Literature DB >> 22784373

Large-scale computational screening of zeolites for ethane/ethene separation.

Jihan Kim1, Li-Chiang Lin, Richard L Martin, Joseph A Swisher, Maciej Haranczyk, Berend Smit.   

Abstract

Large-scale computational screening of thirty thousand zeolite structures was conducted to find optimal structures for separation of ethane/ethene mixtures. Efficient grand canonical Monte Carlo (GCMC) simulations were performed with graphics processing units (GPUs) to obtain pure component adsorption isotherms for both ethane and ethene. We have utilized the ideal adsorbed solution theory (IAST) to obtain the mixture isotherms, which were used to evaluate the performance of each zeolite structure based on its working capacity and selectivity. In our analysis, we have determined that specific arrangements of zeolite framework atoms create sites for the preferential adsorption of ethane over ethene. The majority of optimum separation materials can be identified by utilizing this knowledge and screening structures for the presence of this feature will enable the efficient selection of promising candidate materials for ethane/ethene separation prior to performing molecular simulations.

Entities:  

Year:  2012        PMID: 22784373     DOI: 10.1021/la302230z

Source DB:  PubMed          Journal:  Langmuir        ISSN: 0743-7463            Impact factor:   3.882


  4 in total

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Authors:  Tim M Becker; Jurn Heinen; David Dubbeldam; Li-Chiang Lin; Thijs J H Vlugt
Journal:  J Phys Chem C Nanomater Interfaces       Date:  2017-01-31       Impact factor: 4.126

3.  Computational Screening of Metal-Organic Frameworks for Ethylene Purification from Ethane/Ethylene/Acetylene Mixture.

Authors:  Yageng Zhou; Xiang Zhang; Teng Zhou; Kai Sundmacher
Journal:  Nanomaterials (Basel)       Date:  2022-03-04       Impact factor: 5.076

4.  Design of organic structure directing agents to guide the synthesis of zeolites for the separation of ethylene-ethane mixtures.

Authors:  Frits Daeyaert; Michael W Deem
Journal:  RSC Adv       Date:  2020-05-27       Impact factor: 4.036

  4 in total

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