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This honors thesis is focused on two separate catalysis projects conducted under the mentorship of Dr. Javier Pérez-Ramírez at ETH Zürich. The first project explored ethylene oxychlorination over supported europium oxychloride catalysts. The second project investigated alkyne semihydrogenation over nickel phosphide catalysts. This work is the subject of a publication

This honors thesis is focused on two separate catalysis projects conducted under the mentorship of Dr. Javier Pérez-Ramírez at ETH Zürich. The first project explored ethylene oxychlorination over supported europium oxychloride catalysts. The second project investigated alkyne semihydrogenation over nickel phosphide catalysts. This work is the subject of a publication of which I am a co-author, as cited below.

Project 1 Abstract: Ethylene Oxychlorination
The current two-step process for the industrial process of vinyl chloride production involves CuCl2 catalyzed ethylene oxychlorination to ethylene dichloride followed by thermal cracking of the latter to vinyl chloride. To date, no industrial application of a one-step process is available. To close this gap, this work evaluates a wide range of self-prepared supported CeO2 and EuOCl catalysts for one-step production of vinyl chloride from ethylene in a fixed-bed reactor at 623 773 K and 1 bar using feed ratios of C2H4:HCl:O2:Ar:He = 3:3 6:1.5 6:3:82 89.5. Among all studied systems, CeO2/ZrO2 and CeO2/Zeolite MS show the highest activity but suffer from severe combustion of ethylene, forming COx, while 20 wt.% EuOCl/γ-Al2O3 leads to the best vinyl chloride selectivity of 87% at 15.6% C2H4 conversion with complete suppression of CO2 formation and only 4% selectivity to CO conversion for over 100 h on stream. Characterization by XRD and EDX mapping reveals that much of the Eu is present in non-active phases such as Al2Eu or EuAl4, indicating that alternative synthesis methods could be employed to better utilize the metal. A linear relationship between conversion and metal loading is found for this catalyst, indicating that always part of the used Eu is available as EuOCl, while the rest forms inactive europium aluminate species. Zeolite-supported EuOCl slightly outperforms EuOCl/γ Al2O3 in terms of total yield, but is prone to significant coking and is unstable. Even though a lot of Eu seems locked in inactive species on EuOCl/γ Al2O3, these results indicate possible savings of nearly 16,000 USD per kg of catalyst compared to a bulk EuOCl catalyst. These very promising findings constitute a crucial step for process intensification of polyvinyl chloride production and exploring the potential of supported EuOCl catalysts in industrially-relevant reactions.

Project 2 Abstract: Alkyne Semihydrogenation
Despite strongly suffering from poor noble metal utilization and a highly toxic selectivity modifier (Pb), the archetypal catalyst applied for the three-phase alkyne semihydrogenation, the Pb-doped Pd/CaCO3 (Lindlar catalyst), is still being utilized at industrial level. Inspired by the very recent strategies involving the modification of Pd with p-block elements (i.e., S), this work extrapolates the concept by preparing crystalline metal phosphides with controlled stoichiometry. To develop an affordable and environmentally-friendly alternative to traditional hydrogenation catalysts, nickel, a metal belonging to the same group as Pd and capable of splitting molecular hydrogen has been selected. Herein, a simple two-step synthesis procedure involving nontoxic precursors was used to synthesize bulk nickel phosphides with different stoichiometries (Ni2P, Ni5P4, and Ni12P5) by controlling the P:Ni ratios. To uncover structural and surface features, this catalyst family is characterized with an array of methods including X-ray diffraction (XRD), 31P magic-angle nuclear magnetic resonance (MAS-NMR) spectroscopy, and X-ray photoelectron spectroscopy (XPS). Bulk-sensitive techniques prove the successful preparation of pure phases while XPS analysis unravels the facile passivation occurring at the NixPy surface that persists even after reductive treatment. To assess the characteristic surface fingerprints of these materials, Ar sputtering was carried out at different penetration depths, reveling the presence of Ni+ and P-species. Continuous-flow three-phase hydrogenations of short-chain acetylenic compounds display that the oxidized layer covering the surface is reduced under reaction conditions, as evidenced by the induction period before reaching the steady state performance. To assess the impact of the phosphidation treatment on catalytic performance, the catalysts were benchmarked against a commercial Ni/SiO2-Al2O3 sample. While Ni/SiO2-Al2O3 presents very low selectivity to the alkene (the selectivity is about 10% at full conversion) attributed to the well-known tendency of naked nickel nanoparticles to form hydrides, the performance of nickel phosphides is highly selective and independent of P:Ni ratio. In line with previous findings on PdxS, kinetic tests indicate the occurrence of a dual-site mechanism where the alkyne and hydrogen do not compete for the same site.

