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Lim, Hankwon
Sustainable Process Analysis, Design, and Engineering (SPADE)
Research Interests
  • Process analysis, Process design, Techno-economic analysis, Separation process, Reaction engineering, Computational fluid dynamics, Membrane reactor, H2 energy, Water electrolysis, Vanadium redox flow battery, Greenhouse gas reduction

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Tetracyanoborate anion-based ionic liquid for natural gas sweetening and DMR-LNG process: Energy, exergy, environment, exergo-environment, and economic perspectives

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Title
Tetracyanoborate anion-based ionic liquid for natural gas sweetening and DMR-LNG process: Energy, exergy, environment, exergo-environment, and economic perspectives
Author
Kazmi, BilalHaider, JunaidTaqvi, Syed Ali AmmarAli, Syed ImranQyyum, Muhammad AbdulNagulapati, Vijay MohanLim, Hankwon
Issue Date
2022-12
Publisher
ELSEVIER
Citation
SEPARATION AND PURIFICATION TECHNOLOGY, v.303, pp.122242
Abstract
In this study, less viscous 1-hexyl-3-methylimidazolium tetracyanoborate is used to capture CO2 from the natural gas. The obtained sweet gas was liquefied through dual mixed refrigerant technology. Energy, exergy, environment, exergo-environment, and economic analysis were performed to estimate the feasibility of the process. Energy of CO2 capture process was optimized through artificial neural network using feed forward model of 2*10*3 structural design. The results revealed that the carbon capture process provides 82.1 % of exergy efficiency while MEA-based process has 58 %. The NG liquefaction process was optimized based on three case studies using 3, 4, and 5 combinations of mixed refrigerants (MRs) to minimize the specific energy con-sumption (SEC). The results indicated that the combination of 5 MRs provide a least SEC of 9.6 kW/kmol of LNG. Furthermore, proposed process shows less specific CO2 emissions of 0.91 kg of CO2/kmol with a carbon capture rate of >= 99 %. Exergo-environment analysis reveals that the proposed process is an environmentally benign process in terms of environmental effectiveness and exergy stability factors. Economic analysis of this process provides total cost savings of 62.7 %, 55.37 %, and 52.77 % relative to MEA in combination of 3, 4 and 5 MRs, respectively.
URI
https://scholarworks.unist.ac.kr/handle/201301/60032
DOI
10.1016/j.seppur.2022.122242
ISSN
1383-5866
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