66218 - Mass Spectrometry with Exercises

Learning outcomes

Upon completion of the course, students will be able to interpret the mass spectra of the main classes of organic molecules obtained by electron ionization and recognize the characteristics of those generated by other ionization techniques. They will be familiar with the following aspects of mass spectrometers: - the main components (ion sources and analyzers, detectors, vacuum pumps); - their operating principles; - their applications to analytical problems.

Course contents

General course information

 Course Structure

6 ECTS credits, equivalent to 56 hours, consisting of:

4 ECTS credits of classroom lectures, equivalent to 32 hours (Module 1, Mass Spectrometry)

2 ECTS credits of computer laboratory activities, equivalent to 24 hours (Module 2, Chemometrics)

FINAL COURSE GRADE: weighted average based on ECTS credits of the grades obtained in the two Modules.

The specific contents of the two modules are detailed below.
The following considerations apply to both modules.

Use of Artificial Intelligence

Generative AI may be a useful tool to support individual study, for example through further explanations, summaries, reformulations, and self-assessment activities.

With regard to assessment, limited, declared, and non-substantial use of generative AI is permitted for support activities such as summarization, language revision, or reformulation of texts produced by students.

Substantial use of AI is not permitted for the uncritical generation of texts, content, bibliographies, data interpretations, or communication materials to be presented as personal work.

Students with Special Learning Needs

Students with specific learning disabilities (SLD) or temporary/permanent disabilities are encouraged to contact the relevant University office in advance (https://site.unibo.it/studenti-con-disabilita-e-dsa/it).

The office will propose any necessary accommodations for learning and assessment. Such accommodations must, however, be submitted to the course instructor for approval at least 15 days in advance. The instructor will evaluate their suitability also in relation to the educational objectives of the course.

MODULE 1 – MASS SPECTROMETRY (4 ECTS credits of classroom lectures, equivalent to 32 hours)

 Prerequisites

Students enrolling in this course are expected to have a solid background in the fundamentals of analytical chemistry and basic instrumental analytical techniques, as well as a good knowledge of general chemistry and organic chemistry.

Learning Objectives

The course aims to provide students with a fundamental knowledge of mass spectrometry. The first part focuses on the theoretical principles underlying the generation of mass spectra and introduces the instrumentation involved. The second, application-oriented part enables students to acquire the ability to interpret mass spectra for identification purposes.

Syllabus

 - GENERAL PRINCIPLES. Representation of a mass spectrum. Definitions of average mass, nominal mass, monoisotopic mass, and exact mass. Resolution. Accuracy. Isotopic ions.

- ION SOURCES. Electron Ionization or ectron impact (EI). Chemical Ionization (CI). Fast Atom Bombardment (FAB). Matrix-Assisted Laser Desorption/Ionization (MALDI). ThermoSpray Ionization (TSP). Electrospray Ionization (ESI). Atmospheric Pressure Chemical Ionization (APCI). Inductively Coupled Plasma Ionization (ICP). Types of ions formed: radical cations, cationized ions. adduct ions, multi-charged ions (recognition of multi-charged ions and methods for calculating the number of charges).

- ION ANALYZERS. Introduction to magnetic and electrostatic analyzers (E). Types of analyzers and their operating principles: Quadrupole (Q), three-dimensional ion trap (3DIT), linear ion trap (LIT), Time-of-Flight (TOF), Orbitrap, Hybrid analyzers. Operational characteristics of analyzers: mass range, resolution, acquisition modes.

- HYPHENATED TECHNIQUES. Gas Chromatography/Mass Spectrometry (GC/MS). Liquid Chromatography/Mass Spectrometry (LC/MS).

- INTERPRETATION OF MASS SPECTRA. Characteristics of mass spectra obtained by the different ionization sources (EI, CI, ESI, APCI, (MALDI). Representation and technical terminology. Procedure for interpreting a mass spectrum. Even-electron and odd-electron ions (cations, radical cations, adduct ions). Identification of the molecular ion. Factors affecting ion abundance. Even-electron rule. EI fragmentation rules. Examples of mass spectra: small organic molecules, macromolecules, halogenated compounds. Identification of unknown mass spectra. Searches in the NIST mass spectral library for unknown spectra (criteria for comparing unknown spectra with library spectra).