This work is the subject of a publication of which I am a co-author, as cited below.

D. Albani; K. Karajovic; B. Tata; Q. Li; S. Mitchell; N. López; J. Pérez-Ramírez. Ensemble Design in Nickel Phosphide Catalysts for Alkyne Semi-Hydrogenation. ChemCatChem 2019. doi.org/10.1002/cctc.201801430
ContributorsTata, Bharath (Author) / Deng, Shuguang (Thesis director) / Muhich, Christopher (Committee member) / Chemical Engineering Program (Contributor, Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
This research seeks to answer the question if there is a singular relationship between stishovite nucleation and the atomistic structure of the preshocked amorphous SiO$_2$. To do this a stishovite manufacturing method is developed in which 1,152 samples were produced. The majority of these samples did crystallize. The method was

This research seeks to answer the question if there is a singular relationship between stishovite nucleation and the atomistic structure of the preshocked amorphous SiO$_2$. To do this a stishovite manufacturing method is developed in which 1,152 samples were produced. The majority of these samples did crystallize. The method was produced through two rounds of experiments and fine-tuning with the pressure damp, temperature damp, shock pressure using an NPHug fix, and sample origin. A new random atomic insertion method was used to generate a new and different SiO$_2$ amorphous structure not before seen within the research literature. The optimal values for shock were found to be 60~GPa for randomly atom insertion samples and 55~GPa for quartz origin samples. Temperature damp appeared to have a slight effect optimizing at 0.05~ps and the pressure damp had no visible effect, testing was done with temperature damp from 0.05 to 0.5~ps and pressure damp from 0.1 to 10.0~ps. There appeared to be significant randomness in crystallization behavior. The preshocked and postnucleated samples were transformed into Gaussian fields of crystal, mass, and charge. These fields were divided and classified using a cut-off method taking the number of crystals produced in portions of each simulation and classifying each potion as nucleated or non-nucleated. Data in which some nucleation but not a critical amount was present was removed constituting 2.6\% to 20.3\% of data in all tests. A max method was also used which takes only the maximum portions of each simulation to classify as nucleating. There are three other variables tested within this work, a sample size of 18,000 or 72,728~atoms, Gaussian variance of 1 or 4~\AA, and Convolutional neural network (CNN) architecture of a garden verity or all convolution along with the portioning classification method, sample origination, and Gaussian field type. In total 64 tests were performed to try every combination of variable. No significant classifications were made by the CNNs to nucleation or non-nucleation portions. The results clearly confirmed that the data was not abstracting to atomistic structure and was random by all classifications of the CNNs. The all convolution CNN testing did show smoother outcomes in training with less fluctuations. 59\% of all validation accuracy was held at 0.5 for a random state and 84\% was within $\pm0.02$ of 0.5. It is conclusive that prenucleation structure is not the sole predictor of nucleation behavior. It is not conclusive if prenucleation structure is a partial or non-factor within nucleation of stishovite from amorphous SiO$_2$.
ContributorsChristen, Jonathan Scorr (Author) / Oswald, Jay (Thesis advisor) / Muhich, Christopher (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Polyurea is a highly versatile material used in coatings and armor systems to protect against extreme conditions such as ballistic impact, cavitation erosion, and blast loading. However, the relationships between microstructurally-dependent deformation mechanisms and the mechanical properties of polyurea are not yet fully understood, especially under extreme conditions. In this

