Abstract

Here, we utilize Quantum Chemistry (QC) approaches to predict the structures, vibrational frequencies, infrared intensities and Raman activities of unusual molecular species using the General Atomic and Molecular Structure System (GAMESS(US)) package. A Python-based software, AutoGAMESS, was developed to automate the workflow and take advantage of High Throughput Computing (HTC) techniques enabling the automated generation of spectroscopic data from hundreds of calculations. This approach was utilized to determine these properties for a series of carbon oxides (C2On; n = 3 to 4), anticipated to be produced during the radiation of pure carbon dioxide ices, under conditions relevant to the interstellar medium. Beyond generating predicted spectroscopic results, we additionally performed a benchmark study of 70 different basis sets across multiple levels of theory (including Density Functional Theory, Moller–Plesset, and Coupled Cluster calculations), in QC to identify the method with the best balance between obtaining the lowest error in predictions while being mindful of the computation resources required.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu.

Graduation Date

2021

Semester

Fall

Advisor

Bennett, Christopher

Degree

Master of Science (M.S.)

College

College of Sciences

Department

Physics

Degree Program

Physics

Format

application/pdf

Identifier

CFE0008833

Language

English

Release Date

December 2021

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Share

COinS