Advertised Taste of Research areas

Engineering 2nd and 3rd year students can apply for a project in the below advertised research areas.

If you are interested in this topic, please contact the relevant supervisor via email and discuss your interest – please introduce yourself and attach both your CV and transcript in the email.

We strongly encourage you to contact the relevant supervisor before the 11th of November, to give your supervisor and yourself sufficient time to formulate a sound project plan. This is mandatory and must be submitted as part of your application.

007 Bond, De-Bond and Re-Bond Reversible Thermoplastic Adhesives Using Magnetic Particle and Magnetic Induction Heating

School: 
Chemical Engineering
Supervisory Team: 
Dr May Lim (m.lim@unsw.edu.au)
Prof Chun Wang (chun.h.wang@unsw.edu.au)
A. Prof Victoria Timchenko (v.timchenko@unsw.edu.au)
Research Area: 
Advanced Material Engineering

Description of field of research:

Reversible thermoplastic adhesives that can bond, de-bond and re-bond on-demand hold great potential in numerous applications where bonded structures need to be dissembled and reassembled rapidly based on operational demands. It has many useful applications such as emergency repairs, quick attachment and detachment of objects such as sensors, medical devices or prosthesis, the recycling and reuse of costly electronics components, "nail-less" construction materials, as well as modular system that can be readily be dissembled or selectively removed for an upgrade, repair, maintenance or reuse. Think 3M Post-it notes but even more useful!

As a Taste of Research student involved in this project, you will investigate how the performance of thermoplastic adhesives can be enhanced by the inclusion of magnetic particles and contactless magnetic induction heating. You will explore how the properties of the magnetic particles, the magnetic field strength and the type of thermoplastic affects the bonding, de-bonding and re-bonding properties. You will also explore how this technology can be applied to new applications. If you are interested in computational modelling, there is also the option of developing a multi-physic model in COMSOL that can be used to optimise the technology for specific applications.

Research Environment

The Taste of Research Scholar will work with a team of three academics and two postdoctoral researcher. You are welcome to contact Dr May Lim (by email at m.lim@unsw.edu.au or on Microsoft Team) about the research, the research team or for a tour of the laboratory in the new Science and Engineering Building.

Expected Outcomes

As the Taste of Research Scholar involved in this project, you will gain new skills in magnetic materials characterisation and applications, the development of thermoplastic adhesive, as well as written and aural communication skills. The research will give us new insights into how key factors such as magnetic field strength and magnetic particle properties such as type, loading, and concentration affect the heating performance of the thermoplastic adhesive. This will lead to better design and optimisation of the thermoplastic adhesive, especially its bonding and debonding properties.

Reference Material/Links


A Strategy-game Approch to Solving Logic Formulas

School: 
Computer Science and Engineering
Supervisory Team: 
Abdallah Saffidine (a.saffidine@unsw.edu.au)
Research Area: 
Algorithms
Artificial Intelligence
Theory

Description of field of research:

After decades of engineering, Satisfiability (SAT) and Answer Set Programming (ASP) solvers can now address tasks involving millions of variables. However, the expressivity of these modeling tools is limited and Quantified Boolean Formulas (QBF) were proposed in the 1970s as a natural generalization. The performance of QBF solvers lag behind that of SAT/ASP solvers, and researchers in the community are attempting to replicate the success of SAT/ASP in this more general framework. On the other hand, researchers working on strategy games, from Chess to Starcraft via Poker have had resounding successes over the past two decades (Alpha-Go, Deep Blue, etc.). QBF and 2-player strategy games are similar at a theoretical level, yet the connections between the two areas remain unexplored in practice and the methods used for solving the two problems are vastly different. Could the ideas that led to major successes in the strategy-game world be introduced to the world of QBF and bring the technology to industrial strength? The project will investigate this issue, focusing initially on the Proof Number Search (PNS) algorithm.

Research Environment

This topic is investigated as part of a collaboration with Valentin Mayer-Eichberger (TU Berlin, Germany).

Expected Outcomes

By developing and implementing a QBF solver inspired by this game algorithm, the intern/student may develop new optimizations of PNS appropriate for the QBF domain and will contribute to building a bridge between two distinct AI research communities.

Reference Material/Links

  • Akihiro Kishimoto, Mark HM Winands, Martin Müller, and Jahn-Takeshi Saito. “Game-tree search using proof numbers: The first twenty years”. In: Icga Journal 35.3 (2012), pp. 131–156
  • Ankit Shukla, Armin Biere, Luca Pulina, and Martina Seidl. “A Survey on Applications of Quantified Boolean Formulas”. In: 31st International Conference on Tools with Artificial Intelligence (ICTAI). IEEE. 2019, pp. 78–84
  • Valentin Mayer-Eichberger and Abdallah Saffidine. “Positional Games and QBF: The Corrective Encoding”. In: 23rd International Conference on Theory and Applications of Satisfiability Testing (SAT). Alghero, Italy, July 2020

An Adaptive Brain-Robot Fine-grain Controlling System with Low Cost EEG Headset

School: 
Computer Science and Engineering
Supervisory Team: 
Lina Yao (lina.yao@unsw.edu.au)
Chaoran Huang (chaoran.huang@unsw.edu.au)
Research Area: 
Brain Computer Interface
Machine Learning

Description of field of research:

Recent robotics technology advancement extended human reachabilities and boosted productivities, while effective human-robot communication can be critical. On the other hand, preliminary works on Brain-Computer Interface demonstrate propitious results in the potential direct and fast communication pathway, which may be the ultimate solution for human-robot communication. Hence the combination of these two, Brain-controlled robots has emerged and been studied, and in this project, we proposed to utilise low-cost commercial noninvasive and portable electroencephalogram(EEG) headset for fine-grain robot controlling, present an end-to-end brain-controlled robot solution. This can be especially meaningful to healthcare applications for subjects with motor function issues such as neuromotor disorders and trauma to the nervous system, and subjects with disarticulated or amputated residual limbs. Furthermore, such advances can also enhance normal users’ overall experience in ordinary robot operations, with potential smoother, faster and finer control.

Research Environment

The student will work closely with the Data Dynamics team based in CSE K17, UNSW in Kensington. The team is led by A/Prof. Lina Yao, and there are 2 Postdoctoral fellows and 10+ PhD students and research students, with several alumni, which are highly active considerable research outcomes including top-ranked publications in AI and machine learning, grants, and industrial collaborations with both business and governments locally and abroad. The project will mainly be supervised by A/Prof. Lina Yao (https://www.linayao.com/), and jointly supervised by Dr. Chaoran Huang (http://chaoranh.web.cse.unsw.edu.au/), and involve working with running robots and EEG headset. Potential HDR applicants are welcomed. More details can be found on https://insdata.org/

Expected Outcomes

Develop and implement machine learning algorithms for EEG signal processing and human intention recognition with specific purposes (robot controlling); Implement robot control algorithms; Design and implement a live real-life demonstration of appliable scenario; The publication of high-quality outcomes can be possible while optional.

