EPSRC 2021 VACATION INTERNSHIP PROGRAMME

The University, in conjunction with EPSRC, has a number of summer vacation internship awards available for undergraduate students. The vacation internship scheme gives undergraduate students a taster of what it is like to do research. The students are given practical, first-hand experience of working on and carrying out research in a UK university. The awards are aimed at Home/EU undergraduate students in the middle years of their degree programme (i.e. have completed their 2nd year of study on a 3 year degree course, or have completed their 2nd or 3rd

year of study on a 4 year degree course) who are undertaking their degree in a subject that falls within the remit of EPSRC (https://www.epsrc.ac.uk/research/ourportfolio/).

Application forms should be completed and returned to Debbie Henderson, PGR Student Team, by email to (pgrstudentships@liverpool.ac.uk) no later than 4.30pm on Wednesday 14th April 2021. Successful applicants will be employed as interns and receive a minimum payment rate equivalent to the National Living Wage for a period of up to ten weeks.

The following research projects are being offered by the School of Electrical Engineering & Electronics and Computer Science, School of Physical Sciences, the School of Engineering and the School of Environmental Sciences:

School of Electrical Engineering & Electronics and Computer Science

DEPARTMENT OF ELECTRICAL ENGINEERING & ELECTRONICS

1. Project Title: Gas Sensing with Zno Thin Film Transistors

Supervisors: Dr Ian Sandall, Department of Electrical Engineering & Electronics

Description: Over the last few decades, with the rapid development of industrialization and urbanization, the severe air pollution primarily attributed to automobile exhaust and factory emission has become a great threat to human survival and development. Meanwhile, a leakage of flammable and explosive gases may result in loss of life and property damage. So, real-time and effective detection of those harmful gases via using gas sensors is in pressing need at present. Off all the numerous semiconductor gas sensors, semiconducting metal oxide based gas sensors have received wide research around the globe by virtue of their high gas response, excellent selectivity, good portability, and low fabrication cost.

Thin film and nano particle ZnO based transistors are highly sensitive to their surrounding environment. Chemical compounds in the atmosphere are able to bind and modify the surface potential of the ZnO resulting in measurable

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changes in the transistors electrical performance (i.e. causing a shift in the turn on voltage). As such these devices make promising candidates for low cost and portable gas sensing devices. As well as environmental and industrial based gases as described above, the ability to monitor gases also has applications in medical diagnosis and treatments. One gas of particular interest is ketone (acetone), this is produced in people with diabetes and as such the reliable and accurate monitoring of ketone in breath samples offers a potential route to develop non-invasive diagnosis for diabetes, eliminating the need for repeated blood finger prick based tests, and long term creating the possibility of utilizing a mobile phone sensor and app to monitor glucose levels. . In this project the student will fabricate ZnO thin film Transistors, via thin film deposition techniques and characterize their electrical properties both under ambient conditions and when exposed to gases such as acetone. The selectivity and sensitivity of the devices will be evaluated, with an aim to determine the optimum device design.

2. Project Title: Design and Construction of an Electrochemical Impedance System

Supervisors: Dr Ian Sandall, Department of Electrical Engineering & Electronics

Description: Electrochemical Impedance Spectroscopy is a characterization tool used to diagnosis charges and changes on the surface of a material. Electrochemical impedanceis the response of an electrochemical system (cell) to an applied potential. The frequency dependence of this impedance can reveal information concerning the underlying chemical processes. Commercial systems to measure the impedance in this way are often relatively large and expensive, however the underlying principle only involves applying signals of differing frequencies and measuring a phase shift. Which can easily be achieved using micro-controller. The aim of this project is to identify and make use of suitable micro-controller (i.e. Arduino, Raspberry Pi, etc.) to design and build a low cost and portable Electrochemical Impedance Spectroscopy System.

3. Project Title: Investigation of InAs(Sb) Nanowires for potential use in next generation electronic and optoelectronic devices.

Supervisors: Dr Ian Sandall, Department of Electrical Engineering & Electronics

Description: Semiconductors are able to efficiently convert electrical energy into light; this is the basis of light emitting diodes (LEDs) and semiconductor lasers as well as convert light back into an electrical signal as a photodiode. Semiconductor based nanowire devices have received considerable attention over the last few years due to their unique one-dimensional structure which gives rise to unique electrical and opto-electrical properties. This has resulted in the demonstration of a variety of devices including; photodiodes], light emitting diodes], and transistors. Furthermore due to an intrinsic reduction of strain during the epitaxial growth, it has been possible to realize nanowires from a variety of compound semiconductors on differing substrates, including silicon, graphene and glass opening a potential routes to so called silicon photonics for integrated photonic circuits, flexible circuits and low cost manufacturing.

In this project a range of differing nanowires will be fabricated into electrical devices, exploring differing metallic contacts and then evaluated to help understand their properties and potential performance.

Capacitance-Voltage measurements will be undertaken on different samples and over a range of temperatures to try and determine the electrical doping within the nanowires, in terms of both its concentration and polarity. These

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results will then be compared to the growth parameters for the different samples to try and establish relationships between growth conditions and device performance. Additionally Current-Voltage measurements will be performed to determine turn on voltages, ideality factors and saturation currents. These will again be compared to the differing growth and fabrication procedures to determine the relationships between the manufacturing conditions and the final device performance.

4. Project Title: Wireless Charging of Mobile or Implantable Medical Devices

Supervisors: Dr Jiafeng Zhou, Department of Electrical Engineering & Electronics

Description: Length: 10 weeks

Every year in the UK, more than 40,000 people will have a pacemaker fitted. The battery of the pacemaker usually lasts up to about six years. More advanced pacemakers tend to use more energy so have a shorter battery life. There are many other types of implantable electronic devices as well, such as nerve stimulator, glucose monitoring sensors and capsule endoscope that are widely used worldwide. The batteries in these devices need to be replaced surgically when they become depleted. Typically a patient will need to stay in hospital for a few days due to potential risks associated with the surgery.

This project will develop techniques to charge the batteries wirelessly to extend the lifespan of implantable and wearable devices. Such techniques can also be used for wireless communication of these devices. During this project, a prototype of wireless power transfer system will be constructed and evaluated for the suitability for implantable devices. After the project, the candidate will gain the knowledge of wireless power transfer, energy harvesting and the application of medical implantable devices. The candidate should ideally have some experience of electronic circuit design. This is desired but not compulsory. You will be supported by PhD students who are carrying out research in this area.

The same technology can also be applied to the charging of mobile phones, electrical vehicles or drones etc. The candidate can choose any of the topics during the project.

Informal enquires can be emailed to jiafeng.zhou@liveprool.ac.uk.

5. Project Title: Development of Microwave Devices for Satellite Communications

Supervisors: Dr Jiafeng Zhou Department of Electrical Engineering & Electronics

Description: Length: 10 weeks

The UK has a thriving space sector with significant capability in manufacturing satellites and using the information they collect to drive innovation in other sectors ranging from healthcare to finance. Microwave and radio frequency (RF) signals serve as the backbone of communication between space systems, such as satellites and spaceports, and the ground. It is crucial to develop RF devices capable of transmitting, receiving or utilising radio signals.

This project will look into the design of such devices, including low and high power amplifiers, filters or mixers etc. During this project, you will understand the fundamental elements of satellite communications, and then develop one of these devices by considering its size, weight and performance. For example, waveguide filter offers sharp

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selectivity up to millimeter wavelengths and has the ability to handle high powers. However, they are generally higher in cost, heavier in size and naturally greater in size. In this project, a high-performance filter can be developed which is cable of delivering high power and sharp selectivity, but with much reduced size and weight. The candidate should ideally have some knowledge and experience of radio frequency technology. This is desired but not compulsory. You will be supported by PhD students who are carrying out research in this area.

Informal enquires can be emailed to jiafeng.zhou@liveprool.ac.uk.

6. Project Title: Deep Learning-based Wireless Device Classification

Supervisors: Dr Junqing Zhang Department of Electrical Engineering & Electronics

Description:

(1) OverviewThere are many notorious wireless attacks in recent years, in particular to low cost Internet of Things devices. Device authentication is essential for allowing legitimate devices to access the network while declining malicious users. Conventional schemes rely on MAC addresses, which are not secure; the MAC addresses can be tampered easily even by amateurs. A secure yet lightweight device authentication scheme is thus strongly required.

