Review paper
Machine learning for the design and discovery of zeolites and porous crystalline materials
Abstract
Porous crystalline materials, such as zeolites and metal-organic frameworks (MOFs), have shown great promises with superior separation, catalysis and upgrading performances in many areas of energy, the environment and health. However, the discovery of new zeolites and MOFs with desired properties is a complex process that often involves trial-and-error experimental/computational approaches. Computational discovery of new materials often involves...
Paper Details
Title
Machine learning for the design and discovery of zeolites and porous crystalline materials
Published Date
Mar 1, 2022
Volume
35
Pages
100739 - 100739
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