Title:
Towards More Efficient ab initio Computation of Physical Properties
Towards More Efficient ab initio Computation of Physical Properties
| dc.contributor.advisor | Sherrill, C. David | |
| dc.contributor.author | Zott, Michael D. | |
| dc.contributor.committeeMember | Barefield, E. K. | |
| dc.contributor.department | Chemistry and Biochemistry | |
| dc.date.accessioned | 2019-05-30T16:23:41Z | |
| dc.date.available | 2019-05-30T16:23:41Z | |
| dc.date.created | 2018-05 | |
| dc.date.issued | 2018-05 | |
| dc.date.submitted | May 2018 | |
| dc.date.updated | 2019-05-30T16:23:41Z | |
| dc.description.abstract | The introduction of the modern computer has been a boon to myriad scientific communities. Scientific experiment can be categorized into the categories of physical experiment and thought experiment. In the chemical arena, these thought experiments are now able to be tested for validity through advanced semi-empirical and ab initio computational methods. Theoretical chemistry continues to increase in efficacy, and the spread of classical, wavefunction, and density functional methods into experimental communities is now undeniable. An aspiration of computational chemistry is to provide predictive power to lower the number of physical experiments that need to be performed. This is especially important when systems arise that are difficult to study experimentally. This has the possibility to lower financial and environmental costs, in addition to reducing the time needed to perform physical experiments. Here, methods to computationally study solvent effects and crystal lattice energies are reported on. Both of these physical properties have substantial relevance to human-focused enterprises such as targeted drug design. For example, drugs are often delivered in solid, crystalline form and must dissolve into molecular form prior to being pharmaceutically active. Although the specific research reported on here does not use systems directly related to such applications, it is posited that fundamental advances in computational methods for computing physical properties for arbitrary systems will contribute to solving problems in drug design, material development, and biomolecule recognition. | |
| dc.description.degree | Undergraduate | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1853/61365 | |
| dc.language.iso | en_US | |
| dc.publisher | Georgia Institute of Technology | |
| dc.subject | QM/MM | |
| dc.subject | crystal lattice energy | |
| dc.subject | many body expansion | |
| dc.subject | valiron mayer functional counterpoise | |
| dc.subject | coupled cluster | |
| dc.subject | mp2 | |
| dc.subject | dft | |
| dc.subject | psi4 | |
| dc.subject | openmm | |
| dc.subject | ab initio | |
| dc.subject | benchmark | |
| dc.subject | torsion balance | |
| dc.title | Towards More Efficient ab initio Computation of Physical Properties | |
| dc.type | Text | |
| dc.type.genre | Undergraduate Thesis | |
| dspace.entity.type | Publication | |
| local.contributor.advisor | Sherrill, C. David | |
| local.contributor.corporatename | School of Chemistry and Biochemistry | |
| local.contributor.corporatename | College of Sciences | |
| local.contributor.corporatename | Undergraduate Research Opportunities Program | |
| local.relation.ispartofseries | Undergraduate Research Option Theses | |
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| thesis.degree.level | Undergraduate |