270249 VU Chemometrics (2023W)

This course combines a lecture with the corresponding practical course to train the methods learned.

Modern analytical methods for continuously monitoring e.g. industrial processes or environments usually need to simultaneously acquire a range of analytes. This leads to large amount of data in comparably short time. Their evaluation thus usually needs computer assisted methods as they are developed by chemometrics, whose main fields are:

- Patter Recognition: (hierarchical) cluster analysis, principal component analysis

- Modelling of Data: regression methods in one and more variables, principal component analysis, neural networks.

- Time Series Analysis: autocorrelation functions

- Quality Assurance and Good Laboratory Practice

- Experimental Design.

In addition to simultaneously analyzing multicomponent mixtures, chemometrics also allows to classify samples according to not directly quantifiable criteria, such as discriminating different wines from each other by their smell or taste with so-called "artificial noses" or "artificial tongues". The main focus of the lecture will be on the actual analytical application of these techniques. Therefore, in-deep mathematical derivations will be foregone as far as possible.

During this laboratory course students either will generate multidimensional data sets e.g. by the means of spectrometric methods or sensor arrays, or receive them from their trainers. These will be the basis for getting to know different multivariate data analysis techniques, such as e.g. neural networks, PCA and cluster analysis, but also Experimental Design.