OVERVIEW

The class provides the basic theoretical and experimental knowledge of in-line control techniques based on different spectroscopical methods for monitoring product quality  and industrial processes performance. In addition, the basic concepts of monovariate and multivariate statistics are illustrated, which enable a correct interpretation of experimental data (observations). A series of case studies will be discussed to facilitate the learning of the theoretical and experimental concepts provided.

AIMS AND CONTENT

LEARNING OUTCOMES

Aim of the class is to provide fundamental knowledge on the use of optical and spectroscopic methods for the material quality control and industrial process performance monitoring. Remote detection techniques in the UV-Vis, NIR and MIR spectral ranges will be described and used. Analysis tools to correctly interpret experimental data of chemical nature as well as basic theoretical concepts (introduction to multivariate analysis and to chemometrics) will be provided. The class is accompanied by explanatory examples so that the student can be able to manage experimental data measured in the lab.

AIMS AND LEARNING OUTCOMES

The objective of this class is twofold: a) to provide fundamental knowledge on the process analytical techniques (PAT) based on the spectroscopic methos such as: UV-Vis, NIR, and MIR spectral, b) to provide students with the basic understanding of the methodologies and techniques for data analysis to correctly rationalize experimental observations. In particular, students will acquire knowledge on:

• basic understanding on the electromagnetic spectrum and light-matter interaction;
• fundamentals on the use non-destructive optical methods (light source, spectrometers, optical fibers, filters, monochromators and gratings) for the investigation of polymer properties, catalysis, and chemical processes both at the lab and industrial scale;
• basic understanding on in-line optical detection techniques in the UV-Vis, NIR and MIR spectral ranges;
• fundamentals of descriptive, exploratory and inferential statistics;
• basic statistical tests and parametric and non-parametric tests;
• basic concepts of multivariate statistics;
• fundamentals of model evaluation criteria.

At the end of the class, students will be able to:

• evaluate the quality of the experimental observations using the tools of monovariate and multivariate statistics;
• identify the most important process variables affecting the the observed system/process;
• discriminate between alternative models that describe the investigated system;
• design systems, based on monovariate and multivariate statistics, for quality control and monitoring process performance.

PREREQUISITES

Basic knowledge on Chemical Sciences, Physics, Mathematics, and Spectroscopy

TEACHING METHODS

Class lecture, demo-software, lab work. Powerpoint presentation of teacher and lab notes available from the University Web Site (AulaWeb). Lab simple experiments of spectroscopy on quality of materials. Case studies will be illustrated to help students to acquire the concepts covered in class.

SYLLABUS/CONTENT

SECTION 1: SPECTROSCOPY (4 CFU)

• The electromagnetic spectrum and fundamental quantities, basic optics (refraction, reflection, transmission, polarization, interference, diffraction, gratings, optical fibers).
• Fundamentals light-matter interaction (UV-Vis absorption, NIR, MIR, photoluminescence, Raman).
• Basic information obtained in different spectral ranges with particular emphasis for the comparison between MIR and NIR.
• Principles of common spectrometers in particular compact and transportable systems allowing collection and detection of signals by optical fibers.
• Use of the spectroscopic techniques (in particular those based on remote sensing) to probe the quality of industrial processes.
• Lab: Examples of main sampling collection techniques (transmission, reflection, ATR, DRIFT, PAS, Raman) for on-line process control. Interpretation of spectroscopic data.

SECTION 2: DATA ANALYSIS (2 CFU)

• Introduction to: descriptive, exploratory, and inferential statistics;
• Covariance: coefficient of variation, confidence intervals.
• Significance assumptions: one-sided, two-sided, Kolmogorov-Smirnov test, MAD Test.
• Recalls of the most important statistical distributions  (t-Student distribution, "Chi2" distribution, Fisher's F distribution).
• Introduction to parametric and non-parametric tests: Chi2 test (variance), Student's t-test, Fisher's test.
• Basic concepts of multivariate statistics: Principal Component Analysis.
• Discrimination of alternative models.

RECOMMENDED READING/BIBLIOGRAPHY

• Notes provided by the teachers and used for lessons and lab.

