Metal-Organic Frameworks (MOFs) are three-dimensional porous nanomaterials with a variety of applications, including catalysis, gas storage and separation, and sustainable energy. Their potential as air filtration systems is of interest for designer carbon capture materials. The chemical constituents (i.e. organic ligands) can be functionalized to create rationally designed CO2 sequestration platforms, for example. Hardware and software alike at the bleeding edge of supercomputing are utilized for designing first principles-based molecular models for the simulation of gas sorption in these frameworks. The classical potentials developed herein are named PHAST -- Potentials with High Accuracy, Speed, and Transferability, and thus are designed via a "bottom-up" approach. Specifically, models for N2 and CH4 are constructed and presented.
Extensive verification and validation leads to insights and range of applicability. Through this experience, the PHAST models are improved upon further to be more applicable in heterogeneous environments. Given this, the models are applied to reproducing high level ab initio energies for gas sorption trajectories of helium atoms in a variety of rare-gas clusters, the geometries of which being representative of sorption-like environments commonly encountered in a porous nanomaterial. This work seeks to push forward the state of classical and first principles materials modeling.
Additionally, the characterization of a new type of tunable radical metal--carbene is presented. Here, a cobalt(II)--porphyrin complex, [Co(Por)], was investigated to understand its role as an effective catalyst in stereoselective cyclopropanation of a diazoacetate reagent. Density functional theory along with natural bond order analysis and charge decomposition analysis gave insight into the electronics of the catalytic intermediate. The bonding pattern unveiled a new class of radical metal--carbene complex, with a doublet cobalt into which a triplet carbene sigma donates, and subsequent back-bonding occurs into a pi* antibonding orbital. This is a different type of interaction not seen in the three existing classes of metal-carbene complexes, namely Fischer, Schrock, and Grubbs.
Finally, the virtual engineering of enhanced chemical warfare agent (CWA) detection systems is discussed. As part of a U.S. Department of Defense supported research project, in silico chemical modifications to a previously synthesized zinc-porphyrin, ZnCS1, were made to attempt to achieve preferential binding of the nerve agent sarin versus its simulant, DIMP (diisopropyl methylphosphonate). Upon modification, a combination of steric effects and induced hydrogen bonding allowed for the selective binding of sarin. The success of this work demonstrates the role that high performance computing can play in national security research, without the associated costs and high security required for experimentation.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-6864 |
| Date | 01 January 2015 |
| Creators | Cioce, Christian R. |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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