Physical organic chemistry

Duration

25h Th

Number of credits

Lecturer

Pauline Bianchi, Jean-Christophe Monbaliu

Coordinator

Jean-Christophe Monbaliu

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

This course illustrates the synergy between different computational techniques (computational chemistry, data science, artificial intelligence) to understand and rationalize mechanisms and selectivities in synthetic organic chemistry.

The theoretical course is organized into seven 2-hour modules:

• Module I | Introduction to Data Science
• Module II | Introduction to Computational Organic Chemistry
• Module III | In Silico Description of a Chemical Species
• Module IV | Conceptual Density Functional Theory
• Module V | In Silico Description of a Molecular System
• Module VI | Transition State theory
• Module VII | Artificial Intelligence in Chemistry

Learning outcomes of the learning unit

Upon completion of the course, students will be able to:

• Use computational tools applied to physical organic chemistry
• Use computational chemistry preparation and visualization software (Gaussian, Gaussview, etc.)
• Describe and analyze a reaction in silico
• Understand the fundamental principles of physical organic chemistry
• Rationalize observed mechanisms and selectivities
• Relate theory to a practical case

Prerequisite knowledge and skills

Bachelor or/and Master background in organic chemistry, physical organic chemistry and Quantum Chemistry is necessary. The notions of coding acquired during the years of the Bachelor's degree in chemistry are also recommended.

Planned learning activities and teaching methods

• Interactive lectures, with presentation of the theoretical aspects and recent case studies from the literature (60%)
• Participatory learning, exercises based on a practical case (40%)

Mode of delivery (face to face, distance learning, hybrid learning)

Remote course


Further information:

Remotely via Teams.

E-learning options (exercises, additional resources). 

 

Language of instruction

English

Course materials and recommended or required readings

Platform(s) used for course materials:
- MyULiège

Other site(s) used for course materials
- DOX (https://dox.uliege.be/index.php/s/cF1Og0W1XScnNWT)


Further information:

Platform(s) used for course materials:

• MyULiège

• DOX (https://dox.uliege.be/index.php/s/cF1Og0W1XScnNWT) 

• B. Foresman and A. E. Frisch, Exploring Chemistry with Electronic Structure Methods, 3rd ed., Gaussian, Inc.: Wallingford, CT, 2015.
  ISBN: 978-1-935522-03-4
• Modern Physical Organic Chemistry, E. V. Anslyn, D. A. Dougherty, University Science Books, 2006 (ISBN 978-1-891389-31-3)
• Stereoelectronic effects, A. J. Kirby, Oxford University Press, 1996 (ISBN 978-0-198558-93-4)
• Modern Solvents in Organic Synthesis, P. Knochel (Ed.), Springer, 1999 (ISBN 3-540-66213-8)
• Computational Organic Chemistry, S. T. Bachrach, Wiley, 2014, 2nd ed. (ISBN 978-1118291924)
• Introduction to Machine Learning with Python: A Guide for Data Scientists, A. Müller, S. Guido, O'Reilly Media, 2016, 1rst edition (ISBN 978-1449369415)
• Data Science in Chemistry: Artificial Intelligence, Big Data, Chemometrics and Quantum Computing with Jupyter, T. Gressling, De Gruyter Textbook, 2021, 1rst edition (ISBN 978-3110629392)
• Recent literature (appropriate references will be delivered to illustrate the lectures)

Written work / report


Further information:

There is no exam during the session.

Required work - report

Additional explanations:

Each student regularly enrolled in the course will be asked to study an article from the literature illustrating the use of physical organic chemistry tools to rationalize experimental results. A written report must be submitted during the June session and is expressed on a scale of 20.

 Overall grade

The assessment is weighted as follows:

• an overall presentation of the article (30%)
• a more detailed description of the solution to the problem raised (30%)
• a critical commentary on the approach proposed by the researchers (40%)

Work placement(s)

Nihil

Organisational remarks and main changes to the course

This course will be taught Ein nglish.

Students will receive a list of software to install prior to the course

Contacts

Contacts

• Dr. Pauline Bianchi

• Prof. Jean-Christophe Monbaliu

Association of one or more MOOCs

Items online