Simulation Methods in Chemistry

Module overview

This module builds on the student’s core understanding of the structure of atoms and molecules to predict their behaviour using state-of-the art computational chemistry methods. This will involve learning how quantum chemistry methods can be used to study atoms and molecules and how classical mechanics methods can be used to simulate molecules and biomolecules. These two methodologies are related and we will explore their respective and mutual applications. Emphasis will be placed upon learning how to use these methods for real-life applications.

Syllabus

For force field based simulations, we will cover: 1. Molecular mechanics force fields (functional forms and parameterisation); 2. Energy minimisation techniques (steepest descents and conjugate gradients); 3. Molecular dynamics- theory, scope and limitations; 4. Pros and cons of different Integrators for molecular dynamics; 5. Practicalities of setting up an MD simulation, including equilibration protocols; 6. Extracting the relevant chemical information from your simulations; 7. Enhanced sampling methods, e.g. metadynamics and parallel tempering; 8. Brief introduction into coarse-grain models, scope, limitations; 9. Can we simulate water?; 10. Introduction to Monte Carlo Theory, scope and limitations. Examples of applications; For quantum chemistry calculations, we will cover: 1. Revisiting the Schrödinger equation: can we achieve chemical accuracy? 2. Hamiltonian operators for molecules; 3. The Born-Oppenheimer approximation, a new look at Molecular Orbitals, many-electron wavefunctions; 4. Energies of different electronic configurations; 5. The Hartree-Fock equations, the self-consistent field procedure, exchange energy; 6. Practical details of calculations: Basis functions, matrix form of the Hartree-Fock equations; 7. Gaussian basis sets; 8. How to set up and perform a Hartree-Fock calculation with available software; 9. How to compute molecular properties from your Hartree-Fock calculations; 10. Making your molecules move: geometry optimisation, ab initio molecular dynamics; 11. Connection with spectroscopy: visualising molecular vibrations and computing IR spectra; 12. Electronic correlation. Introduction to more sophisticated methods, in particular Density Functional Theory (DFT) and its variants (exchange-correlation functionals).

Learning and Teaching

Teaching and learning methods

Lectures and workshops

Study time
Type	Hours
Workshops	8
Preparation for scheduled sessions	48
Revision	10
Follow-up work	60
Lecture	24
Total study time	150

Assessment

Summative

This is how we’ll formally assess what you have learned in this module.

Breakdown
Method	Percentage contribution
Final Assessment	50%
Written assignment	50%