Outline

Overview

This unit introduces the fundamental principles, types, and real-world applications of smart materials - materials that respond to external stimuli such as temperature, stress, electric or magnetic fields. Students will explore the underlying science of shape memory alloys, piezoelectric/piezoresistive materials, magnetostrictive materials, electro- and magneto-rheological fluids, etc. Students are expected to develop an essential understanding of structure-property relationship of smart materials, as well as their integration into functional systems for practical applications; develop capability to design functional structures using smart materials. The unit provides students with an opportunity to develop both theoretical knowledge and practical skills through a project-based approach.

Unit details and rules

Academic unit	Aerospace, Mechanical and Mechatronic
Credit points	6
Prerequisites ?	(AMME9301 or AMME2301) and (AMME9302 or AMME2302 or AMME1362) or equivalent study at another institution
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	Fundamental knowledge in materials science and engineering: 1) atomic and crystal structures 2) metallurgy 3) structure-property relationship 4) mechanics of engineering materials 5) solid mechanics
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Shuying Wu, shuying.wu@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Presentation	Individual Presentation on Case Study Individual presentation on case study	15%	Multiple weeks	N/A	AI allowed
Outcomes assessed:
Written work	Group Project Report: Lab 1 Piezoresistive Materials Group Project Report: Lab 1 Piezoresistive Materials	15%	Week 07 Due date: 19 Sep 2025 at 23:59	N/A	AI allowed
Outcomes assessed:
Written work	Group Project Report: Lab 2 Piezoelectric Materials Group Project Report: Lab 2 Piezoelectric Materials	15%	Week 08 Due date: 26 Sep 2025 at 23:59	N/A	AI allowed
Outcomes assessed:
Presentation	Group Presentation on Lab 3 & 4 Shape Memory Materials Group Presentation on Lab 3 & 4 Shape Memory Materials	15%	Week 12	N/A	AI allowed
Outcomes assessed:
Portfolio or journal	Lab logbook and raw data record Lab logbook and raw data record: Notes on four lab activities	5%	Week 12 Due date: 31 Oct 2025 at 23:59	N/A	AI allowed
Outcomes assessed:
In-class quiz	In-class quiz In-class quiz: Questions based on lectures (open book)	35%	Week 13	N/A	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

1. Two lab reports for the Lab 1 & 2 activities (Piezoresistive Materials & Piezoelectric Materials): Group reports related to the two lab activities, including attempt to analyze and present the test results, address some questions that may need literature search beyond the lecture notes. Reports must be submitted no later than two weeks after attending laboratory class.

2. Individual Presentation on Case Study: Case study references will be uploaded to Canvas by week 7. Students will review the reference and prepare slides to summarize the novelty, methodology, key findings of the work. This presentation is an individual assessment.

3. Group presentation: This is assessed based on presentation, Q&A performance. The slides are required to be uploaded to Canvas. The presentation is to report the design and characterization results of the shape memory materials (polymer & metal alloy) in Lab 3 & 4.

4.Logbook: this is to train students in maintaining accurate and consistent records of their work and observations.

5.In-class quiz: Quiz is open book and aims to assess students’ understanding of the working principles of the different smart materials and devices. No electronic devices are allowed.

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	Awarded when students demonstrate the learning outcomes for the unit at an exceptional standard.
Distinction	75 - 84	Awarded when students demonstrate the learning outcomes for the unit at a very high standard.
Credit	65 - 74	Awarded when students demonstrate the learning outcomes for the unit at a high standard.
Pass	50 - 64	Awarded when students demonstrate the learning outcomes for the unit at an acceptable standard.
Fail	0 - 49	Awarded when students do not 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.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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:

The Assessment Procedures 2011 provide that any written work submitted after 11:59pm on the due date will be penalised by 5% of the maximum awardable mark for each calendar day after the due date. If the assessment is submitted more than ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Multiple weeks	Non-contact independent work doing research, and working on case study, group meetings and prior readings across multiple weeks	Independent study (90 hr)
Multiple weeks	Lab Work: Piezoresitive sensing, Piezoelectric sensing, Shape memory materials fabricaiton and characterization	Practical (8 hr)
Week 01	Introduction, Resistive Sensing Materials	Lecture (2 hr)
Week 02	Piezoelectric Materials	Lecture (2 hr)
Week 03	Triboelectric Materials	Lecture (2 hr)
Week 04	Magnetostrictive materials and smart fluids	Lecture (2 hr)
Week 05	Shape Memory Materials	Lecture (2 hr)
Week 06	Self-directed learning - group projects	Independent study (4 hr)
Week 07	Fibre Optic Sensors	Lecture (2 hr)
Week 08	Chromogenic Materials	Lecture (2 hr)
Week 09	Case Study Presentations	Presentation (4 hr)
Week 10	Case Study Presentations	Presentation (4 hr)
Week 11	Lecture Review	Lecture (2 hr)
Week 12	Project Work, Group Presentations	Project (4 hr)
Week 13	In-class quiz	Performance (2 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.

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. design and construct simple functional structures using smart materials
LO2. describe and characterise mechanical behaviour of smart materials
LO3. characterise interaction between smart materials and simple structures in actuation and sensing
LO4. describe and characterise unique functions of smart materials using structure-property relationships
LO5. present and demonstrate the functions of smart structures.

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.

Lecture content have been reviewed and revised since this unit was last offered. Moreover, four practical classes have been developed to offer students to gain hands-on experience and consolidate their learning in the classroom.

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

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

MECH5305: Smart Materials

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links