Module overview
Computational modelling is of increasing importance in chemical engineering as it enables prediction of behaviour over many length and time scales, from molecules, through to the microscopic and mesoscopic scales, and on to the macroscopic scale. This module will cover aspects of molecular modelling, introducing concepts in quantum mechanics, statistical dynamics, and molecular dynamics.
Aims and Objectives
Learning Outcomes
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Design unique chemical engineering simulations to predict thermodynamic behaviour of chemical systems. (Design)
- Evaluate current computational tools and the benefits of a multi-scale approach for chemical engineering problems. (Practice)
- Apply the principles of quantum mechanics to predicting chemical reaction mechanisms. (Breadth)
- Describe the phase behaviour of fluids in terms of intermolecular forces and using the concepts of statistical mechanics. (Depth)
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Aligning advanced computational tools with appropriate chemical engineering problems. (Breadth)
- The underlying concepts and methods required to implement multi-length and multi-time scale models and simulations to chemical engineering problems. (Breadth)
Syllabus
For quantum chemistry calculations, we will cover:
1.The basic concepts of quantum mechanics - 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.Practical Quantum Chemical calculations.
6.Density Functional Theory and levels of accuracy.
7.Making your molecules move: geometry optimisation, ab initio molecular dynamics.
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.
8.Simulation of shear flows.
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.
Type | Hours |
---|---|
Lecture | 20 |
Completion of assessment task | 36 |
Practical classes and workshops | 18 |
Preparation for scheduled sessions | 76 |
Total study time | 150 |
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Exam | 50% |
Written assignment | 50% |
Repeat Information
Repeat type: Internal & External