In recent years there have been many efforts to develop and expand the ability of mathematical models capable of describing polymerization systems. Models can provide a key competitive advantage for the industry and research in terms of production and technology development. As new resins are continuously produced to meet the requirement of final applications and processability, it is imperative to pursue strong polymer characterization with special attention to detailed analysis of polymer microstructure. The microstructure of polyolefin is defined by its distribution of molecular weight, chemical composition, branching topology, and stereoregularity. <br /><br /> In this work, a Monte Carlo simulation model was developed to describe the polymerization mechanisms of olefin homopolymerization and copolymerization using single-site coordination catalyst. The mathematical model is meant to describe molecular weight and chemical composition distribution in copolymerization system. More specifically, this research work gives a detailed study of the molecular structure for ethylene- alfa-olefin copolymer. <br /><br /> The chemical and physical properties of copolymers are influenced not only by their average composition, but also by the monomer sequence distribution along the polymer chains. Predicting the molecular weight and comonomer distributions can lead to a better understanding of the possible morphology in solid stated because they are considered to be the main structural parameters that affect the crystallinity of polymeric materials. As a consequence, final physical properties such as the tensile properties of a copolymer could be controlled by the ratio of crystalline species in the polymer. <br /><br /> This work is considered to be a useful tool that enables us to understand and explore specific polymerization catalytic system. Being able to describe the short chain branching and the monomer sequence distribution as a function of chain length enables us to have a better control over semi-batch polymerization reactors.

In recent years there have been many efforts to develop and expand the ability of mathematical models capable of describing polymerization systems. Models can provide a key competitive advantage for the industry and research in terms of production and technology development. As new resins are continuously produced to meet the requirement of final applications and processability, it is imperative to pursue strong polymer characterization with special attention to detailed analysis of polymer microstructure. The microstructure of polyolefin is defined by its distribution of molecular weight, chemical composition, branching topology, and stereoregularity. <br /><br /> In this work, a Monte Carlo simulation model was developed to describe the polymerization mechanisms of olefin homopolymerization and copolymerization using single-site coordination catalyst. The mathematical model is meant to describe molecular weight and chemical composition distribution in copolymerization system. More specifically, this research work gives a detailed study of the molecular structure for ethylene- alfa-olefin copolymer. <br /><br /> The chemical and physical properties of copolymers are influenced not only by their average composition, but also by the monomer sequence distribution along the polymer chains. Predicting the molecular weight and comonomer distributions can lead to a better understanding of the possible morphology in solid stated because they are considered to be the main structural parameters that affect the crystallinity of polymeric materials. As a consequence, final physical properties such as the tensile properties of a copolymer could be controlled by the ratio of crystalline species in the polymer. <br /><br /> This work is considered to be a useful tool that enables us to understand and explore specific polymerization catalytic system. Being able to describe the short chain branching and the monomer sequence distribution as a function of chain length enables us to have a better control over semi-batch polymerization reactors.

Hydrogen storage has been identified as a primary bottleneck in the large-scale implementation of a hydrogen-based economy. Many research efforts are underway to both improve the capacity of existing hydrogen storage systems and develop new systems. One promising area of research is hydrogen physi-sorbed into carbonbased structures such as nanotubes and graphene. Two novel systems consisting of a phthalocyanine salt with a large cation were studied. Ab initio, density functional theory, and molecular dynamics simulations of tetramethylammonium lithium phthalocyanine (TMA-LiPc) and trimethyl-(2-trimethylazaniumylethyl) azanium phthalocyanine (TMA2-Pc) were undertaken to estimate the H2 gas-solid adsorption uptake (wt/wt) as a function of pressure and temperature. For TMA-LiPc, the maximum H2 binding energy was approximately 0.9 kcal/mol for an isolated system and 1.2 kcal/mol for a crystal. H2 adsorption at the optimal inter-layer distance of 8.49 Å ranged from 2.1% to 6.0% (wt/wt) at 300 K, 2.5% to 6.5% at 273K, 3.3% to 7.2% at 236K, 5.2% to 8.6% at 177K, and 10.4% to 11.7% at 77K. At ILD 10 Å H2 adsorption was about 1.5% (wt/wt) higher at all points. For TMA2-Pc, the maximum H2 binding energy was approximately 1.3 kcal/mol for an isolated system and 1.2 kcal/mol for a crystal. H2 adsorption at the optimal inter-layer distance of 8.12 Å ranged from 0.5% to 2.6% (wt/wt) at 300 K, 0.6% to 2.8% at 273K, 0.8% to 3.2% at 236K, 1.4% to 3.9% at 177K, and 4.5% to 6.0% at 77K. At ILD 10 Å H2 adsorption ranged from about 0.1% (wt/wt) at 40 bar to 0.5% higher at 250 bar. The behavior of H2 adsorption for both TMA-LiPc and TMA2-Pc were compared. The adsorbed H2 probability density was compared to pair correlation function data and surfaces of constant binding energy. Regions of relatively high H2 density appear to correlate well with the binding energy, but the total adsorption does not, indicating that the adsorption is driven by factors other than binding energetics. Lithium ion transport in TMA2-Pc was also investigated for suitability as an electrolyte medium for use in lithium ion battery systems.

