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Multi-scale computational screening of MOFs for Xe/Kr separation

Workflow of this work

Contact

Prof. Chung: drygchung@gmail.com
Guobin Zhao: sxmzhaogb@gmai.com
Yu Chen: yuchen.drake@gmail.com

Group: Molecular Thermodynamics & Advance Processes Laboratory

Cite as

Guobin Zhao, Yu Chen and Yongchul G. Chung. High-Throughput, Multiscale Computational Screening of Metal–Organic Frameworks for Xe/Kr Separation with Machine-Learned Parameters. Industrial & Engineering Chemistry Research DOI: 10.1021/acs.iecr.3c02211. read paper

Introduction

The Xe/Kr separation program contain 3 parts:

  • Dataser preparation (GCMC simulation, Fitting)
  • Machine learning (Train models, Evaluation models, Features analysis, Predict targets)
  • Ideal VSA and High-fidelity VSA simualtion (High-througput ~6,500 MOFs & 15 MOFs)

Data download

For all csv data, code and models, you can download from zenodo
ZHAO GUOBIN, & Chung Yongchul G. (2023). Multiscale high-throughput computational screening of nanoporous materials for Xe/Kr adsorption separation. https://doi.org/10.5281/zenodo.8312801

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Data, Models, Codes of Xe/Kr Separation Project

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