Prediction of Xe/Kr Separation in Metal-Organic Frameworks by a Precursor-Based Neural Network Synergistic with a Polarizable Adsorbate Model

Prediction of Xe/Kr Separation in Metal-Organic Frameworks by a Precursor-Based Neural Network Synergistic with a Polarizable Adsorbate Model

Adsorption and separation of Xe/Kr are significant for making high-density nuclear energy environmentally friendly and for meeting the requirements of the gas industry. Enhancing the accuracy of the adsorbate model for describing the adsorption behaviors of Xe and Kr in MOFs and the efficiency of th...

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Bibliographic Details
Main Authors: Zewei Liu, Qibin Xia, Bichun Huang, Hao Yi, Jian Yan, Xin Chen, Feng Xu, Hongxia Xi
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Molecules
Subjects:
Xe/Kr
polarizable model
MOFs
precursor-based BPNN model
physical parameter
Online Access:https://www.mdpi.com/1420-3049/28/21/7367

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