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DRPS : Course Catalogue : School of Chemistry : Chemistry

Postgraduate Course: Computational Modelling of Materials (CHEM11047)

Course Outline
SchoolSchool of Chemistry CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate)
Course typeOnline Distance Learning AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryAn online distance-learning course covering key areas of electronic structure theory and classical simulation methods as applied to the modelling of materials and the solid state, building on students' knowledge of quantum and theoretical chemistry and the topics covered in Course 1 electronic structure theory and classical simulation methods.
Course description The course comprises individual lectures and interactive sessions on: QM and MD simulation methods for the solid state and plane wave basis sets for SCF and DFT, Brillouin zones and periodic boundary conditions, electronic properties from solid state calculations, thermodynamic properties and predicting phase transitions, magnetic and spectroscopic properties, multi-scale modelling, and implicit solvation models.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Electronic Structure Theory and Classical Simulation Methods (CHEM11046)
Prohibited Combinations Other requirements At least a 2:1 BSc (Hons) degree or equivalent in chemistry, physics, or other cognate discipline. Formal enrolment only for PG students on the distance learning PG Cert programme. Not available as formal credit-bearing courses to Tier 4 visa students or to other visiting students.

Electronic Structure Theory and Classical Simulation Methods (CHEM11046) is a pre-requisite for the Computational Modelling of Materials course for students enrolled on the PG Certificate programme. However, students wishing to study Computational Modelling of Materials as part of a continuing professional development (CPD) programme may do so without passing the Electronic Structure Theory and Classical Simulation Methods course provided they have relevant previous experience, by permission of the course organiser.
Additional Costs Students must have regular and reliable access to the internet.
Course Delivery Information
Academic year 2015/16, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Please contact the School directly for a breakdown of Learning and Teaching Activities
Assessment (Further Info) Written Exam 25 %, Coursework 75 %, Practical Exam 0 %
Additional Information (Assessment) This course is assessed on the basis of coursework and an 'open-book' online exam. Written Exam 25 %, Coursework 75 %.
Feedback Feedback will be provided through two major channels:

Tutorials: Each of the five course topics will have questions for you to complete prior to an online tutorial where the questions and answers will be discussed. Feedback will also be given when you receive your grade.

Continual assessments: In addition to the tutorial problems, assessments based on the practical use of computational chemistry software and a journal club will be carried out for each topic. Feedback will be given when you receive your grade and there will be opportunity for discussions in the online tutorial.

Towards the end of the course you will also be given the opportunity to provide us with feedback regarding all aspects of the course.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand and describe the theoretical ideas that underpin modern quantum chemistry (electronic structure theory) and classical-based techniques, develop the knowledge and understanding of why and how the techniques were formulated and appreciate how they are used to address materials chemistry problems.
  2. Develop the confidence to apply computational chemistry knowledge to solve materials chemistry problems, understanding the chosen quantum- or classical-based methods and develop the analytical and computing skills, including familiarity with the software, required to do so.
  3. Analyse scientific data to formulate reasoned arguments and be critical of both computational chemistry and experimental techniques.
  4. Use a high-performance computing cluster to generate numerical data to analyse in order to complete written practical assignments.
  5. Be responsible for completing continuous assessment tasks based on the lecture topics and participate in discussions with peers during synchronous online tutorials and critique them in peer assessments.
Reading List
Additional Information
Course URL
Graduate Attributes and Skills 1. Advanced data analysis and processing skills, including using a variety of computational chemistry software.
2. Highly developed written communication skills (continual assessments).
3. Ability to work independently (continual assessments).
4, Advanced computing skills (use of a HPC linux cluster).
Additional Class Delivery Information One of five topics, comprising five video lectures and associated continuous assessments, will be presented per two-week teaching block. Each topic will have an online tutorial.
KeywordsComputational chemistry,materials modelling
Course organiserDr Carole Morrison
Tel: (0131 6)50 4725
Course secretaryDr David Michael Rogers
Tel: (0131 6)50 4830
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