Predicting the Mechanical Properties of Zeolite Frameworks by Machine Learning

We
show here that machine learning is a powerful new tool for predicting
the elastic response of zeolites. We built our machine learning approach
relying on geometric features only, which are related to local geometry,
structure, and porosity of a zeolite, to predict bulk and shear moduli
of zeolites with an accuracy exceeding that of force field approaches.
The development of this model has illustrated clear correlations between
characteristic features of a zeolite and elastic moduli, providing
exceptional insight into the mechanics of zeolitic frameworks. Finally,
we employ this methodology to predict the elastic response of 590 448
hypothetical zeolites, and the results of this massive database provide
clear evidence of stability trends in porous materials.