Similar to the biometric fingerprints of human being, wireless devices also have their intrinsic features, termed as radio frequency fingerprinting (RFF). Therefore, RFF identification can be used to classify wireless devices based on the received signals [1,2].

(2) ObjectiveThis intern project will investigate WiFi-based RFF identification and build a prototype system. As shown in the figure, FiPy1 platforms, serving as the WiFi devices to be classified, will emit WiFi signals. A PlutoSDR 2 will collect extensive wireless signals from different FiPy devices at different locations. The PlutoSDR will then adopt deep learning algorithms to train a network and classify devices.

(3) Expected Procedures Conduct a literature review into RFF identification.Learn WiFi protocol. Learn deep learning methods such as CNN.Build a PlutoSDR-based prototype system.

1 https://pycom.io/product/fipy/2 https://www.analog.com/en/design-center/evaluation-hardware-and-software/evaluation-boards-kits/adalm-pluto.html4 | P a g e

Besides the supervision from the supervisor, the student will be assisted by the PhD student who is working in this area. Sufficient and efficient supervision will thus be provided.(4) RequirementsStrong interests in the wireless communications and securityStrong Python/Matlab programming skills.(5) Reference[1] Deep Learning Based RF Fingerprint Identification Using Differential Constellation Trace Figure, IEEE Transactions on Vehicular Technology, 2019[2] Design of a hybrid RF fingerprint extraction and device classification scheme, IEEE Internet of Things Journal, 2019.

7. Project Title: Instrumentation for bioreactor to monitor artificial muscle constructs

Supervisors: Dr Kai Hoettges, Department of Electrical Engineering & Electronics

Description: This project will be alighted to MicroAge, a UK space agency funded research project.

https://www.liverpool.ac.uk/ageing-and-chronic-disease/microage-in-partnership-with-the-uk-space-agency/

MicroAge studies ageing of artificial muscles in microgravity and is designing a bioreactor system to fly on the international space station. Due to the restricted size and weight for space experiments, a novel electrical monitoring technique was developed for this project allowing to sense that the artificial muscles are contracting and measure the contraction strength. However for benchmarking a different set of electronics will be needed that allows to integrate the current electrical technique with mechanical force measurements and optical monitoring, this enhanced version of the electronics will also be used for outreach demonstrations.

The student will design circuits based on the fight hardware but will add additional capabilities to allow more flexible use of the system. As well as allowing to synchronise the electrical characterisation circuits with image acquisition and force data in parallel.

8. Project Title: Creating a generalised database of Bayesian models

Supervisors: Dr P Clemson

Description: Bayes’ theorem is a mathematical tool which provides a way of fitting statistical models to data given prior knowledge. Specifically, rather than finding a simple best fit, one can estimate the posterior probability (the probability of the model parameters given the data and prior knowledge). Such Bayesian models have become increasingly popular with the advent of Markov chain Monte Carlo (MCMC) algorithms. However, the countless implementations of MCMC and other similar posterior estimation algorithms makes comparisons of speed and accuracy difficult to assess.

The current standard of demonstrating the effectiveness of an algorithm is to compare its performance across a small selection of models. While care might be taken to choose particularly difficult models, this still does not guarantee that performance will not vary for other types of models.

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The internship project will aim to remedy this problem by generating a large database of curated Bayesian models. Posteriordb is a generalised (implementation-independent) database containing known posteriors with corresponding data, model code and descriptive information. The database has been recently developed alongside a popular MCMC software package known as Stan. Working in conjunction with the Stan developers, the database will be expanded using another database of ~450 uncategorised models. The main task will be to describe and categorise these models using the information found in the original sources.

The project will ultimately provide a means of validation for a new Stan algorithm being developed by a collaboration of researchers from the University of Liverpool, IBM, and the Hartree Centre. Once validated, this algorithm promises to vastly improve computation speeds for various fields of science which is critically important for applications to coronavirus modelling for colleagues working in epidemiology, infection and statistics. In particular, it would make it possible to downscale daily updates and forecasts from the nation level to the level of towns and city districts.

9. Project Title: Integration and development of tracker parameter estimation algorithms in Stone Soup

Supervisors: Lyudmil Vladimirov and Professor Simon Maskell

Description: Stone Soup [1, 2] is an open-source Python framework that aims to provide researchers and practitioners with the ability to develop and implement new and existing tracking and state estimation algorithms for ease of comparison. The development of Stone Soup is being led by the UK government’s Defence Science and Technology Laboratory (DSTL) and has thus far included contributions from various governmental research bodies and from across the globe, including the US Air Force Research Laboratory and National Research Laboratory, Defence Research and Development Canada and the Australian Defence Science and Technology Group. The University of Liverpool Signal Processing Group (SPG) has been a core part of the Stone Soup moderating panel since its initial development stages and has a number of active contracts contributing to Stone Soup as a core part of their planned research and impact.

The tuning of the parameters used by tracking algorithms is vital to user’s ability to ensure that such algorithms work well. However, it is also a highly involved process, that routinely involves manual testing of many different parameters to hand-craft an assumed-to-be near-optimal setting. Over the years, there has been extensive research (in disjoint subsets of the academic literature) in developing methods for the generic process of automated offline learning of parameters from data (and which are applicable to automating parameter tuning in tracking algorithms). Indeed, as part of the £2.5M EPSRC grant, “Big Hypotheses”, and motivated by specific use-cases associated with COVID, there is currently ongoing research within the SPG in extending a specific (flexible articulation of a) state-of-the-art technique, Particle Markov Chain Monte Carlo (PMCMC), that is applicable in this context. However, as of today and to the best of our knowledge, no such technique is yet used to automate the parameter tuning of any tracking algorithms (including those in Stone Soup).

The proposed project will involve the enhancement of the recently developed PMCMC software (as developed in Big Hypotheses) to be applicable with Stone Soup as well as subsequent integration of PMCMC and Stone Soup. This will involve developing the mathematical models for Stone Soup in the PMCMC software as well as interfacing the parameter learning algorithms with Python in general, as well as integration of such implementations within Stone Soup specifically. Involvement in the project will provide the successful student with experience in working with Python (and potentially Matlab and C++) as well as software management tools (e.g. Git), and provide invaluable exposure to an active and energising international research/collaboration environment.6 | P a g e

[1] P. Thomas, J. Barr, S. Hiscocks, C. England, S. Maskell, B. Balaji, and J. Williams, “Stone Soup: An Open-Source Framework for Tracking and State Estimation, “International Society for Information Fusion (ISIF)Perspectives, vol. 1, no. 2, pp. 1–38, 2019[2] D. Last, S. Hiscocks, J. Barr, D. Kirkland, M. Rashid, S. B. Li, L. Vladimirov, and P. Thomas, “Stone Soup: announcement of beta release of an open-source framework for tracking and state estimation,” April2019.

10. Project Title: Assessing light curves of Earth-Orbiting objects

Supervisors: Dr Lee Devlin (PDRA, School of EEE and Comp. Sci.), Professor Simon Maskell (School of EEE and Comp. Sci.), Dr Stefania Soldini (School of Engineering)

Description: Space Situational Awareness (SSA) is the capability of identifying and keeping track of objects orbiting the Earth. Space is a rapidly changing domain which is important for the nations digital and telecommunications infrastructure. It is therefore important to maintain an ongoing awareness of the space domain to minimise accidental or intentional damage to UK space assets. As objects orbit, they reflect light emitted from the Sun towards the Earth. While it may be possible to see large low-altitude satellites with the naked eye. To observe objects at higher altitudes requires electro-optical telescopes. The amount of light detected depends on several factors including the material properties of the satellite and the phase angle in the Sun-Satellite-Earth system. Measuring the amount of detected light allows ground-based observers to assess what it is they are observing, e.g., whether it is a satellite or debris, the amount it is spinning, etc.

We are looking for a summer intern to build a processing chain (ideally written in Python) to analyse light detected from Earth-orbiting objects. This will involve analysing data collected from the Liverpool Telescope (a robotic telescope located in La Palma, owned and operated by Liverpool John Moores University) in historic and current projects being undertaken for Dstl. It is anticipated that the project will last for five weeks and will be conducted in two stages. First, extracting the location of objects in the image and second, attempting to measure the light curves by using data from stars with ‘known’ brightness as a comparative baseline.

