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AssigneePhilips Petroleum Company
InventorsMaziar Sardashti, Xiaonian Lai
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A chemometric method for predicting unknown properties in polymers using an on-line NMR system comprising the steps of producing a predictive data set and using the predictive data set to obtain unknown amounts of properties in a polymer. In a preferred embodiment, the process begins by obtaining free induction decays for samples of polypropylene with measured concentrations of xylene soluble polypropylene from a xylene soluble polypropylene data set to produce a free induction decay data set. The free induction decay data set is analyzed using PCA to produce a principle component data set. The principle component data set, the xylene soluble polypropylene data set, and the free induction decay data set, are analyzed using partial-least squares analysis to produce a training data set and the training data set is subsequently validated to produce a predictive data set. Using the predictive data set involves the steps of obtaining free induction decays of samples of polypropylene with unknown concentrations of xylene soluble polypropylene and applying the free induction decays to the predictive data set to predict the unknown concentrations.
An on-line process to produce a predictive data set which can be used to predict the amount of a property of a polymer in a composition, said process comprising:
An on-line process of using a predictive data set to predict the amount of a component in a polymer composition, said process comprising:
An on-line process to predict the concentration of xylene soluble polypropylene in a composition, said process comprising:
Dependencies are inferred from the claim text.