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.
Pre-requisites: CHEM2012 AND CHEM2013
Aims and Objectives
Having successfully completed this module you will be able to:
- To develop in students the ability to adapt and apply methodology to the solution of unfamiliar types of problems
- Problems of an unfamiliar nature are tackled with appropriate methodology and taking into account the possible absence of complete data.
- To instil a critical awareness of advances at the forefront of the chemical science discipline
- To prepare students effectively for professional employment or doctoral studies in the chemical sciences;
- Knowledge base extends to a systematic understanding and critical awareness of topics which are informed by the forefront of the discipline
- To extend students' comprehension of key chemical concepts and so provide them with an in-depth understanding of specialised areas of chemistry;
- The ability to adapt and apply methodology to the solution of unfamiliar problems
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. Free energy calculations used in drug design.
9. Brief introduction into coarse-grain models, scope, limitations.
10. Can we simulate water?
11. 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 such as Density Functional Theory (DFT)
Learning and Teaching
Teaching and learning methods
Teaching methods: Lectures, workshops, directed reading, Blackboard online support.
Learning methods: Independent study, student motivated peer group study, student driven tutor support.
|Practical classes and workshops||6|
|Wider reading or practice||60|
|Preparation for scheduled sessions||40|
|Total study time||150|
Resources & Reading list
Frank Jensen (2006). Introduction to computational chemistry. Wiley.
Andrew Leach. Molecular Modelling: Principles and Applications.
Attila Szabo and Neil S. Ostlund. Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory. Dover.
This is how we’ll formally assess what you have learned in this module.
This is how we’ll assess you if you don’t meet the criteria to pass this module.