282
Views
3
CrossRef citations to date
0
Altmetric
CO2 Capture

Simulation of carbon dioxide absorption by amino acids in two-phase batch and bubble column reactors

ORCID Icon, ORCID Icon & ORCID Icon
Pages 2013-2025 | Received 21 Oct 2018, Accepted 15 Apr 2019, Published online: 05 May 2019
 

ABSTRACT

The absorption of carbon dioxide (CO2) is an important process in many practical applications. The use of amino acid solutions as absorption solvents has the potential to reduce the amount of energy required by the regeneration process. The goal of this research project is to develop dynamic models to simulate CO2 absorption by using amino acid solutions as absorption solvents. A reaction scheme is proposed to represent the chemical reactions between the amino acid and CO2. Two reaction models, for a two-phase batch reactor and a bubble column, based upon transient mass and energy balances for the chemical species found in CO2 gas-liquid absorption are presented. Computer codes have been written to implement the proposed models. Simulation results are presented and discussed. The proposed models can be used to optimize and control CO2 absorption in practical applications.

Acknowledgments

Notice: This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Additional information

Funding

Funding for this research provided by the Office of Technology of the U.S. Department of Energy, under the Transition’s Technology Commercialization Fund [Grant # TCF-17-13299], is gratefully acknowledged by the authors. This study was conducted at Prairie View A&M University and the Oak Ridge National Laboratory (ORNL). ORNL is managed by UT-Battelle, LLC under Contract DE-AC05-00OR22725 with the U.S. Department of Energy.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 681.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.