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New Physical Insights from a Computational Catalysis Perspective 1. COMPUTATIONAL CATALYSIS ON THE ASCENT Over the last 20 years the number of studies that apply molecular-level computational methods to catalysis has grown at an incredible pace. A Web of Science query for works that contain the topics “DFT” and “catalysis” or “catalytic” returns more than 15 000 hits, including more than 2100 in 2016 alone. Actual numbers are surely much greater, given the diverse terminology and wide variety of computational methods and approaches that are applied to catalytic problems. The origins of this phenomenal growth are easy to understand. Catalysis in general and heterogeneous catalysis in particular are essential to providing the comforts of modern life, and they are recognized as becoming only more important as society confronts pressing food, energy, and environmental challenges. New synthetic methods, spectroscopies, and microscopies are yielding information about catalysts at the atomic scale and under operating conditions, information that becomes only richer and more valuable when married with computational models. At the same time computers continue to become faster and less expensive. Density functional theory has emerged as a reliable computational workhorse; new algorithms and theoretical approaches increase the speed and reliability of those computational predictions and allow trends and correlations to be identified across diverse materials; and those predictions feed into an array of coarse-grained models to facilitate direct comparisons with quantities that can be measured in the laboratory. Computational catalysis has become an integral element of the science of catalysis. Today, the computational machinery to carry out molecular simulations is widely available from both academic and commercial sources. Many include graphical interfaces that lower the barrier (so to speak!) for an appropriately trained scientist to make predictions about a catalytic system. Unlike, say, an atomic-resolution microscope or high-field NMR spectrometer, essentially every university and research institute has its own computer facilities, and access to supercomputers is available to many at the cost of just a short proposal. Many of us now teach computational catalysis in summer schools, in graduate electives, and even in undergraduate classes. Thus, the basic tools are as widely available, and as widely used, as any in the field.
insights can and do often emerge from solely computational research, for instance by rationalizing observations already in the literature or by making predictions useful to motivate and guide future experiments. When considering whether a computational catalysis study is appropriate to JPC, ask yourself the following: 1. Is the problem motivated by and connected to experimental observation? If not, do the results offer insights beyond predicting the potential catalytic utility of a previously unstudied material? 2. Are computed mechanistic steps (intermediates, transition states) critically compared against other models, proposals, and/or results from the literature? In a field as active as computational catalysis, it is the rare reaction that has not received some attention in the literature. New insights emerge when new results are placed in the context of prior work. 3. Are the kinetic implications of the computational results considered beyond identifying transition states and comparing reaction barriers? Microkinetic modeling and associated analyses (most abundant surface intermediates, reaction rate orders, degree of rate control, ...) are today nearly as routine as DFT calculations and can considerably enhance the insights extracted from a computational study. 4. Does the work propose and demonstrate a new computational methodology, theory, or analysis of potential broader application? 5. Are the problem and the results presented in a manner accessible to a physical chemistry audience, and do they lead to some deeper insights of particular relevance to that audience? Is the manuscript Title appropriately descriptive, and do the Conclusions highlight the new physical insights and their potential implications? 6. Are the computational methods appropriate and state-ofthe-art, are they described in sufficient detail that they could be replicated by others, and are primary results (structures, energies, ...) provided in Supporting Information? No one computational catalysis contribution will satisfy all these criteria, but if a particular contribution does not clearly satisfy at least a couple, it is most likely not appropriate to JPC. The cover letter is a great place to make the case. The Journal of Physical Chemistry accounts for a larger fraction of those 15 000 Web of Science hits mentioned above than any other journal. We look forward, with your help, to continuing to publish the most insightful research at the nexus of physical, computational, and catalytic chemistry.
2. WHAT CONSTITUTES COMPUTATIONAL CATALYSIS INSIGHT? As the field of computational catalysis has grown and matured, the bar for “new physical insights” as they pertain to the Journal of Physical Chemistry has necessarily evolved. Calculations that were at one time novel and appropriate to the Journalthe intermediates and transition states for a reaction on some catalyst model, trends in reaction energies, computed surface structures or spectraare now routine and as such are generally more appropriate to a journal with a more specialized scope than JPC. The new insights bar is more easily met when computational results are compared and contrasted side-by-side with complementary experiments. However, new physical © 2017 American Chemical Society
William F. Schneider* Department of Chemical and Biomolecular Engineering and Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United States Published: July 27, 2017 15491
DOI: 10.1021/acs.jpcc.7b06535 J. Phys. Chem. C 2017, 121, 15491−15492
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The Journal of Physical Chemistry C
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. ORCID
William F. Schneider: 0000-0003-0664-2138 Notes
The author declares no competing financial interest.
15492
DOI: 10.1021/acs.jpcc.7b06535 J. Phys. Chem. C 2017, 121, 15491−15492
