Use of Melatonin Derivatives as Spin Traps for Hydroxyl Radicals: A Computational Studies. Aaron Teye Caesar and Dr. Scott Jeffery Kirkby, Department of Chemistry, College of Arts and Sciences, East Tennessee State University, Johnson City, TN. Free radicals, especially reactive oxygen species, have been implicated in several deleterious processes which result in degenerative and cardiovascular diseases. Melatonin (N-acetyl-5-methoxytryptamin, MLT) is a naturally occurring antioxidant which has shown some potential for use as a spin trap. Spin traps react with short lived radicals such as hydroxy (.OH) or superoxide (O2-) to produce more stable products called spin adducts which may be characterized by electron paramagnetic resonance spectroscopy. This work examines whether MLT derivatives show improved spin adduct stability which may enhance their spin trapping characteristics. Electronic structure calculations of MLT, selected derivatives and 2-OH radical products were performed at the HF/6-31G(d), cc-pVDZ and DFT/B3LYP/6-31G(d) and cc-pVDZ levels of theory using NWChem. The stabilization energy was calculated using; ∆Estabilization = Espin adduct – (Espin trap + Ehydroxy radical). In units of hartrees, the results of 2-OHMLT, 2-OHMLT-Me and 2-OHMLT-CN are -0.43738, -1.60054, -1.60380 for HF/6-31G(d); -1.46071, -1.44788 and -1.46173 for DFT/6-31G(d) respectively. Also, HF/cc-pVDZ and DFTB3LYP/cc-pVDZ respectively gave -1.61268, -1.60233, -1.61409 and -1.44929, -0.26318, -1.45521.

The need for renewable and cleaner sources of energy has made biofuels an interesting alternative to fossil fuels, especially in the case of butanol isomers, with their favorable blend properties and low hygroscopicity. Although C4 alcohols are prospective fuels, some key reactions governing their pyrolysis and combustion have not been adequately studied, leading to incomplete kinetic models. Butanol reactions kinetics is poorly understood. Specifically, the unimolecular and H-assisted tautomerism of propen-2-ol to acetone, which are included in butanol combustion kinetic models, are assigned rate parameters based on the analogous unimolecular tautomerism vinyl alcohol ↔ acetaldehyde and H addition to the double bound of iso-butene, respectively. In an attempt to update current kinetic models for tert- and 2-butanol, a theoretical kinetic study of the unimolecular and H-assisted tautomerism, i-C3H5OH⟺CH3COCH3 and i-C3H5OH+Ḣ⟺CH3COCH3+Ḣ, was carried out by means of CCSD(T,FULL)/aug-cc-pVTZ//CCSD(T)/6-31+G(d,p) and CCSD(T)/aug-cc-pVTZ//M062X/cc-pVTZ ab initio calculations, respectively. For H-assisted tautomerism, the reaction takes place in two consecutive steps: i-C3H5OH+Ḣ⟺CH3ĊOHCH3 and CH3ĊOHCH3⟺CH3COCH3+Ḣ. Multistructural torsional anharmonicity and variational transition state theory were considered in a wide temperature and pressure range (200 K – 3000 K, 0.1 kPa – 108 kPa). It was observed that decreasing pressure leads to a decrease in rate constants, describing the expected falloff behavior for both isomerizations. Results for unimolecular tautomerism differ from vinyl alcohol ↔ acetaldehyde analogue reactions, which shows lower rate constant values. Tunneling turned out to be important, especially at low temperatures. Accordingly, pyrolysis simulations in a batch reactor for tert- and 2-butanol with computed unimolecular rate constants showed important differences in comparison with previous results, such as larger acetone yield and quicker propen-2-ol consumption. In the combustion and pyrolysis batch reactor simulations, using all the rate constants computed in this work, H-assisted reactions are limited because H radicals become abundant once the propen-2-ol has been consumed by other reactions, such as the non-catalyzed tautomerism i-C3H5OH⟺CH3COCH3, which becomes one of the main source of acetone. The intermediate radical (CH3ĊOHCH3) is formed exclusively from tert-butanol, with its concentration in 2-butanol oxidation being smaller because the secondary alcohol is unable to produce the radical directly. In all cases, the intermediate is converted effectively to acetone.