Molecular electrostatic potentials (MEPs) and vibrational electronics (“vibronics”) have developed into novel scenarios proposed by our group to process information at the molecular level. They along with the traditional current-voltage scenario can be used to design and develop molecular devices for the next generation electronics. Control and communication features of these scenarios strongly help in the production of “smart” devices able to take decisions and act autonomously in aggressive environments. In sensor science, the ultimate detector of an agent molecule is another molecule that can respond quickly and selectively among several agents. The purpose of this project is the design and development of molecular sensors based on the MEPs and vibronics scenarios to feature two different and distinguishable states of conductance, including a nano-micro interface to address and interconnect the output from the molecular world to standard micro-technologies. In this dissertation, theoretical calculations of the electrical properties such as the electron transport on molecular junctions are performed for the components of the sensor system. Proofs of concept experiments complement our analysis, which includes an electrical characterization of the devices and measurement of conductance states that may be useful for the sensing mechanism. In order to focus this work within the very broad array between nanoelectronic and molecular electronics, we define the new field of Molecular Engineering, which will have the mission to design molecular and atomistic devices and set them into useful systems. Our molecular engineering approach begins with a search for an optimum fit material to achieve the proposed goals; our published results suggest graphene as the best material to read signals from molecules, amplify the communication between molecular scenarios, and develop sensors of molecular agents with high sensitivity and selectivity. Specifically, this is possible in the case of sensors, thanks to the graphene atomic cross section (morphology), plasmonic surface (delocalized charge) and exceptional mechanical and electrical properties. Deliverables from this work are molecular devices and amplifiers able to read information encoded and processed at the molecular level and to amplify those signals to levels compatible with standard microelectronics. This design of molecular devices is a primordial step in the development of devices at the nanometer scale, which promises the next generation of sensors of chemical and biological agents molecularly sensitive, selective and intelligent.

Assessing hazards due to energetic or reactive chemicals is a challenging and complicated task and has received considerable attention from industry and regulatory bodies. Thermal analysis techniques, such as Differential Scanning Calorimeter (DSC), are commonly employed to evaluate reactivity hazards. A simple classification based on energy of reaction (-H), a thermodynamic parameter, and onset temperature (To), a kinetic parameter, is proposed with the aim of recognizing more hazardous compositions. The utility of other DSC parameters in predicting explosive properties is discussed. Calorimetric measurements to determine reactivity can be resource consuming, so computational methods to predict reactivity hazards present an attractive option. Molecular modeling techniques were employed to gain information at the molecular scale to predict calorimetric data. Molecular descriptors, calculated at density functional level of theory, were correlated with DSC data for mono nitro compounds applying Quantitative Structure Property Relationships (QSPR) and yielded reasonable predictions. Such correlations can be incorporated into a software program for apriori prediction of potential reactivity hazards. Estimations of potential hazards can greatly help to focus attention on more hazardous substances, such as hydroxylamine (HA), which was involved in two major industrial incidents in the past four years. A detailed discussion of HA investigation is presented.