Polyurea is a highly versatile material used in coatings and armor systems to protect against extreme conditions such as ballistic impact, cavitation erosion, and blast loading. However, the relationships between microstructurally-dependent deformation mechanisms and the mechanical properties of polyurea are not yet fully understood, especially under extreme conditions. In this work, multi-scale coarse-grained models are developed to probe molecular dynamics across the wide range of time and length scales that these fundamental deformation mechanisms operate. In the first of these models, a high-resolution coarse-grained model of polyurea is developed, where similar to united-atom models, hydrogen atoms are modeled implicitly. This model was trained using a modified iterative Boltzmann inversion method that dramatically reduces the number of iterations required. Coarse-grained simulations using this model demonstrate that multiblock systems evolve to form a more interconnected hard phase, compared to the more interrupted hard phase composed of distinct ribbon-shaped domains found in diblock systems. Next, a reactive coarse-grained model is developed to simulate the influence of the difference in time scales for step-growth polymerization and phase segregation in polyurea. Analysis of the simulated cured polyurea systems reveals that more rapid reaction rates produce a smaller diameter ligaments in the gyroidal hard phase as well as increased covalent bonding connecting the hard domain ligaments as evidenced by a larger fraction of bridging segments and larger mean radius of gyration of the copolymer chains. The effect that these processing-induced structural variations have on the mechanical properties of the polymer was tested by simulating uniaxial compression, which revealed that the higher degree of hard domain connectivity leads to a 20% increase in the flow stress. A hierarchical multiresolution framework is proposed to fully link coarse-grained molecular simulations across a broader range of time scales, in which a family of coarse-grained models are developed. The models are connected using an incremental reverse–mapping scheme allowing for long time scale dynamics simulated at a highly coarsened resolution to be passed all the way to an atomistic representation.
ContributorsLiu, Minghao (Author) / Oswald, Jay (Thesis advisor) / Muhich, Christopher (Committee member) / Jiang, Hanqing (Committee member) / Peralta, Pedro (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Functional materials can be characterized as materials that have tunable properties and are attractive solutions to the improvement and optimization of processes that require specific physiochemical characteristics. Through tailoring and altering these materials, their characteristics can be fine-tuned for specific applications. Computational modeling proves to be a crucial methodology in

Functional materials can be characterized as materials that have tunable properties and are attractive solutions to the improvement and optimization of processes that require specific physiochemical characteristics. Through tailoring and altering these materials, their characteristics can be fine-tuned for specific applications. Computational modeling proves to be a crucial methodology in the design and optimization of such materials. This dissertation encompasses the utilization of molecular dynamics simulations and quantum calculations in two fields of functional materials: electrolytes and semiconductors. Molecular dynamics (MD) simulations were performed on ionic liquid-based electrolyte systems to identify molecular interactions, structural changes, and transport properties that are often reflected in experimental results. The simulations aid in the development process of the electrolyte systems in terms of concentrations of the constituents and can be invoked as a complementary or predictive tool to laboratory experiments. The theme of this study stretches further to include computational studies of the reactivity of atomic layer deposition (ALD) precursors. Selected aminosilane-based precursors were chosen to undergo density functional theory (DFT) calculations to determine surface reactivity and viability in an industrial setting. The calculations were expanded to include the testing of a semi-empirical tight binding program to predict growth per cycle and precursor reactivity with a high surface coverage model. Overall, the implementation of computational methodologies and techniques within these applications improves materials design and process efficiency while streamlining the development of new functional materials.
ContributorsGliege, Marisa Elise (Author) / Dai, Lenore (Thesis advisor) / Derecskei-Kovacs, Agnes (Thesis advisor) / Muhich, Christopher (Committee member) / Emady, Heather (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2021