Kinetic procedures for mixture analysis have been scarcely used. That fact can be explained a) a low reproducibility, and, b) the difficulty of the calibration process. Although modern instrumentation has improved the precision of measurements, there are yet important problems related to the calibration step. The aim of this project is to develop general calibration procedures that overcome the present limitations and let enlarge the aplications of kinetic analytical procedures. A rapid scanning spectrophometer coupled to a stopped-flow mixing unit will be used to record a multiparametric analytical signal as a function of time. It is projected to develop calibration procedures based on partical least squares regressions, using linear, quadratic and spline function algorithms: artifical neural netwoks; and tensorial algebra. Common characteristics of all these calibration procedures are
|Effective start/end date||1/07/95 → 1/07/98|
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