Detailed chemical kinetic models are important to the understanding and prediction of combustion properties. Better estimations require an accurate description of thermochemistry and kinetic rate parameters. This study identifies important reaction pathways at the low temperature chemistry of branched conventional and alternative fuels. Rate constants and branching ratios for important reactions are provided and important phenomena are investigated. The thermochemistry and kinetics of the 2-methylhexane model, an important component in gasoline surrogate, is updated using recent group values and rate rules from the literature. New reactions, such as hydroperoxyalkylperoxy (OOQOOH) alternative isomerization, are also added to the model. The results show that both conventional and alternative isomerization of OOQOOH radicals significantly affect the model reactivity. The kinetics of a biofuel; iso-butanol, is also investigated in this study to understand alcohol combustion chemistry and identify sensitive reactions that require more attention. The results indicate that iso-butanol is sensitive to the chain propagation reaction of α-RO2 radical and the water elimination of γ-QOOH. Because both reactions decrease model reactivity, accurate rate constants are needed to correctly determine fuel reactivity. In light of the above mentioned kinetic modeling studies, high levels computational chemistry calculations were performed to provide site-specific rates rules for OOQOOH conventional isomerization considering all possible reaction sites. This is also one of the first studies to investigate the effect of chirality on calculated rate constants. Results indicate that chirality is important when two chiral centers exist in the reactant. OOQOOH alternative isomerization rate constants are usually assigned in analogy to the isomerization of an alkylperoxy (RO2) radical which may introduce some uncertainty. To test the validity of using analogous rates, this study calculates the rate constants for selected alternative isomerization reactions. The effect of intramolecular hydrogen bonding in the calculated energies and rate constants for different reaction pathways is investigated. The result shows that alternative isomerization is a competing pathway only when it proceeds via a less strained transition state relative to the conventional isomerization transition state. A detailed analysis of the hydrogen bonding effect helped to identify cases where assigning rates in analogy may not be valid.

The spectral line-shape of the mid-IR absorption spectrum provides valuable information about the "hole" polaron coherence length in doped and undoped conjugated polymer films. In poly(3-hexylthiophene) (P3HT) films the spectrum generally consists of a narrow, low-energy peak A (700-1000 $cm^{-1}$) followed by a much broader, higher-energy peak B (2500-5000 $cm^{-1}$). Using a theory based on the Holstein Hamiltonian for mobile holes in P3HT, the IR line-shape is successfully reproduced for several recently measured spectra recorded in doped and undoped films, confirming the association of an enhanced peak ratio (A/B) with extended polaron coherence. Emphasis is placed on the origin of components polarized along the intra- and inter-chain directions and their dependence on the spatial distribution of disorder as well as the position of the dopant relative to the $\pi$-stack. The model is further adapted to treat donor-acceptor copolymers where the local HOMO energy varies periodically from donor unit to acceptor unit. The calculated line shape for a diketopyrrolopyrrole-based copolymer agrees well with the recently measured spectrum. / Chemistry

Density functional theory (DFT), a powerful toolbox, can unveil chemical transformations in detail. This dissertation focuses on exploring catalytic puzzles, deciphering experimental results, and occasionally, reevaluating conventional concepts. In the first problem, a combination of DFT and kinetic studies uncovers the hidden role of borane in directed borylation reactions catalyzed by iridium complex. Borane, initially considered a side product, is revealed to be an autocatalyst. Chiral catalysts are pivotal for achieving asymmetric molecular construction. However, when the chirality center in the catalyst changes with each turnover, what impact does this have? In our second investigation, we delved into a thorough mechanistic study of enantiomeric selectivity during ruthenium complex-catalyzed hydroarylation. This study leads to a reevaluation and refinement of our concepts of asymmetric induction, specifically tailored to dynamic chirality. A series of six Ni(II) complexes featuring N-heterocyclic carbene (NHC) ligands demonstrate photocatalytic CO2 reduction to CO. Remarkably, these complexes retain their activity even in the absence of a photosensitizer, exhibiting self-sensitized photocatalytic capabilities. Our investigation involved ultrafast transient absorption spectroscopy (TAS) experiments and computational studies to provide a deeper understanding of these catalytic activities. Throughout my PhD journey at Mississippi State University, I engaged in diverse research areas within the chemistry department. The final chapter presents a series of chemistry problems encountered in the Hand Lab, where the application of DFT offers insightful solutions. These problems emerged from discussions and collaborations among graduate students, reflecting the spirit of teamwork and collective problem-solving in the department: 1. Understanding electronic structure of FAVE polymer (Smith lab); 2. Explaining the unexpected isomerization of RhCl(3-Si,Si,P) complex (Montiel lab); 3. Understanding stable dinitrogen pincer abnormal CCCPt(N2) complex (Hollis lab) and 4. Characterization of Ni tripodal PE (E = Si, Ge) complexes and studies on the hydroboration mechanism (Montiel lab)

