Program Overview

SPECTROSCOPY FOR PROCESS ANALYTICAL TECHNIQUES (PAT)

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.

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 will be provided.

Aims and Learning Outcomes

The objective of this class is twofold:

• to provide fundamental knowledge on the process analytical techniques (PAT) based on the spectroscopic methods,
• to provide students with the basic understanding of the methodologies and techniques for data analysis to correctly rationalize experimental observations. Students will acquire knowledge on:
• basic understanding on the electromagnetic spectrum and light-matter interaction
• fundamentals on the use non-destructive optical methods for the investigation of polymer properties, catalysis, and chemical processes
• 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 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 observed system/process
• assess 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.
• 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

• The electromagnetic spectrum and fundamental quantities, basic optics
• Fundamentals light-matter interaction
• Basic information obtained in different spectral ranges
• Principles of common spectrometers
• Use of the spectroscopic techniques to probe the quality of industrial processes
• Lab: Examples of main sampling collection techniques for on-line process control

SECTION 2: DATA ANALYSIS

• Introduction to: descriptive, exploratory, and inferential statistics
• Covariance: coefficient of variation, confidence intervals
• Significance assumptions: one-sided, two-sided, Kolmogorov-Smirnov test, MAD Test
• Basic concepts of multivariate statistics: Principal Component Analysis
• Selection 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
  • J. Workman, L. Weyer, Pratical Guide to Interpretative Near-Infrared Spectroscopy, CRC Press
  • Internal Reflection Spectroscopy, edited by F.M. Mirabella, Marcel Dekker Inc
  • Optical Fiber Sensor edited by K.T.V. Grattan and B.T. Meggit, Kluwer Academic Publisher
  • 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
  • D. Himmelblau, "Process Analysis by Statistical Methods", John Wiley & Sons
  • Yuri A.W. Shardt, "Statistics for Chemical and Process Engineers. A modern approach", Springer

Teachers and Exam Board

Teachers

• DAVIDE COMORETTO

Exam Board

• DAVIDE COMORETTO (President)
• MARINA ALLOISIO
• PAOLA LOVA

Lessons

Lessons Start

This class is held on the second semester.

Class Schedule

The timetable for this course is available.

Exams

Exam Description

Oral examination by two professors.

• 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.

Assessment Methods

The aim of assessment is to verify the achievement of learning outcomes.

• 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.

Exam Schedule

• 20/02/2026 | 09:00 | GENOVA | Esame su appuntamento
• 31/07/2026 | 09:00 | GENOVA | Esame su appuntamento
• 18/09/2026 | 09:00 | GENOVA | Esame su appuntamento

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