Skip to main content
 

CHEM4471: ADVANCED COMPUTATIONAL CHEMICAL PHYSICS

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box, and this may change from year to year, due to, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback. Current modules are subject to change in light of the ongoing disruption caused by Covid-19.

Type Open
Level 4
Credits 20
Availability Available in 2024/2025
Module Cap
Location Durham
Department Chemistry

Prerequisites

  • EITHER Computational Chemistry (CHEM2061) OR Computational Chemical Physics (CHEM3151).

Corequisites

  • None.

Excluded Combinations of Modules

  • Advanced Computational Chemistry (CHEM3071).

Aims

  • To develop an advanced understanding of computational chemistry including specialised topics.
  • To provide further practical experience in using computational methods to study molecules.
  • To develop an understanding of important concepts in theoretical chemistry.

Content

  • Molecular simulation.
  • Numerical methods in quantum mechanics.
  • Linear response and an introduction to stochastic dynamics
  • Time dependent quantum mechanics.
  • Density Functional theory.
  • Practical computing.

Learning Outcomes

Subject-specific Knowledge:

  • Explain the concepts of time-dependent linear response.
  • Explain the use of numerical methods in quantum mechanics.
  • Explain the principles and applications of density-functional theory.
  • Understand the strengths and limitations of each technique studied.

Subject-specific Skills:

  • Demonstrate a knowledge of additional computational chemistry packages and be able to apply this knowledge to tackle current chemical research problems.

Key Skills:

  • Group working, encouraged and developed through workshop teaching and the practicals.
  • Analytical scientific writing skills through the use of essay type questions in lecture-support worksheets and the programming assignment.
  • Problem-solving developed through workshops.
  • Practical programming skills.
  • Application of number, acquired through the calculations required in all components of this module.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Lectures are used to convey concepts, demonstrate what is required to be learned and to illustrate the application of theory to practical examples. When appropriate, lectures will be supported by written on-line material, or by information and relevant links on Blackboard Learn Ultra.
  • Private study should be used by students to develop their subject-specific knowledge and self-motivation, through reading textbooks and literature. Students will be able to obtain further help in their studies by approaching their lecturers, either after lectures or at other mutually convenient times.
  • Workshops are where groups of students consider problems and explore common shared difficulties. Problem exercises provide students the chance to develop their theoretical understanding and problem-solving skills. This ensures that students have understood the work and can apply it to real life situations. These are formatively assessed.
  • Student performance will be assessed through examinations. Examinations test students' ability to work under pressure under timed conditions, to prepare for examinations and direct their own programme of revision and learning and develop key time management skills. The examination will provide the means for students to demonstrate the acquisition of subject knowledge and the development of their problem-solving skills.
  • Computer classes give students the opportunity to learn to use off the shelf computer packages and those specific to chemists. They are continuously assessed so that the student can learn from one session to the next.
  • A practical course on programming in the context of computational chemistry with continuously assessed exercises and a final coding assignment.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Lectures171 or 2 per week1 hour17 
Practicals101 per week2 hours20Yes
Workshops31 or 2 per term2 hourh6Yes
Preparation and Reading157 
Total200 

Summative Assessment

Component: ExaminationComponent Weighting: 70%
ElementLength / DurationElement WeightingResit Opportunity
Written examination2 hours100
Component: CourseworkComponent Weighting: 30%
ElementLength / DurationElement WeightingResit Opportunity
Results of continuous assessment 100

Formative Assessment

Set work in preparation for workshops.

More information

If you have a question about Durham's modular degree programmes, please visit our FAQ webpages, Help page or our glossary of terms. If you have a question about modular programmes that is not covered by the FAQ, or a query about the on-line Undergraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.