Simulations were used to assist in both the optimization and experimental support of polymer-supported immobilized homogeneous catalysts. This work is a starting point for using molecular modeling to assist in the design of immobilized homogeneous catalysts, where the broader impact is the use of such catalysts which offer high reactivity and selectivity while also providing improved separability and recyclability over heterogeneous catalysts. ROMP poly(norbornene) was examined because it was hypothesized that one of its isomeric configurations might have a helical conformation like vinylic PNB. Alpha shapes were used to determine the accessibility of these polymers with an approximated catalyst group attached to the backbone. The polymer size, reactant size, catalyst size, and linker length were all varied. The simulations were validated by reproducing the expected trends of a random coil for accessibility across the range of the varied properties. Structural analysis of the final conformations showed that these structures were all random coils. It was found that the assumption that the backbone cyclopentane ring was a non-rotatable bond was invalid, which was most likely the largest contributing factor in the lack of a helical structure. It was also found that increasing the size of the virtual catalyst group caused this polymer to have a regions with a local helical conformation. The backbone cyclopentane ring of ROMP PNB was stiffened by adding a dicarboximide group to the ring. The simulation results showed that the TR configuration produced a broad helical conformation. This helix is broad, so its radius of gyration is indistinguishable from that of an equivalent random coil with less than 100 repeat units. Additionally, accessibility did not properly capture this structural difference, but that was mainly because these simulations were pre-optimized for accessibility by having a long linker length and relatively small polymer dimensions. Co(III)salen catalysts were simulated to determine a way to use simulations to optimize polymer supports for these catalysts. The supports examined were an oligomer synthesized by Jacobsen, poly(cyclooctene) polymerized as a macrocycle, and PCO polymerized as a straight chain polymer. The MMFF94 force field was extended to accommodate cobalt terms based on the ESFF force field, X-ray diffraction structures, and ab initio quantum calculations. In order to compare the supports, the individual catalyst efficiency and the overall catalyst efficiency were combined into a "reaction score." The results showed that the PCO macrocycle was the optimal support in the range of 3-5 repeat units, which was consistent with experimental work.

Throughout biological, chemical, and pharmaceutical research,conformational searches are used to explore the possiblethree-dimensional configurations of molecules. This thesis describesa new systematic method for conformational search, including anapplication of the method to determining the structure of a peptidevia solid-state NMR spectroscopy. A separate portion of the thesis isabout protein-DNA binding, with a three-dimensional macromolecularstructure determined by x-ray crystallography.The search method in this thesis enumerates all conformations of amolecule (at a given level of torsion angle resolution) that satisfy aset of local geometric constraints, such as constraints derived fromNMR experiments. Systematic searches, historically used for smallmolecules, generally now use some form of divide-and-conquer forapplication to larger molecules. Our method can achieve a significantimprovement in runtime by making some major and counter-intuitivemodifications to traditional divide-and-conquer:(1) OmniMerge divides a polymer into many alternative pairs ofsubchains and searches all the pairs, instead of simply cutting inhalf and searching two subchains. Although the extra searches mayappear wasteful, the bottleneck stage of the overall search, which isto re-connect the conformations of the largest subchains, can be greatlyaccelerated by the availability of alternative pairs of sidechains.(2) Propagation of disqualified conformations acrossoverlapping subchains can disqualify infeasible conformations veryrapidly, which further offsets the cost of searching the extrasubchains of OmniMerge.(3) The search may be run in two stages, once at low-resolutionusing a side-effect of OmniMerge to determine an optimalpartitioning of the molecule into efficient subchains; then again athigh-resolution while making use of the precomputed subchains.(4) An A* function prioritizes each subchain based onestimated future search costs. Subchains with sufficiently lowpriority can be omitted from the search, which improves efficiency.A common theme of these four ideas is to make good choices about howto break the large search problem into lower-dimensional subproblems.In addition, the search method uses heuristic local searches withinthe overall systematic framework, to maintain the systematic guaranteewhile providing the empirical efficiency of stochastic search.These novel algorithms were implemented and the effectiveness of eachinnovation is demonstrated on a highly constrained peptide with 40degrees of freedom.

Made available in DSpace on 2014-06-11T19:23:30Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-02-17Bitstream added on 2014-06-13T18:50:42Z : No. of bitstreams: 1 bataginneto_a_me_bauru.pdf: 728792 bytes, checksum: 1630464fa8b5bc3088ecee698a2e6b9e (MD5) / Os polímeros orgânicos conjugados têm sido amplamente utilizados em diversos campos tecnológicos devido às suas características semicondutoras e ópticas. Recentemente foi relatada a possibilidade de sua utilização na área de dosimetria. O polímero MEH-PPV, quando diluído em solventes que contenham halogênios, tem apresentado características bastante promissoras nesta área, contudo não há ainda uma completa compreensão dos mecanismos envolvidos. No presente trabalho realizou-se o estudo conformacional e da estrutura eletrônica do polímero MEH-PPV em clorofórmio e as possíveis alterações provenientes da irradiação desta solução com radiações ionizantes. Métodos de modelagem de materiais foram utilizados a fim de simular o sistema. Resultados experimentais sugerem que os efeitos observados são oriundos da interação do solvente com a cadeia polimérica. A fim de investigar tal possibilidade, uma análise dos prováveis sítios de maior reatividade sobre o polímero foi realizada, apontando um mecanismo de incorporação de radicais sobre a cadeia principal. / Organic conducting polymers have been employed in several technological fields due to its semiconducting and optical properties. Recently, several reports points to applications in radiation dosimetry. When diluted in halogen-containing solvents, the polymer MEH-PPV shows interesting properties after gamma irradiation. Despite the promising application, still is lacking a complete understanding of the underlying phenomena. In the present work, we studied the geometry conformation and electronic structure of MEH-PPV in the presence of chloroform employing molecular modeling techniques to simulate the system. Several possibilities for polymer modification under gamma radiation were investigated, following suggestion from experimental results. Finally, a model for the color modifications of the solution is present.

