Perturbation Theory-Machine Learning Study of Zeolite Materials Desilication

J Chem Inf Model. 2018 Dec 24;58(12):2414-2419. doi: 10.1021/acs.jcim.8b00383. Epub 2018 Sep 7.

Abstract

Zeolites are important materials for research and industrial applications. Mesopores are often introduced by desilication but other properties are also affected, making its optimization difficult. In this work, we demonstrate that Perturbation Theory and Machine Learning can be combined in a PTML multioutput model describing the effects of desilication. The PTML model achieves a notable accuracy ( R2 = 0.98) in the external validation and can be useful for the rational design of novel materials.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Machine Learning*
  • Models, Molecular
  • Monte Carlo Method
  • Silicon / chemistry*
  • Surface Properties
  • Zeolites / chemistry*

Substances

  • Zeolites
  • Silicon