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Status: Unchecked ×Keyword: quantum chemical properties ×Clear all

2 claims from 1 paper

1. Materials Science › Machine Learning in Materials Science

   Machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery

   Rosen, Iyer, Ray et al. · Matter · 2021

   The authors built a quantum-chemical database of over 14,000 experimentally synthesised MOFs, tested machine learning models for predicting band gaps, and used the results to identify MOFs with targeted electronic properties.

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   1. Unchecked“We also show how unsupervised learning methods can aid the discovery of otherwise subtle structure–property relationships using the computational findings in this work.”
   2. UncheckedThe paper highlights several metal–organic frameworks with low band gaps, which is hard because most of these materials are electrical insulators.“We conclude by highlighting several MOFs with low band gaps, a challenging task given the electronically insulating nature of most MOF structures.”