M2 - Theoretical Chemistry and Modeling

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Examples of homogeneous catalysis reactions will be presented, emphasizing the underlying concepts and limitations of theoretical approaches (mainly DFT). Olefin metathesis and examples of polymerization will illustrate supported catalysis, emphasizing the influence of the support.

Various examples will illustrate the specificity of nanocatalysts, distinguishing between the respective roles of electronic and geometric factors.

Hourly volumes:

CM: 20

TD: 10

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The objective is to acquire strong skills in theoretical chemistry by discovering or exploring various topics in depth.

This module is organized in two phases: (i) online seminars, delivered throughout the first semester; (ii) a week of intensive training at the beginning of January, at one of the sites of the South-West cluster of the French Network for Theoretical Chemistry (Bordeaux, Montpellier, Pau, Toulouse).

The topics covered are:

– quantum chemistry and relativity

– Monte Carlo methods

– exploration of potential energy surfaces

– calculation of the electronic structure of periodic systems

– quantum dynamics

– calculation of spectroscopic properties

Hourly volumes:

CM: 40

TD: 20

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This module prepares students for doctoral studies in theoretical chemistry, particularly in the field of quantum chemistry. Recent methodological advances and the development of increasingly powerful software have democratized the use of quantum chemistry software.

The module covers topics in the fields of electronic structure and molecular dynamics. The formalism of the various methods and their areas of application will be explained in detail to enable informed use of theoretical chemistry software, particularly quantum chemistry software.

(1) electronic structure

– Hartree-Fock

– electronic correlation, configuration interaction, coupled cluster

– Density Functional Theory (DFT)

(2) nuclear dynamics

– Classical and ab initio dynamics (Car Parrinello, Born-Oppenheimer, propagators, thermodynamic ensembles, free energy calculation)

– quantum dynamics of photo-induced processes (wave packet, adiabatic and non-adiabatic dynamics, link with the absorption spectrum, diabatic representation, mixed classical-quantum dynamics)

Hourly volumes:

CM: 10

TD: 20

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Present methods for exploring the physical and chemical properties of materials through numerical calculation. Provide the mathematical foundations for the numerical tools presented in the "Modeling" course in the first year of the Master's program and supplement the applications covered in that course.

Hourly volumes:

CM: 28

TD: 12

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During this course, students will learn about the main numerical methods used in scientific software, particularly in theoretical chemistry programs.

Hourly volumes:

CM: 21

TD: 9

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Present methods that enable the physical and chemical properties of materials to be explored through numerical calculation. Provide the mathematical foundations of the associated numerical tools.

I- Introduction

II- Quantum approach: molecular methods: Quantum mechanics, Schrödinger equation, DFT methods.

III- Quantum approach: periodic systems

IV- Molecular dynamics: classical approach

Hourly volumes:

CM: 30

TD: 10

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A 5- to 6-month internship must be completed in a research or research and development laboratory specializing in theoretical chemistry. Students will therefore have the opportunity to complete this end-of-study internship in academic or private research laboratories. Subject to prior approval by the teaching team (internship topic related to the master's program and adequate environment/resources), students may seek a host team in an academic setting at the institutes of the Chemistry Department of the University of Montpellier, in academic laboratories outside the University of Montpellier (in France or abroad), or in the private sector (chemical, pharmaceutical, etc.).

This internship, lasting 5 to 6 months, may begin in mid-January after the exam session and may not exceed 6 months for a period including semester 10 during the validity of university enrollment.

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