The students are introduced to advanced concepts and methods of theoretical chemistry and finally to computer modeling and simulations, including links with various computer algorithms. A key aspect of the course is to allow students to understand the role of the input parameters necessary for the calculations. Some specific issues that are treated in the course are the determination of molecular and bulk properties, of molecular reactivities, as well as aspects of electron correlation.
The students are introduced to advanced concepts and methods of theoretical chemistry and finally to computer modeling and simulations, including links with various computer algorithms. A key aspect of the course is to allow students to understand the role of the input parameters necessary for the calculations. Some specific issues that are treated in the course are the determination of molecular and bulk properties, of molecular reactivities, as well as aspects of electron correlation.
Y. Olivier
Part I :
1. Representations of molecular structures
2. Interaction energy and force fields
3. Potential Energy Surface Sampling
a. Monte Carlo
b. Molecular Dynamics
c. Simulated annealing
d. Entropy and free energy
4. "Soft Computing"
a. Genetic algorithms
b. Artificial neural networks
5. "Comparative modelling"
a. Molecular similarity
b. QSAR
c. Molecular alignments
B. Champagne
Density functional theory
1. Introduction and densities within wavefunctionapproaches
2. The Thomas-Fermi model
3. The Hohenberg and Kohn theorems
4. The Kohn-Sham approach
4.A. Kohn-Sham equation
4.B. XC functionals and their performance for determining geometries, vibrational spectra, optical properties, interaction energies
4.C. Self-Interaction
4.D. Conceptual DFT
Time-Dependent Density functional theory
5.A. TDDFT equations
5.B. Approximate TDDFT schemes
5.C. GW and BSE methods
5.D. Simulating UV/vis absorption and CD spectra
Y. Olivier
Part I :
1. Representations of molecular structures
2. Interaction energy and force fields
3. Introduction to geometry optimization methods
Part II :
1. Introduction to statistical mechanics simulations
a. Background theory (reminder)
b. Monte Carlo
c. Molecular Dynamics
d. Simulated annealing
e. Entropy and free energy
2. "Soft Computing"
a. Genetic algorithms
b. Artificial neural networks
3. "Comparative modelling"
a. Molecular similarity
b. QSAR
c. Molecular alignments
B. Champagne
Density functional theory
1. Introduction and densities within wavefunctionapproaches
2. The Thomas-Fermi model
3. The Hohenberg and Kohn theorems
4. The Kohn-Sham approach
4.A. Kohn-Sham equation
4.B. XC functionals and their performance for determining geometries, vibrational spectra, optical properties, interaction energies
4.C. Self-Interaction
4.D. Conceptual DFT
Time-Dependent Density functional theory
5.A. TDDFT equations
5.B. Approximate TDDFT schemes
5.C. GW and BSE methods
5.D. Simulating UV/vis absorption and CD spectra
For the quantum chemistry part,
1°) 50% for the written report (length: 3 pages/student). The reports will be submitted by November 30th at the latest. The report should include the presentation and critical discussion of the results.
2°) 50% for the written exam (1H of preparation) on the essential aspects of DFT and TDDFT, followed by a oral discussion (Questions will be asked on the methodological DFT and TDDFT aspects as well as on the results of the project).
A. Szabo and N.S. Ostlund, Modern Quantum Chemistry (MacMillan, New York), (1982). R.G. Parr and W. Yang, Density-Functional Theory of Atoms and Molecules, (Oxford University Press, Oxford, 1989). R. McWeeny, Methods of Molecular Quantum Mechanics, (Academic, San Diego, 1992). W. Koch and M.C. Holthausen, A Chemist's Guide to Density Functional Theory, (Wiley-VCH, Weinheim, 2001).
A. Leach Molecular Modelling: Principles and Applications 2nd Edition (Pearson Education (US))