Performance modeling of nano structure graphene membrane for hydrogen separation using CFD methods

Document Type : Chemistry Article

Authors

1 chemical engineering department, Urmia university of technology, Urmia, Iran

2 chemical engineering department, Urmia university of technology, Urmia, West Azerbaijan, Iran

3 Chemical Engineering department, Urmia university of technology, Urmia, Iran

Abstract

Due to high energy consumption and pollution rate caused by fossil fuels, in the world, hydrogen has been considered by many researchers as a clean fuel. Therefore, process of hydrogen separation can also be very important in this regard. Among various methods of hydrogen separation, membrane processes have been proposed as one of the promising methods for hydrogen purification. One the other hand, among several hydrogen selective membranes, inorganic membranes have also been considered more applicable owing to their high temperature tolerance. Meanwhile, in 2014, graphene membrane was first introduced for hydrogen separation, which showed a high selectivity over other inorganic membranes. Therefore, in this research, the performance of graphene membrane is evaluated using a CFD based model and the impact of important operating parameters such as pressure, temperature, membrane surface area and membrane selectivity on its performance have been investigated. According to the model results, the graphene membrane (with a 7% error) has the best performance at 293 K, while by increasing temperature up 373 K, H2 / CO2 selectivity is decreased from 2800 to 200 and permeances of hydrogen and carbon dioxide are indicated 2*10-7 mole /m2.Pa.s and 1.5*10-10 mole / m2.Pa.s, respectively. On the other hand, increasing the pressure and surface area values also show negative effects on hydrogen selectivity of graphene membranes.

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References

 
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Journal of Modeling in Engineering
Volume 16, Issue 55
December 2018
Pages 77-86

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History

  • Receive Date: 04 October 2017
  • Revise Date: 23 November 2017
  • Accept Date: 30 December 2017

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