Ionic liquids (IL) are salts which are liquid at low temperatures, typically with melting points under 100 °C. In recent years ILs have been treated as novel solvents and used in a wide variety of applications such as analytical and separation processes, electrochemical devices and chemical syntheses. The properties of many ILs have been extensively studied; these studies have primarily focused on the investigation of key physical properties including viscosity, density and solubility. This thesis presents mass spectrometry (MS) and computational data to investigate the intrinsic interactions between a small number of IL ions and also their interactions with contaminants. MS was used to study gas-phase aggregates of three ILs based on the 1-butyl-3- methylimidazolium (C4mim+) cation. The influence of different ion sources was investigated on C4mimCl. Conventional electrospray ionisation (ESI) and nano-ESI techniques were compared with recently developed sonic-spray ionisation (SSI) and plasma assisted desorption ionisation (PADI). SSI was found to be beneficial to the formation of larger aggregates while PADI was significantly less efficient. Gas-phase structures of the singly charged cationic aggregates of C4mimCl were characterised with the aid of collision induced dissociation (CID) and density functional theory (DFT) calculations. Additionally, CID and DFT gave consistent results for the relative stability of the C4mimCl aggregates, showing a good agreement between experiment and theory. Mixed solutions of C4mimCl with a range of metal chloride salts were used to form aggregates incorporating both IL and metal chlorides. LiCl, NaCl, KCl, CsCl, MgCl2 and ZnCl2 were all combined with C4mimCl. Magic number characteristics were observed for a number of pure IL and mixed aggregates. Many of the mixed species were characterised using MS and DFT calculations. In particular, the relative stabilities were determined and the structures of the aggregates were calculated. It was found that the metal ions would normally act as a core for the aggregates with the stability determined by the metal-chlorine binding strength and the steric hindrance of the aggregates. It was necessary to exploit pseudopotentials as opposed to all-electron basis sets for the larger aggregates and aggregates containing heavy atoms. While water is a very effective contaminant for ILs it was not possible to observe gas-phase IL aggregates incorporating this despite using multiple methods. Additionally the presence of protonated aggregates was likewise not observed throughout the range of experiments. Possible structures where these features would be incorporated were studied with DFT to obtain some insight into their lack of formation.

Aggregation of amyloid β (Aβ) protein has been linked to the development of Alzheimer's Disease (AD). The genesis of Aβ involves the cleavage Amyloid Precursor Protein (APP) by β-secretase, producing the 99-residue C99 peptide, and the subsequent cleavage of C99 by γ-secretase to produce Aβ. A detailed understanding of the γ-cleavage process is essential to our undertsanding of the pathological mechanisms linking the aggregation of Aβ to the development of AD. This work seeks to provide insight into critical aspects of the structure and dynamics of C99, and the particular roles played by (1) C99 amino acid sequence and (2) the lipid composition of the membrane environment. Many studies have focused on the importance of the C99 sequence, including known studies of Familial AD (FAD) mutants as well as engineered mutations. Specific mutations have been found to affect the processing of C99, which has been linked to changes in the structure of C99 and the formation of C99 homodimers. Similarly, changes in the membrane environment, through variation in lipid composition and the presence of cholesterol, have been found to affect C99 structure and positioning within the membrane as well as C99 dimerization. The results of this work extend our understanding of the APP-C99 system and its interaction with the environment. Using a multiscale simulation approach, we find key structural effects of engineered mutations that suggest possible mechanistic insight into the γ-cleavage process. Using C99 congener peptides, we examine the effect of local membrane environment on the dimerization of C99, focusing on the roles of both the transmembrane (TM) region as well as the juxtamembrane (JM) domain. Further studies characterize the role of a FAD mutation, and demonstrate the effect of the mutation on the dimerization of C99 in agreement with experimental findings. Overall, this work leads to critical insight into the role of sequence and membrane on the structure of C99 in a membrane environment, and provides support for the conjecture that the structure of C99 monomer and homodimer are critical to our understanding of the processing of C99, a critical step in the genesis of Aβ peptide and the etiology of Alzheimer's Disease.

