Modeling Interactions Between Carbon Dioxide and Biomolecules
Pubblico DepositedWith CO2 levels on the rise in the earth, air, and water, reducing emissions to combat global warming is more important than ever. Solvent carbon capture is an effective method for removing CO2 from industrial flue gas streams, but traditional solvents pose issues for the sustainability of the process. New solvents that are environmentally friendly and more efficient are in demand. Biomolecules, specifically amino acids, may be able to fill this demand. Atomistic modeling (density functional theory) was employed to model the interactions of nine amino acids with CO2 in an aqueous setting. The goals of the project were to determine which density functional theory methods were most effective for modeling the binding interactions between CO2 molecules and amino acids, and to quantify the binding energies of amino acid-CO2 complexes. Analysis with t-tests revealed significant effects when solvation modeling was removed, or the basis set was altered. Conversely, excluding dispersion corrections showed no significant impact. Switching the exchange-correlation functional from M06-2X to B3LYP did not significantly alter the internal energies or reaction geometries, except for in the geometries of the amino acid-CO2 zwitterions. However, changing the base which deprotonates the zwitterion in the reaction notably affected the internal energy change. DFT calculations performed at a 6-311++G** level with the M06-2X functional, solvation modeling with COSMO, and without dispersion correction are recommended as the most effective method, among those explored, for modeling the interactions of amino acids with CO2. The binding energies for the complexes of nine amino acids with CO2 were calculated and data supports that the binding energies of these complexes are independent of the amino acid.
- This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
- Creator
- Subject
- Publisher
- Identifier
- 121580
- E-project-042424-181659
- Parola chiave
- Advisor
- Year
- 2024
- UN Sustainable Development Goals
- Date created
- 2024-04-24
- Resource type
- Major
- Source
- E-project-042424-181659
- Rights statement
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