Graduate Thesis Or Dissertation
 

Elucidating the Origins of Trends and Selectivities of Organic Reactions through Computations and Data Analysis Techniques

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/nv935b04r

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  • In this dissertation, a novel method for analyzing computed transition states (TS) for organic reactions is disclosed. It introduces the use of localization-delocalization matrices as parameters in a linear free energy relationship to determine the transition state interactions responsible for differences in energy between the major and minor TS in an organic reaction. First, the theory and practice of traditional analysis between major and minor structures is shown and linear free energy relationships are introduced through a study of PN-heterocycle small molecule fluorophores. The analysis in this paper is an example of indirect analyses usually used to determine the interactions that differentiate between major and minor structures. A thorough examination of the P-N heterocycle dimerization and their geometries leads to the hypothesis disclosed rather than any direct method of comparison. Several linear free energy relationships are included to interpret the differences in energy in these P-N heterocycles due to R substituents, most notably a multiple linear regression that predicts the ΔGexp from the σpara values from two different R substituents (R1 and R2). Next, a software designed to help find linear free energy relationships is disclosed. Linear free energy relationships have the potential to get very complicated with the inclusion of multiple R groups and multiple electronic and steric parameters. Recent papers have also disclosed the use of parameters such as IR frequencies, IR intensities, and pKa values. For linear regression, the limit to the number of parameters you can include is one less than the number of experimental observables obtained. In cases where the number of parameters is equal to or greater than the number of observables, a software was designed to evaluate all possible models given your parameters and a method disclosed to choose the best one. Several experimental examples are included to demonstrate the efficacy of this software. In the final example, the linear free energy relationship (LFER) model was used to predict the ΔGexp of a new substrate from a previously described substrate scope. The substrate was then made experimentally, and the experimental ΔGexp matched what was predicted beforehand. Finally, a novel approach to transition state analysis in computational organic chemistry is disclosed. Localization-delocalization matrices (LDMs) that describe the sharing of electrons on a molecule in a matrix are used as parameters in a LFER to determine the interactions that differentiate between TS. Five previously published papers by the Cheong group with traditional computational transition state analyses were re-analyzed using this new method and the results were compared. TS that previously took months to analyze indirectly can now be directly analyzed in a few hours.
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  • Ongoing Research
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  • 2021-09-21 to 2024-01-11

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