Reference texts

• N.B, Colthup, L.H. Daly, S.E. Wiberley, Introduction to Infrared and Raman Spectroscopy, Academic Press.
• H.W. Siesler, Y. Ozaki, S. Kawata, H.M. Heise, Near-Infrared Spectroscopy: principles, instruments, applications, Wiley (3rd reprint, 2006); ISBN: 3-527-30149-6.
• J. Workman, L. Weyer, Pratical Guide to Interpretative Near-Infrared Spectroscopy, CRC Press (2008, Boca Raton - FL, USA).
• Internal Reflection Spectroscopy, edited by F.M. Mirabella, Marcel Dekker Inc. (1993, New York, USA).
• Optical Fiber Sensor edited by K.T.V. Grattan and B.T. Meggit,  Kluwer Academic Publisher (1999, Dordrecht, The Netherlands).
• J.W. Niemantsverdriet, Spectroscopy in catalysis, Wiley-VCH.
• H.J. Harrick, Internal Reflection Spectroscopy, Interscience Publisher 1967.
• M. Spiegel, “Statistics”, Schaum.
• J.E. Jackson, “A User’s Guide to Principal Components”, John Wiley & Sons.
• W.J. DeCoursey, “Statistics and Probability for Engineering Applications”, Newnes (2003)
• D. Himmelblau, “Process Analysis by Statistical Methods”, John Wiley & Sons
• Yuri A.W. Shardt, “Statistics for Chemical and Process Engineers. A modern approach”, Springer (2022)

Additional materials for working students or students with specific learning disabilities is available upon request.

Note: the copies of the lecture slides are not sufficient for a good preparation for the exam; it is strongly recommended to use the textbooks and reference books.

TEACHERS AND EXAM BOARD

Exam Board

DAVIDE COMORETTO (President)

ALBERTO SERVIDA (President Substitute)

LESSONS

LESSONS START

This class is held on the second semester. Lesson starting is managed according to the Manifesto (avaialble at https://corsi.unige.it/corsi/11767/). A specific communication will be sent to registered students.

The class schedule is available at https://easyacademy.unige.it/portalestudenti/ 

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Oral examination by two professors, one of whom is D. Comoretto/A. Servida. The duration of the exam is not shorter than 30 minutes. The student discusses an original power point presentation or a written relation on a topic from class or lab activities. The student, with the help of the instructor, selects a topic that most closely matches his/her abilities/needs and that can be found in the scientific literature and/or on the AulaWeb (usually one or two papers or patents). The presentation must be designed so that it can be understood by students at the same level.

Students must show that they have understood the key physics/chemistry/technology principles of the topic and can report the results using suitable technical vocabulary, answering questions critically and professionally (up to 15/30).

They must also show that they have understood the experimental features of the techniques described (up to 10/30).

Finally, clarity of presentation will also be assessed (up to 5/30).

Registration must be done by registering on-line and sending an e-mail to the lecturers of the class within 7 days of the date of the call.

For students with disabilities or with SLD, the assessment method corresponds to the UNIGE rules summarized at https://unige.it/disabilita-dsa.

Only in urgent cases can the examination be carried out telematically, in accordance with the regulations issued by the University.

ASSESSMENT METHODS

The aim of assessment is to verify the achievement of learning outcomes. If these are not achieved, the student will be asked to extend their studies. In addition, the oral examination will serve to verify the achievement of an adequate level of knowledge of the topics taught in the lectures and the ability to use correct terminology. To ensure consistency between the exam topics and the topics actually covered in the class, the detailed program will be uploaded on AulaWeb and described at the beginning of the class.

FURTHER INFORMATION

For any other information, students are invited to directly contact teachers by email (davide.comoretto@unige.it; servida@unige.it), telephone (0103538736/8744; 01013538704) or visiting them in their offices/labs.

Attending lectures is strongly recommended in order to familiarize yourself with the examination procedure, as the lectures are always accompanied by concrete examples from industrial practice.

The class has a theoretical section (5 cfu) and an experimental one (1 cfu lab)

Agenda 2030 - Sustainable Development Goals

Quality education

Gender equality

Responsible consumption and production

Climate action

Students who have valid certification of physical or learning disabilities on file with the University and who wish to discuss possible accommodations or other circumstances regarding lectures, coursework and exams, should speak both with the instructor and with Professor Sergio Di Domizio (sergio.didomizio@unige.it), the Department’s disability liaison.