Reference Material/Links


Analysis of Nanoparticles for Remediation of Contaminated Lands

School: 
Civil and Environmental Engineering
Supervisory Team: 
Denis O'Carroll (d.ocarroll@unsw.edu.au)
Adele Jones (adele.jones1@unsw.edu.au)
Research Area: 
Environmental Engineering

Description of field of research:

Groundwater is of immense importance for personal and industrial use in Australia and throughout the world as such protection of this resource is essential to the health and well-being of Australians. Historically, the subsurface was thought to act as a natural filter of wastes injected into the ground. The potential for these wastes to persist in the subsurface for decades, potentially contaminating drinking water sources was ignored. Non-aqueous phase liquids (NAPLs), such as perchlorethlyene, are one class of waste liquids that were subject to improper disposal practices. These liquids are extremely difficult to remove from subsurface aquifers and are the focus of this project. Nanoparticles are one promising innovative groundwater remediation technology that convert these contaminants into less toxic or nontoxic materials. They are particularly useful because of their size — a single human hair is 500 to 5,000 times as wide. At that scale, they can move through microscopic flow channels in soil and rock, reaching and destroying groundwater pollutants that larger particles cannot. In this study nanoparticles will developed to degrade subsurface NAPL source zones. This project will involve an integrated nanoparticle synthesis, characterization, reactivity and mobility approach. Established connections with industrial will facilitate direct application of this work to actual sites. Although nanoparticles may represent a novel approach for the remediation of subsurface contaminated sites significant research is necessary to develop this technology. This technology has the potential to revolutionize contaminated site remediation by significantly reducing costs and increasing efficiency.

Research Environment

You would join a team of 10.

Expected Outcomes

There are many possible outcomes from this project, including interactions with industry partners, development of data for an honour's thesis, presentation of data at an international conference and publication of the study in a peer reviewed journal.

Reference Material/Links

Please see Professor O'Carroll's 2013 journal paper in Advances in Water Resources for more information on the use of nanometals.


Automatically Creating NP-completeness Reductions

School: 
Computer Science and Engineering
Supervisory Team: 
Abdallah Saffidine (a.saffidine@unsw.edu.au)
Serge Gaspers (serge.gaspers@unsw.edu.au)
Research Area: 
Algorithms
Artificial Intelligence
Theory

Description of field of research:

The field of computational complexity studies how to build efficient algorithms as well as what makes some tasks fundamentally harder to achieve than others. This field is also host to one of the most famous computer science question, P vs. NP. Two important notions of computational complexity are that of decision problems and reductions between problems.

The objective of this project is to develop Artificial Intelligence techniques to automaticaly synthesize existing and new reductions between problems.

Research Environment

This topic is investigated as part of a collaboration with a small team of UNSW/USYD colleagues and students (6–8).

Expected Outcomes

The student/intern will first investigate how to synthesize reduction between bounded-size instances of problems, then examine approaches to abstract the discovered reductions to the general case.

Reference Material/Links

  • Charles Jordan and Lukasz Kaiser. “Experiments with reduction finding”. In: International Conference on Theory and Applications of Satisfiability Testing. Springer. 2013, pp. 192–207"

Bubble Coalescence in Non-ionic Surfactant Solutions in the Presence of Salt

School: 
Minerals and Energy Resources Engineering
Supervisory Team: 
Ghislain Bournival (g.bournival@unsw.edu.au)
Research Area: 
Mineral Processing

Description of field of research:

Froth flotation is the most used process in the mineral processing industry for concentrating minerals. It is fundamentally used to separate valuable particles from unwanted gangue. Valuable particles, which are rendered hydrophobic with the use of chemical reagents, attach to bubbles and rise to the surface to form the froth phase. The resistance of the bubble to coalescence is important in order to maximise the recovery of valuable particles and is in part controlled by the frother. Increasingly stringent regulations on water released from mineral processing plants incite the recycling of water which accumulates inorganic electrolytes. This project will focus on the effect of frothers to delay bubble coalescence in the presence of inorganic electrolytes. This work is an extension of industrial work already being performed.

Research Environment

The student will be working in the School of Mineral and Energy Resources Engineering laboratory. The research facility required to conduct this project is in place. The student will be well-supported whilst working under the guidance of the School’s academic staff, Dr Ghislain Bournival (and A/Prof Seher Ata). The experimental set-up and technique have been previously used and have already led to a number of publications.

Novelty and Contribution

Bubble stability is crucial for the efficiency of the flotation process. This project aims to further our understanding of the effect of water quality on the effectiveness of frothers in stabilising bubbles.

Student Benefits

The student will be exposed to a high-quality research environment, in which experience in research methodology, data analysis and report writing can be gained. Froth flotation being so prevalent in the mining industry, an in-depth knowledge of this process is an advantage when seeking employment in the mineral processing industry.

Expected Outcomes

It is expected that the results from this project will contribute or lead to a journal publication.

Reference Material/Links

  • Ata, S., 2008. Coalescence of bubbles covered by particles. Langmuir, 24(12), 6085-6091.
  • Bournival, G., Pugh, R.J., Ata, S., 2012. Examination of NaCl and MIBC as bubble coalescence inhibitor in relation to froth flotation. Minerals Engineering, 25(1), 47-53.
  • Bournival, G., Ata, S., Karakashev, S.I., Jameson, G.J., 2014. An investigation of bubble coalescence and post-rupture oscillation in non-ionic surfactant solutions using high-speed cinematography. Journal of Colloid and Interface Science, 414, 50-58.
  • Bournival, G., Muin, S.R., Lambert, N., Ata, S., 2017. Characterisation of frother properties in coal preparation process water. Minerals Engineering, 110, 47-56.

Carbon-based catalysts for electrochemical H2O2 generation

School: 
Chemical Engineering
Supervisory Team: 
Zhaojun Han (zhaojun.han@unsw.edu.au)
Xunyu Lu (xunyu.lu@unsw.edu.au)
Research Area: 
Energy

Description of field of research:

Low-cost and efficient catalysts for on-site production of valuable chemicals, such as H2O2, is of great interest in chemical industry. In this project, carbon-based catalysts, particularly vertical graphene, will be implemented for electrochemical H2O2 production at high efficiency and selectivity. Vertical graphene shows unique structure of graphene nanosheets oriented perpendicularly to the substrate surface. Compared to random graphene nanoflakes, vertical graphene possesses advantageous features of large surface area, interconnected porosity, mechanical rigidity and electrochemically active edges. The project will investigate a number of structural factors in vertical graphene, such as surface wettability and functional groups, to achieve the optimised H2O2 production performance.

Research Environment

The student will have the opportunity to work in a highly prolific team in the PartCat Research Group at School of Chemical Engineering, under the guidance of Dr Zhaojun Han and Dr Xunyu Lu. He/she will also have the opportunity to interact with Sci. Prof. Rose Amal, director of the PartCat Research Group. In addition, the student could work with CSRIO, Australia’s national research agency, and have access to industry-focused research environment.

Expected Outcomes

The student is expected to i) understand the electrochemical route of producing H2O2; ii) understand the role of vertical graphene in the catalytical process; iii) obtain hands-on experience in preparing the catalysts and setting up the electrochemical reaction cell; and iv) gain knowledge in evaluating the electrochemical performance of catalysts for H2O2 production.

Reference Material/Links

  • Zhang, Q.; Tan, X.; Bedford, N. M.; Han, Z.; Thomsen, L.; Smith, S.; Amal, R.; Lu, X., Direct insights into the role of epoxy groups on cobalt sites for acidic H2O2 production. Nat. Comm. 2020, 11, 4181.
  • Roman, D. S.; Krishnamurthy, D.; Garg, R.; Hafiz, H.; Lamparski, M.; Nuhfer, N. T.; Meunier, V.; Viswanathan, V.; Cohen-Karni, T., Engineering Three-Dimensional (3D) Out-of-Plane Graphene Edge Sites for Highly Selective Two-Electron Oxygen Reduction Electrocatalysis. ACS Catal. 2020, 10, 1993.

