The reaction mechanism of the mild hydrogenation of guaiacol over Pt(111) has been investigated by density functional theory calculations and microkinetic modeling.Our model suggests that at 573 K catechol is the preferred reaction product and that any deoxygenation to, e.g., phenol or benzene is at least four orders of magnitude slower than the production of catechol.Slow deoxygenation of guaiacol can occur by decarbonylation and possibly by hydrogenation of the phenyl ring followed by C-OH bond cleavage. Direct -OH removal without activation of the phenyl ring is found to be at least five orders of magnitude slower. Overall, this study suggests that Pt (111) sites are not active deoxygenation sites and that the experimentally observed deoxygenation activity of Pt catalysts originates likely from the involvement of the catalyst support or Pt step and corner sites.

We present a new open repository for chemical reactions on catalytic surfaces, available at https://www.catalysis-hub.org . The featured database for surface reactions contains more than 100,000 chemisorption and reaction energies obtained from electronic structure calculations, and is continuously being updated with new datasets. In addition to providing quantum-mechanical results for a broad range of reactions and surfaces from different publications, the database features a systematic, large-scale study of chemical adsorption and hydrogenation on bimetallic alloy surfaces. The database contains reaction specific information, such as the surface composition and reaction energy for each reaction, as well as the surface geometries and calculational parameters, essential for data reproducibility. By providing direct access via the web-interface as well as a Python API, we seek to accelerate the discovery of catalytic materials for sustainable energy applications by enabling researchers to efficiently use the data as a basis for new calculations and model generation.

A comprehensive database of chemical properties on a vast set of transition metal surfaces has the potential to accelerate the discovery of novel catalytic materials for energy and industrial applications. In this data descriptor, we present such an extensive study of chemisorption properties of important adsorbates - e.g., C, O, N, H, S, CH x , OH, NH, and S H - on 2,035 bimetallic alloy surfaces in 5 different stoichiometric ratios, i.e., 0%, 25%, 50%, 75%, and 100%. To our knowledge, it is the first systematic study to compile the adsorption properties of such a well-defined, large chemical space of catalytic interest. We propose that a collection of catalytic properties of this magnitude can assist with the development of machine learning enabled surrogate models in theoretical catalysis research to design robust catalysts with high activity for challenging chemical transformations. This database is made publicly available through the platform www.Catalysis-hub.org for easy retrieval of the data for further scientific analysis.