CHEMOMETRICS

The course aims to introduce students to chemometrics tools that can be useful in studying and interpreting complex systems.
The course, through mathematical-statistical methods of Multivariate Analysis (chemometrics), start with the description of the multivariate structure of data for studying a complex system. The main methods of Pattern Recognition, with particular focus on clustering, classification and Experimental Design techniques will be illustrated. Particular emphasis will be given to the study of industrial processes in the biotechnology field and of contaminated sites. Different cases of study will be presented and discussed in-depth.
These knowledge are extremely important inside the Degree’s program, because the students will acquire the necessary skills for interpreting data from the characterization of the studied cases and for understanding the mechanisms and the dynamics of chemical and biological processes. That is the starting point for implementing environmental remediation strategies and optimizing the processes in the sustainable development field.
The course has a predominant experimental approach and is focused on the understanding and the practical use of the main methods of Pattern Recognition.

The student will be able to acquire:
1) the appropriate skills for using chemometric and statistical methods of multivariate analysis, such as Pattern Recognition methods and Experimental Design;
2) the ability to apply these methods to new environmental and process problems, or knowing how to interpret new data regarding the studied systems. These skills will be given by the presentation of specific cases of study in which chemometrics methods are applied;
3) a sufficient critical approach on choosing the right chemometrics methods for solving environmental and technological problems and on extrapolating from the results useful information, which can lead him to implement a decisional strategy of action.
The student will have to learn a consistent and correct use of the language and terminology, so he will be able to propose and communicate this methodological approach even to people who don’t have these skills and with whom he will have to collaborate in a professional future.

High school basic knowledge of mathematics, statistics and General Chemistry

Pattern Recognition.
Preliminary data treatment, clustering and classification methods: K-NN, Cluster Analysis.
Principal Component Analysis (PCA): theory, use, applications; the SIMCA method.
Experimental Design: Factorial Design, D-efficiency and D-optimal design. Practical use of chemometrics software. A part of the course will be dedicated to the study of real cases from the relevant literature.

Didactic materials and presentations provided by the professor.
Roberto Todeschini: "Introduzione Alla Chemiometria". EDiSES, Napoli.
D.L. Massart et al: "Chemometrics:a Textbook", Data Handling in Science and Technology, 2, ELSEVIER, Amsterdam

The final mark will be given after an oral examination concerning the topics discussed during the course. The student will be asked to discuss cases of study and show the ability to apply the chemometrics approach to real problems in environmental and biotechnology field.

Classroom lessons. The lessons will have the main goal of explaining the “philosophy” of the chemometrics approach, which is completely different from the one commonly used in the traditional scientific method.

Italian

oral

This subject deals with topics related to the macro-area "Climate change and energy" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development