Since our society became industrialised, the levels of carbon dioxide in our atmosphere have been steadily rising, to the point where it in early 2020 at is 413 ppm. The high concentration is causing several troubling effects worldwide because of the increase in mean temperature that it creates, which causes longer draughts, more severe floods, and rising seawater levels to name a few. There are a few measures that can be taken to reduce carbon dioxide in the atmosphere, among which there are a number of methods that currently are being researched and/or used. The prospect of capturing carbon dioxide and using it as a carbon building block to make methanol is one solution that is particularly interesting, since it in theory could provide a fuel for combustion engines that is net neutral regarding carbon emission. Methanol can be synthesised from carbon dioxide using a heterogeneous catalyst consisting of copper, Cu, and zinc oxide, ZnO. This research is focused on one of the components of the catalyst, the metal oxide ZnO in the form of crystallites or nanoparticles (ZnO)n. Quantum chemistry is a branch of computational chemistry which is centered on solving the Schrödinger equation for molecular systems. Density functional theory, DFT, is an approach to quantum theory which in this study was used to calculate the geometry and energy of the particles. The supercomputer Tetralith in the National Supercomputer Centre, NSC, was used to carry out the calculations. The DFT calculations utilized the functional B3LYP and the basis set 6-31G (d,p). One of the largest particle sizes studied, (ZnO)20, with a structure that has a large, flat surface, was found to be the most energetically favourable. According to studies, the presence of an oxygen vacancy on the surface of ZnO reduces the amount of activation energy required for CO2 to bond to the particle, which increases the chance of forming CO and thus continuing the process of forming methanol. Two structures of (ZnO)20 were investigated in this regard, where oxygen atoms were removed at different locations, creating four versions of Zn20O19 in total. This proved yet again that the version with a large, flat surface yields the lesser amount of energy when an O atom is removed from the centre of its surface. The adsorption of CO2 to the ZnO clusters was studied by calculating the energy of adsorption, and this showed that it was the second version of (ZnO)20, without an O vacancy, that yielded the least amount of energy, thus being the most favourable species to engage in physisorption with CO2. Lastly, the activation energy was investigated, and a diagram of the reaction process of CO2 adsorbing to Zn20O19 forming (ZnO)20 and CO is presented in this paper, which shows that the required activation energy is 127 kJ/mol.

Surface self-assembly, the spontaneous aggregation of molecules into ordered, sta- ble, noncovalently joined structures in the presence of a surface, is of great importance to the bottom-up manufacturing of materials with desired functionality. As a bulk phenomenon informed by molecular-level interactions, surface self-assembly involves coupled processes spanning multiple length scales. Consequently, a computational ap- proach towards investigating surface self-assembled systems requires a combination of quantum-level electronic structure calculations and large-scale multi-body classical simulations. In this work we use a range of simulation approaches from quantum-based methods, to classical atomistic calculations, to mean-field approximations of bulk mixed phases, and explore the self-assembly strategies of simple dipoles and polyaromatic hydrocarbons on symmetric surfaces. / Graduate

Everything in the universe is made up of elements from the periodic table. Each element has its own role that it plays in the formation of things it makes up. For instance, pencil lead is graphite. A series of honeycomb-like structures made up of carbon stacked on top of one another. Carbon’s neighbor to the left, boron doesn’t like to form such stacked honeycomb-like structures. But, what if there was a way to make boron act like carbon so it did like to form such structures? That question is the basis of the electronic transmutation concept presented in this dissertation. Electronic transmutation states that an element, such as boron, can behave structurally like carbon (form stacked honeycomb structures) if you make them valence (outer most) isoelectronic (“iso”- same; “electronic”- electrons), so both would have the same number of outer most electrons. As a result, chemists would have a new tool to aid in the rational design of new materials.

Isomerization is a synthetically useful technique to form the more stable internal alkene from terminal alkene feedstock. Unfortunately, these transformations form a variety of isomers without catalyst control. Z alkenes are thermodynamically challenging to form compared to their E counterparts but are useful in pharmaceutical, fragrance, and flavor industries, making them sought-after products. Therefore, catalysts targeting specific regio- and stereoisomers, particularly Z alkenes, will benefit many fields. This work analyzes several Mo(0) complexes as Z-2-alkene selective isomerization catalysts. Particular focus has been given to cis-Mo(CO)4(PCy3)(piperidine) due to easy purification and characterization. Substantial improvement to reported Z selectivities have been obtained with this complex, though disadvantages exist. To have a clearer understanding of the mechanism and source of Z selectivity, DFT analysis was completed, and a mechanism proposed. A rare rotation of hydride and carbonyl ligands was found, only reported in one prior Mo complex, that facilitates the isomerization. Key characteristics were discovered that will be applied to develop future iterations with the goal of reducing, or removing, the disadvantages of this system. / Chemistry

Stereodivergent and enantiodivergent pathways for the Friedel–Crafts reactions were computationally studied with DFT methods. This study aims to explain recently observed solvent-dependent regioselectivity, and enantioselectivity when cinchona catalyst is used. Deprotonation reaction, Frontier Kohn-Sham orbitals, dual descriptors, Mulliken charges, and Hirshfeld atomic charge for reactant were calculated and analyzed. The most probable position of electrophilic attack and nucleophilic attack in-silico predicted aligns with experimental observations. The calculation of the transition states on the anionic and neutral model in a vacuum show preference for the electrophilic attack in the para position. In comparison to the anionic system, the presence of potassium cation improves ortho/para selectivity and increases the energy barrier. For the key enantioselective step, 12 transition states were calculated which covers 4 representative product such: (R)-ortho, (S)-ortho, (R)-para, and (S)-para. The computational study suggests, that the presence of the cesium cation is essential for the arrangement of the reactant and catalyst in the transition state, which leads to observed selectivity.

