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dc.contributor.authorPell, Randall James, 1956-en_US
dc.date.accessioned2009-10-07T15:15:45Z
dc.date.available2009-10-07T15:15:45Z
dc.date.issued1990en_US
dc.identifier.otherb25668900en_US
dc.identifier.other24051099en_US
dc.identifier.otheren_US
dc.identifier.urihttp://hdl.handle.net/1773/11545
dc.descriptionThesis (Ph. D.)--University of Washington, 1990en_US
dc.description.abstractChemometrics is a discipline of chemistry that uses mathematical and statistical techniques to extract useful information from chemical data. Infrared emission spectroscopy is one of a very few analytical techniques that allows noninvasive and remote measurements. This dissertation uses the chemometric methods of multivariate calibration and multiresponse nonlinear optimization to extract useful information from infrared emission data. Partial Least Squares and Locally Weighted Regression are used for prediction of chemical and physical properties of a free standing polymer system and a polymer coated aluminum system. Multiresponse nonlinear optimization is used to model the dynamic process of a polymer curing reaction. The choice of the proper objective function for multiresponse nonlinear optimization is also investigated.en_US
dc.format.extentxviii, 229 p.en_US
dc.language.isoen_USen_US
dc.rightsCopyright is held by the individual authors.en_US
dc.rights.urien_US
dc.subject.otherTheses--Chemistryen_US
dc.titleChemometrics and infrared emission spectroscopy for remote analysisen_US
dc.typeThesisen_US


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