Characterisation of Oxide Quality for Silicon Quantum Dot Devices

School: 
Electrical Engineering and Telecommunications
Supervisory Team: 
Andrew Dzurak (a.dzurak@unsw.edu.au)
Wee Han Lim (wee.lim@unsw.edu.au)
Research Area: 
Quantum Computing

Description of field of research:

Due to their similarity to conventional CMOS devices and their ability to leverage existing industrial technology and know-how, quantum dot devices in silicon hold immense potential for the realisation of full-scale quantum computers. In these MOS quantum devices, the quantum dots are formed by accumulating carriers against the Si/SiO2 interface, and therefore the properties of this interface can influence the behaviour of the quantum dots. This project aims to further our understanding of the properties of the oxide interface, which is critical to the development of these MOS devices.

Research Environment

The research group is lead by Prof Andrew Dzurak and includes 8 postdoctoral staff and faculty collaborators and 11 PhD students.

Expected Outcomes

The student will measure Hall effect devices in cryogenic test setups to determine properties of the interface, such as the mobility and carrier density in order to extract oxide parameters relevant to quantum device operation.

Reference Material/Links

Relevant journal articles for this project include:

 


Cryogenic Electronics for Quantum Computing

School: 
Electrical Engineering and Telecommunications
Supervisory Team: 
Andrea Morello (a.morello@unsw.edu.au)
Research Area: 
Quantum Engineering

Description of field of research:

The research pertains the testing, operation and characterisation of an amplifier chain designed to operate at cryogenic (below 1 kelvin) temperatures, and used for the real-time readout of solid-state quantum bits. The student will design and perform measurements to extract the noise performance of the amplifiers, and to estimate its fidelity and speed for reading out quantum bits.

Research Environment

The team comprises 6 PhD students and 4 postdoctoral fellows. The main contact will be the supervisor (Prof Andrea Morello), but day-to-day supervision will be provided by some of the PhD students directly involved in the readout of solid-state qubits.

Expected Outcomes

The expected outcome is the full calibration and operation of the first 3-MHz cryogenic lock-in amplifier, capable of reading out quantum information in 1 microsecond with high fidelity.

Reference Material/Links

Relevant papers and background material will be provided to the successful applicant.


Developing Automated Speech Annotation Methods

School: 
Electrical Engineering and Telecommunications
Supervisory Team: 
Beena Ahmed (beena.ahmed@unsw.edu.au)
Mostafa Shahin (m.shahin@unsw.edu.au)
Research Area: 
Digital Signal Processing

Description of field of research:

Recent advances in speech science mean that applications of automatic speech recognition (ASR) have become essential attributes of mainstream mobile devices and consumer electronics. Voice assistants and speech biometrics all developed from large speech corpora, are now commonplace. Despite this progress, work on ASR for those with non-standard speech, i.e. children and people with speaking difficulties, is sadly lagging behind. The lack of progress made in applications for children and people with speaking difficulties can be attributed to the poor accuracy of ASR systems for this substantive group. As current ASR systems are trained with large amounts of adult speech, when they are used on children’s speech, the accuracies of ASR are so disturbingly low as to be practically unusable. The limited number of large, databases of children’s speech available internationally has hindered research on systems for children. UNSW is thus leading a team of universities across the country in a project, AusKidTalk, to collect an annotated database of Australian children’s speech large enough to train ASR algorithms specific to children. In this project, you will be applying signal processing techniques and machine learning methods to develop automated tools to speed up the annotation of the collected speech recordings for use in the development of ASR based tools for children.

Research Environment

Main contact: Beena Ahmed; Team of 5 researchers

Expected Outcomes

The development and testing of code that 1) analyses the speech recordings to identify noisy parts or parts where someone else other than the child is talking 2) segments the recordings into child only sections and 3) divides the child only segments on word and sound level for ASR development.

Reference Material/Links

  • M. Shahin, U. Zafar and B. Ahmed, "The Automatic Detection of Speech Disorders in Children: Challenges, Opportunities, and Preliminary Results," in IEEE Journal of Selected Topics in Signal Processing, vol. 14, no. 2, pp. 400-412, Feb. 2020 https://ieeexplore.ieee.org/document/8931568

Development of Advanced Oxidation Processes for Contaminant REmoval and Resource Recovery in Wastewater Treatment

School: 
Civil and Environmental Engineering
Supervisory Team: 
Scientia Professor David Waite (d.waite@unsw.edu.au)
Dr Jinxing Ma (jinxing.ma@unsw.edu.au)
Research Area: 
Environmental Engineering

Description of field of research:

Advanced Oxidation Processes (AOP) including catalytic ozonation and anodic oxidation are being increasingly used in water and wastewater treatment for removal of contaminants and recovery of valuable resources. We are offering a number of scholarships in this area with emphasis in 1) design and testing of new catalysts for enhancing ozonation, 2) developing improved electrodes for anodic oxidation and cathodic reduction purposes, and 3) utilising computational fluid dynamics tools to improve AOP reactor design.

Research Environment

Professor Waite's team involves around 25 research staff, higher degree research and Honours students. The ToR students will work closely with a small team undertaking R&D in a related area.

Expected Outcomes

ToR students will be expected to contribute to experimental and computational studies related to advancing AOP technologies. The results of these studies would be expected to lead to publications and/or patents. Some interaction with industry partners can be expected.

Reference Material/Links

  • Xie, J., Ma, J.X., Zhang, C.Y., Kong, X., Wang, Z. and Waite, T.D. (2020). Effect of the presence of carbon in Ti4O7 electrodes on anodic oxidation of contaminants. Environmental Science and Technology (in press, accepted February 2020).
  • Yuan, Y., Xing, G.W., Garg, S., Ma, J.X., Kong, X., Dai, P. and Waite, T.D. (2020). Mechanistic insights into the catalytic ozonation process using iron oxide-impregnated activated carbon. Water Research (in press, accepted April 2020).
  • Song, Z., Garg, S., Ma, J.X. and and Waite, T.D. (2020). Selective arsenic removal from groundwaters using redox active polyvinylferrocene functionalized electrodes: role of oxygen. Environmental Science and Technology (in press, accepted September 2020).
  • Liu, J.Y., Ma, J.X., Dai, R.B., Wang, X., Chen, M., Waite, T.D. and Wang, Z.W. (2020). Self-catalytic decomplexation of Cu-organic complexes and Cu recovery from wastewaters using an electrochemical membrane filtration system. Environmental Science and Technology (in press, accepted October 2020).

Electrocatalysis of Biomass: Toward Sustainable H2 Hydrocarbon Generation

School: 
Chemical Engineering
Supervisory Team: 
Nicholas Bedford (n.bedford@unsw.edu.au)
Research Area: 
Sustainable Energy/Materials

Description of field of research:

The ability to generate fuels and commodity chemicals from renewable feedstocks is an ever-pressing global issue. At present, the building blocks of most fuels and products can be traced back to fossil fuels, a non-renewable resource that is plagued with various environmental issues. Biomass, broadly defined as natural occurring organic matter, is inherently renewable and could supplement and eventually replace fossil fuels as the world’s atomic feedstock with increased research efforts. One current bottleneck in biomass conversion technology is the inability to efficiently convert biomass compounds into molecules of industrial value/relevance. While thermal catalysis routes have been studied for decades, more recently researchers have implemented electrocatalysis as a means to improve reaction selectivity while simultaneously reducing the energy input.

This ToR project will be focused on the evaluation of novel nanocatalysts for the conversion of relevant biomass compounds into commodity chemicals and/or fuels using electrocatalytic methods. The student will participate in catalyst synthesis and catalyst evaluation in conjunction with graduate students and researchers. Over the course of the summer, the student will gain valuable chemistry skills often missing in ChemEng lab classes while providing insights into academic research.

Research Environment

Dr Bedford's immediate research group consist of 7 graduate students. In addition, we have additional graduate students from the Particle and Catalysis Research Laboratory (PartCat) that can provide valuable guidance to the project as well.