As part of this internship, you will have the opportunity to join a team of friendly researchers who make up the signal processing group who are involved in extracting critical information using data science and machine learning. You will also work with real data collected from the Liverpool Telescope, future upgrades of which are part of the Liverpool City Region’s Data strategy and involved more broadly with the North-West space hub. While no previous knowledge of telescopes is required, experience in a computing language, such as Python, is highly desirable.

11. Project Title: Identifying Problems through Natural Language Processing

Supervisors: Professor Simon Maskell, Matthew Carter (EEE, DA CDT) and Phillip Marshall (Physics, LIV.DAT CDT)

Description: Markov Chain Monte Carlo (MCMC) describes a family of algorithms that are commonly applied to Bayesian inference problems in areas ranging from epidemiology to manufacturing. Despite their success, MCMC algorithms are poorly suited to modern computing architectures. As part of the “Big Hypotheses” research project, the University of Liverpool, in collaboration with IBM Research and the STFC Hartree Centre, has developed alternatives to MCMC (Sequential Monte Carlo (SMC) Samplers) which are capable of exploiting multi-core and multi-processor computing architectures. In order to maximise the impact of Big Hypotheses, it is important to identify applications where SMC Samplers can make a significant difference.

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This vacation project provides an to be embedded in a friendly and creative interdisciplinary team of engineers, physicists, mathematicians, computer scientists and economists working together to develop transformational solutions to tough data science problems. Specifically, the successful student will apply natural language processing (NLP) techniques to academic literature to identify the types of inference problems (static, online, dynamic) that MCMC algorithms are commonly applied to in a number of domains. The project compliments previous research to analyse the time taken to solve, and perceived societal benefit of, various applications of MCMC. It is intended that this project will inform decisions about which applications should be considered by Big Hypotheses, with the explicit aim of maximising the projects impact through the design of a portfolio of common Bayesian inference applications. The output of this project is likely to be utilised by academic, government and industrial partners of Big Hypotheses.

Should the aforementioned tasks be completed in good time, the scope of the project can be extended to incorporate an information extraction task. This would involve extracting the run-time of applications and the hardware (e.g. make of CPU, clock speed) that they were run on from the previously analysed literature.

12. Project Title: Inkjet Printing Solutions for Flexible Electrodes

Supervisors: Dr Simon Maher (EEE), Dr Kate Black (SoE)

Description: There currently lacks an established means to directly write out electronics, just like you might print pictures on paper with an office printer. However, inkjet printing shows much promise as a non-contact, low-cost, high-speed, additive and eco-friendly technique that can be adapted for the purpose of printing conductive materials. Printed electronics is attracting interest from researchers and businesses alike as it offers potential for large-scale and low-cost fabrication of electronic devices on a variety of substrates.

In this project, you will investigate the possibility of using conductive inkjet printing as the basis for fabricating a charge particle guidance device. You will investigate a range of conductive materials, printing techniques, ink formulations and possible substrates. As a demonstrator you will print a flexible drift tube (e.g., https://pubs.acs.org/doi/abs/10.1021/acs.analchem.0c01357), populate it and test its performance against an equivalent commercially sourced board.

You should have a keen interest in electronics and a practical hands-on approach. Having prior experience with design or development of PCBs (electronics design, schematic capture, PCB layout) is advantageous.

This is a multidisciplinary project being supervised by Dr Simon Maher (EEE) and Dr Kate Black (SoE). Dr Maher’s research group sits at the interface between engineering and analytical instrumentation. The Mass Spectrometry and Instrumentation group at the University of Liverpool has an established track record of developing new instruments for a wide range of applications (www.liv.ac.uk/mass-spec). Dr Kate Black is a Senior Lecturer in Additive Manufacturing and co-founder of Meta additive. Her research is focused on the development of novel functional materials, using inkjet printing, for the manufacture of electronic and optoelectronic devices.

13. Project Title: Head Mounted Olfactory Display for Interactive Smell Generation in Multi-Sensory Immersive Reality Applications

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Supervisors: Professor Alan Marshall, Department of Electrical Engineering and Electronics, Professor Sophie Wuerger, Cognitive and Clinical Neuroscience Group, Institute of Life and Human Sciences, Dr Andrew Levers, Director VEC

Description: Virtual & augmented (V/A) reality applications currently focus on two primary senses: aural and visual. It is recognised that V/A reality can be made more immersive by introducing multi-sensory modalities e.g. odour and touch. Although some initial prototype devices for added sensory experience have been developed recently, there are currently no odour-generating devices with practical and useful control of induced olfaction (sense of smell). Any Olfactory Display (OD) device intended for use in V/A reality environments must be portable, non-intrusive and allow repeatable and reliable introduction and switching of odours at an acceptable quality. However, these requirements have proven challenging for OD developers. Another challenge unique to olfaction is its lingering nature. Attempts to address this include presenting minimal amounts of scents to the user, the use of ventilation systems to remove lingering scents, and the evaluation of olfactory adaptation.

Staff in EEE, Psychology and VEC will supervise the successful student to evaluate and improve three types of OD created at the Immersive Reality Laboratory in EEE. This exploratory work follows on from two EPSRC funded projects: EP/M029425/1 ‘Creating a Stink - Investigating Olfactory Transport Streams’, and EP/P004040/1 ‘Context Aware network architectures for Sending Multiple Senses (CASMS)’, totalling £1.8M.

The aim will be to develop an OD which is integrated into a A/V game. The student will investigate the most appropriate OD delivery mechanisms for use with a VR headset, then rig up a test game in which users encounter objects generating smells that trigger the OD to produce an appropriate odour at the appropriate time and intensity, and then flushes it whenever they move away. During the project, prospective students will be exposed to modern game development (C# / “Unity”), 3D printing mechanisms (CAD), electronic circuit design and systems engineering; they will also be exposed to research (with psychology) in evaluating users’ quality of experience and how to “productise” research concepts (VEC). It is anticipated that this work will continue as a showcase in the new DIF facility being built.

Alignment with EPSRC Research Themes: Digital Economy, Engineering & ICT. The proposed work also aligns with a number of other national programmes e.g. ‘Audience of the Future’ (UKRI/digital Catapult), and remote working initiatives, e.g. the digital workplace.

14. Project Title: Overcoming low vision in virtual reality – the use of Head Mounted Displays to optimise immersive visual experiences

Supervisors: Professor Sophie Wuerger, Cognitive and Clinical Neuroscience Group, Department of Psychology, (PGR student: Maliha Ashraf, Engineering), Professor Alan Marshall, Department of Electrical Engineering and Electronics, Dr Andrew Levers, Director VEC

Description: Recent studies have shown several positive impacts of the use of immersive technologies like VR by older adults. These findings are especially significant against the backdrop of the COVID pandemic where older adults, being the most vulnerable demographic, are left with very limited options for enrichment opportunities. The potential of the technology, however, is limited by the physiological changes that happen in human vision with normal aging. We have developed a mathematical model that quantifies these age-dependent contrast sensitivity losses as functions of optical and neural changes [1]. We also have in place an image processing pipeline that manipulates images to mimic age-dependent vision losses.

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In the proposed internship project, the student will i) refine and implement the ageing-vision model, (ii) modify and optimise the VR image processing pipeline, and iii) evaluate various compensatory models while maintaining a pleasant visual experience, using psychological techniques.

The aim of the project is twofold: (1) to produce a VR demonstrator that allows people of all ages to experience age-related vision loss in a rich virtual visual environment, and (2) vice versa, individuals with age-related vision losses will be able to experience immersive visual environments as seen through a ’young eye’.

It is anticipated that this work will continue as a showcase in the new DIF facility being built.

The student will be involved in coding (‘Unity’) and the psychological evaluation of the developed VR models. The student will benefit from the expertise in Electrical Engineering, the VEC and Psychology. The findings of the project will be invaluable in assessing the needs of aging adults and in progressing towards accessible immersive technologies that improve quality of life in the ageing population.

This work follows on from the EPSRC funded project EP/P007503: A spatio-chromatic colour appearance model for retargeting high dynamic range image appearance across viewing conditions.

