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Estimating vibrational and thermodynamic properties of adsorbates with uncertainty using data driven surrogates
Author(s) -
Tian Huijie,
Rzepa Christopher,
Upadhyay Ronak,
Rangarajan Srinivas
Publication year - 2019
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.16838
Subject(s) - ab initio , thermodynamics , chemistry , entropy (arrow of time) , zeolite , statistical physics , polynomial , computational chemistry , catalysis , physics , mathematics , mathematical analysis , organic chemistry
In this work, we propose a strategy to develop data driven local surrogate models of ab initio potential energy functions describing the interaction of adsorbates on heterogeneous catalytic materials. We show that these multivariable surrogate models, based on orthogonal polynomial expansion and trained on sampled ab‐initio energies/forces, can be used to compute harmonic vibrational frequencies and the entropy of adsorbates. Further, we show that the errors in our surrogate model can be estimated and propagated to calculate the uncertainty in the computed properties. We show proof‐of‐concept illustrations of our method to calculate the vibrational frequencies of ethene on 1D edges of molybdenum sulfide (MoS 2 ), (b) 2D surfaces of Pt(111), and (c) 3D micropores of a HZSM‐5 zeolite; the entropy of ethane adsorbed on Pt(111); and the associated uncertainties in all the cases.