Expected Outcomes

Working in conjunction with PhD students, we expect the outcomes from the ToR project to help support our research direction in understanding and improving nanocatalysts for biomass electro-reactions. If successful, we anticipate the student contributing to academic publication.

Reference Material/Links


Electrostatic Modelling of Silicon Qubit Devices

School: 
Electrical Engineering and Telecommunications
Supervisory Team: 
Chris Escott (c.escott@unsw.edu.au)
Andre Saraiva (a.saraiva@unsw.edu.au)
Research Area: 
Quantum Computing

Description of field of research:

Adapting industrial CMOS technology to silicon-CMOS quantum dot qubit device fabrication is a promising road towards full-scale quantum computers. Devices currently used for successful demonstration of 1- and 2-qubit gates possess strong similarities to conventional CMOS devices, by making use of biasing gates to accumulate electrons at the Si/SiO2 interface. Understanding the influence of the electrode/gate geometry and the biasing configuration in many-electrode devices is paramount to further improvements in device design and control.

Research Environment

The research group is lead by Prof Andrew Dzurak and includes 8 postdoctoral staff and faculty collaborators and 11 PhD students.

Expected Outcomes

This project will require the student to simulate the electrostatics of silicon quantum dot devices to capture the influence of biasing, design, cryogenic operation and real-world imperfections. The simulations will be performed with a mix of industry standard and bespoke tools to accurately describe the behaviour of the quantum dot devices.

Reference Material/Links

Relevant journal articles for this project include:

 


Enzyme-based Nanomaterials for Applications in Drug Delivery and as Molecular Machines

School: 
Chemical Engineering
Supervisory Team: 
Peter Wich (p.wich@unsw.edu.au)
Ziqing Wang (ziqing.wang2@unsw.edu.au)
Research Area: 
Biopolymers, Bioorganic Chemistry, Nanomaterials, Drug Delivery, Nanoparticles, Catalysis, Nanomedicine

Description of field of research:

Natures biopolymers represent interesting materials for the development of drug delivery systems and functional molecular machines. They are readily accessible, can be obtained in high quantity and trigger in most cases only a low reaction of the immune system. Especially proteins have favourable properties as structurally well-defined biopolymers for the formation of nanoparticles. They can have advantages over synthetic polymers when looking at specific areas like biodegradability, non-antigenicity, stability or toxicity. Because of these unique properties, protein-based carriers are promising candidates for multifunctional nanomaterials, for example for the delivery of therapeutic drugs.

The Taste of Research project will focus on the preparation of enzyme-based nanomaterials, featuring a novel concept for the formation based on the assembly of surface-modified proteins. This special method allows the use of solvent evaporation techniques for the formation of stable nanoparticles and can be universally applied to various proteins and enzymes. As part of this preparation method various payloads, like small molecular drugs, proteins or genetic material will be encapsulated in the particles.

This new biotechnological approach has the potential to be universally applied to various proteins and enzymes. Therefore, the project opens the opportunity for the preparation of multifunctional nanosystems and molecular machines, where the function and structure of the particle material itself might be as important as the transported payload.

Key techniques: (the project can be adjusted based on interest and experience) organic chemistry, bioconjugation methods, biotechnological techniques, nanoparticle preparation, enzyme assays

Research Environment

The successful candidate will work in a highly interdisciplinary and world-leading research environment. Our research labs are currently run by 5 fulltime PhD students and are fully equipped for the above-mentioned research project. We are part of the Centre for Advanced Macromolecular Design (CAMD, www.camd.unsw.edu.au) and the Australian Center for NanoMedicine (ACN, www.acn.unsw.edu.au).

We are looking for creative and highly motivated candidates who enjoy science and are excited about new challenges. Ideally, you are currently studying in one of these areas: (bio)organic chemistry, chemical engineering, material/polymer science, nano-technology (but also, all neighbouring fields would be ok). Don't worry, no specific pre-knowledge is necessary. As long as you are enthusiastic about science and willing to learn, you are a good match! Don't hesitate to get in touch with us if you have any questions

Expected Outcomes

As ToR student, you have the unique chance to work on a state-of-the-art research project and make a valuable contribution in the development of novel drug delivery systems, with the potential of future applications in therapeutic settings.

As part of having a taste of research, you will learn about all aspects of a research project, which will prepare you well for a future career in industry or as postgraduate researcher. You will learn the process of project design, information search, material synthesis and characterization, in addition to gaining valuable aspects of science communication and the work in an interdisciplinary team.

We highly value the work and contribution of all our team members, hence, the potential to be listed as a co-author in a peer-reviewed publication is high.

Reference Material/Links

  • Nanoparticle Assembly of Surface-Modified Proteins M. Fach, L. Radi, P. R. Wich, J. Am. Chem. Soc. 2016, 138 (45), 14820-14823.
  • "Protein" Based Nanoparticles for the Delivery of Enzymes with Antibacterial Activity E. Steiert, L. Radi, M. Fach, P. R. Wich, Macromol. Rapid Commun. 2018, 39,1800186 (DOI: 10.1002/marc.201800186)
  • "pH-Responsive protein nanoparticles via conjugation of degradable PEG to the surface of cytochrome c" E. Steiert, J. Ewald, A. Wagner, U. A. Hellmich, H. Frey and P. R. Wich
  • Polym. Chem., 2020, 11, 551 - 559 (DOI: 10.1039/C9PY01162E)

For further information about us and our research interests, please visit:

Contact: p.wich@unsw.edu.au
Science and Engineering Building, E8, Room 321


Fatigue Behaviour of Additive Manufactured AlSi10Mg

School: 
Mechanical and Manufacturing Engineering
Supervisory Team: 
Bernd Gludovatz (b.gludovatz@unsw.edu.au)
Research Area: 
Mechanical Properties of Advanced Structural Materials

Description of field of research:

Low density and easy malleability make aluminium alloys important materials for use in engineering applications. Pure Al has low strength; however, small additions of alloying elements can significantly strengthen the material. One alloy system that utilizes strengthening mechanisms in Al is Al-Si-Mg. In conventional manufacturing processes, alloys of this system are produced through die-casting followed by a heat treatment which can increase their strength up to 3-times. Additionally, their excellent weldability characteristics makes them ideal candidates for use in additive manufacturing (AM) applications.

AM is a processing technique to fabricate parts using a layer-by-layer build-up method. The common principle is to melt individual layers of powder locally followed by their rapid solidification. In recent years, industries in the fields of automotive, aerospace, the medical device industry have started to explore and utilize the technology extensively. The main concern that arises in AM-products is their reliability when compared to conventionally manufacturing products which is generally associated with the significantly different microstructures that result from the unconventional fabrication approach. This has a major influence on their mechanical properties. For example, due to their often somewhat increased porosity together with residual stresses, many AM-products have a higher tendency to fail prematurely under cyclic loading. Understanding the effect of crack propagation behaviour on AM parts is therefore vital to ensure sufficient and reliable lifetime of components in service.

Research Environment

The supervisor of the project, Dr. Bernd Gludovatz, was educated at the University of Leoben, Austria, where he received his M.S. and Ph.D., both in Materials Science and Engineering. Subsequently he was working as post-doctoral fellow at the Lawrence Berkeley National Laboratory in the US before joining UNSW as a Senior Lecturer of Mechanical and Manufacturing Engineering in 2017.

Dr. Gludovatz's team has currently four PhD students and one thesis student which are all working on the mechanical behaviour of structural materials. One PhD student, Moses James Paul, who is working on the same additive manufactured AlSi10Mg alloy, will be directly involved in supervision, guidance and training of the ToR student. He has extensive experience with the material and the characterization techniques.