Alignment with EPSRC Research Themes: Information and Communication Technology (ICT) & Digital Economy;

[1] Ashraf M, Wuerger S, Kim M, Martinovic J, Mantiuk R. Spatio-chromatic contrast sensitivity across the life span: interactions between age and light level in high dynamic range. Color and Imaging Conference 28, Society for Imaging Science and Technology; 2020. https://doi.org/10.1167/jov.20.11.1286.

15. Project Title: Human Movements Characterisation Using Millimetrewaves and AI

Supervisors: Dr Jiafeng Zhou (EEE), Dr Xiaowei Huang (CS) and Professor Mark Turner (Life Science)

Description: Strong medical evidence has shown that many life-changing conditions of babies can be diagnosed through monitoring their general movements. By assessing the general movements, trained doctors can reliably predict neurodevelopmental disorders such as Downs syndrome, autism and cerebral palsy of preterm and term babies. Then, the question is how to automate a trained doctor.

Medical artificial intelligence (AI) can outperform human doctors in many areas, by delivering expert-level cost-effective healthcare at scale. Radar technology is well known for its ability to detect aircraft, ships and motor vehicles. By using millimetrewave signals, whose wavelength is less than 1 cm, it can detect small body movements of heads, arms, torso and legs when sleeping, sitting, walking and running, etc.

Based on a millimetrewave radar that has already been developed at the University of Liverpool, this summer project will combine the radar technology with medical AI through deep learning to characterise human movements. The objectives during the ten weeks are:

Getting familiar with the millimetrewave human movements detection system, with the support of a PhD student in EEE, 2 weeksRecording multiple waveforms of typical human movements (standing up and sitting down), with the support of a PhD student in EEE, 1 week.

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Using the recorded waveforms to train the movement characterisation system by applying AI machine learning techniques, with the support of a PhD student in CS, 4 weeksOptimising and verifying the system performance, and summarise the project, 3 weeks.

The long-term aim of the project, after further development, is to provide a fully autonomous, contactless, unobtrusive, and reliable way for the diagnosis of serious diseases associated with abnormal body movements. The system can also be used for real-time monitoring of home-care patients or elder people who live alone.

DEPARTMENT OF COMPUTER SCIENCE

16. Project title: Reachability Problems for Dynamical Networks

Supervisors: Professor Igor Potapov, Department of Computer Science

Description: Reachability is a fundamental problem that appear in several different contexts. In Theoretical Computer Science (TCS) a description of processes that we need to analyse is typically given in form of transition functions, rewriting rules, transformations, iterative functions, logical formulas and the reachability questions related to understanding of the dynamics of such processes. Informally speaking the standard reachability problem is to check whether a given set of target states can be reached starting from some initial states. Other variants can be defined about the questions of reaching from at least one initial state or from all possible states, deterministically reachable or with a certain probability, synchronously from different states as well as reachable or not reachable under some control.

Currently there is a high demand on understanding dynamic trends, information spreading, epidemic chains, migration processes and this project aims to look at the such next-generation reachability problems through the prism of TCS models and abstractions such as temporal graphs [1], probabilistic models of computation [2], automata and matrix theories [3,4], etc.

The project may be either focused on combined abstractions or can consider reachability problems in individual concepts:

Project A: Reachability in Dynamical Networks Project B: Reachability in Temporal Graphs Project C: Reachability in Probabilistic Models Project D: Reachability in Automata and Matrix Semigroups

References: [1] A. Deligkas, I. Potapov. Optimizing Reachability Sets in Temporal Graphs by Delaying. Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI-20, 2020

[2] Stefan Kiefer. Probabilistic Models of Computationhttps://stekie.blogspot.com/2018/03/probabilistic-models-of-computation.html

[3] Vincent D Blondel, Raphaël M Jungers, Alex Olshevsky. On primitivity of sets of matrices11 | P a g e

Automatica Journal, Vol. 61, 2015

[4] Sang-Ki Ko, Reino Niskanen, Igor Potapov: Reachability Problems in Nondeterministic Polynomial Maps on the Integers. DLT 2018: 465-477

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17. Project title: Speeding up bioinformatics algorithms by GPU programming

Supervisors: Mr Thomas Carroll, Professor Prudence Wong, Department of Computer Science

Description: In bioinformatics, we look to use computational approaches in solving biological problems. For example, we can use specialized pattern matching on strings to match-up a DNA sample to a database record. GPU computing is to use GPU (graphics processing unit) together with CPU to accelerate computation. It is particularly useful when we need to process massive amount of data, e.g., biological data. The project involves * understanding of the GPU architecture * learning of CUDA * learning of a bioinformatics problem and algorithms to solve it * implementing the algorithms learnt to exploit the speed up of GPU * running experiments to analyse the degree of speed up achieved

The student taking this project would have access to machines with NVIDIA GPUs installed. This is a great opportunity for students to learn to program on these machines with cutting edge technology. This project requires students to be strong in programming and be able to pick up a new language in a short time.

18. Project title: Speeding up network visualisation using GPU programming

Supervisors: Mr Thomas Carroll, Professor Prudence Wong, Department of Computer Science

Description: In order to gain information from a graph or network, it is often desirable to display it on the screen. The positioning of the nodes on the screen can affect how the graph is interpreted – one positioning may show something that is jumbled up with many overlapping edges, whereas another positioning may show a clear layout or pattern to the information.

GPU computing is to use GPU (graphics processing unit) together with CPU to accelerate computation. It is particularly useful when we need to process massive amount of data, e.g., data represented as graphs. The project involves * understanding of the GPU architecture * learning of CUDA * learning of the graph drawing problem and algorithms to solve it * implementing the algorithms learnt to exploit the speed up of GPU * running experiments to analyse the degree of speed up achieved

The student taking this project would have access to machines with NVIDIA GPUs installed. This is a great opportunity for students to learn to program on these machines with cutting edge technology. This project requires students to be strong in programming and be able to pick up a new language in a short time.

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19. Project title: Interactive visualisations of large crystal datasets

Supervisors: Dr Viktor Zamaraev (Computer Science) and Dr Vitaliy Kurlin (Materials Innovation Factory)

This project applies Computer Science ideas to Materials Discovery and involves a few PhD students from Dr Kurlin’s group http://kurlin.org#group.

Description: Solid crystals underpin many technological advances from solid-state batteries to safer crystalline drugs. However, materials discovery still relies on trial-and-error through manual choices or random simulations.

The state-of-the-art approach to materials discovery is Crystal Structure Prediction (CSP), which optimises geometric arrangements of given atoms pr molecules on supercomputers. A typical CSP output consists of thousands or even millions of predicted crystals, though only a few crystals can be really synthesised. The past work in Dr Kurlin’s group [W] has shown that many predicted crystals can be recognised as nearly identical by using recent invariants of periodic points sets considered up to rigid motions in 3-space.

The project aims to implement an interactive software tool to visualise any dataset of crystals in a hierarchical way so that all given data are initially presented by a few big clusters, which can be later zoomed in for a more detailed exploration. We collaborate with Prof Andy Cooper FRS and Prof Matt Rosseinsky FRS, whose groups provide us with real and simulated data.

The work plan over 10 weeks: background reading, combining the existing software (producing distances between crystal invariants) with the TMap [P] algorithm to display any set of points with pairwise distances in the form of a Minimum Spanning Tree, testing on available CSP datasets and the world largest Cambridge Structural Database of 1M+ known crystals. This project can accept three undergraduates in Computer Science, who completed Dr Kurlin’s COMP229 module (Introduction to Data Science) and have strong skills in Python and/or C++.

[P] D.Probst, J.-L.Reymond. Visualization of very large high-dimensional data sets as minimum spanning trees. J Cheminformatics 12:12 (2020).https://tmap.gdb.tools

[W] D.Widdowson, M.Mosca, A.Pulido, V.Kurlin, A.Cooper. Average Minimum Distances of periodic point sets, arXiv:2009.02488.

20. Project title: Topological graph kernels

Supervisors: Ana Lucía García-Pulido and Professor Paul Spirakis

Description: A graph kernel is a similarity measure on the space of graphs. These kernels use methods of feature extraction to embed the space of graphs into a Hilbert space and take the inner product between these features. Graph kernels have become a standard method in machine learning used in the context of graph classification.

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This project aims to improve the existing kernel methods by exploiting tools from topological data analysis to develop a new class of richer feature vectors. One can associate a topological space to any graph, called the flag complex. Topological features of the flag complex provide revealing properties of the original network that, in contrast to classical graph features, capture higher order structures.

