Computational Design and Evaluation of New Materials for Energy and Environmental Applications

With a constant demand for efficient energy devices, significant efforts were invested into the development of proton exchange membrane (PEM) fuel cells. Yet, water management and hydration in these PEM fuel cells are a well-known limiting factors for proton transport. The first-principles density functional theory (DFT) study helped to develop two novel 2- D materials that can potentially alleviate the need for aqueous conditions to propagate proton conduction within fuel cells. Anhydrous proton conduction can be achieved when graphane is functionalized with hydroxyl and amine groups as graphamine and graphanol, respectively. Ab-initio molecular dynamics simulations indicated that the proton transport is facile with a relatively low reaction barrier due to the presence of a self-assembling network of hydrogen bonds established over the surface of these materials. Moreover, proton self-diffusivity increases with temperature and thermodynamic stability calculations indicate that these materials are appropriate for intermediate-temperature fuel cells. Given the environmental concerns of tritiated water (HTO), this work is an attempt to understand the fundamental nature of differential hydrogen bonding offered by the hydrogen isotopes. When two phases (liquid and vapor) of water are in equilibrium, there can be slight difference in the relative abundance of water isotopes for each phase. The treatment of nuclei under classical mechanics is not appropriate for the study of lighter atoms like hydrogen and its isotopes. By employing path-integral-based molecular simulations one can account for quantum motion of the nuclei to determine isotopic fractionation ratios for water isotopologues in phase equilibrium and cocrystallization of water isotopologues with poly- oxacyclobutane. Due to the inherent computationally intensive nature of these calculations, a combination of reduced-cost and accelerated techniques such as high-order splitting and thermostating procedures were used to achieve convergence of quantum mechanical proper- ties

Master of Science

thesisRecent advancements in High Performance Computing (HPC) infrastructure with tradi- tional computing systems augmented with accelerators like graphic processing units (GPUs) and coprocessors like Intel Xeon Phi have successfully enabled predictive simulations specifi- cally Computational Fluid Dynamics (CFD) with more accuracy and speed. One of the most significant challenges in high-performance computing is to provide a software framework that can scale efficiently and minimize rewriting code to support diverse hardware configurations. Algorithms and framework support have been developed to deal with complexities and provide abstractions for a task to be compatible with various hardware targets. Software is written in C++ and represented as a Directed Acyclic Graph (DAG) with nodes that implement actual mathematical calculations. This thesis will present an improved approach for scheduling and execution of computational tasks within a heterogeneous CPU-GPU com- puting system insulting application developers with the inherent complexity in parallelism. The details will be presented within a context to facilitate the solution of partial differential equations on large clusters using graph theory

Impact of Support Interactions for Single-Atom Molybdenum Catalysts on Amorphous Silica

Amorphous silica is a commonly used catalyst support, yet there are relatively few experimental or computational studies on catalyst–support interactions for this material. This is largely due to the inherent difficulty in modeling and experimentally characterizing amorphous silica. We used a recently developed surface model for amorphous silica surfaces to study the support effects on single-atom molybdenum catalysts. We found that the local structure of the silica support in the vicinity of the Mo site has a profound effect on the energetics and kinetics of metallacycle rotation, which is related to ethene metathesis. We have compared site energies, reaction energies, and reaction barriers computed from simple cluster models with results from surface models. The cluster models show a clear relationship between Si–Si distances and the site energies and reaction energies. In contrast, the surface model shows no correlation between Si–Si distances and energetics. The reaction barriers clearly increase with increasing Si–Si distances in the cluster model, whereas there is only a qualitative trend in the surface model. Analysis of the surface results indicates that the reaction energetics are affected by neighboring hydroxyl groups and Si atoms in the surface that are not accounted for in the cluster models. We therefore conclude that the simple trends relating support atom geometries to reaction energetics observed in the cluster models are artifacts of the model