Expected Outcomes

  • Understanding fatigue crack propagation behaviour in additive manufactured AlSi10Mg alloys and correlating micro- and meso-structure of various processing conditions with mechanical performance.
  • Evaluating the effect of processing parameters on the change in anisotropy behaviour of fatigue crack growth rate in AM AlSi10Mg materials. To achieve the above-mentioned outcomes, AlSi10Mg alloys with different built rates will be fabricated and the fatigue properties will be characterized using a servo-hydraulic Instron 8872 testing equipment in accordance with ASTM standard E647 in two different crack growth directions, i.e., parallel and perpendicular to the built direction. Results will be analysed and discussed in terms of suitability of parts for use in structural applications. "

Reference Material/Links

Key literature related to the project can be found below:

Note: A more extensive literature survey is required to get a comprehensive picture of current work on this topic.


Impact of Social Media Networks on COVID-19 Containment or Expansion

School: 
Computer Science and Engineering
Supervisory Team: 
Dr. Rahat Masood (rahat.masood@unsw.edu.au)
Dr. Muhammad Ikram (muhammad.ikram@mq.edu.au)
Research Area: 
Cyber Security
Data Privacy and Security

Description of field of research:

This research project intends to analyse COVID-19 twitter dataset with the purpose of understanding the relationship between tweets (and the metadata such as hashtags) and the containment/spread of a disease. There will be multiple perspective that we will investigate mainly including geolocation analysis, sentiment analysis, tweets utility analysis, temporal analysis on the spread or containment of disease in multiple countries, effect of tweets in the containment of disease and many more. In addition, we aim to uncover the trends or patterns between these perspectives; for-example, we will analyse if the high sentiment analysis from tweets is directly proportional to the geolocation i.e. a country with high infection rate may have more emotional comments than a country with less infection rate. Similarly, we want to analyse if a tweet requesting people to stay at home is well received by the community or not and then we can take an extra measurement to investigate if community with high negative response have high infection rate or not. In summary, twitter dataset will help us analyse people behaviour/responses towards COVID-19, countries infection rate w.r.t time, and to conclude if tweets from the social platforms like twitter may be used by agencies for better containment of a disease.

To perform such analysis, we will extract information such as like, follow, retweets, hashtags, comments, posts, tweet ids, geo-location, and datetime using twitter ids provided by Panacealab. We will also use various supervised machine learning techniques with the amalgamation of natural language processing tools (NLTK).

Research Environment

This topic will be a joint project with CSE and Macquarie University, Department of Computing. Dr. Muhammad Ikram from Macquarie University has expertise in collecting/crawling and analyzing the Internet data. His experiences with Internet measurement will help in identifying critical trends and producing key findings from the data. Hence, this project will also provide an opportunity to a student to get a taste of research from two different academic institute and learn ways to conduct research for real applications. Regular meetings are expected throughout the project.

Expected Outcomes

From this project, student with the help of supervisors are expected to:

  • Collect/Crawl COVID-19 twitter dataset using Twitter API service.
  • Analyze the data from various perspectives as mentioned in project description.
  • Produce critical findings and document in the form of research paper

Reference Material/Links


Implementing microarchitectural timing channel attacks and evaluation infrastructure for RISC-V processors

School: 
Computer Science and Engineering
Supervisory Team: 
Sri Parameswaran (sri.parameswaran@unsw.edu.au)
Tuo Li (tuoli@unsw.edu.au)
Research Area: 
Computer Security and Architecture

Description of field of research:

Microarchitectural timing attack is a notorious security threat in modern processors. The advanced examples are the recent Spectre and Meltdown attacks in Intel processors.

In this project, we aim to create the timing channel attacks to understand the vulnerabilities for a range of microarchitectural components (such as instruction cache, data cache, translation lookaside buffer, and branch predictors) in a modern RISC-V processor with a real-world operating system. The implementation will involve both software and hardware development. Software development in this project will create attacks (a range of attacks can be ported from existing research and open-source community) and a set of testbenches to mount the attacks. Hardware development is optional and aims to provide architectural support for monitoring the microarchitectural events during attacks, which involves adding special performance counters and hardware assertions into the processor.

Research Environment

This research will be performed in embedded system group. This project will involve one ToR student, Prof. Sri Parameswaran (main contact), and a postdoctoral researcher, Dr. Tuo Li.

Expected Outcomes

First, a novel benchmarking and demo tool set for microarchitectural timing channel attacks for RISC-V processors. Second, new processor hardware extension for tracing and analyzing the microarchitectural timing attacks. Third, the knowledge of the relationship between microarchitectural events and the software procedures in the attacks.

Reference Material/Links


Improving the Functional Properties of Plant-based Food Products

School: 
Chemical Engineering
Supervisory Team: 
Cordelia Selomulya (cordelia.selomulya@unsw.edu.au)
Yong Wang (yong.wang2@unsw.edu.au)
Research Area: 
Food Engineering, Process and Products

Description of field of research:

Three industry research projects are available with the aim to improve the properties of a range of products including gluten-free cereal and plant-based milk products from a major food manufacturer. The objectives will be achieved by developing a comprehensive understanding of the effects of processing parameters on desired product properties. Expected outcomes include extending the shelf life of gluten-free cereal, a new protocol to quantitatively assess the functionality of plant-based milk, and potentially a better formulation for fortified plant-based milk.

Research Environment

The projects will be conducted at the company's R&D site at Central Coast, and at the School of Chemical Engineering, UNSW Sydney. Successful candidates must be willing to potentially relocate to the site during the course of the projects (accommodation will be provided). The projects will run for 12 weeks full time (successful candidates may need to defer T1, 2021). The projects provides unique opportunity with a blend of industry based research as well as university research environment.

Expected Outcomes

The projects will provide useful knowledge to improve the manufacturing process and product formulation for existing commercial products that are currently being distributed in retail and food service.

Successful completion will lead to a better understanding of parameters and processing conditions to improve shelf life, stability, and functionality of these products. Outcomes include a new protocol for quality control on site, and potentially a new formulation for fortified plant-based milk products.

Reference Material/Links

The projects will suit students with strong interest in food engineering, food chemistry, analytical chemistry, and equipment / plant design.


Industry scale-up and process optimisation of antimicrobial nanosurface for medical devices

School: 
Chemical Engineering
Supervisory Team: 
Sarah Grundy (s.grundy@unsw.edu.au)
Jason Scott (jason.scott@unsw.edu.au)
Toby Brown
Research Area: 
Advanced Materials and Process Optimisation

Description of field of research:

Whilst medical devices such as hip and knee joint replacements are transformative for people with chronic diseases, 1% - 2% of implanted devices become infected, including approximately 30,000 of the 2 million hip and knee joint replacements that are implanted each year. These implant infections represent an enormous burden on national health budgets and are associated with significant morbidity and mortality for the patient. Corin has developed an antimicrobial nanosurface that shows significant potential to dramatically reduce the incidence of implant infection.

The main outcome of the project is focussed on: Investigation into how varying process operating parameters (process inputs includes raw material selection, pre and post treatment steps and surface coating) in combination may affect the resulting oxidised layer on the substrate surface (process outputs – the physical dimensions, mechanical properties and surface chemistry of processed substrate surfaces). Thus, theoretical relationships between the various post-treatment process/es and operating parameters as the process is scaled, should be derived.

Research Environment

This project will be carried out in laboratories at UNSW and in the offices of Corin Australia at Pymble. The Taste of Research Scholar will work under the direct supervision of James Morel (post graduate), Dr Sarah Grundy, A/Professor Jason Scott, Professor Rose Amal and Dr Toby Brown (Corin). A great opportunity to work on an independent project but also be part of an industry and university research (PARTCAT) team. This project provides unique opportunity with a blend of industry based research as well as traditional university research environment.