MODULE 2 – CHEMOMETRICS (2 ECTS credits of computer laboratory activities, equivalent to 24 hours)

 Prerequisites

Students enrolling in this course are expected to have a solid background in the fundamentals of analytical chemistry and basic instrumental analytical techniques.

Learning Objectives

The course aims to provide students with the ability to design a chemical-analytical methodology from sampling to data analysis, starting from experimental design and progressing to proper data processing and preparation of the final technical report.

To achieve these objectives, the following mathematical and statistical knowledge will be provided:

· Elements of multivariate statistical analysis.

· Methods for exploring multivariate data.

· Multivariate modeling methods: classification and multivariate regression.

· Design of Experiments (DOE).

Students will acquire the computational skills necessary for applying the chemometric methods learned during the course.

Finally, students will develop the specific competence of the Chemometrician: optimizing the entire chemical analysis process.

Syllabus

 - UNIVARIATE STATISTICAL ANALYSIS

Confidence intervals. Significance tests. Calibration using linear regression. Validation. Matrix effects. Detection limits Error propagation.

- EXPLORATION OF MULTIVARIATE DATA

Principal Component Analysis (PCA). Cluster Analysis.

- MULTIVARIATE MODELING

Models. Model order and linearity. Control parameters. Model validation. Classification: Qualitative models.

Classification: performance parameters. Discriminant Analysis (DA). The SIMCA classification method.

Calibration: Quantitative models. Multivariate regression: MLR, PCR, PLS. Validation of regression models. Diagnostic methods for regression models.

- DESIGN OF EXPERIMENTS

Multivariate methods for selecting standard samples and variables for model building. Full Factorial Design. D-Optimal Design.

Readings/Bibliography

Module 1

The PowerPoint slides presented during lectures, which will be available on the “Virtuale” platform (https://virtuale.unibo.it), together with the notes taken during class, are essential for exam preparation.

Reference Texts

· E. de Hoffmann, V. Stroobant, Mass Spectrometry – Principles and Applications, Third Edition, Wiley, 2007.

· T.A. Lee, A Beginner's Guide to Mass Spectral Interpretation, Wiley, 1998.

· F. W. McLafferty, F. Turecek, Interpretation of Mass Spectra, University Science Books, Fourth Edition, 1993.

· J. H. Gross, Mass Spectrometry – A Textbook, Springer, Second Edition, 2011.

· J. T. Watson, O. D. Sparkman, Introduction to Mass Spectrometry – Instrumentation, Applications and Strategies for Data Interpretation, Wiley, Fourth Edition, 2007.

· R. E. March, J. F. J. Todd, Practical Aspects of Trapped Ion Mass Spectrometry, Volume V, Applications of Ion Trapping Devices, pp. 491–507, CRC Press, 2010.

· O. D. Sparkman, Z. E. Penton, F. G. Kitson, Gas Chromatography and Mass Spectrometry – A Practical Guide, Academic Press, Second Edition, 2011.

· M. C. McMaster, LC/MS – A Practical User's Guide, Wiley, 2005.

· R. B. Cole, Electrospray and MALDI Mass Spectrometry – Fundamentals, Instrumentation, Practicalities, and Biological Applications, Wiley, Second Edition, 2010.

Module 2

Students’ notes taken during in-person lectures or while listening to recorded lectures are essential.

For each lecture, the instructor provides a PDF document corresponding to what is written on the electronic whiteboard used during the lesson; this document is published on the virtuale.unibo.it platform.

All course contents are included in the lecture notes provided by the instructor on the virtuale.unibo.it platform; reading these materials is strongly recommended.

Reference Texts for Further Study

· Roberto Todeschini, Introduzione alla Chemiometria, Edises, 1998.

· J.C. Miller, J.N. Miller, Statistics and Chemometrics for Analytical Chemistry, Pearson Education, 2010.

· Richard G. Brereton, Applied Chemometrics for Scientists, Wiley, 2007.

Teaching methods

- Module 1

Lectures are delivered through classroom teaching in which the course topics are presented and discussed, with practical examples.

Following the theoretical section, students independently complete exercises on mass spectrum interpretation similar to the guided examples, with assistance from the instructor.

Teaching materials include PowerPoint presentations and board work.

- Module 2

The module is conducted in a computer laboratory and in classroom.

