An Automated Machine Learning architecture for the accelerated prediction of Metal-Organic Frameworks performance in energy and environmental applications

Title
An Automated Machine Learning architecture for the accelerated prediction of Metal-Organic Frameworks performance in energy and environmental applications
Authors
Keywords
Automated machine learning, Metal-organic frameworks, Carbon dioxide, Methane, Environment, Energy
Journal
MICROPOROUS AND MESOPOROUS MATERIALS
Volume 300, Issue -, Pages 110160
Publisher
Elsevier BV
Online
2020-03-13
DOI
10.1016/j.micromeso.2020.110160

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