Expected Outcomes

Successful completion of the project will lead to better understanding of operation conditions which can be scaled up, thus providing a vital step along the pathway to implementing this process in a medical device manufacturing process. Student will gain experience in material engineering, reaction engineering and simulation, a medical implant design and manufacturing environment and co-authorship of any scientific paper that emerge from the research.

Reference Material/Links

This project will suit a student with strong interest in material engineering, reaction engineering simulation and equipment / plant design. Read more about the technology for antimicrobial surfaces via this link: https://www.imcrc.org/2018/07/03/globalorthopaedic/


Investigating the Impact of Metallisation Schemes with Reduced Metal/Silicon Interface Area on Performance and Reliability of Screen Printed Solar Cells

School: 
Photovoltaic and Renewable Energy Engineering
Supervisory Team: 
Brett Hallam (brett.hallam@unsw.edu.au)
Yuchao Zhang (yuchao.zhang@unsw.edu.au)
Research Area: 
Photovoltaics
Solar Cells

Description of field of research:

Metallization is essential for solar cells to extract electricity. However, the direct contact between metal electrodes and the silicon surface results in significant power losses, which limits the efficiency potential of industrial solar cells including PERC and TOPCon. As such, approaches are being developed to reduce the metal/silicon interface area, including the use of floating busbars. In addition, a new metallization scheme is being developed in our group with a substantial reduction in the metal/silicon interface area to minimize metal/silicon recombination losses along the fingers. One potential concern of the modified metallisation schemes is reduced adhesion strength of the contacts caused by different chemical composition of pastes and modified contact geometries. Another potential concern is an undesirable penetration of non-fire through pastes through dielectric layers to contact the underlying silicon. Therefore, it is critical to understand the adhesion of floating metallisation schemes, and identify key factors those have detrimental impact on the adhesion, as well as the likelihood and impact of undesirable penetration of floating metallisation contacts through dielectric layers on cell performance.

Research Environment

Our research team has 10 post-docs and 6 PhD students. The student is expected to work closely with Associate Professor Brett Hallam and joint supervisor Yuchao Zhang on an ARENA funded project with close links to industry partners. The supervisors' research background relates closely to the project where they can guide the student's work.

Expected Outcomes

The first expected outcome is understand the impact of reduced metal/silicon interface area and floating metallisation schemes on the adhesion of screen-printed contacts. The second expected outcome is understanding the impact of potential penetration of non-fire through pastes on solar cell performance. The understanding can potential help on designing a new metallization structure that can reduce power losses at metal contacts.

The student can expect to learn characterisation techniques such as I-V measurements, TLM measurements, photoluminescence imaging.

Reference Material/Links

  • D. Paretkar, N.J. Glassmaker, K.R. Mikeska, G. Blackman, A. Jagota, Adhesion of Screen-Printed Silver Metallization to Crystalline Silicon Solar Cells, IEEE J. Photovoltaics. 6 (2016) 1141 - 1151. https://doi.org/10.1109/JPHOTOV.2016.2583792.
  • E. Kurtz, L. Karpowich, D. Moyer, P. Gundel, M. Koenig, W. Zhang, Reducing solar cell production costs via low silver containing backside metallization pastes, 27th Eur. Photovolt. Sol. Energy Conf. Exhib. (2012) 1806 - 1808. https://doi.org/10.4229/27thEUPVSEC2012-2CV.6.2.

Investigating the Long-term Stability Due to Boron-oxygen Defects in Industrial PERC Solar Cells

School: 
Photovoltaic and Renewable Energy Engineering
Supervisory Team: 
Brett Hallam (brett.hallam@unsw.edu.au)
Moonyong Kim (moonyong.kim@unsw.edu.au)
Research Area: 
Photovoltaics
Solar Cells

Description of field of research:

Boron-oxygen related light-induced degradation (LID) has been a significant concern for the photovoltaics industry. However, there now exist two known pathways to eliminate LID. The first approach is using hydrogen passivation to neutralise the recombination activity and extensive work has been conducted in this area, including processes developed by the UNSW supervisors. The second is through a thermal pathway; modifying defect precursors and preventing the recombination active defect from forming. However, a reverse reaction also exists, which could inadvertently increase the concentration of defect precursors overtime in the field. Currently, the reaction rates of both reactions are unknown, leaving uncertainty of the potential activation of defect precursors in the field, and whether this could be a source of additional instability for solar panels over time. This project will determine the reaction rates for precursor annihilation and formation to understand modifications to the precursor concentration during solar cell processing the potential impact during operation in the field.

Research Environment

Our research team has 10 post-docs and 6 PhD students. The student is expected to work closely with Associate Professor Brett Hallam and joint supervisor Moonyong Kim. Their research background relates closely to the project where they can guide the student’s work in both experimental and theoretical areas.

Expected Outcomes

The expected outcome is to quantify the potential performance loss of the commercial PERC monocrystalline silicon solar cells, which currently dominates 50% of the total world market share of PV technology. All p-type boron doped Czochralski-grown crystalline silicon solar cells can potentially suffer from boron-oxygen related light induced degradation, which can reduce the performance up to 10% relative. In particular, the student will focus on the new state of boron-oxygen defects that has been recently identified in 2017 and how it responses under operating condition. It is a crucial aspect to understand whether this state can potentially lead to long-term degradation in commercial PERC cells.

The student can expect to learn processes such as rapid thermal annealing and characterisation techniques such as photoluminescence imaging, quasi-steady-state photoconductance techniques, as well as methods for determining the extent of LID in the material.

Reference Material/Links

  • D.C. Walter, R. Falster, V.V. Voronkov, J. Schmidt, On the equilibrium concentration of boron-oxygen defects in crystalline silicon, Sol. Energy Mater. Sol. Cells. 173 (2017) 33 - 36. https://doi.org/10.1016/j.solmat.2017.06.036
  • N. Nampalli, H. Li, M. Kim, B. Stefani, S. Wenham, B. Hallam, M. Abbott, Multiple pathways for permanent deactivation of boron-oxygen defects in p-type silicon, Sol. Energy Mater. Sol. Cells. 173 (2017) 12 - 17. https://doi.org/10.1016/j.solmat.2017.06.041
  • D.C. Walter, B. Lim, K. Bothe, V. V. Voronkov, R. Falster, J. Schmidt, Effect of rapid thermal annealing on recombination centres in boron-doped Czochralski-grown silicon, Appl. Phys. Lett. 104 (2014) 042111. https://doi.org/10.1063/1.4863674
  • B. Hallam, M. Abbott, J. Bilbao, P. Hamer, N. Gorman, M. Kim, D. Chen, K. Hammerton, D. Payne, C. Chan, N. Nampalli, S. Wenham, Modelling Kinetics of the Boron-Oxygen Defect System, Energy Procedia. 92 (2016) 42 - 51. https://doi.org/10.1016/j.egypro.2016.07.008

Join the Group: Socially Aware Mobile Robots Navigation to Approach Groups

School: 
Computer Science and Engineering
Supervisory Team: 
Dr Wafa Johal (wafa.johal@unsw.edu.au)
Prof. Claude Sammut (c.sammut@unsw.edu.au)
Research Area: 
Robotics and Human-Robot Interaction

Description of field of research:

Enabling robots to navigate in indoors environments in a safe and socially acceptable manner around groups of humans is still an open research area. Socially aware navigation considers the multi-modal assessment of the group dynamics, group formation inferring, path planning, real-time path adaptation, and human-robot communication. Up to now the research in the field has considered a couple of classical scenarios such as crossing a group in a corridor or passing a door. Limitations in terms of lack of realistic datasets is often mentioned in the field. In this research project, we will aim to design several scenarios involving groups of humans in realistic settings. Our work will focus on two main tasks for the robot: 1) approach and integrate a group and 2) passing by a group. A first step of the project will be to record a novel dataset with rich interactions between the humans (H-H scenarios) and between humans and a teleoperated robot (H-R scenarios). The dataset will be collected at the HRI facility allowing multimodal synchronous recording. After that, a model for path planning will be developed. The model will integrate rule-based constraints (i.e. not passing between two persons speaking together) and learned constrained using the dataset recorded to infer implicit social norms. Finally, the model will be tested empirically with new users in which the robot will have to take real-time path planning decisions.

