Module CHEM3071: ADVANCED COMPUTATIONAL CHEMISTRY

Department: Chemistry

CHEM3071: ADVANCED COMPUTATIONAL CHEMISTRY

Prerequisites

• Computational Chemistry (CHEM2061).

Corequisites

• Core Chemistry 3 (CHEM3012) OR Chemical Physics 3 (CHEM3411).

Excluded Combination of Modules

• This module may not be taken in the same year of study as Computational Chemical Physics (CHEM3151). This module may not be taken in any combination with Advanced Computational Chemical Physics (CHEM4471).

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

• 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.

• Demonstrate a working knowledge of a range of additional computational chemistry packages and be able to apply this knowledge to tackle real chemical problems.

• Group working, encouraged and developed through workshop teaching and practical classes.
• Written communication advanced 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.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment:

Set work in preparation for workshops.

■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University