Extensive all-atom molecular dynamics studies of polyethylene glycol (PEG(2000)) when solvated and in the polymer bulk condensed phases were performed across a wide temperature range. We proposed two modified all-atom force field and observed the fate of the PEG(2000) macromolecule when solvated in water, water with 4% ethanol, and ethyl acetate. In aqueous solutions, the macromolecule collapsed into a prolate spheroidal ball-like structure while adopting a rather elongated coiled structure in ethyl acetate. Inspection of the polymer-condensed phases across the 150-340 K temperature range enabled the atomistic view of the solid glass below the glass transition temperature of 230 K < T-g < 250 K and the rubber behavior above T-g. Predicted properties include the enthalpy, density, and cohesive energy temperature behavior, the specific heat, thermal expansivity, thermal compressibility, bulk modulus, and Hildebrand solubility parameter both below and above T-g. Within the polymer matrix, the PEG(2000) macromolecules were entangled displaying a wide distribution of sizes that persisted when transitioning from the glass to the rubbery phases. Calculated properties agree very well with experiments when available or stand as crucial predictions while awaiting experimental measurement. Understanding the thermodynamics and structure of this useful polymer enables the efficient prediction of its behavior when building novel composite materials for nanomedicine and nanotherapeutics.

A logarithmic oscillator has the outstanding property that the expectation value of its kinetic energy is constant for all stationary states. Recently the ansatz that this property can be used to define a Hamiltonian thermostat has been put forward and a suggestion has been made that this logarithmic oscillator weakly coupled to a small system would serve as a thermostat as long as few degrees of freedom are involved as is the case in atomic clusters. We have applied these ideas to a cluster of four Lennard-Jones atoms and inspected two different models of coupling between the cluster and the logarithmic oscillator in three dimensions. In both cases we show that there is a clear generation of kinetic motion of the cluster center of mass, but that kinetic energy due to interatomic vibrations is not significantly affected by coupling to the logarithmic oscillator. This is a failure of the published ansatz, as the logarithmic oscillator is unable to modify the kinetic energy due to vibrations in small atomic clusters.

Collisions between pairs of galaxies usually end in the coalescence (merger) of the two galaxies. Collisions and mergers are rare phenomena, yet they may signal the ultimate fate of most galaxies, including our own Milky Way. With the onset of massive collection of astronomical data, a computerized and automated method will be necessary for identifying those colliding galaxies worthy of more detailed study. This project researches methods to accomplish that goal. Astronomical data from the Sloan Digital Sky Survey (SDSS) and human-provided classifications on merger status from the Galaxy Zoo project are combined and processed with machine learning algorithms. The goal is to determine indicators of merger status based solely on discovering those automated pipeline-generated attributes in the astronomical database that correlate most strongly with the patterns identified through visual inspection by the Galaxy Zoo volunteers. In the end, we aim to provide a new and improved automated procedure for classification of collisions and mergers in future petascale astronomical sky surveys. Both information gain analysis (via the C4.5 decision tree algorithm) and cluster analysis (via the Davies-Bouldin Index) are explored as techniques for finding the strongest correlations between human-identified patterns and existing database attributes. Galaxy attributes measured in the SDSS green waveband images are found to represent the most influential of the attributes for correct classification of collisions and mergers. Only a nominal information gain is noted in this research, however, there is a clear indication of which attributes contribute so that a direction for further study is apparent.