Research Environment

The main supervisor will be Dr Johal, ECA at CSE. She will take this opportunity to collaborate with Professor Claude Sammut and gain experience in supervision. Other doctoral students and MPhil students work in the field of robotics at CSE. The student will be integrated into this research environment and will be able to deepen her knowledge in robotics and work on cutting-edge research problems.

Expected Outcomes

  • A dataset featuring different scenarios of groups and spatial interactions will be recorded at the HRI facility in Paddington. After anonymization, the dataset will be made open.
  • Development of a novel socially aware module allowing the robot to approach and leave groups using a hybrid method (rule-based and data-driven)
  • Empirical evaluation with end-users in the National Facility for HRI
  • Conference publication at CoRL (Conference on Robot Learning (deadline July 2021) or at the Robotics and Automation-Letters (RA-L)
  • Building on this research application for other funding schemes will be investigated by the PIs on this project

Reference Material/Links

The project will make use of the robots present at CSE robotics lab (L5 J17): turtlebots and Toyota HSR. The Fetch robot present at the HRI Facility in Paddington campus will also be used for the final empirical evaluation. The HRI facility (https://hri.edu.au/) will allow to record a novel dataset with rich scenarios featuring robot-group interactions.


Matching Algorithms with Distributional Constraints

School: 
Computer Science and Engineering
Supervisory Team: 
Haris Aziz (haris.aziz@unsw.edu.au)
Research Area: 
Algorithms
Game theory

Description of field of research:

Centralized matching market design is one of the success stories of algorithmic game theory. This project concerns two-sided matching that captures the setting where students have preferences over schools, schools have priorities over students, and the goal is to match the students to the schools in a stable manner. Although the Deferred Acceptance algorithm is a well-known solution for the problem, it need not work seamlessly when there are additional distributional constraints involved in the matching problem. For example, there may be diversity constraints that a school must accept a certain proportion of minority students. Another example of a distributional constraint is that a school in a certain region should get a minimum number of students.

The goal of the project will be to examine challenging matching problems with distributional constraints and design algorithms for them.

Research Environment

The student will be hosted by the Algorithmic Decision Theory group at UNSW. https://research.csiro.au/adt/

Expected Outcomes

Expected outcomes include valuable learning of important algorithms for high impact societal problems; experience of mathematical writing including proofs, implementation of algorithms, and an opportunity to get a real taste of doing research.

Reference Material/Links


Mobile App Development (Android) and Virtual Reality, Working on a Simulator for Prosthetic Vision

School: 
Biomedical Engineering
Supervisory Team: 
Mohit Shivdasani (m.shivdasani@unsw.edu.au)
Xerxes Battiwalla (Industry)
Brian Gordon (Industry)
Research Area: 
Software Engineering

Description of field of research:

Software is your "thing". You're highly motivated and excited by the prospect of solving programming problems and have some experience programming in a few languages.

You are completing an undergraduate degree in an engineering/science discipline, in particular, Software/Computer Engineering, Computer Science or IT.

You have a GitHub (or similar) public repository showcasing some of your work.

You don't need to have an understanding of medical device principles, tools and practices.

Being an excellent communicator and the having the ability to work within a small team is paramount.

We are aiming to make a real difference in people's lives, and you can too. If you're ready to be a part of it, we'd love to have you!

Research Environment

Bionic Vision Technologies (BVT) is an Australian medical device start-up that aims to restore a sense of vision by developing a range of world-leading technologies to help people who are blind from degenerative inherited retinal diseases.

The BVT developed bionic eye consists of implanted and body worn components. The patient wears glasses with a small video camera mounted on the side. The live feed from the camera is processed and transmitted via an implanted microchip to an electrode array placed in a naturally occurring pocket behind the retina, called the suprachoroidal space. The electrodes stimulate remaining cells in the retina, to generate spots of light that give a patient a sense of vision.

BVT is looking for a student to work in our Research & Development group, contributing to a range of our software/firmware projects, with an initial focus on mobile app development (Android) and Virtual Reality, working on a simulator for prosthetic vision. This position is based in Sydney, with flexible working arrangements.

Contact: careers@bionicvis.com

Expected Outcomes

A unique opportunity to shape the development of the Australian bionic eye.


Modelling of Hydrogen Direct Injection Engines

School: 
Mechanical and Manufacturing Engineering
Photovoltaic and Renewable Energy Engineering
Supervisory Team: 
Evatt Hawkes (evatt.hawkes@unsw.edu.au)
Armin Wehrfritz (armin.wehrfritz@unsw.edu.au)
Research Area: 
Combustion and Solar Energy

Description of field of research:

The overall aim of our hydrogen engine research program is to develop the most efficient hydrogen engine to date, targeting heavy duty applications in transportation (e.g. ships and trucks) and power generation, in partnership with MAN Diesel and Turbo. We believe we can beat, or at least approach, the real world efficiency of a fuel cell by exploiting some of hydrogen's unique combustion properties, while providing a more robust power plant that is resistant to thermal and mechanical shock, and enabling the operation on hydrogen containing impurities. The bigger picture is in a possible future where Australia would export hydrogen to countries such as Japan which has not got enough solar energy to supply their own needs. Our project diversifies the possible end uses for hydrogen.

The taste of research project will involve numerical simulations of hydrogen combustion to support the overall aim to develop and optimise a hydrogen engine. Topics will be individualised to the student's interests but can include:

  • Laminar flame study of the ignition of hydrogen by a diesel pilot flame;
  • Laminar flame study of the quenching of a hydrogen flame at the wall;
  • CFD simulation of turbulent hydrogen flame propagation in engine-relevant conditions;
  • CFD simulation of ignition of hydrogen jets in diesel-engine conditions;
  • Machine learning applied to dual-fuel combustion simulations.

Research Environment

The successful applicant will join the UNSW Combustion & Solar Energy Research Group and will be closely advised by Evatt Hawkes, and two postdocs, Armin Wehfritz, and Deepak Dalakoti. PhD students may also be involved. Multiple taste of research students are likely to join the project, providing a friendly group environment for the research.

Expected Outcomes

Overall, this work contributes to the design of a very efficiency hydrogen engines, which can operate on renewably produced hydrogen, thus opening a door to a future free of fossil fuels and the associated emissions of greenhouse gases.

Reference Material/Links

Please contact the supervisor.


Modelling Particle Solar-energy Receivers

School: 
Mechanical and Manufacturing Engineering
Photovoltaic and Renewable Energy Engineering
Supervisory Team: 
Evatt Hawkes (evatt.hawkes@unsw.edu.au)
Deepak Dalakoti (d.dalakoti@unsw.edu.au)
Research Area: 
Combustion and Solar Energy

Description of field of research:

Decarbonising our energy systems will be one of the greatest challenges of your generation. Different energy sectors present different challenges in decarbonisation. One of the most difficult sectors is high-temperature minerals processing applications, which require high-temperature heat that is currently provided by fossil fuel combustion.