This thesis explores the use of computational chemistry to aid in the design of metal-organic frameworks (MOFs) and other materials. A focus is placed on finding exceptional materials to be used for removing CO2 from fossil fuel burning power plants, with other avenues like vehicular methane storage and landfill gas separation being explored as well. These applications are under the umbrella of carbon capture and storage (CCS) which aims to reduce carbon emissions through selective sequestration. We utilize high-throughput screenings, as well as machine learning assisted discovery, to identify ideal candidate materials using a holistic approach instead of relying on conventional gas adsorption properties. The development of ideal materials for CCS requires all aspects of a material to be considered, which can be time-consuming. A large portion of this work has been with high-throughput, or machine learning assisted discovery of ideal candidates for CCS applications. The chapters of this thesis are connected by the goal of finding ideal materials for CCS. They are primarily arranged in increasing complexity of how this research can be done, from using high-throughput screenings with more simple metrics, up to multi-scale machine learning optimization of pressure swing adsorption systems. The work is not presented chronologically, but in a way to tell the best story. Work was done by first applying high-throughput computational screening on a set of experimentally realized MOFs for vehicular methane storage, post-combustion carbon capture, and landfill gas separation. Whenever possible, physically motivated figures of merits were used to give a better ranking and consideration of the materials. From this work, we were able to determine what the realistic limits might be for current MOFs. The work was continued by looking at carbon-based materials (primarily carbon nanoscrolls) for post-combustion carbon capture and vehicular methane storage. The carbon-based materials were found to outperform MOFs; however, further studies are needed to verify the results. Next, we looked at ways to improve the high-throughput screening methodology. One problem area was in the charge calculation, which could lead to unrealistic gas adsorption results. Using the split-charge equilibration method, we developed a robust way to calculate the partial atomic charges that were more accurate than its quick calculation counterparts. This led to gas adsorption properties which more closely mimicked the results determined from time-consuming quantum mechanically derived charges. Simplistic process optimization was then applied to nearly ~3500 experimental structures. To the best of our knowledge, this is the first time that any process optimization has been applied to more than 10s of materials for a study. The process optimization was done by evaluating the desorption at various pressures and choosing the value which gave the lowest energetic cost. It was found that a material synthesized by our collaborators, IISERP-MOF2, was the single best experimentally realized material for post-combustion carbon capture. What made this an interesting result is that by conventional metrics IISERP-MOF2 does not appear to be outstanding. Next, functionalized versions of MOFs were tested in a high-throughput manner, and some of those structures were found to outperform IISERP-MOF2. Although high-throughput computational screenings can be used to determine high-performance materials, it would be impossible to test all functionalized versions of some MOFs, let alone all MOFs. Functionalized MOFs are noteworthy because MOFs are highly tuneable through functionalization and can be made into ideal materials for a given application. We developed a genetic algorithm which, given a base structure and a target parameter, would be able to find the ideal functionalization to optimize the parameter while testing only a small fraction of all structures. In some cases, the CO2 adsorption was found to more than quadruple when functionalized. A better understanding of how materials perform in a PSA system was achieved by performing multi-scale optimizations. Experimentally realized MOFs were tested using atomistic simulations to derive gas adsorption properties. After passing through a few sensible filters, they were then screened using macro-scale pressure swing adsorption simulators, which model how gas separation may occur at a power plant. Using another genetic algorithm, the conditions that the pressure swing adsorption system runs at was optimized for over 200 materials. To the best of our knowledge, this is the highest amount of materials that have had been optimized for process conditions. IISERP-MOF2 was found to perform the best based on many relevant metrics, such as the energetic cost and how much CO2 was captured. It was also found that conventional metrics were unable to be used to predict a material’s pressure swing adsorption performance.

Organic and organometallic electronic materials continue to attract considerable attention among researchers due to their cost effectiveness, high flexibility, low temperature processing conditions and the continuous emergence of new semiconducting materials with tailored electronic properties. In addition, organic semiconductors can be used in a variety of important technological devices such as solar cells, field-effect transistors (FETs), flash memory, radio frequency identification (RFID) tags, light emitting diodes (LEDs), etc. However, organic materials have thus far not achieved the reliability and carrier mobility obtainable with inorganic silicon-based devices. Hence, there is a need for finding alternative electronic materials other than organic semiconductors to overcome the problems of inferior stability and performance. In this dissertation, I research the development of new transition metal based electronic materials which due to the presence of metal-metal, metal-?, and ?-? interactions may give rise to superior electronic and chemical properties versus their organic counterparts. Specifically, I performed computational modeling studies on platinum based charge transfer complexes and d10 cyclo-[M(?-L)]3 trimers (M = Ag, Au and L = monoanionic bidentate bridging (C/N~C/N) ligand). The research done is aimed to guide experimental chemists to make rational choices of metals, ligands, substituents in synthesizing novel organometallic electronic materials. Furthermore, the calculations presented here propose novel ways to tune the geometric, electronic, spectroscopic, and conduction properties in semiconducting materials. In addition to novel material development, electronic device performance can be improved by making a judicious choice of device components. I have studied the interfaces of a p-type metal-organic semiconductor viz cyclo-[Au(µ-Pz)]3 trimer with metal electrodes at atomic and surface levels. This work was aimed to guide the device engineers to choose the appropriate metal electrodes considering the chemical interactions at the interface. Additionally, the calculations performed on the interfaces provided valuable insight into binding energies, charge redistribution, change in the energy levels, dipole formation, etc., which are important parameters to consider while fabricating an electronic device. The research described in this dissertation highlights the application of unique computational modeling methods at different levels of theory to guide the experimental chemists and device engineers toward a rational design of transition metal based electronic devices with low cost and high performance.

