CHEM ENG 7102 - Computation for Materials Engineering
North Terrace Campus - Semester 2 - 2023
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General Course Information
Course Details
Course Code CHEM ENG 7102 Course Computation for Materials Engineering Coordinating Unit School of Chemical Eng and Advanced Materials(Ina) 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: Dr Ling Chen
Course Timetable
The full timetable of all activities for this course can be accessed from .
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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.
1,2,4 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.
3,5,6 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.
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Learning Resources
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. CramerOnline Learning
https://myuni.adelaide.edu.au/enroll/MW9AN9 -
Learning & Teaching Activities
Learning & Teaching Modes
Discussion and hands-on based interactive lectures; problem-solving based practicals.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Activity Contact Hours Workload Hours Lectures 24 48 Practicals 22 44 Total 46 92 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:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- 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.Submission
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 .
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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 (http://www.adelaide.edu.au/policies/101/) 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.
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Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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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鈥檚 disciplinary procedures.
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