<p>The recent surge in shale gas production led to increases in alkane resources across the United States. One promising approach to convert the alkanes to higher value products is through dehydrogenation and oligomerization processes. This conversion to alkenes, if done in small modular units near the shale wells further aids in the ease of transportation and distribution of the final products. However, having highly selective processes is a major hindrance to improve the economic feasibility of the modular processes. Theoretical studies are of great significance to analyze detailed reaction mechanisms and identify the reaction pathways that leads to unselective product formations. These studies further enable the search for selective catalysts for any given chemistry based on descriptor analysis. Therefore, in this work Density Function Theory and Ab-initio Molecular Dynamics methods are used in conjunction with microkinetic modeling analyses to investigate the complex reaction networks involved in the shale gas conversion. Specifically, the work focuses on propane dehydrogenation (PDH) on alloy surfaces along with ethylene oligomerization on zeolite catalysts.</p><p> A major part of thesis is focused on finding selective and stable alloy catalysts for PDH chemistry. The initial work focused on understanding the selectivity, activity, and stability differences between 1:1 intermetallic alloys (PdIn) and the pure metal surfaces. This combined experimental and computational study shed light on the important role of step surfaces in understanding the activity trends across alloys. Through a detailed microkinetic analysis and simplified rate expression analysis, a novel selectivity descriptor in terms of effective barriers for propane C-H bond breaking and propyne C-C bond breaking was derived for propylene formation. This newly proposed descriptor showed greater fidelity for predicting the trends in experimental selectivities for a small set of Pd alloys than the previously proposed selectivity descriptors. Building upon these insights, a high throughput screening framework using graph-theory algorithms and python-based databasing has been developed to identify trends across a larger set of alloy combinations. The framework helped us identify a novel set of alloys that have not been explored until now for this chemistry. These alloy combinations were then experimentally tested and shown to have high selectivities for propylene formation and along with stabilities close to benchmark Pt-Sn catalysts. Detailed transition state analysis on terraces shows that the undesired C-C bond breaking pathways involves larger surface atom ensembles (4-5 atoms) while the C-H bond breaking involves smaller surface atom ensembles (1-2 atoms). This led to the conclusion that the site-isolation of active metal atoms is important to increase the selectivities for propylene formation. More importantly the combination of detailed mechanistic and screening studies using graph-theory methods shows a generalized framework towards finding new catalysts spaces for complex chemistries.</p><p>The work on ethylene oligomerization on the other hand is focused on understanding the role of mobility of active Ni species in the zeolites towards isomerization and deactivation reaction mechanisms. For this specific project, we have used state-of-the-art AIMD methods, including potential of mean force calculations, for accurate estimation of free energies for the reaction intermediates and transition states. The thermodynamic and kinetic analyses show that the reaction pathways involving mobile intermediates have the highest rates towards butene formations even under pressures lower than 1 bar. Further the isomerization step is found to be feasible on Ni-ethyl complex in agreement with experiments. Finally, the mobile complexes were shown to dimerize through alkyl bridged complexes and the generated complex has higher barriers for C-C bond formation than the isolated complex indicating that these are likely pathways for catalyst deactivation. This mechanistic understanding paves the way for fine-tuning the reaction conditions as well as ways in which the active site can be speciated inside the zeolitic frameworks to increase the selectivity towards 1-butene and reduce deactivation.</p>

<p>Partition density functional theory (P-DFT) is a density-based embedding method used to calculate the electronic properties of molecules through self-consistent calculations on fragments. P-DFT features a unique set of fragment densities that can be used to define formal charges and local dipoles. This dissertation is concerned mainly with establishing how the optimal fragment densities and energies of P-DFT depend on the specific methods employed during the self-consistent fragment calculations. First, we develop a procedure to perform P-DFT calculations on three-dimensional heteronuclear diatomic molecules, and we compare and contrast two different approaches to deal with non-integer electron numbers: Fractionally occupied orbitals (FOO) and ensemble averages (ENS). We find that, although both ENS and FOO methods lead to the same total energy and density, the ENS fragment densities are less distorted than those of FOO when compared to their isolated counterparts. Second, we formulate partition spin density functional theory (P-SDFT) and perform numerical calculations on closed- and open-shell diatomic molecules. We find that, for closed-shell molecules, while P-SDFT and P-DFT are equivalent for FOO, they partition the same total density of a molecule differently for ENS. For open-shell molecules, P-SDFT and P-DFT yield different sets of fragment densities for both FOO and ENS. Finally, by considering a one-electron system, we investigate the self-interaction error (SIE) produced by approximate exchange-correlation functionals and find that the molecular SIE can be attributed mainly to the non-additive Hartree-exchange-correlation energy.</p>

<p>Co and Ni are two major elements in high temperature structural alloys that include superalloys for turbine engines and hard metals for cutting tools. The recent development of complex concentrated alloys (CCAs), loosely defined as alloys without a single principal element (e.g. CoNiFeMn), offers additional opportunities in designing new alloys through extensive composition and structure modifications. Within CCAs and Co- and Ni-based superalloys, solid-solution strengthening and stacking fault energy engineering are two of the most important strengthening mechanisms. While studied for decades, the potency and quantitative materials properties of these mechanisms remain elusive. </p> <p><br></p> <p>Solid-solution strengthening originates from stress field interactions between dislocations and solute of various species in the alloy. These stress fields can be engineered by composition modification in CCAs, and therefore a wide range of alloys with promising mechanical strength may be designed. This thesis initially reports on experimental and computational validation of newly developed theories for solid-solution strengthening in 3d transition metal (MnFeCoNi) alloys. The strengthening effects of Al, Ti, V, Cr, Cu and Mo as alloying elements are quantified by coupling the Labusch-type strengthening model and experimental measurements. With large atomic misfits with the base alloy, Al, Ti, Mo, and Cr present strong strengthening effects comparable to other Cantor alloys. </p> <p> </p> <p>Stacking fault energy engineering can enable novel deformation mechanisms and exceptional strength in face-centered cubic (FCC) materials such as austenitic TRIP/TWIP steels and CoNi-based superalloys exhibiting local phase transformation strengthening via Suzuki segregation. We employed first-principles calculations to investigate the Suzuki segregation and stacking fault energy of the FCC Co-Ni binary alloys at finite temperatures and concentrations. We quantitatively predicted the Co segregation in the innermost plane of the intrinsic stacking fault (ISF). We further quantified the decrease of stacking fault energy due to segregation.  </p> <p><br></p> <p>We further investigated the driving force of segregation and the origin of the segregation behaviors of 3d, 4d and 5d elements in the Co- and Ni-alloys. Using first-principles calculations, we calculated the ground-state solute-ISF interaction energies and revealed the trends across the periodic table. We discussed the relationships between the interaction energies and the local lattice distortions, charge density redistribution, density of states and local magnetization of the solutes. </p> <p><br></p> <p>Finally, this thesis reports on new methodologies to accelerate first-principles calculations utilizing active learning techniques, such as Bayesian optimization, to efficiently search for the ground-state energy line of the system with limited computational resources. Based on the expected improvement method, new acquisition strategies were developed and will be compared and presented. </p>