No description available.

Under certain conditions, reactive chemicals may proceed into uncontrolled chemical reaction pathways with rapid and significant increases in temperature, pressure, and/or gas evolution. Reactive chemicals have been involved in many industrial incidents, and have harmed people, property, and the environment. Evaluation of reactive chemical hazards is critical to design and operate safer chemical plant processes. Much effort is needed for experimental techniques, mainly calorimetric analysis, to measure thermal reactivity of chemical systems. Studying all the various reaction pathways experimentally however is very expensive and time consuming. Therefore, it is essential to employ simplified screening tools and other methods to reduce the number of experiments and to identify the most energetic pathways. A systematic approach is presented for the evaluation of reactive chemical hazards. This approach is based on a combination of computational methods, correlations, and experimental thermal analysis techniques. The presented approach will help to focus the experimental work to the most hazardous reaction scenarios with a better understanding of the reactive system chemistry. Computational methods are used to predict reaction stoichiometries, thermodynamics, and kinetics, which then are used to exclude thermodynamically infeasible and non-hazardous reaction pathways. Computational methods included: (1) molecular group contribution methods, (2) computational quantum chemistry methods, and (3) correlations based on thermodynamic-energy relationships. The experimental techniques are used to evaluate the most energetic systems for more accurate thermodynamic and kinetics parameters, or to replace inadequate numerical methods. The Reactive System Screening Tool (RSST) and the Automatic Pressure Tracking Adiabatic Calorimeter (APTAC) were employed to evaluate the reactive systems experimentally. The RSST detected exothermic behavior and measured the overall liberated energy. The APTAC simulated near-adiabatic runaway scenarios for more accurate thermodynamic and kinetic parameters. The validity of this approach was investigated through the evaluation of potentially hazardous reactive systems, including decomposition of di-tert-butyl peroxide, copolymerization of styrene-acrylonitrile, and polymerization of 1,3-butadiene.

Under certain conditions, reactive chemicals may proceed into uncontrolled chemical reaction pathways with rapid and significant increases in temperature, pressure, and/or gas evolution. Reactive chemicals have been involved in many industrial incidents, and have harmed people, property, and the environment. Evaluation of reactive chemical hazards is critical to design and operate safer chemical plant processes. Much effort is needed for experimental techniques, mainly calorimetric analysis, to measure thermal reactivity of chemical systems. Studying all the various reaction pathways experimentally however is very expensive and time consuming. Therefore, it is essential to employ simplified screening tools and other methods to reduce the number of experiments and to identify the most energetic pathways. A systematic approach is presented for the evaluation of reactive chemical hazards. This approach is based on a combination of computational methods, correlations, and experimental thermal analysis techniques. The presented approach will help to focus the experimental work to the most hazardous reaction scenarios with a better understanding of the reactive system chemistry. Computational methods are used to predict reaction stoichiometries, thermodynamics, and kinetics, which then are used to exclude thermodynamically infeasible and non-hazardous reaction pathways. Computational methods included: (1) molecular group contribution methods, (2) computational quantum chemistry methods, and (3) correlations based on thermodynamic-energy relationships. The experimental techniques are used to evaluate the most energetic systems for more accurate thermodynamic and kinetics parameters, or to replace inadequate numerical methods. The Reactive System Screening Tool (RSST) and the Automatic Pressure Tracking Adiabatic Calorimeter (APTAC) were employed to evaluate the reactive systems experimentally. The RSST detected exothermic behavior and measured the overall liberated energy. The APTAC simulated near-adiabatic runaway scenarios for more accurate thermodynamic and kinetic parameters. The validity of this approach was investigated through the evaluation of potentially hazardous reactive systems, including decomposition of di-tert-butyl peroxide, copolymerization of styrene-acrylonitrile, and polymerization of 1,3-butadiene.