Extracting these features enables one to employ the tools of topological data analysis to study the structure of a network. These techniques have proved successful in a variety of applications which aim to understand biological, social and technological networks, several examples are listed in [1].

Amongst different types of graph kernels, the Weisfeiler–Lehman (WL) kernels [3] achieve state-of-the-art results on most benchmark datasets. However, these kernels do not capture even the simplest of the aforementioned topological features. A topology-based enhancement of the WL kernel was developed in [2], called WL-P. WL-P performs better than the WL kernels but only uses the most basic topological features.

In this project, we extend the kernel developed in [2] to take into account higher order topological structures. We test our kernel by performing graph classification on benchmark datasets and compare the accuracy of our kernel to the WL kernels and to WL-P.

References[1] F. Battiston, G. Cencetti, I. Iacopini, V. Latora, M. Lucas, A. Patania, J.-G. Young, and G. Petri. Networks beyond pairwise interactions: Structure and dynamics. Physics Reports, 874:1–92, 2020. Networks beyond pairwise interactions: Structure and dynamics.[2] B. Rieck, C. Bock, and K. Borgwardt. A persistent weisfeiler-lehman procedure for graph classification. In K. Chaudhuri and R. Salakhutdinov, editors, Proceedings of the 36th International Conference on Machine Learning, volume 97 of Proceedings of Machine Learning Research, pages 5448–5458. PMLR, 09–15 Jun 2019.[3] N. Shervashidze, P. Schweitzer, E. J. Van Leeuwen, K. Mehlhorn, and K. M. Borgwardt. Weisfeiler-lehman graph kernels. Journal of Machine Learning Research, 12(9),2011.

21. Project title: Interactive visualisations of large crystal datasets

Supervisors: Dr Viktor Zamaraev (Computer Science) and Dr Vitaliy Kurlin (Materials Innovation Factory)

This project applies Computer Science ideas to Materials Discovery and involves a few PhD students from Dr Kurlin’s group http://kurlin.org#group.

Description: Solid crystals underpin many technological advances from solid-state batteries to safer crystalline drugs. However, materials discovery still relies on trial-and-error through manual choices or random simulations.

The state-of-the-art approach to materials discovery is Crystal Structure Prediction (CSP), which optimises geometric arrangements of given atoms pr molecules on supercomputers. A typical CSP output consists of thousands or even millions of predicted crystals, though only a few crystals can be really synthesised. The past work in Dr Kurlin’s group [W] has shown that many predicted crystals can be recognised as nearly identical by using recent invariants of periodic points sets considered up to rigid motions in 3-space.

The project aims to implement an interactive software tool to visualise any dataset of crystals in a hierarchical way so that all given data are initially presented by a few big clusters, which can be later zoomed in for a more detailed

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exploration. We collaborate with Prof Andy Cooper FRS and Prof Matt Rosseinsky FRS, whose groups provide us with real and simulated data.

The work plan over 10 weeks: background reading, combining the existing software (producing distances between crystal invariants) with the TMap [P] algorithm to display any set of points with pairwise distances in the form of a Minimum Spanning Tree, testing on available CSP datasets and the world largest Cambridge Structural Database of 1M+ known crystals.

This project can accept an undergraduate student in Computer Science, who completed Dr Kurlin’s COMP229 module (Introduction to Data Science) and have strong skills in Python and/or C++.

[P] D.Probst, J.-L.Reymond. Visualization of very large high-dimensional data sets as minimum spanning trees. J Cheminformatics 12:12 (2020).https://tmap.gdb.tools

[W] D.Widdowson, M.Mosca, A.Pulido, V.Kurlin, A.Cooper. Average Minimum Distances of periodic point sets, arXiv:2009.02488.

22. Project title: Analysis of new multiway quicksort variants

Supervisors: Dr Sebastian Wild and Benjamin Smith

Description: Understanding the performance characteristics of our basic algorithmic toolbox is key to building robust programming libraries and a fundamental endeavour in computer science. The goal of this project is to analyze a new variant of multiway quicksort that has been invented by programmers [1], but not scientifically investigated. It follows a recent trend in practical implementations of quicksort which use several pivot elements to split the input into several segments in one round. The advantage of these methods is a reduced memory transfer volume [2].

We will start with implementing a clean version of this new algorithm, studying it empirically (following the algorithm science methodology), and ideally conclude with a mathematical average-case analysis of this new method. The outcome will be to predict for what applications this new idea for partitioning method is superior to the variants used in current programming libraries. Moreover, the analysis will provide a sound explanation for these differences.

I have worked extensively on the mathematical analysis and empirical study of algorithms, and am a leading expert on quicksort in particular. This project is ideal for a student research internship: It concerns an active cutting-edge research area, but does not require extensive background knowledge (with core sorting algorithms taught in every computer-science undergraduate program). It can also easily be scaled up and down depending on progress: An implementation and simple running-time study can be completed very quickly, but the mathematical analysis requires novel ideas and leaves room for continued research. A comprehensive empirical comparison with competing designs offers an alternative route to publishable results.

[1]: https://github.com/ddccc/fivesort/blob/master/D3sort.c

[2]: “Dual-pivot and beyond: The potential of multiway partitioning in quicksort”, doi: 10.1515/itit-2018-0012; preprint available here: https://www.wild-inter.net/publications/wild-2018b16 | P a g e

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School of Physical Sciences

DEPARTMENT OF CHEMISTRY

23. Project Title: Visible light accelerated photocatalysis in-the-flow: direct harvesting and re-use of visible light energy

Supervisors: Dr Konstantin Luzyanin, Department of Chemistry

Description: Visible light-induced reactions have since recently emerged as a powerful tool in organic synthesis. Three types of photocatalytic reactions include (i) conventional photocatalysis based on photosensitisation by a photocatalyst enabling the transformation via redox-, atom transfer-, or energy transfer pathway,1 (ii) dual photocatalysis, combining photosensitisation by a photocatalyst with subsequent transition metal catalysis,2 and exceptionally rare examples of (iii) self-photosensitising transition-metal photocatalysis, in which a metal catalyst itself serves as both photo-absorbing species and enables catalysis.3

While advantages of the latter type system can be easily recognised, one of the first ever reported catalysts of this type based on the rationally designed organometallics, was recently discovered in our group.4 We demonstrated its application for the hydrosilylation catalysis under visible light irradiation in the batch reactor, and in the current project, we would like to combine its efficiency with advantages of a specially designed in our group photocatalytic flow setup. Project will involve a basic programming of the setup and optimization of the flow conditions leading to direct harvesting and re-use of visible light energy in the new photocatalytic process in-the-flow.

References 1. D. M. Schultz and T. P. Yoon, Science, 2014, 343, 1239176.

2. X. Lang, J. Zhao and X. Chen, Chem. Soc. Rev., 2016, 45, 3026–3038.

3. M. Parasram and V. Gevorgyan, Chem. Soc. Rev., 2017, 46, 6227–6240

4. a) J. C. Gee, B. A. Fuller, H.-M. Lockett, G. Sedghi, C. M. Robertson and K. V. Luzyanin, Chem. Commun., 2018, 54, 9450–9453; b) M. A. Kinzhalov, M. V. Kashina, A. S. Mikherdov, E. A. Mozheeva, A. S. Novikov, A. S. Smirnov, D. M. Ivanov, M. A. Kryukova, A. Y. Ivanov, S. N. Smirnov, V. Y. Kukushkin and K. V. Luzyanin, Angew. Chem., 2018, 57, 12785–12789.

24. Project Title: Designing new molecular semiconductors

Supervisors: Professor Alessandro Troisi, Department of Chemistry

Description: This is a theoretical computational project suitable for chemistry students with interest in the most quantitative aspects of chemistry and don’t mind working with numbers and computers. It can also be of interest to physics students. The student will use one of the following either (i) quantum chemistry software or (ii) python programming to contribute to our research in the design of new semiconducting materials. The student can also select what type of methodology they are more interested in learning/developing.

