An ab Initio Investigation of van der Waals-Rich Systems and a Machine Learning Approach to Finding Analytical Functions Describing Tabulated Data
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- abstract
- van der Waals interactions are weak, non-specific forces arising at the atomic scale. Although they are weak---much weaker than a covalent or ionic interaction---they occur in large numbers, and in total, can make a significant contribution to the properties of a system. Several systems are herein explored whose properties are influenced strongly by van der Waals interactions. These systems are investigated largely through the non-local van der Waals density functional (vdW-DF) working within density functional theory (DFT), with accurate quantum chemistry calculations and experimental results to serve as a reference against which we compare our results. Properties calculated for (H2O)n with n=1--5 showed systematic improvement when van der Waals interactions were included. The low-temperature phase of Mg(BH4)2 is incorrectly predicted by standard local or semi-local approximations. However, the inclusion of van der Waals interactions brings theory in line with experiment. Dimers of phenalenyl and the nitrogen- and boron-substituted closed-shell analogues show an interesting collection of phenomena, including a 2-electron/multi-center bond and an anomalous barrier in a rotational total energy profile caused by electron kinetic energy. In the final part of this work, the theoretical groundwork is laid for a computational tool that uses network concepts to perform analytical calculations. These \emph{network functions} are capable of learning the mathematical connection in a set of data. A course to use network functions to improve DFT through a search for a kinetic energy functional and an improved exchange-correlation functional is discussed.
- subject
- chemical physics
- density functional theory
- machine learning
- van der Waals
- contributor
- Thonhauser, Timo (committee chair)
- Thonhauser, Timo (committee member)
- Salam, Akbar (committee member)
- Cook, Gregory B (committee member)
- Holzwarth, Natalie (committee member)
- Jurchescu, Oana (committee member)
- date
- 2012-09-05T08:35:15Z (accessioned)
- 2014-09-05T08:30:09Z (available)
- 2012 (issued)
- degree
- Physics (discipline)
- embargo
- 2014-09-05 (terms)
- identifier
- http://hdl.handle.net/10339/37427 (uri)
- language
- en (iso)
- publisher
- Wake Forest University
- title
- An ab Initio Investigation of van der Waals-Rich Systems and a Machine Learning Approach to Finding Analytical Functions Describing Tabulated Data
- type
- Dissertation