CME8129 : Modelling Materials and Processes
- Offered for Year: 2023/24
- Module Leader(s): Dr Adrian Oila
- Lecturer: Dr Jie Zhang
- Owning School: Engineering
- Teaching Location: Newcastle City Campus
Semesters
| Semester 1 Credit Value: | 20 |
| ECTS Credits: | 10.0 |
Aims
The aim of this module is to introduce the practical aspects of the basic methods used in the computational modelling of materials and processes. Both fundamental modelling and data-driven modelling techniques will be introduced.
Outline Of Syllabus
Time-scales and length-scales in materials structure and behaviour.
Interatomic potentials: cohesive energy, pair potentials, determining parameters in potentials.
Electronic structure methods: density functional theories, wave functions, pseudopotentials.
Molecular dynamics: atomic model in MD, embedded atom method, solutions for Newton’s equations of motion.
Multivariate statistical data analysis: linear regression, multiple linear regression, principal component analysis (PCA), principal component regression, ridge regression
Nonlinear regression: polynomial regression, orthogonal least square regression
Machine learning techniques: neural networks, radial basis function networks, extreme learning machines, recurrent neural networks, bootstrap aggregated neural networks, advanced topics in machine learning
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Structured Guided Learning | Lecture materials | 6 | 1:00 | 6:00 | Non-synchronous online |
| Scheduled Learning And Teaching Activities | Lecture | 12 | 1:00 | 12:00 | PiP sessions |
| Guided Independent Study | Assessment preparation and completion | 1 | 84:00 | 84:00 | Assessment preparation and completion |
| Scheduled Learning And Teaching Activities | Small group teaching | 8 | 1:00 | 8:00 | PiP sessions (tutorials). |
| Guided Independent Study | Independent study | 1 | 90:00 | 90:00 | Review lecture notes and recommended texts as appropriate |
| Total | 200:00 |
Teaching Rationale And Relationship
Recorded lectures will be used to introduce the main topics. PiP lectures will be used to deliver material not covered in the recorded lectures and also to revise the content of recorded lectures.
The small group teaching online sessions are supervised activities in which the students apply the knowledge that they gain during lectures and private study to setup and run simulations and to analyse the results.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Prob solv exercises | 1 | M | 50 | Problem Solving Exercise 1 |
| Prob solv exercises | 1 | M | 50 | Problem Solving Exercise 2 |
Formative Assessments
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Computer assessment | 1 | M | Canvas quizzes with feedback throughout the module. |
Assessment Rationale And Relationship
The problem solving exercises provide an appropriate way to assess both theoretical understanding and practical problem solving skills and software skills. It also develops the ability to apply the broad base of scientific principles in conjunction with deeper knowledge and understanding in a specific subject area.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CME8129's Timetable