Brief explanation and history of cinchona based Phase Transfer Catalysis (PTC). Studied aryl acetates in PTC, encompassing napthoyl, 6-methoxy napthoyl, phenyl and protected 4-hydroxy phenyl acetates. Investigated means of controlling the selectivity of the PTC reaction by changing the electrophile size, the ether side group size or by addition of inorganic salts. Found that either small or aromatic electophiles increased enantioselectivity more than aliphatic electrophiles, and that increasing the size of ether protecting group also increased selectivity. Positive effects of salt addition included either decreasing reaction time or increasing enantiomeric excess. Applied findings towards the synthesis of S-equol. Computational experiments working towards deducing the transition state between PTC and aryl acetate substrates.

<p>Automated reaction prediction has the potential to elucidate complex reaction networks for many applications in chemical engineering, including materials degradation, drug design, combustion chemistry and biomass conversion. Unlike traditional reaction mechanism elucidation methods that rely on manual setup of quantum chemistry calculations, automated reaction prediction avoids tedious trial-and-error learning processes and greatly reduces the risk of leaving out important reactions. Despite these promising advantages, the potential of automated reaction prediction as a general-purpose tool is still largely unrealized, due to high computational cost and inconsistent reaction coverage. Therefore, this dissertation develops methods to simultaneously reduce the computational cost and increase the reaction coverage. Specifically, the computational cost is reduced by the development of more efficient transition state (TS) localization workflows and fast molecular and reaction property prediction packages, while the reaction coverage is increased by a comprehensive reaction space exploration based on mathematically defined elementary reaction steps. These components are implemented in two open-source packages, one is TAFFI (Topology Automated Force-Field Interactions) component increment theory (TCIT) and the other is Yet Another Reaction Program (YARP).</p> <p><br></p> <p>The first package, TCIT, is the first component increment theory based molecular property prediction package. TCIT is based on the locality assumption, which decomposes molecular thermochemistry properties into the summation of the contributions of each subgraph. In contrast to the traditional "group" increment theory, TCIT treats each subgraph as the central atom plus its nearest and next-nearest neighboring atoms, and consistently parameterizes the contribution of each component according to purely quantum chemistry calculations. Although all parameterizations are based on quantum chemical calculations, when benchmarked against experimental data, TCIT provides more accurate predictions compared to traditional methods using the same experimental dataset for parameterization. With TCIT, the molecular properties (e.g., enthalpy of formation) and reaction properties (e.g., enthalpy of reaction) can be accurately predicted in an on-the-fly manner. The second package, YARP, is developed for automated reaction space exploration and deep reaction network prediction. By optimizing the reaction enumeration, geometry initialization, and transition state convergence algorithms that are common to many prediction methodologies, YARP (re)discovers both established and unreported reaction pathways and products while simultaneously reducing the cost of reaction characterization nearly 100-fold and increasing convergence of transition states, comparing with recent benchmarks. In addition, an updated version of YARP, YARP v2.0, further reduces the cost of reaction characterization from 100-fold to 300-fold, while increasing the reaction coverage beyond the scope of elementary reaction steps. This combination of ultra-low cost and high reaction-coverage creates opportunities to explore the reactivity of larger systems and more complex reaction networks for applications like chemical degradation, where computational cost is a bottleneck.</p> <p><br></p> <p>The power of TCIT and YARP has been demonstrated by a broad range of applications. In the first application, YARP was used to explore the reactivity of unimolecular and bimolecular reactants, comprising a total of 581 reactions involving 51 distinct reactants. The algorithm discovered all established reaction pathways, where such comparisons are possible, while also revealing a much richer reactivity landscape, including lower barrier reaction pathways and a strong dependence of reaction conformation in the apparent barriers of the reported reactions. Secondly, YARP was applied to the search for prebiotic chemical pathways, which is a long-standing puzzle that has generated a menagerie of competing hypotheses with limited experimental prospects for falsification. With YARP, the space of organic molecules that can be formed within four polar or pericyclic reactions from water and hydrogen cyanide (HCN) was comprehensively explored. A surprisingly diverse reactivity landscape was revealed within just a few steps of these simple molecules and reaction pathways to several biologically relevant molecules were discovered involving lower activation energies and fewer reaction steps compared with recently proposed alternatives. In the third application, predicting the reaction network of glucose pyrolysis, YARP generated by far the largest and most complex reaction network in the domain of biomass pyrolysis and discovered many unexpected reaction mechanisms. Further, motivated by the fact that existing reaction transition state (TS) databases are comparatively small and lack chemical diversity, YARP, together with the concept of a graphically defined model reaction, were utilized to address the data gap by comprehensively characterizing a reaction space associated with C, H, O, and N containing molecules with up to 10 heavy (non-hydrogen) atoms. The resulting dataset, namely Reaction Graph Depth 1 (RGD1) dataset, is composed of 176,992 organic reactions possessing at least one validated TS, activation energy, enthalpy of reaction, reactant and product geometries, frequencies, and atom-mapping. The RGD1 dataset represents the largest and most chemically diverse TS dataset published to date and should find immediate use in developing novel machine learning models for predicting reaction properties. In addition to exploring the molecular reaction space, YARP was also extended to explore and characterize reaction networks in heterogeneous catalysis systems. With ethylene oligomerization on silica-supported single site Ga catalysts as a model system, YARP illustrates how a comprehensive reaction network can be generated by using only graph-based rules for exploring the network and elementary constraints based on activation energy and system size for identifying network terminations. The automated reaction exploration (re)discovered the Ga-alkyl-centered Cossee-Arlman mechanism that is hypothesized to drive major product formation while also predicting several new pathways for producing alkanes and coke precursors. The diverse scope of these applications and milestone quality of many of the reaction networks produced by YARP  illustrate that automated reaction prediction is approaching a general-purpose capability.</p>

