Towards Computational CO2 Capture and Storage Models
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Keywords

Models
Computational
CO2 capture and storage

How to Cite

1.
Makul N. Towards Computational CO2 Capture and Storage Models: A Review. Glob. Environ. Eng. [Internet]. 2021 Dec. 25 [cited 2023 Jan. 28];8:55-69. Available from: https://www.avantipublishers.com/index.php/tgevnie/article/view/1159

Abstract

This review is aimed to increase knowledge on computational CO2 capture and storage models that are gradually evolving in the design and development to act as more effective carbon capture agents with acceptable toxicity and costs and complementary adjuncts to experiments for comprehending amino-CO2 reaction mechanisms. Also, the review discussed experimental research of degradation reactions of aqueous organic amines, measurements, kinetics and forecasts of amine pKₐ values and amine-CO2 equilibria. Also, the researcher comprehensively discussed the computational simulation of mechanisms of carbon capture reactions. In the contexts of experimental and computational studies, the comparative advantages of bicarbonate, carbamic acid, termolecular and zwitterion are described. Computational approaches shall gradually evolve in the design and development to act as more effective carbon capture agents with acceptable toxicity and costs and complementary adjuncts to experiments for comprehending amino-CO2 reaction mechanisms. Some of the main research findings indicate that advancements in quantum computing might help in simulating larger complex molecules such as CO2. Moreover, the simulations might discover new catalysts for CO2 capture that are more efficient and cheaper than present models. CO2 capture and storage (CCS) could minimize the CO2 emission volume by 14%. The first stride in CCS is capturing CO2. It accounts for 70% -80% of this technology total costs. Virtually, 50% of the costs to operate the post-combustion capture (PCC) plants are related to steam costs. It is thus important to acquire the best possible data to avoid unnecessary costs and overdesigns.

https://doi.org/10.15377/2410-3624.2021.08.5
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