Inferring Chemical Reaction Rates from a Sequence of Infrared Spectra

dc.contributor.authorStarszyk, Peter
dc.date.accessioned2016-01-22T18:34:36Z
dc.date.available2016-01-22T18:34:36Z
dc.date.issued2016-01-22
dc.date.submitted2016-01-19
dc.description.abstractMany chemical compounds used by the energy and agricultural industries introduce large amounts of arsenic into the environment. As this poses serious health and environmental risks, designing safe and effective decontaminating agents remains an active research area. To do this, it is crucial to understand the chemical kinetics between arsenic and certain geochemicals at the molecular level; of particular interest are the reaction rate constants which describe the behaviour and properties of arsenic in relation to different chemicals. These rates can be inferred from a time series of individual concentration measures of all constituent chemicals in a mixture. However, current laboratory technology cannot produce such measures but instead produces time series of infrared spectra, from which individual chemical concentrations must be deconvoluted. Existing techniques to analyze such data focus on minimizing modeling assumptions and point estimation. In this thesis, we propose a fully specified parametric statistical model directly relating the rate constants to the spectra. This model drastically reduces the number of free parameters, offers statistically principled uncertainty estimates for parameters of interest and provides the added flexibility of incorporating important prior information, which current methodologies do not seem to account for. We further apply the model to experimental data in order to compare two plausible models of arsenic neutralization.en
dc.identifier.urihttp://hdl.handle.net/10012/10207
dc.language.isoenen
dc.pendingfalse
dc.publisherUniversity of Waterlooen
dc.titleInferring Chemical Reaction Rates from a Sequence of Infrared Spectraen
dc.typeMaster Thesisen
uws-etd.degreeMaster of Mathematicsen
uws-etd.degree.departmentStatistics and Actuarial Scienceen
uws-etd.degree.disciplineStatisticsen
uws-etd.degree.grantorUniversity of Waterlooen
uws.comment.hiddenHello, I have defended the thesis successfully on January 19th with approval from the committee. The approval form is on its way to GSO and I am submitting the thesis. Ideally I would really appreciate if the process was completed by January 22nd (Friday) so that the tuition balance is cleared on Quest by this tuition deadline. Thank you very much in advance!en
uws.contributor.advisorLysy, Martin
uws.contributor.affiliation1Faculty of Mathematicsen
uws.peerReviewStatusUnrevieweden
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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