<p>Radical polymers bearing open-shell moieties at their pendant sites offer potential advantages in processing, stability, and optoelectronic properties compared to conventional doped conjugated polymers. The rapid development of radical-containing polymers has occurred across various applications in energy storage devices and electronic systems. However, significant gaps still exist in understanding the key structure-property-function relationships governing charge transport phenomena in these materials. Most reported radical conductors primarily rely on (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO) radicals, which raises fundamental questions about the ultimate limits of charge transport capabilities and the impact of radical chemistry choice on material deficiencies. Moreover, an understanding gap persists when it comes to connecting the computable electronic features of individual units and the charge transport behavior of these materials in condensed phases. This dissertation seeks to address these gaps by developing a molecular understanding of charge transport in radical-bearing materials through a combined computational and experimental approach.</p> <p><br></p> <p>The initial stage of this dissertation investigated the impact of dimeric orientations and interactions on charge transport by conducting a density functional theory (DFT) study on a diverse set of open-shell chemistries relevant to radical conductors. The results revealed the anomalously high reorganization energies of the TEMPO radical due to strong spin-localization, which may result in inefficient charge transfer. Additionally, a significant mismatch was identified between dimeric conformations favored by intermolecular interactions and those maximizing charge transfer. This study provided new insights into the impact of steric hindrance and spin delocalization on elementary charge transfer steps and suggests opportunities for exploiting directing interactions to enhance charge transport in these materials.</p> <p><br></p> <p>Building upon these findings, we established a direct relationship between the molecular architecture and intrinsic charge transport properties. To accomplish this, single-molecule characterization methods (i.e., break junction techniques) were implemented to study the nanoscale charge transport properties of radical-containing oligomeric nonconjugated molecules. Temperature-dependent measurements and molecular modeling revealed that the presence of radicals improves tunneling at the nanoscale. Integrating open-shell moieties into nonconjugated molecular structures significantly enhances charge transport, thereby characterizing charge transport through radicals at the individual level and opening new avenues for implementing molecular engineering in the field of nanoelectronics.</p> <p><br></p> <p>To further connect the electronic properties of repeat units with the condensed-phase charge transport behavior of radical polymers, a quantum chemical study was carried out to explicitly evaluate the interplay between polymer design, open-shell chemistries, and intramolecular charge transport. After comprehensive conformational sampling of the configurational space of radical polymers, we determined their anticipated intrachain charge transport values by utilizing graph-based transport metrics. We show that charge transport in radical polymers primarily hinges on the choice of radical chemistry, which in turn affects the optimal selection of backbone chemistry and spacer group to ensure proper radical alignment and prevent undesired trap states. These findings highlight the potential for a substantial synthetic exploration in radical polymers for radical conductors.</p> <p><br></p> <p>In summary, this dissertation provides compelling evidence of radical-mediated charge transport and suggests potential design guidelines to enhance the charge transfer behavior of radical-containing polymer materials. Furthermore, these findings inform future research directions in fine-tuning molecular engineering and modular design to enable the development of radical-based materials and their end-use applications in organic electronics.</p>