Direct Determination of Additives in Polymers and Rubbers

Much recent work on the development of direct methods has been carried out and is discussed next. 

Chemometrics is the art of extracting chemically relevant information out of data produced in chemical experiments with the use of mathematical and statistical methods [2]. The main issue is to structure the chemical problem in a form that can be expressed as a mathematical problem. Chemometrics have become an integral part of spectroscopy and other areas of chemistry. 

Principal component analysis (PCA) is a statistical technique which, over the last decade, has become a regular tool for analysing chemical data [3-6]. If there is a relationship among any samples in a data set, the PCA will separate the samples into groups. 

To discuss the prediction error, one must validate the calibration model [2]. There are two sorts of validation. One method is based on a new set of objects (external prediction). It requires a large and representative set of objects which have to be kept apart from the calibration for testing purposes only. The other validation method is based on the calibration data themselves (internal validation). In most cases, internal validation methods such as cross-validation and leverage correction [2] give sensible results with valuable information about the prediction ability. Cross-validation seeks to validate the calibration model with independent test data, but contrary to external validation it does not use data for testing only. The cross-validation is performed a number of times, each time with the use of only a few calibration samples as a test set. From the validation set it is possible to compare the prediction ability for the models, expressed by the estimated prediction mean square error. 

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R. Crompton. Determination of Additives in Polymers and Rubbers, pp. 1-68, Rapra Technology. Shawbury. Chapitre 1. Direct determination of Additive in Polymers and rubbers (2007). 

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