MAT ENG 7102 - Computation for Materials Engineering

North Terrace Campus - Semester 2 - 2024

This course provides an introduction to modelling and simulation of materials, covering force-field based atomistic and molecular simulation, and first principle calculation based on quantum mechanics. Students will learn how to use computation as new tools to predict functional material properties. Students will also learn how to design materials and structures from the bottom up - to make lighter, stronger, more efficient, and less expensive materials. In this subject, students will get hands-on training in both the fundamentals and applications of these exciting new methods to key engineering problems, such as energy, optical, and quantum.

  • General Course Information
    Course Details
    Course Code MAT ENG 7102
    Course Computation for Materials Engineering
    Coordinating Unit Materials Engineering
    Term Semester 2
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 6 hours per week
    Available for Study Abroad and Exchange Y
    Assessment Exams, assessments, in-class quiz
    Course Staff

    Course Coordinator: Professor Yan Jiao

    Course Lecturer: Dr Ling Chen
    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:

    1 Demonstrate knowledge of theories for computation, such as force field methods and quantum mechanics
    2 Demonstrate knowledge of modern computation techniques for materials engineering
    3 Understand the capability and limitation of computation techniques for materials engineering
    4 Understand the architecture of high-performance-computing (HPC) facilities
    5 Apply computation techniques to model specific chemical and physical properties of materials for energy, optical, or quantum applications
    6 Apply basic scripting to facilitate and accelerate the modelling of materials
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)

    Attribute 1: Deep discipline knowledge and intellectual breadth

    Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.


    Attribute 2: Creative and critical thinking, and problem solving

    Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.


    Attribute 3: Teamwork and communication skills

    Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.

  • Learning Resources
    Required Resources

    Computational Materials Science - An Introduction, Second Edition, By June Gunn Lee

    Recommended Resources
    Reference Books

    Computer Simulation of Liquids: Second Edition. by Michael P. Allen and Dominic J. Tildesley
    Essentials of Computational Chemistry: Theories and Models 2nd Edition, by Christopher J. Cramer
    Online Learning

  • Learning & Teaching Activities
    Learning & Teaching Modes
    Discussion and hands-on based interactive lectures; problem-solving based practicals.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Activity Contact Hours Workload Hours
    Online Concept Videos 0 24
    Workshop style Lecture 24 30
    Practicals 24 48
    Total 48 102
    Learning Activities Summary
    The following topics will be covered in lectures and practicals:
    Topic 1. Introduction to Computation for Materials Engineering
    Topic 2. High Performance Computing (HPC) basics and operations
    Topic 3. Molecular Dynamics (MD) – theoretical foundation and simulation tools
    Topic 4. Molecular Dynamics (MD) – input files: PSF and PDB
    Topic 5. Molecular Dynamics (MD) – input files: forcefields
    Topic 6. Molecular Dynamics (MD) – build, run and analyse your own models
    Topic 7. Density Functional Theory (DFT) – quantum mechanics basic and software
    Topic 8. Density Functional Theory (DFT) – running VASP with HPC and MedeA
    Topic 9. Density Functional Theory (DFT) – geometry optimization and charge analysis
    Topic 10. Density Functional Theory (DFT) – DOS and band structure
    Topic 11. Density Functional Theory (DFT) – Model a reaction
    Topic 12. Prospective in Computation for Materials Engineering: the application of Machine Learning

    Assignments, reports, and tests will assess the theory and problem solving associated with each of the topics.
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Task Type Due* Weighting Learning Outcome
    Assignments Formative

    Weeks 2-12

    20% 1,2,3
    Projects Formative Weeks 2-12 40% 1,2,4,5,6
    Final Exam Summative 40% 1,2,5,6

    * The specific due date for each assessment task will be available on MyUni.
    Assessment Detail
    Assignment (individual) – 4 assignments based on the theory covered in the lectures.

    Project Report (group or individual) – 4 group report on outcomes of simulation to solve certain problems.

    Final Exam - undertaken during the exam period.
    All assignments and reports will be submitted electronically via MyUni. The exam will occur in class.
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy ( course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

The University of Adelaide is committed to regular reviews of the courses and programs it offers to students. The University of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.