Ab initio quantum chemical studies on neutral-radical reactions of ethynyl (C2H) and cyano (CN) with unsaturated hydrocarbons

An Ab Initio/RRKM study of the reaction mechanism and product branching ratios of neutral-radical ethynyl (C2H) and cyano (CN) radical species with unsaturated hydrocarbons is performed. The reactions studied apply to cold conditions such as planetary atmospheres including Titan, the Interstellar Medium (ISM), icy bodies and molecular clouds. The reactions of C2H and CN additions to gaseous unsaturated hydrocarbons are an active area of study. NASA's Cassini/Huygens mission found a high concentration of C2H and CN from photolysis of ethyne (C2H2) and hydrogen cyanide (HCN), respectively, in the organic haze layers of the atmosphere of Titan. The reactions involved in the atmospheric chemistry of Titan lead to a vast array of larger, more complex intermediates and products and may also serve as a chemical model of Earth's primordial atmospheric conditions. The C2H and CN additions are rapid and exothermic, and often occur barrierlessly to various carbon sites of unsaturated hydrocarbons. The reaction mechanism is proposed on the basis of the resulting potential energy surface (PES) that includes all the possible intermediates and transition states that can occur, and all the products that lie on the surface. The B3LYP/6-311g(d,p) level of theory is employed to determine optimized electronic structures, moments of inertia, vibrational frequencies, and zero-point energy. They are followed by single point higher-level CCSD(T)/cc-vtz calculations, including extrapolations to complete basis sets (CBS) of the reactants and products. A microcanonical RRKM study predicts single-collision (zero-pressure limit) rate constants of all reaction paths on the potential energy surface, which is then used to compute the branching ratios of the products that result. These theoretical calculations are conducted either jointly or in parallel to experimental work to elucidate the chemical composition of Titan's atmosphere, the ISM, and cold celestial bodies.<.

Ab Initio Quantum Chemical Studies on Neutral-Radical Reactions of Ethynyl (C2H) and Cyano (CN) with Unsaturated Hydrocarbons

An Ab Initio/RRKM study of the reaction mechanism and product branching ratios of neutral-radical ethynyl (C2H) and cyano (CN) radical species with unsaturated hydrocarbons is performed. The reactions studied apply to cold conditions such as planetary atmospheres including Titan, the Interstellar Medium (ISM), icy bodies and molecular clouds. The reactions of C2H and CN additions to gaseous unsaturated hydrocarbons are an active area of study. NASA’s Cassini/Huygens mission found a high concentration of C2H and CN from photolysis of ethyne (C2H2) and hydrogen cyanide (HCN), respectively, in the organic haze layers of the atmosphere of Titan. The reactions involved in the atmospheric chemistry of Titan lead to a vast array of larger, more complex intermediates and products and may also serve as a chemical model of Earth’s primordial atmospheric conditions. The C2H and CN additions are rapid and exothermic, and often occur barrierlessly to various carbon sites of unsaturated hydrocarbons. The reaction mechanism is proposed on the basis of the resulting potential energy surface (PES) that includes all the possible intermediates and transition states that can occur, and all the products that lie on the surface. The B3LYP/6-311g(d,p) level of theory is employed to determine optimized electronic structures, moments of inertia, vibrational frequencies, and zero-point energy. They are followed by single point higher-level CCSD(T)/cc-vtz calculations, including extrapolations to complete basis sets (CBS) of the reactants and products. A microcanonical RRKM study predicts single-collision (zero-pressure limit) rate constants of all reaction paths on the potential energy surface, which is then used to compute the branching ratios of the products that result. These theoretical calculations are conducted either jointly or in parallel to experimental work to elucidate the chemical composition of Titan’s atmosphere, the ISM, and cold celestial bodies.

Chlorine contribution to quantitative structure and activity relationship models of disinfection by -products' quantum chemical descriptors and toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Chlorine Contribution to Quantitative Structure and Activity Relationship Models of Disinfection By-Products' Quantum Chemical Descriptors and Toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Evaluation of contact and non-contact trapping efficiencies of human scent chemical profiles and their stabilities under different environmental conditions

Establishing an association between the scent a perpetrator left at a crime scene to the odor of the suspect of that crime is the basis for the use of human scent identification evidence in a court of law. Law enforcement agencies gather evidence through the collection of scent from the objects that a perpetrator may have handled during the execution of the criminal act. The collected scent evidence is consequently presented to the canines for identification line-up procedures with the apprehended suspects. Presently, canine scent identification is admitted as expert witness testimony, however, the accurate behavior of the dogs and the scent collection methods used are often challenged by the court system. The primary focus of this research project entailed an evaluation of contact and non-contact scent collection techniques with an emphasis on the optimization of collection materials of different fiber chemistries to evaluate the chemical odor profiles obtained using varying environment conditions to provide a better scientific understanding of human scent as a discriminative tool in the identification of suspects. The collection of hand odor from female and male subjects through both contact and non-contact sampling approaches yielded new insights into the types of VOCs collected when different materials are utilized, which had never been instrumentally performed. Furthermore, the collected scent mass was shown to be obtained in the highest amounts for both gender hand odor samples on cotton sorbent materials. Compared to non-contact sampling, the contact sampling methods yielded a higher number of volatiles, an enhancement of up to 3 times, as well as a higher scent mass than non-contact methods by more than an order of magnitude. The evaluation of the STU-100 as a non-contact methodology highlighted strong instrumental drawbacks that need to be targeted for enhanced scientific validation of current field practices. These results demonstrated that an individual's human scent components vary considerably depending on the method used to collect scent from the same body region. This study demonstrated the importance of collection medium selection as well as the collection method employed in providing a reproducible human scent sample that can be used to differentiate individuals.