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.

Chirality can be induced in achiral solvent molecules located near a chiral molecule or surface, but there have been very few systematic studies in this field either experimentally or theoretically. The focus of this thesis is to study the chirality transfer from chiral molecules to achiral solvents. To capture the chirality transfer in solvent molecules, a solvent model that is sensitive to the changes in the environment is needed. We developed new polarizable and flexible models based on an extensive series of ab initio calculations and molecular dynamics simulations. The models include electric field dependence in both the atomic charges and the intramolecular degrees of freedom. Modified equations of motion are required and we have implemented a multiple time step algorithm to solve these equations. Our methodology is general and has been applied to ethanol as a test. For other solvents in our simulations, such as 2-propanol, limited models are used. The chirality transfer from chiral solutes to achiral solvents and its dependence on the solute and solvent characteristics are then explored using the new polarizable models in molecular dynamics simulations. The chirality induced in the solvent is assessed based on a series of related chirality indexes originally proposed by Osipov[Osipov et al., Mol. Phys.84, 1193(1995)]. Two solvents are considered: Ethanol and benzyl alcohol. The solvation of three chiral solutes is examined: Styrene oxide, acenaphthenol, and n-(1-(4-bromophenyl)ethyl)pivalamide (PAMD). All three solutes have the possibility of hydrogen-bonding with the solvent, the last two may also form π-π interactions, and the last has multiple hydrogen bonding sites. The chirality transfer from chiral surfaces to achiral solvents is also explored. Emphasis is placed on the extent of this chirality transfer and its dependence on the surface and solvent characteristics is explored. Three surfaces employed in chiral chromatography are examined: The Whelk-O1 interface; a phenylglycine-derived chiral stationary phase (CSP); and a leucine-derived CSP. The solvents consist of ethanol, a binary n-hexane/ethanol solvent, 2-propanol, and a binary n-hexane/2-propanol solvent. Molecular dynamics simulations of the solvated chiral interfaces form the basis of the analysis and position dependent chirality indexes are analyzed in detail. / Thesis (Ph.D, Chemistry) -- Queen's University, 2009-09-24 00:25:15.174

No description available.

Zugl.: Tübingen, Univ., Diss., 2006

Zugl.: Frankfurt (Main), University, Diss., 2008.

<p> I used molecular dynamics (MD) simulations as a primary tool to study folding and dynamics of signaling and regulatory proteins. Specifically, I have studied two classes of proteins: the first part of my thesis reports studies on peptides and receptors of the insulin family, and the second part reports on studies of regulatory proteins from the G-protein coupled receptor family. The first problem that I investigated was understanding the folding mechanism of the insulin B-chain and its mimetic peptide (S371) which were studied using enhanced sampling simulation methods. I validated our simulation approaches by predicting the known solution structure of the insulin B-chain helix and then applied them to study the folding of the mimetic peptide S371. Potentials of mean force (PMFs) along the reaction coordinate for each peptide are further resolved using the metadynamics method. I further proposed receptor-bound models of S371 that provide mechanistic explanations for competing binding properties of S371 and a tandem hormone-binding element of the receptor known as the C-terminal (CT) peptide. Next, I studied the all-atom structural models of peptides containing 51 residues from the transmembrane regions of IR and the type-1 insulin-like growth factor receptor (IGF1R) in a lipid membrane. In these models, the transmembrane regions of both receptors adopt helical conformations with kinks at Pro961 (IR) and Pro941 (IGF1R), but the C-terminal residues corresponding to the juxta-membrane region of each receptor adopt unfolded and flexible conformations in IR as opposed to a helix in IGF1R. I also observe that the N-terminal residues in IR form a kinked-helix sitting at the membrane-solvent interface, while homologous residues in IGF1R are unfolded and flexible. These conformational differences result in a larger tilt-angle of the membrane-embedded helix in IGF1R in comparison to IR to compensate for interactions with water molecules at the membrane-solvent interfaces. The metastable/stable states for the transmembrane domain of IR, observed in a lipid bilayer, are consistent with a known NMR structure of this domain determined in detergent micelles, and similar states in IGF1R are consistent with a previously reported model of the dimerized transmembrane domains of IGF1R. I further studied dimerization propensities of IR transmembrane domains using three different constructs in a lipid bilayer (isolated helices, ectodomain-anchored helices, and kinase-anchored helices). These studies revealed that the transmembrane domains can dimerize in isolation and in kinase-anchored forms, but not significantly in the ectodomain construct. The final studies in my thesis are focused on interplay of protein dynamics and small-molecule inhibition in a set of regulatory proteins known as the Regulators of G-protein Signaling (RGS) proteins. Thiadiazolidinone (TDZD) compounds have been shown to inhibit the protein-protein interaction between RGS and the alpha subunit of G-proteins by covalent modification of cysteine residues in RGS proteins. However, some of these cysteines in RGS proteins are not surface-exposed. I hypothesized that transient binding pockets expose cysteine residues differentially between different RGS isoforms. To explore this hypothesis, long time-scale classical MD simulations were used to probe the dynamics of three RGS proteins (RGS4, RGS8, and RGS19), and characterize flexibility in various helical motifs. The results from simulation studies were validated by hydrogen-deuterium exchange (HDX) studies, and revealed motions indicating solvent exposure of buried cysteine residues, thereby providing insights into inhibitor binding mechanisms. In addition, I used different published HDX models which have resulted in a comprehensive comparison of existing models. Furthermore, I developed the new HDX models with optimized parameters which had comparable accuracy and more computational efficiency compared to other models. Overall, my thesis has resulted in the development and applications of several state-of-the-art computational methods that have provided a detailed mechanistic understanding of peptide and small-molecule based inhibitors and their interactions with large proteins that are potentially useful in designing novel approaches to target protein-protein interactions. </p><p>

Iron containing metalloenzymes are an extremely important class of biocatalysts conserved throughout evolution because of their vital role in the biochemistry of life. Here we discuss a specific class of these enzymes that use molecular oxygen binding to enable there activity. We also attempt to describe synthetic analogues whose chemistry is based on that seen in those natural systems. This dissertation will highlight how computational research can illuminate specific aspects of the reaction mechanisms that these systems catalyse, which in many cases are unable to be understood purely experimentally. We report on two combined QM/MM and density functional theory (DFT) projects, which describe the AlkB demethylation enzyme and the SyrB2 halogenase; both highlight the strengths and weaknesses of each method. Our DFT work on an i-propyl-bis(imino)pyridine, an equatorial tridentate ligand, developed by one of the papers’ co-authors (Badiei, Siegler et al. 2011) exampifies superoxo chemistry based on the dioxygenases. Our other projects focus on monooxygenase catalysed chemistry one based on the biomimic [FeIV(O)(TPA)Cl]+ reports on a halogenase mimic that shows exciting chemoselectivity in halogenation vs. hydroxylation. I also report on publications examining two other biomimetic ligands. A imido-bridged diiron-oxo phtalocyanine complex capable of hydroxylating methane and a nonheme iron system which gives us a good deal of insight into the effects of secondary coordination sphere chemistry [FeII(N4Py2Ph)(NCCH3)](BF4)2. My computational studies have given insight into the chemical properties of metal-oxo oxidants and their reactivity patterns with substrate and have been utilized to explain experimentally observed data.