This module will introduce the student to the growing field of computational chemistry and its viability as a cost effective alternative to experiment that provides unique insight. It is critically important that an MChem student is trained in this area because many peer reviewer publications in physical, inorganic and organic chemistry include a computational component. The module will run primarily as a set of computational labs with lectures delivering the understanding, background and application of the methods used in the laboratory sessions including:
Classical Mechanics:
Atomistic Simulation, Force-fields, Energy Minimisation, Molecular Dynamics, Monte Carlo
Quantum Mechanics:
Density Functional Theory, Hartree-Fock theory, Wave-Function mechanics
Simulation Codes:
Examples may include for example: DL_POLY, GULP (classical mechanics), Gaussian, Castep, Dmol (quantum mechanics). The experiments will cover the use of computer modelling to explore the structure, properties, processes and applications of organic and inorganic materials. Typically, they might comprise:
• Simulating the adsorption of molecules on surfaces (catalysis).
• Calculating the density of states and phonon modes of materials (band gap).
• Calculating activation energy barriers of a chemical reaction (organic chemistry).
• Simulating diffusion processes (fuel cells, battery materials).
• Simulating (hard, soft) systems at the mesoscale, such as surfactant-polymer interactions and architectures.
• Quantitative Structure – Activity Relationship (QSAR) models; the application of descriptor calculations and statistical modelling to design new molecules.
• Machine Learning – intelligent computer-aided design of new materials.
Private Study: 92
Contact Hours: 58
Total: 150
Not available as an elective module
• Computational Assessment 1 (3,000 words) – 20%
• Computational Assessment 2 (3,000 words) – 20%
• Poster – 10%
• Examination (3 hours) – 50%
The University is committed to ensuring that core reading materials are in accessible electronic format in line with the Kent Inclusive Practices. The most up to date reading list for each module can be found on the university's reading list pages.
See the library reading list for this module (Canterbury)
On successfully completing the module students will be able to:
1. Provide a critical understanding of the field of computational chemistry.
2. Show how computational chemistry can provide unique insight to complement experimental chemistry.
3. Show how computational chemistry can deliver understanding in areas that are not, thus far, accessible to experiment.
4. Understand methods of computational chemistry in depth, spanning hierarchical length and time scales including: quantum mechanical, molecular dynamics (atomistic), mesoscale modelling and molecular graphics.
5. Use computational methods to calculate the structure, properties and processes of materials.
6. Evaluate computational chemistry critically with regards to scope and limitations.
7. Plan, design and formulate a simulation (or set of simulations) that realise a truly predictive capability.
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