(349d) Catmap: A Software Package for Descriptor-Based Micro-Kinetic Mapping of Catalytic Trends

Authors: 
Medford, A., SLAC National Accelerator Laboratory
Lausche, A., University of Michigan
Fitzgibbon, S., Stanford University
Norskov, J. K., SUNCAT Center for Interface Science and Catalysis, Stanford University and SLAC National Accelerator Laboratory
Bligaard, T., SLAC National Accelerator Laboratory

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. The module is designed to be both flexible and powerful. 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 talk will explain the general structure of the code, provide an introduction to the implementation, and show examples of catalytic rate and selectivity maps generated with the code.

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