Preface: Trends in Computational Catalysis
John Kitchin, “Preface: Trends in Computational Catalysis”, Topics in Catalysis 55, 227-228 (2012). https://doi.org/10.1007/s11244-012-9808-0
This summary was written by a language model from the paper and has not been checked line by line. Rely on the published paper for details.
Question
This two-page editorial preface introduces a special issue of Topics in Catalysis on computational catalysis. It asks where the field stood in 2012 and which directions were gaining ground, using the invited papers as examples (Kitchin 2012). It reports no original results of its own.
Approach
Kitchin, as guest editor, groups the issue’s papers into three themes: adsorption and molecular interactions, kinetics and mechanism, and new methodologies. For each theme he briefly describes what the contributing papers did and what trend they represent. The papers were invited from speakers in the Catalysis and Reaction Engineering division at the 2011 AIChE Fall meeting in Minneapolis, which held 33 computational catalysis talks across five sessions.
Key findings
The preface attributes the growth of computational catalysis to faster and more parallel hardware, the availability of high quality software, and new algorithms. Under adsorption, it highlights work on sulfur-containing aromatics on oxides, chiral molecules on chiral bimetallic surfaces, and CO2 reacting with organometallic molecules, and it identifies the use of DFT to parameterize coverage-dependent coarse-grained models (lattice gas Hamiltonians for Monte Carlo) as a growing trend. One example in the issue showed that sulfur poisoning not only lowers CO coverage but also strongly reduces CO mobility.
Under kinetics, the preface notes that barriers and prefactors remain costlier than adsorption energies but have become routine enough for reactivity trend studies, for example glycerol decomposition selectivity on Pt(111), furan decomposition on Pd(111), N2O reduction by H2 on Pd in water, water gas shift on alloys, segregation and dissolution in fuel cell alloy electrocatalysts, and reactions on Au and Pt nanoparticles and subnanometer clusters.
Under methods, it points to cheap estimation of adsorbate thermochemistry from gas-phase properties plus adsorption energies, electronic structure descriptors estimated from simple elemental properties such as electronegativity and atomic radius, a DFT-parameterized reactive force field for molecular dynamics, and exchange-correlation functionals built by large-scale fitting to energy databases. Kitchin argues that DFT alone will not solve every problem because of timescale limits, dynamics, and functional errors, so such extensions will remain important.
Significance
The preface is a snapshot of the field’s priorities in 2012, and several of its themes (coverage-dependent models, cheap descriptors for screening, force fields fit to DFT, and data-fitted functionals) became central directions in later work by the Kitchin group and others.