The ability of the Gaussian-2, Gaussian-3, Complete Basis Set–QB3, and Complete Basis Set–APNO model chemistries to model the geometries of small water clusters

The Gaussian-2, Gaussian-3, Complete Basis Set-QB3, and Complete Basis Set-APNO methods have been used to calculate geometries of neutral clusters of water, (H2O)n, where n = 2–6. The structures are in excellent agreement with those determined from experiment and those predicted from previous high-level calculations. These methods also provide excellent thermochemical predictions for water clusters, and thus can be used with confidence in evaluating the structures and thermochemistry of water clusters.

Benchmark Structures and Binding Energies of Small Water Clusters with Anharmonicity Corrections

For (H2O)n where n = 1–10, we used a scheme combining molecular dynamics sampling with high level ab initio calculations to locate the global and many low lying local minima for each cluster. For each isomer, we extrapolated the RI-MP2 energies to their complete basis set limit, included a CCSD(T) correction using a smaller basis set and added finite temperature corrections within the rigid-rotor-harmonic-oscillator (RRHO) model using scaled and unscaled harmonic vibrational frequencies. The vibrational scaling factors were determined specifically for water clusters by comparing harmonic frequencies with VPT2 fundamental frequencies. We find the CCSD(T) correction to the RI-MP2 binding energy to be small (<1%) but still important in determining accurate conformational energies. Anharmonic corrections are found to be non-negligble; they do not alter the energetic ordering of isomers, but they do lower the free energies of formation of the water clusters by as much as 4 kcal/mol at 298.15 K.

The Search for Low Energy Conformational Families of Small Peptides: Searching for Active Conformations of Small Peptides in the Absence of a Known Receptor

Breast cancer is the most common cancer among women. Tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment, yet many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Therefore, scientists are searching for breast cancer drugs that have different molecular targets. Previous work revealed that 8-mer and cyclic 9-mer peptides inhibit breast cancer in mouse and rat model systems, interacting with an unknown receptor, while peptides smaller than eight amino acids did not inhibit breast cancer. We have shown that the use of replica exchange molecular dynamics predicts structure and dynamics of active peptides, leading to the discovery of smaller peptides with full biological activity. These simulations identified smaller peptide analogs with a conserved turn, a β-turn formed in the larger peptides. These analogs inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition. We outline the computational methods that were tried and used with the experimental information that led to the successful completion of this research.

Benchmark Structures and Binding Energies of Small Water Clusters with Anharmonicity Corrections

For (H2O)n where n = 1–10, we used a scheme combining molecular dynamics sampling with high level ab initio calculations to locate the global and many low lying local minima for each cluster. For each isomer, we extrapolated the RI-MP2 energies to their complete basis set limit, included a CCSD(T) correction using a smaller basis set and added finite temperature corrections within the rigid-rotor-harmonic-oscillator (RRHO) model using scaled and unscaled harmonic vibrational frequencies. The vibrational scaling factors were determined specifically for water clusters by comparing harmonic frequencies with VPT2 fundamental frequencies. We find the CCSD(T) correction to the RI-MP2 binding energy to be small (

The Investigation of Uniform, Monodisperse Crystalline Particles via the Evaporation of Small Droplets

Many industrial solids processes require the production of disperse particles. In industries such as food, personal care, and pharmaceuticals, particle formation is widely used to produce solid products or to separate substances in intermediate process steps. The most important characteristics known to impact the effectiveness of a solid product are purity, size, internal structure, and morphology. These characteristics are essential to maintain optimal operation of subsequent process steps and for obtaining the desired high quality product. This thesis aims to aid in the advancement of particle production technology by (1) investigating the use of a vibrating orifice aerosol generator (VOAG) for collecting data to predict particle attributes including morphology, size, and internal structure as a function of processing parameters such as solvent, solution concentration, air flow rate, and initial droplet size, as well as to (2) determine the extent to which uniform droplet evaporation can be a tool to achieve novel particle morphologies, controlled sizes, or internal structures (crystallinity and crystal form). Experimental results for succinic acid, L-serine, and L-glutamic acid suggest that particles of controlled characteristics can indeed be produced by this method. Analysis by scanning electron microscopy (SEM), nanoindentation, and X-ray diffraction (XRD) shows that various sizes, internal structures, and morphologies can be obtained using the VOAG. Furthermore, unique morphologies and unexpected internal structures were able to be achieved for succinic acid, providing an added benefit to particle formation by this method.