Duration
20h Th, 5h Pr
Number of credits
| Master in chemistry, research focus | 3 crédits | |||
| Master in chemistry, teaching focus (Réinscription uniquement, pas de nouvelle inscription) | 3 crédits | |||
| Master in chemistry, professional focus | 3 crédits |
Lecturer
Coordinator
Language(s) of instruction
English language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
The course illustrates recent applications of advanced molecular spectroscopy and introduces the fundamentals of instrumental design and spectral data processing. It is tailored to the needs of chemists, linking theoretical principles with practical aspects of instrument construction and the exploitation of complex datasets. It is structured into 7 theoretical Lessons (2h each) and 2 practical sessions (4h each), covering the following topics:
Lesson 1. Fundamentals of molecular spectroscopy: transitions and selection rules, spectral line broadening (natural and instrumental), and the notion of spectral quality through the signal-to-noise ratio.
Lesson 2. Light sources in spectroscopy: presentation of the main light sources (lamps, LEDs, lasers, ...), analysis of their technical characteristics, and selection criteria according to the chemical application.
Lesson 3. Detectors in spectroscopy: presentation of the main detectors (photodiodes, PMTs, CCD/CMOS, InGaAs, ...) and their performance parameters (quantum efficiency, noise, response and readout dynamics).
Lesson 4. Optical design of spectrometers: exploration of instrumental architectures and their performance, spectral resolution (point detectors and array detectors), spatial resolution (refractive and reflective objectives), confocality, and spectral imaging.
Lesson 5. Spectral preprocessing: preparation of spectral data, estimation of the signal-to-noise ratio, smoothing, baseline correction, derivation, and spectral subtraction. Introduction to spectral databases and their use.
Lesson 6. Advanced chemometric analyses: presentation of multivariate statistical approaches for spectroscopic data processing, exploratory analyses (PCA), supervised regression methods (MLR, PCR, PLS, PLS-DA), and an introduction to multivariate curve resolution (MCR).
Lesson 7. Advanced spectroscopic techniques and applications: multiphoton spectroscopies, time-resolved fluorescence, pump-probe spectroscopy, and femtosecond techniques.
Practical Session 1. Construction and alignment of a spectrometer: alignment of optical components, calibration, and spectrum acquisition.
Practical Session 2. Principal Component Analysis on spectroscopic data: application of PCA, interpretation of results for compound identification, reaction monitoring, and mixture discrimination.
Learning outcomes of the learning unit
By the end of the course, the students should be able to propose a strategy to characterise a sample, including the spectral characterisation itself and the associated data treatment. The stategy must be compatible with the sample and the technical aspects of the complementary spectral methods.
Prerequisite knowledge and skills
Students should have some basic knowledge about spectroscopy.
Planned learning activities and teaching methods
The course will be composed of 7 lessons (2h each), covering a complete chapter. Applied exercices (TDs) will be resolved during 2 sessions of 4h. The chemiometric data treatment will be realised on commercial software. The student will developpe their own optical instrument design.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Course materials and recommended or required readings
The students will have access to the lecture support and to lecture notes.
Exam(s) in session
Any session
- In-person
oral exam
Written work / report
Out-of-session test(s)
Further information:
The students will carry out a mini-project consisting in aligning a miniatirised instrument enable to record spectral data and analysing complex spectral data using accessible data treament softwares. The students will be evaluated by a presentation of their results generated from the spectral data (either provided for this course or a dataset relevant for their Master's thesis) and their suitable data treatment.
Identical modalities stand for the evaluation in September, would the evaluation in June be less than 10/20.
Work placement(s)
Organisational remarks and main changes to the course
The lecture is given in English.
Contacts
Prof. Gauthier EPPE
Department of Chemistry, Bat B6c (bureau 1/8), Allee du 6 aout, 11 at 4000 Liege
Tel: +32 4366.34.22; e-mail : g.eppe@uliege.be
Dr. Cedric MALHERBE
Department of Chemistry, Bat B6c (bureau 1/9), Allee du 6 aout, 11 at 4000 Liege
Tel: +32 4366.36.47; e-mail : c.malherbe@uliege.be