TY - JOUR
T1 - Developing a Descriptor-Based Approach for CO and NO Adsorption Strength to Transition Metal Sites in Zeolites
AU - Göltl, Florian
AU - Müller, Philipp
AU - Uchupalanun, Pajean
AU - Sautet, Philippe
AU - Hermans, Ive
N1 - Funding Information:
F.G. P.M., and I.H. acknowledge financial support from the University of Wisconsin-Madison and the Wisconsin Alumni Research Foundation (WARF). F.G. acknowledges financial support from the U.S. Department of Energy-Basic Energy Sciences (DOE-BES), Division of Chemical Sciences, Grant DE-FG02-05ER15731. P.M. and I.H. acknowledge support from the Donors of the American Chemical Society Petroleum Research Fund under Grant No. PRF 56136-ND5. We acknowledge computational time at Phoenix Supercomputer, which is in part supported by National Science Foundation Grant CHE-0840494 and the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Project No. m2070-Zeo-genome.
Publisher Copyright:
© 2017 American Chemical Society.
PY - 2017/8/8
Y1 - 2017/8/8
N2 - The discovery of new materials tailored for a given application typically requires the screening of a large number of compounds, and this process can be significantly accelerated by computational analysis. In such an approach the performance of a compound is correlated to a materials property, a so-called descriptor. Here we develop a descriptor-based approach for the adsorption of CO and NO to Cu, Ni, Co, and Fe sites in zeolites. We start out by discussing a possible design strategy for zeolite catalysts, define the studied test set of sites in the zeolites SSZ-13 and mordenite, and define a set of appropriate descriptors. In a subsequent step we use these descriptors in single-parameter, two-parameter, and multiparameter regression analysis and finally use a machine-learning genetic algorithm to reduce the number of variables. We find that one or two descriptors are not sufficient to accurately capture the interactions between molecules and metal centers in zeolites, and indeed a multiparameter approach is necessary. Even though many of the descriptors are directly correlated, we identify the position of the s orbital and the number of valence electrons of the active site as well as the HOMO-LUMO gap of the adsorbate as most important descriptors. Furthermore, the reconstruction of the active sites upon adsorption plays a crucial role, and when it is explicitly included in the analysis, correlations improve significantly. In the future we expect that the fundamental methodology developed here will be adapted and transferred to selected problems in adsorption and catalysis and will assist the rational design of materials for the given application.
AB - The discovery of new materials tailored for a given application typically requires the screening of a large number of compounds, and this process can be significantly accelerated by computational analysis. In such an approach the performance of a compound is correlated to a materials property, a so-called descriptor. Here we develop a descriptor-based approach for the adsorption of CO and NO to Cu, Ni, Co, and Fe sites in zeolites. We start out by discussing a possible design strategy for zeolite catalysts, define the studied test set of sites in the zeolites SSZ-13 and mordenite, and define a set of appropriate descriptors. In a subsequent step we use these descriptors in single-parameter, two-parameter, and multiparameter regression analysis and finally use a machine-learning genetic algorithm to reduce the number of variables. We find that one or two descriptors are not sufficient to accurately capture the interactions between molecules and metal centers in zeolites, and indeed a multiparameter approach is necessary. Even though many of the descriptors are directly correlated, we identify the position of the s orbital and the number of valence electrons of the active site as well as the HOMO-LUMO gap of the adsorbate as most important descriptors. Furthermore, the reconstruction of the active sites upon adsorption plays a crucial role, and when it is explicitly included in the analysis, correlations improve significantly. In the future we expect that the fundamental methodology developed here will be adapted and transferred to selected problems in adsorption and catalysis and will assist the rational design of materials for the given application.
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U2 - 10.1021/acs.chemmater.7b01860
DO - 10.1021/acs.chemmater.7b01860
M3 - Article
AN - SCOPUS:85027338578
SN - 0897-4756
VL - 29
SP - 6434
EP - 6444
JO - Chemistry of Materials
JF - Chemistry of Materials
IS - 15
ER -