Each lesson consists of a theoretical section followed by a practical section involving guided exercises and the acquisition of specific computational tools (software for multivariate statistical applications).

Students then independently complete exercises similar to the guided examples, with assistance from the instructor.

Given the nature of the activities and the teaching methods adopted, attendance in this educational activity requires prior completion by all students of Modules 1 and 2 of the University’s workplace and study-place safety training, delivered through e-learning.

All lectures and practical sessions will be recorded and made available on virtuale.unibo.it, in order to assist students who are unable to attend in person or who wish to review the lectures to clarify specific topics.

- Applicable to Both Modules

For both modules, the use of teaching materials provided by the instructor and made available online (https://virtuale.unibo.it) and students’ lecture notes will be essential.

Attendance in person at all teaching activities is strongly recommended. Please note that it will no longer be possible to attend teaching activities live remotely.

Assessment methods

Assessment is based exclusively on the final examination, which verifies the acquisition of the expected knowledge and skills through a written report (Module 2) and an oral examination (Modules 1 and 2) covering the entire syllabus of both teaching modules. No mid-term assessments are scheduled. The grades obtained in the individual modules are combined to determine the final examination grade through a weighted average. The grades awarded in the individual modules remain valid for one academic year.

Registration through AlmaEsami is mandatory in order to sit the examination, and the published registration deadlines must be strictly respected. Students who no longer intend to take the examination are requested to withdraw their registration before the registration list closes.

- Module 1

The examination consists of an oral test. Specifically: all registered students will simultaneously complete a mass spectrum interpretation exercise (Part A). Subsequently, according to the registration order, students will take the oral examination (Part B). Part B consists of discussion of the exercise completed in Part A and two theoretical questions.

The final grade for the module is the sum of the scores obtained in the two parts: Part A maximum 8 points, Part B maximum 11 points for each theoretical question.

- Module 2

The Module 2 examination is divided into two parts.

1. Written Report

Students must prepare a Word-format report on the chemometric analysis of a dataset provided by the instructor. Assignments are individual: each student works on a dataset different from those assigned to other students. The required chemometric analysis is analogous to the analyses presented during guided practical sessions based on a model dataset. The report must be submitted as a text document.

Students are not required to submit files containing the numerical analyses themselves; however, all numerical and graphical outputs generated using the software tools must be included in the report.

The instructor assigns a grade to the final report.

2. Oral Examination

An oral examination covering: Discussion of the report. Theoretical concepts presented during lectures (definitions and demonstrations included in the course notes). Duration: up to 30 minutes.

A grade is awarded for the report and a separate grade for the answers to the theoretical questions. The final module grade is calculated as a weighted average: Report grade: weight 0.3. Theory grade: weight 0.7

Assessment Criteria (Applicable to Both Modules)

Assessment takes into account of Mastery of course content. Clarity of presentation. Ability to connect theory and practice. Independence in discussion and reasoning.

The grading criteria are as follows:

Satisfactory (18–20) - Essential knowledge. Correct but uncertain and insufficiently articulated presentation.

Good (21–24) - Consolidated knowledge. Generally adequate presentation, although predominantly based on memorization and with limited ability to connect different topics.

Very Good (25–27) - Strong command of the subject matter. Confident, well-structured presentation and good analytical skills.

Excellent (28–30 cum laude) - Comprehensive and in-depth knowledge. Rigorous, independent, and critical presentation.

Cum laude is awarded in cases of outstanding excellence.

The instructors are available, by appointment, for further clarification and to help students assess their level of preparation prior to the examination.

Teaching tools

Video projector for classroom lectures. Whiteboard for theoretical explanations. Video projector for spreadsheet demonstrations. Computer laboratory for practical exercises. All teaching materials used during lectures will be available through the “Virtuale” platform: https://virtuale.unibo.it

For lectures and practical sessions in Module 2, the instructor uses the following software, installed on both the computer laboratory workstations and the research laboratory computers: Microsoft Excel and R. The R software is used in the CAT version, which can be downloaded free of charge from: http://gruppochemiometria.it/index.php/software

Students may complete the individual exercises and calculations required for the final report either using the computers available in the computer laboratory or their own personal computers.

Office hours

See the website of Jessica Fiori

See the website of Dora Melucci