In this project supported by the Australian Renewable Energy Agency, our group is looking at using concentrated solar thermal energy in the process of alumina calcination. This process is one of the steps needed to make aluminium from bauxite, which is a big industry in Australia. This process needs a high temperature to work, higher than conventional solar receivers can achieve.

Our approach is to use a particle-based receiver wherein the is a fluid flow containing a suspension of particles which absorb the solar energy. These systems can achieve much higher temperatures mainly because of reduced need to deal with cyclic thermal stresses in structural components.

The work at UNSW involves the development of validated computational fluid dynamics models of particle-laden flows. These models will then be used in later phases of the project to help design the receiver and to scale up prototype receivers into commercial scale.

Your project will involve:

  • testing of various existing models against a reference dataset
  • using machine-learning techniques to develop new models.

Research Environment

The successful applicant will join the UNSW Combustion & Solar Energy Research Group and will be closely advised by Evatt Hawkes, and two postdocs, Deepak Dalakoti and Huaa Zhou. PhD students may also be involved. Multiple taste of research students are likely to join the project, providing a friendly group environment for the research.

Expected Outcomes

Overall, the outcomes will be recommendations for the best choice of CFD models for particle-laden flows. These models will in the future be adopted for the design and scale-up of the solar receivers.

Reference Material/Links

Please contact the supervisor.


Monitoring Bushfires from Space

School: 
Civil and Environmental Engineering
Supervisory Team: 
Linlin Ge (l.ge@unsw.edu.au)
Research Area: 
Information Technology

Description of field of research:

Australia has a vast geographic extent. Because of the impact of climate change, major disasters such as bushfire, flood and tropical cyclones will be more severe and more frequent. Therefore, there is much more satellite remote sensing technologies can offer in monitoring these events.

This project focuses especially on monitoring bushfires from space. The Academic Supervisor and his team have developed innovative techniques for this purpose. The ToR candidate will develop these techniques further and streamline the conversion from satellite imagery to bushfire intelligence through creative implementation of IT technologies.

Research Environment

The ToR candidate will join a team of about 10 researchers, consisting of senior academics, postdoc researchers and PhD students. He/she will also have access to the Team's high performance computing facilities, such as servers and image processing workstations.

Expected Outcomes

The Academic Supervisor and his team have developed innovative techniques for monitoring busfires, such as visible, infrared and radar.

It is expected that the ToR candidate will fully automate at least one of these techniques, in collaboration with other members in the Team.

The skills and experiences required from the ToR researcher to undertake this project include:

  • computer programming (e.g. C++, Matlab, and Python)
  • general understanding of natural disasters
  • image processing
  • digital signal processing

Reference Material/Links

High winds kept firefighting aircraft from flying, and authorities used satellite imagery to locate the blaze in Colorado, USA https://www.washingtonpost.com/weather/2020/10/24/colorado-wildfire-east-troublesome-estes/


Neural Differential Equation Models of Cochlea for Speech Processing

School: 
Electrical Engineering and Telecommunications
Supervisory Team: 
Dr Vidhyasaharan Sethu (v.sethu@unsw.edu.au)
Prof. Eliathamby Ambikairajah (e.ambikairajah@unsw.edu.au)
Research Area: 
Machine Learning
Speech Processing

Description of field of research:

Neural networks are widely used in many speech processing tasks and underpin most current state-of-the-art speech processing systems. However, they have a number of drawbacks including, but not limited to: (a) being black box systems that make accurate predictions but are not interpretable; and (b) requiring large amounts of data to train. In this project you will investigate and develop novel speech analyses model mimicing the human cochlea, based on integrating differential equations with neural networks. This is a blue-sky research project that seeks to develop the foundations for next generation speech processing systems in the upcoming decade.

Research Environment

The work environment will be within the speech and audio processing laboratories of the School of Electrical Engineering and Telecommunications under the supervision of Dr Sethu. In this group there are 5 PhD students working on speaker verification and recognition, emotion detection and cochlear modelling. It is expected that the development work in this project will be carried out in Julia (a newish programming language) and be capable of running on the high performance GPU computing platforms available to the research group.

Expected Outcomes

A software library/toolkit (most likely in Julia) that can be used to implement the intended neural differential equation model of a cochlea and in the process of developing this model, understand and validate the pros and cons of this approach. If the topic were extended into an honours thesis, more would be possible. Additionally, if it leads to significant research findings then the findings could be published as a paper.

Reference Material/Links


Next Generation Biomedical Technologies

School: 
Mechanical and Manufacturing Engineering
Supervisory Team: 
Susann Beier (s.beier@unsw.edu.au)
Ray Tapabrata (t.Ray@adfa.edu.au)
Research Area: 
Biomedical Flow and Devices

Description of field of research:

There is a high demand for mechanical engineers to develop and improve medical devices and to understand underlying biomedical fluid mechanics principals. During your Taste of Research placement you will have the opportunity to be exposed to a range of exciting new developments of medical devices and improvement of existing once. We for example work on vascular scaffolding stents, heart pump grafts, 3D printing realistic vessels, or immersive technology to assist heart surgery.

Research Environment

Your main contact is Dr Susann Beier, a young German biomedical engineer who has risen through the ranks quickly in the industry research sector and is now passionately running her own research group at UNSW. Her team is international across New Zealand and Australia and consists of PostDocs, HDR students, research assistants, international practicum, and research thesis students from many backgrounds including clinical, mechanical, biomedical, mechatronics, bioinformatics, chemical and materials.

Expected Outcomes

You will learn a range of research skills including computational and experimental methods, how to effectively communicate and work in an interdisciplinary team. Ideally we would like you to be involved in some sort of output to showcase your learned skills, this may include an internal seminar or participation towards a conference presentation.

Reference Material/Links


PFAS Environmental Fate

School: 
Civil and Environmental Engineering
Supervisory Team: 
Denis O'Carroll (d.ocarroll@unsw.edu.au)
Matt Lee (mattlee70@gmail.com)
Research Area: 
Environmental Contamination

Description of field of research:

Per- and poly-fluoroalkyl substances (PFAS) are a class of chemicals that have rapidly become one of the biggest emerging contaminants of concern worldwide due to the extremely low concentrations of regulator concern and their prevalence in drinking water sources around the world. In Australia, PFAS has received considerable media attention (e.g., numerous front page news articles; ABC Four Corners episode which aired Oct. 9th, 2017) due to subsurface contamination emanating from a number of military installations (e.g., Williamtown, Oakey, Tindal) and fire training areas (e.g., Fiskville). They represent a class of fluorinated surfactants ranging in chain length and containing a variety of hydrophilic groups giving them exceptional interfacial properties and chemical resistance. They have been widely used since the 1950s for a range of consumer and industrial applications, including in aqueous film forming foam (AFFF). A recent study suggests that on the order of six million people in the US were served by drinking water supplies where at least some of the water source had PFAS levels that exceed regulatory limits. Given that PFAS is pervasive in the environment they have been quantified at measureable levels in serum since the 1960s with ~97% of participants in a 2011-12 US study having measureable serum PFAS levels.

This project will investigate the fate of PFAS in the environment. This project will include a combination of laboratory work as well as an assessment of the global distribution of PFAS. We have collected PFAS data in surface water, groundwater, soil, plants and animals from a significant number of countries. This data will be used to determine the factors that impact PFAS fate.

Research Environment

The student will join a group of 15 investigating PFAS environmental fate. Professor O'Carroll will be the main contact.

Expected Outcomes

There are numerous potential outcomes of this study, they include interactions with our industry partners, development of preliminary data for an honour's thesis, presentation of work at an international conference and publication of work in a peer review journal.

Reference Material/Links

Applicants can find out about PFAS in the environment by reading publications of the supervisory team and those of others.


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