This work provides an insight into how the molecular interactions influence macroscale properties of two materials: swelling clay and oil shale. Swelling clays cause enormous damage to infrastructure: buildings, roads, and bridges. Understanding the mechanisms are essential to prevent the detrimental effects and use of these clays for engineering applications. Our group studied the effect of fluid polarity on sodium montmorillonite (Na-MMT) swelling clay mineral using molecular modeling and experiments for bridging the molecular level behavior with the microstructure, swelling pressure, permeability, and compressibility. Various polar fluids (Dielectric Constant 110 to 20) found in landfill leachates are used. Our molecular dynamics (MD) simulations show that the nonbonded interactions of Na-MMT with polar fluids are higher than with low and medium polar fluids. These results are consistent with the results from Fourier transform infrared (FTIR) spectroscopy experiments. The polarity of the fluids and the fluid content influence the interlayer spacing, interlayer modulus, nonbonded interactions, and conformation as well as the shear strength parameters, the angle of internal friction (φ) and cohesion (c). Furthermore, the unconfined compressive strength experiments are used to evaluate the undrained cohesion at various swelling level. The nanomechanical properties, the modulus of elasticity (E) and hardness (H), of the undisturbed dry and saturated Na-MMT at various level of swelling are evaluated using nanoindentation experiments for the first time. The undrained cohesion, modulus of elasticity, and hardness decrease with increase in swelling level. Swelling controls the microstructure of Na-MMT clay, and the clay particles breakdown into smaller sizes with increase in swelling level. The Green River Formation located in the United States is the richest oil shale deposit in the world. Oil shale contains clay minerals, bitumen, and kerogen—a precursor to crude oil. A three-dimensional (3D) kerogen model is built from seven fragments, and the interactions of kerogen with Na-MMT is investigated using MD simulations to understand how the kerogen is bound to the clay mineral. The nonbonded interactions between Na-MMT and kerogen as well as among kerogen fragments are found. This work seeks to develop new methods to extract kerogen economically and efficiently. / Department of Energy (DoE) / Mountain Plains Consortium (MPC) / North Dakota Established Program to Stimulate Competitive Research (ND EPSCoR)

The Influenza virus is a major human respiratory pathogen responsible for seasonal ‘flu’ outbreaks and sporadic global pandemics. The Influenza polymerase complex is necessary for viral RNA synthesis and full virulence and requires the assembly of three conserved subunits: PA, PB1 and PB2. A recombinant chimeric protein mimetic consisting of the N-terminus (20 amino acids) of PB1 fused to Maltose Binding Protein (MBP) and Tat Nuclear Localization Signal (NLS) was designed and purified with the aim of inhibiting the assembly of the polymerase by mimicking PB1. The cell-penetrating protein mimetic was shown to efficiently enter the cell nucleus and prevent assembly of the Influenza polymerase, thus inhibiting viral replication. When MDCK cells were incubated with the mimetic and subsequently challenged with Influenza A virus, viral replication decreased up to 98% at 50 µM. Using a nuclear extraction assay, the mimetic was shown to efficiently penetrate the plasma membrane and enter the host nucleus. GST pull-down assays showed that the mimetic interacts with PA. Molecular modeling was then employed to predict the improved hypothetical free energy of binding between PB1 and PA and determined two significant substitutions for PB1 threonine at position six: glutamic acid (T6E) and arginine (T6R). These mutations increased potency of the mimetic at 25 µM (71% for T6E and 77% for T6R compared to 36% for the native construct) and 12.5 µM (27% for T6E and 70% for T6R compared to 16% for the native construct), suggesting a more stable interaction with PA consistent with molecular modeling. Using various in vitro assays, the mimetic was shown to be non-toxic to host cells. Targeting critical protein-protein interactions using a peptide fused to a cell-penetrating carrier protein presents a novel and intriguing approach in designing anti-viral therapeutics. / Thesis / Master of Science in Medical Sciences (MSMS)