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CatMAP: A Software Package for Descriptor-Based Microkinetic Mapping of Catalytic Trends

Authors :
Jens K. Nørskov
Chuan Shi
Max J. Hoffmann
Andrew J. Medford
Sean Fitzgibbon
Thomas Bligaard
Adam C. Lausche
Source :
Catalysis Letters. 145:794-807
Publication Year :
2015
Publisher :
Springer Science and Business Media LLC, 2015.

Abstract

Descriptor-based analysis is a powerful tool for understanding the trends across various catalysts. In general, the rate of a reaction over a given catalyst is a function of many parameters—reaction energies, activation barriers, thermodynamic conditions, etc. The high dimensionality of this problem makes it very difficult and expensive to solve completely, and even a full solution would not give much insight into the rational design of new catalysts. The descriptor-based approach seeks to determine a few “descriptors” upon which the other parameters are dependent. By doing this it is possible to reduce the dimensionality of the problem—preferably to 1 or 2 descriptors—thus greatly reducing computational efforts and simultaneously increasing the understanding of trends in catalysis. The “CatMAP” Python module seeks to standardize and automate many of the mathematical routines necessary to move from “descriptor space” to reaction rates for heterogeneous (electro) catalysts. The module is designed to be both flexible and powerful, and is available for free online. A “reaction model” can be fully defined by a configuration file, thus no new programming is necessary to change the complexity or assumptions of a model. Furthermore, various steps in the process of moving from descriptors to reaction rates have been abstracted into separate Python classes, making it easy to change the methods used or add new functionality. This work discusses the structure of the code and presents the underlying algorithms and mathematical expressions both generally and via an example for the CO oxidation reaction.

Details

ISSN :
1572879X and 1011372X
Volume :
145
Database :
OpenAIRE
Journal :
Catalysis Letters
Accession number :
edsair.doi...........8bf2a33c0c9d77cf8f9a230ca51ee44a
Full Text :
https://doi.org/10.1007/s10562-015-1495-6