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25. Project Title: Automated continuous flow nanoprecipitation of polymeric nanoparticles for drug delivery

Supervisors: Dr Anna Slater, Professor Steve Rannard, Department of Chemistry

Description: Polymeric nanoparticles (PNP) have great potential for cancer therapy. Systems using PNP offer benefits over conventional therapies such as enhanced targeting, reduced side effects, and controlled release. The mechanism of action and clearance from the body of PNP nanomedicines can be controlled by tuning the properties of the system, but many challenges remain. For example, PNP systems designed to target the acidic environment of tumour cells may also accumulate in stomach epithelial cells. The immune system is primed to remove foreign bodies from the body; any nanomedicine must run a gauntlet of defence mechanisms before reaching the target drug delivery site. Nanomedicine researchers seek to understand the relationship between PNP structure and ultimate behaviour of the nanomedicine in the body.

Several factors affect a PNP system’s behaviour, including i) the properties of the polymer used, and ii) the properties of the nanoparticle itself: size, shape, density, and stabilization. Highly reproducible methods of nanoparticle formation are required in order to build robust structure/property relationships. Furthermore, scalable methods of nanoparticle production are needed to produce large scale PNP batches that are homogenous and have the same properties as those made on a small scale. This project will investigate the use of continuous flow nanoprecipitation to achieve reproducible, scalable polymer nanoparticle formation.

The student will start by synthesising polymers and carrying out their batch nanoprecipitation under the supervision of Prof. Rannard. Then, they will be taught how to use commercial and custom flow reactors and, with the supervision of Dr Anna Slater, develop an automated flow nanoprecipitation process. They will systematically investigate the effect of changing flow rate, polymer concentration, and residence time on the composition of the PNP. They will be trained to fully characterise PNP using the equipment in the Rannard group and the Materials Innovation Factory.

26. Project Title: Understanding the fundamental chemistry of Transfer dominated Branching Radical Telomerisation (TBRT)

Supervisors: Professor Steve Rannard, Department of Chemistry

Description: The control of polymer architecture is a key aspect of current polymer research globally. The Rannard Group has created a new approach to branched polymer synthesis that involves the use of chain transfer agents and multivinyl monomers – called TBRT. Branched polymers offer materials with unique properties and the ability to rapidly introduce new functional groups has the potential to allow new properties to be evaluated and exploited. TBRT involves a critical reaction cycle that maintains radical concentrations and avoids termination. The extent of termination suppression is the subject of the project. Utilising model reactions and comparing with materials understanding, the student will tease apart the fine details of mechanism that will lead to publications within this highly active research theme. The student will be exposed to a range of leading-edge synthesis techniques and subsequent characterisation of materials, generating experience and skills to compliment ongoing activities.

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27. Project Title: Developing Predictive Models for the Mechanical Properties of Solid Electrolytes

Supervisors: Dr Matthew S Dyer, Department of Chemistry

Description: Although recent advances in the discovery of new materials has revealed inorganic compounds with ionic conductivities high enough to function as electrolytes in all solid-state batteries, there are still significant materials challenges to overcome. For instance, there does not yet exist a solid state electrolyte material with the ideal mechanical properties to enable simple processing during cell construction. Oxide materials (e.g. derivatives of Li7La3Zr2O12 and LiTi2(PO4)3) are too hard and brittle, whereas the leading sulphide materials (e.g. Li6PS5I) are considered too soft. It would be very helpful to be able to predict compositions which are likely to have intermediate mechanical properties to these oxides and sulphides.

In this 10 week internship, we propose to develop and test mathematical models to predict the elastic constants of candidate material compositions. Data on existing materials will be extracted from the materials project database (https://materialsproject.org/) using the connected python API. This data will then be used in connection with simple fitting and machine learning approaches to develop models capable of predicting the elastic constants of potential new compounds without knowing their crystal structure. These models will then be tested and their accuracy evaluated.

This project forms part of a wider project funded by the Faraday Institution on the development of all solid state lithium ion batteries. It will be supported by colleagues in the Leverhulme Research Centre for Functional Materials Design, hosted in the Materials Innovation Factory, who will add their knowledge and understanding of data analytics to the computational materials chemistry expertise of the supervisor.

28. Project Title: Development of waterborne organic polymer coating for electrical/electronic power applications

Supervisors: Professor Dmitry Shchukin, Department of Chemistry Co-Investigators: Professor Yannis Goulermas & Dr Vladimir Gusev, Department of Computer Science, School of Electrical Engineering, Electronics and Computer Science Industrial/Company: Becker Industrial Coatings

Background/ Introduction: Advanced coatings are used in laminated magnetic cores of transformers, motors and generators to provide surface insulation between the interlaminar cores, minimising core losses caused by Eddy currents and hysteresis. The coatings also provide improved magnetic properties by inducing tension, corrosion resistance, and lubrication during downstream manufacturing and assembly processes.

With the move to electrification of vehicles, light-weighting of drive trains and electrical systems, there is now an opportunity for developing chemically sustainable coatings to meet future market performance and volume demands.

In response, Becker has developed waterborne coatings for magnetic cores of electrical devices and continues R&D activity to improve products through better understanding of coagulation, emulsion chemistry and stability of the media during manufacturing and application. This internship will help build knowledge of the new coating systems and complex interactions between the organic polymer (acrylics, alkyds, epoxies, esters and urethanes), inorganic media, co-solvents and other additives in film formation and processability.

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Aims: The project will quantify the stability of a range of organic polymers, as a function of pH, waterborne inorganic media, co-solvents and additives. The main aim is to identify approaches to characterise the nature of constituent components’ surface charges, their magnitudes and interactions inside mixed colloidal systems, linking these surface characteristics to coagulation resistance. The project will assess alternative approaches to bring organic / inorganic polymers together for direct application to electrical steel and other substrates with similar performance.

This project will connect with an established collaboration between Becker and the university to bring statistical analysis and machine learning approaches to the development of coatings. This will ensure expertise and learning from both computer science and chemistry disciplines is incorporated in the project and inform the direction of potential future collaborations with Becker.

29. Project Title: Synthesis and optimisation of Vorinostat Proteolysis-Targeting Chimera (PROTAC) compounds for suppression of HDAC 1 and 2

Supervisors: Dr Gemma Nixon (Department of Chemistry), Prof Sonia Rocha (Institute of Systems, Molecular and Integrative Biology)

Compounds synthesised during this scholarship and subsequent biological assessment will provide a preliminary data set to facilitate a new collaboration and funding applications between the supervisors.

Description: Vorinostat is a HDAC inhibitor, which causes tumour growth arrest, as well as cell apoptosis and has a role in the treatment of multiple cancers. It is one of the only drugs licensed for treatment of Cutaneous T cell lymphoma (CTCL). CTCL is a rare type of cancer that primarily effects the skin but can also affect the blood and lymphatic system caused by an imbalance between histone acetyltransferase and histone deacetylase enzymes. There is a clear need for more efficacious, less toxic therapies within both CTCL and other cancers where this balance is prevalent such as cervical, breast and prostate cancers.

The PROTAC strategy has the potential to provide this solution. A PROTAC molecule consists of an inhibitor ligand (in this case Vorinostat) that will bind to the target receptor (HDAC 1 and 2), linker chain and E3 ubiquitin ligase warhead. Binding to E3 ubiquitin ligase means that ubiquitination of the target protein can occur, hence protein degradation occurs. There are a variety of E3 ligase ligands that can be targeted, cereblon (CRBN) and von Hippel-Lindau (VHL) will be investigated here. PROTAC molecules have been found to have an increased selectivity and potency and therefore reduced toxicity, compared to the drug alone.

The aim of this project is to synthesise the Vorinostat PROTAC molecules detailed in Figure 1. Previous PROTAC work on alternative targets within the group will help facilitate this. The compounds synthesised will then undergo in vitro testing in Prof S Rocha’s lab to establish binding and activity against the target (HDAC 1 and 2) and whole cell antiproliferative activity to provide proof of concept data for the new collaboration and subsequent funding applications.

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Figure 1: Two target Vorinostat PROTAC molecules with differing E3 ligase ligandsa) CRBN targeting ligand, b) VHL targeting ligand.

