AMME5271: Semester 2, 2020

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Units AMME5271 Semester 2 2020 [Normal day]

Unit of study_

AMME5271: Computational Nanotechnology

Semester 2, 2020 [Normal day] - Camperdown/Darlington, Sydney

Overview

This course introduces atomistic computational techniques used in modern engineering to understand phenomena and predict material properties, behaviour, structure and interactions at nano-scale. The advancement of nanotechnology and manipulation of matter at the molecular level have provided ways for developing new materials with desired properties. The miniaturisation at the nanometre scale requires an understanding of material behaviour which could be much different from that of the bulk. Computational nanotechnology plays a growingly important role in understanding mechanical properties at such a small scale. The aim is to demonstrate how atomistic level simulations can be used to predict the properties of matter under various conditions of load, deformation and flow. The course covers areas mainly related to fluid as well as solid properties, whereas, the methodologies learned can be applied to diverse areas in nanotechnology such as, liquid-solid interfaces, surface engineering, nanorheology, nanotribology and biological systems. This is a course with a modern perspective for engineers who wish to keep abreast with advanced computational tools for material characterisation at the atomic scale.

Unit details and rules

Unit code	AMME5271
Academic unit	Aerospace, Mechanical and Mechatronic
Credit points	6
Prohibitions ?	None
Prerequisites ?	None
Corequisites ?	None
Assumed knowledge ?	Understanding of basic principles of Newtonian mechanics, physics and chemistry, fluid mechanics and solid mechanics.
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Ahmad Jabbarzadeh, ahmad.jabbarzadeh@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Assignment 1 Please check Canvas for description and submission requirements.	20%	Week 04	n/a
Outcomes assessed:
Assignment	Assignment 2 Please check Canvas for description and submission requirements.	20%	Week 07	n/a
Outcomes assessed:
Assignment	Project Please check Canvas for Project description and submission requirements.	50%	Week 12	6 weeks
Outcomes assessed:
Presentation	Presentation/seminar The seminar will report the Major Project results. See Canvas for details.	10%	Week 12	10 minutes
Outcomes assessed:
= group assignment ?

Assessment summary

Assignment 1 20% (week 4)
Assignment 2 20% (week 7)
Major Project 50% (week 12)
Seminar Presentation: 10% (week 12)

Presentation/seminar: In the last week of the course the students should give seminars on the topic of their major project. All the presentations should be in PowerPoint format

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

5% per day including weekend days.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	1. Introduction to modelling and simulation; 2. Continuum and atomic view of matter	Lecture and tutorial (5 hr)
Week 02	1. Deterministic versus stochastic methods; 2. Particle methods, 3. Molecular dynamics algorithms	Lecture and tutorial (5 hr)
Week 03	1. Molecular dynamics algorithms and techniques	Lecture and tutorial (5 hr)
Week 04	Calculating physical properties using statistical mechanics, Temperature, Pressure, rheological properties	Lecture and tutorial (5 hr)
Week 05	Error Analysis, Radial Distribution Function, Calculation of Local Properties, other Potentials, and, Temperature control	Lecture and tutorial (5 hr)
Week 06	Starting Configurations, Energy Minimization, Visualization, NVT and NPT Ensembles	Lecture and tutorial (5 hr)
Week 07	Efficient computations, Parallel Processing	Lecture and tutorial (5 hr)
Week 08	Coarse Graining Methods	Lecture and tutorial (5 hr)
Week 09	Modelling polymers, phase transitions, and nanofluidics	Lecture and tutorial (5 hr)
Week 10	Time dependent phenomena, modeling nano- mechanics- tribological contacts	Lecture and tutorial (5 hr)
Week 11	Practical applications - Case studies	Lecture and tutorial (5 hr)
Week 12	Practical applications - Case studies	Lecture and tutorial (5 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Please see the course eReading on Canvas

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. calculate properties of materials such as simple fluids and polymer melts, solids, explore structure-property relations in various situations
LO2. understand specific processes stated in the aims and goals, and apply it to specific problems
LO3. relate the microscopic state of materials to their macroscopic properties such as stresses, temperature, strain and viscosity. They will learn how to set up simulations of materials and probe their properties, interpret the results from visualised molecular snapshots
LO4. understand basic and advanced theory of molecular dynamics simulation techniques such as force potentials for modelling fluids and solids, statistical analysis and accuracy, and advanced algorithms of high performance computations
LO5. be familiar with available scientific software for computational nanotechnology and will learn how to use software and conduct their projects
LO6. prepare reports and present their findings in a professional manner
LO7. work within a group to conduct research and share work load to achieve common objectives.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

I am pleased with the excellent satisfaction rating and encouraging comments and kind words from the students who participated in this unit. The course has been on Dean’s Commendation list several times. Students cited working with advanced computational systems and software as those they liked most. They also mentioned the challenging aspects of working on their Major Project. I will take your suggestions into account to further improve those components so that the students achieve even better learning experience. In discussions with you, some students expressed a desire to learn more about computational nanotechnology. For those students who want to learn more, I will be happy to discuss possibilities to do honours thesis/Capstone Project/Dissertation on this topic.

Additional information

Please check Canvas site for additional information.

Site visit guidelines

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Work, health and safety

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Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Site visit guidelines

Work, health and safety

Disclaimer

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