Honors Theses

Date of Award

Spring 4-12-2022

Document Type

Undergraduate Thesis

Department

Chemistry and Biochemistry

First Advisor

Gregory S. Tschumper

Second Advisor

Nathan Hammer

Third Advisor

Eden Tanner

Relational Format

Dissertation/Thesis

Abstract

The study of water clusters is an important area of research in many disciplines, such as biology, physical chemistry, and environmental studies. However, due to the difficulty in studying larger water clusters, such as clathrate hydrates, it is beneficial to obtain accurate descriptions of smaller water clusters to use as models for larger systems via computational methods. By starting with small water clusters, such as (H2O)6, and moving into larger systems it is possible to build up data on various water structures that can determine the energetics of the various geometries within a certain number of water molecules. This research focuses on using full geometry optimizations that were performed on (H2O)n clusters (where n=6-8) utilizing second order MøllerPlesset perturbation theory (MP2) and density fitted Møller-Plesset perturbation theory (df-MP2). The results compiled from the MP2 and df-MP2 methods were then compared to the 2-body:Many-body technique (CCSD(T):MP2) on same structures. All three methods used the haTZ basis set, and the energetic ordering of the identified stationary points stayed the same. The deviations between the MP2 methods stayed essentially the same (no more than 0.01 kcal mol−1 ), while the deviations between the MP2 methods and CCSD(T):MP2 were much larger depending (ranging from 0.01 to 0.84 kcal mol−1 ) on the size of the water cluster. In future studies, analysis of these methods can be further implemented into larger water structures such as the water nonamer and decamer, or moved into smaller water structures such as the water trimer. By moving into other structures a better comparison of these three methods can be seen and analyzed to see how MP2 and df-MP2 compare to CCSD(T):MP2 in different sized water clusters.

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