30. Project Title: Polymer based imaging probes for diagnostic nanomedicine

Supervisors: Dr Marco Giardiello

Description: Organic/inorganic hybrid nanocomposite particles have attracted much attention due to their potential for a wide range of applications in biomedical research, spanning both diagnostic and therapeutic medicine. The aim of this project is to develop a range of polymer nanoparticles which will incorporate various inorganic metal ions and metal ion chelators for use in diagnostic nanomedicine. This proof-of-concept project will develop chitosan based nanoparticles designed to incorporate a range of metal ions for differing diagnostic purposed: Zirconium (Zr 89) for use in Positron Emission Tomography (PET); Gadolinium (Gd(III) for use in Magnetic Resonance Imaging (MRI); Europium (III) for use in Optical Imaging. This project will provide training and experience in organic nanoparticle synthesis, inorganic coordination chemistry as well as characterisation techniques, such as NMR, fluorimetry and dynamic light scattering (DLS).

References: Fairclough et al., Applied Radiation and Isotopes 130 (2017) 7–12.

31. Project Title: Physics-guided Learning for Robotic Manipulation in Chemistry Laboratory

Supervisors: Dr Gabriella Pizzuto and Professor Andy Cooper (Department of Chemistry), Dr Shan Luo (Department of Computer Science)

Description: Real-world robotic manipulators interact with objects present in their surroundings. In these scenarios, accurate models of robots’ dynamics are pivotal for control, stability and motion optimisation. These tasks are highly dependent on accurate force control, where the system should be compliant to ensure safety of human co-workers. There has been recurring efforts to improve the dynamics models through better measurements and data-driven learning. However, learning-based methods suffer shortcomings when it comes to domain generalisation, interpretability and safety mechanisms which classical systems used to provide. This project will bridge the gap between traditional model-based methods with modern data-driven learning approaches specifically for discontinuous dynamics model learning. For example, when a robot grasps an object, there is a non-smooth

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transition in the dynamics model where contact occurs. We will build on previous work by Dr. Pizzuto and collaborators at the Edinburgh Centre for Robotics on physics-guided learning for point contacts to address specifically multi-point contact through real-world object manipulation such as grasping glassware in a chemistry laboratory.

The student will be working closely with Dr. Pizzuto and will be part of the Materials Innovation factory (Prof. Cooper) and the smARTLab (Dr. Luo). The expected work plan will include a literature review on physics-guided learning, familiarisation with PyTorch and robot simulator (or robotic platform should COVID-19 situation improve), implementation of the dynamics model learning approach on a robotic manipulator (e.g. Kuka or Franka) and final demo of pick-and-place task with chemistry laboratory glassware (e.g. test tubes/flasks). This is a research-driven project where the ideal planned outputs would result in a publication at a robotics conference. The ideal student should have solid programming skills (Python, C++), be reading for a Computer Science degree or Chemistry degree with strong programming component, and an interest of applying robotics to real-world problems (e.g. Chemistry laboratory).

32. Project Title: Using Machine Learning to Develop New Types of Solar Cells

Supervisors: Marcos del Cueto and Professor A Troisi For further information: m.del-cueto@liverpool.ac.uk

Description: Perovskite solar cells have been at the forefront of photovoltaics and are continuously pushing their efficiency. As a result of their success, many charge transporting materials have been developed during the last years, including a large number of hole-transporting materials (HTMs). At the same time, machine learning has been introduced in materials science. Machine learning uses different algorithms to detect correlations in data, and uses the learned patterns to make predictions on unknown data.

In this project, we will use machine learning to make predictions on new best-performing HTMs. The project will involve a data-gathering part, in which the chemical structure and efficiency of different HTMs will be extracted from the literature. Then, computer codes will be developed (e.g. using Python) to extract information from the chemical structure of the molecule: number of rotatable bonds, aliphatic and aromatic rings, heteroatoms etc. In addition, quantum chemistry software will be used to calculate electronic and orbital properties, like HOMO/LUMO energies, emission/absorption maxima, ionization potentials etc. Finally, additional Python codes will be developed to write simple machine learning models that are able to detect patterns in our data.

Machine learning models are trained with a representative subset of the data, and their performance is tested on an unknown sample of data. This way, one can train models capable of predicting the efficiency of prospective HTMs. Due to the complexity of these systems, it is not clear which structural and electronic properties have a larger correlation with the efficiency. However, one can analyse the models to identify the most relevant properties used to train the model, and use this information to gain new insight on which properties affect the efficiency.

33. Project Title: Synthesis and toxicity testing of diet-derived glucuronides

Supervisors: Dr Andrew Stachulski (Dept. Chemistry) and Dr Ed Yates (Dept. Biochemistry & Systems Biology)

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Description: The human body is subjected to daily contact with potentially damaging toxins that include phenolic compounds and their derivatives that include carboxylated and hydroxylated forms and cresols [1]. These can arise from the natural environment, for example, from dietary plant polyphenols and anthrocyanins, the digestion of particular amino acids from food (L-Tyrosine to p-cresol) or, from the breakdown of drugs, such as the anaesthetic, propofol. The potential effects of these materials are now beginning to be elucidated in more detail but, the body's own clearance mechanisms include derivatisation to β D-glucuronides, to increase solubility and aid clearance. This summer project arose from our on-going work establishing both a direct synthetic route to the production of defined standards for metabolomic analysis (by HPLC, mass spec and NMR) and testing of their toxicity in cells [2], which is part of our wider collaborative effort investigating the interplay of these compounds with host intestinal bacteria and health and to developing methods for their detection and quantification (the subject of a BBSRC application involving AVS).

This summer project, hosted by Dr Andrew Stachulski (Dept. Chemistry), will provide complementary, cross-faculty training in the chemical synthesis of glucuronides, the targets comprising the β-D-glucuronides of several breakdown products of naturally-occurring plant anthrocyanins, together with characterisation (NMR spectroscopy) and testing of their effect on human cells in collaboration with Dr Edwin Yates (Dept. Biochemistry & Systems Biology).

We are also involved with several external collaborations, offering additional expertise in metabolomic analysis of gut bacteria and the effects of these materials on a range of cell types.

References

[1]. AV Stachulski and X Meng. Glucuronides from metabolites to medicines: a survey of the in vivo generation, chemical synthesis and properties of glucuronides. Nat. Prod. Rep., (2013) 30, 806.

[2]. JA London, ECS Wang, IL Barsukov, EA Yates and AV Stachulski. Synthesis and toxicity profile in 293 human embryonic kidney cells of the β-D-glucuronide derivatives of ortho-, meta- and para-cresols. Carbohydr. Res., (2021) 499, 108225.

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DEPARTMENT OF MATHEMATICAL SCIENCES

34. Project Title: From random walks to random trees

Supervisors: Dr Gabriel Hernan Berzunza Ojeda

Pick a tree uniformly at random amongst the nn−2 different trees on a set of n labelled vertices, say {1,2 ,... , n }. How does this (random) tree look like?

Description: In this project, we are going to use one-dimensional random walks to answer the previous question and to study the geometry of random trees coding the genealogy of an (asexual) population, where individuals reproduce independently of each other according to the same offspring distribution. These are the famous Galton-Watson trees.

A random walk is a simple mathematical model that consists of a succession of random steps on some mathematical space. They have several applications to engineering and many scientific fields including ecology, computer science, physics, chemistry, biology, economics, and sociology. In particular, the long-term behaviour of one-dimensional random walks leads to the famous Brownian motion. Therefore, random walks represent a fundamental object of study in mathematics.

On the other hand, trees are an important concept in both pure and applied mathematics, appearing (for example) in biology to represent genealogies, in computer science as a data structure, as well as an important example of a combinatorial class. More importantly, random trees are useful in analysing the asymptotic behaviour of certain families of deterministic trees and real-world networks. For example, Galton-Watson trees are used to study the phase transition for the component sizes in the well-known model of the random graph due to Erdös and Rényi.

The project requires a strong background in combinatorics and probability theory. In thisproject, besides the theoretical aspects, the student will also have the opportunity to simulate the random walks associated with Galton-Watson trees, and perhaps the Galton-Watson tree itself.

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Figure: From left to right, a simulation of a one-dimensional random walk and a large critical Galton-Watson tree.

DEPARTMENT OF PHYSICS

35. Project Title: Optimising magnetic nanostructures using thermal probe lithography

Supervisors: Liam O’Brien

Description: In condensed matter physics research, patterning samples to nanoscale dimensions provides a key method to probe the electrical, optical, magnetic and structural properties of new materials, on lengthscales inaccessible to bulk measurements. This approach continues to elucidate new phenomena in a variety of fields, from energy applications to 2D materials. It is particularly important, for example, in thin film magnetism, where the patterned shape (islands, wires, discs...) and competition between energy terms at these lengthscales lead to entirely unconventional equilibrium configurations of the collective magnetic state.

