaction intermediates. With the ever-increasing range of techniques used to analyse catalytic processes generating an expanding body of data, it is clear that data collection, availability and analysis must also evolve.
This volume brings together researchers from across the heterogenous catalysis and surface chemistry communities to advance the design of new catalysts needed for society's most pressing problems, which range from energy production and air quality to developing environmentally sustainable industry.
The topics discussed cover four main categories:
The quality of data, the role of machine learning and artificial intelligence, as well as novel approaches that can be employed in the design of atomically precise catalytic sites and strategies for self-repair to achieve control over long-term stability are all discussed.
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