In this project we will use a newly available fabrication technique at UoL, termed thermal scanning probe lithography, to pattern arrays of magnetic nanoscale element, tuning their interaction and observing the corresponding magnetic reversal. The project will develop a set of methods and thermal treatments for the fabrication of high-quality nanoscale magnetic devices. The aim will be to test the feasibility of using the method to develop new, novel magnetic groundstates, previously inaccessible from more conventional lithography techniques.

The project will run for up to 10 weeks and is ideally suited for a student interested in experimental condensed matter, nanoscale and device physics.

36. Project Title: Studying the effects of electron beam distribution on X-ray beam generation

Supervisors: Dr Tessa Charles

Description: Synchrotron light sources have proven to be an incredibly powerful tool in a range of applications including cultural heritage studies. Various techniques involving synchrotron radiation allow researchers perform chemical analysis on object of cultural significance, in a non-destructive and non-invasive manner. However, in some cases it may not be feasible to remove an object from the field or museum, in which case more compact particle accelerators are needed.

This project will investigate the impact of the accelerated electron beam properties on the output X-Ray beam distribution, in a compact linear accelerator. In general, smaller electron beam size and smaller energy spread are desirable when generating intense X-rays. This project will determine the relationship between these electron beam parameters, as well as other important parameters such as the target thickness, on the intensity and directionality of the output X-ray beam, to determine limits and optimal configurations of a future compact X-ray source.

This project will be mainly computational and will allow the intern to gain understanding of important accelerator physics concepts. The intern will perform a range of simulations relating to the X-ray production component of a larger project, that is considering the feasibility of compact accelerators for cultural heritage applications. Finally, this project will provide a good introduction to particle accelerators and allow an interested student to gain first-hand experience of simulation-based research with practical applications in mind.

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37. Project Title: Electrochemical formation and characterisation of catalytic layers for oxygen evolution from water using earth-abundant metal oxides for greenhouse gas reduction technology

Supervisors: A. Creeth (Andrew.Creeth@liverpool.ac.uk), Dr Y. Grunder (Yvonne.grunder@liverpool.ac.uk )

Description: Electrolysis is the process of converting electrical energy into chemical energy by storing electrons in the form of stable chemical bonds. In the case of water energy is stored in hydrogen, which can be used as a fuel or converted back to electricity when needed. Electrolysis requires two catalytic processes to split water, generating hydrogen and oxygen respectively. Of these, the production of oxygen is a greater challenge due to the complexity of the processes involved. The development of new earth-abundant metal oxide-based catalysts for oxygen evolution is thus a major scientific and industrial challenge.

One route to produce such electrocatalysts is to produce layers of mixed metal oxides formed via electrochemical deposition. The layer has to be stable under the extreme conditions of high potential. This requires a stable structural component combined with an active component providing the required catalytic properties – e.g. Mn, Co. 3 The catalysts should be stable under the reaction conditions acidic conditions and ideally be based on earth-abundant and nontoxic materials.4

The project will begin with a short literature search, to place the proposed research in context, training in the laboratory methods and a systematic study to develop a preparation protocol for catalytic layers stable and active in acidic conditions by electrochemical deposition of appropriate. The layers will subsequently be tested for their oxygen evolution capability and characterised via electrochemical methods and complementary surface techniques (if COVID travel restrictions allow this could involve characterisation of the layers at the x-ray source based in Grenoble)

The project will be closely supervised and involve practical experiments, equipment design and data analysis.

38. Project Title: Non-invasive particle beam property measurements using machine learning

Supervisors: Dr Joseph Wolfenden and Dr Egidijus Kukstas

Description: Accelerator facilities require an exact understanding of the particle beam properties they provide to their users; e.g. fundamental physics experiments, spectroscopy, or medical treatments. For facilities which produce ultra-short electron bunches (e.g. free electron lasers, novel accelerators, etc.), at <100 femtoseconds, the longitudinal profile can be extremely difficult to measure. Conventional ways of measuring this profile involve destroying the beam in the process, or give limited online information. This restricts full bunch profile measurements to the calibration stage, prior to when the beam is used. An “online diagnostic” measurement is much more desirable, whereby, bunch profiles are measured at the same time as the experiment is carried out on a bunch-by-bunch basis.

3 M. W. Kanan and D. G. Nocera, Science, 2008, 321, 1072–10754 E.g. M. Huynh, T. Ozel, C. Liu, E. C. Lau and D. G. Nocera, Chem. Sci., 2017, 8, 477927 | P a g e

Coherent transition radiation (CTR) originates as a beam passes through a dielectric screen. The electric field of the particles interacts with the foil and emits radiation, which carries information about the beam structure. The beam itself is largely unaffected by this interaction, making this technique minimally-invasive.

Extraction of bunch profile measurements from CTR images is non-trivial. The width of a CTR image has been demonstrated to correlate well with the length of the overall bunch profile, but the mapping between the two quantities is highly non-linear. A more sophisticated technique should extract further profile information encoded within the image.

Supervised machine learning (ML) models are ideally suited for this task as they have the capability of fitting such non-linear mappings. In this case, a model will be trained using CTR images and bunch profiles (simulated and measured) in order to make predictions for when bunch profile measurements are not available. The student will gain understanding of beam diagnostic and data manipulation techniques, as well as experience in training machine learning models.

39. Project Title: Fluid dynamics of a gas-filled capillary plasma target under high-voltage discharges

Supervisors: Dr Oznur Apsimon and Professor Carsten Welsch

Description: High power laser pulses or high-energy charged particles can drive tens of GV/m electric fields whilst traversing a plasma. This relies on either the Coulomb force of particles or ponderomotive force of laser pulses. Plasmas generated in capillary tubes ionised by high voltage discharges are becoming popular targets. This is because they can sustain much longer plasma columns and have a potential for scalability. Once a discharge ionises such a target, plasma density profile evolves in time. A spaciotemporal characterisation of the target provides timing for formation of a parabolic plasma channel which allows high power lasers propagate in plasmas for multiple Rayleigh lengths with a constant spot size under certain matching conditions. This enables control over the interaction length of a laser with plasma target . Channel formation is simulated using specialist fluid dynamics codes such as OpenFoam and Fluent. In this project, a capillary source will be numerically modelled for spatiotemporal characterisation and study of correlation with discharge circuit properties. The student will:

Model the plasma resistance and evolution of discharge current as a function of time and circuit characteristics to explore their correlation with radial plasma channel profile,

Benchmark OpenFoam against Fluent,

Identify of the spatiotemporal characteristics of plasma density profile for a capillary-based discharge plasma target compatible with LATTE laser in Daresbury Laboratory.

Once the plasma characteristics are studied in depth, this can be not necessarily but possibly extended towards the interaction of such a plasma channel with a high-power laser pulse using particle-in-cell solver, EPOCH. If required by covid restrictions, this project can be executed and delivered remotely via regular online meetings with the student, supervisory team and expert colleagues.

40. Project Title: Model of the beam cavity interaction in the CERN PS

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Supervisors: Dr Aaron Farricker

Description: The Proton Synchrotron (PS) at CERN is an important part of the injector chain responsible for producing beams for several experiments, such as the High Luminosity-LHC (HL-LHC). To produce the beams with a quality that can be used in the HL-LHC, the spread in bunch parameters along each batch of protons must be reduced. To reduce the beam induced voltage responsible for the spread in bunch parameters a new multi-harmonic feedback system for the main RF accelerating cavities is proposed. Compared to the present one-turn delay feedback, this system can significantly increase gain therefore reducing the beam induced voltage. As this project has strong links with CERN we would like the student be an active part of the collaboration with the Radio Frequency group at CERN. The student will be responsible for developing a model of the beam cavity interaction in the PS. This model will help to set the requirements of the system and to determine the improvement with such a scheme installed. Additionally, the student will include this model in the beam tracking code BLonD to demonstrate the improvement in the bunch-by-bunch parameters.

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School of Engineering

SCHOOL OF ENGINEERING

41. Project Title: Bio-inspired morphing solutions for aeroelastic problems.

Supervisors: Dr Sebastiano Fichera, School of Engineering

Description: Aim: This PhD project will explore morphing designs as redundancy systems for actively controlled aeroelastic structures.

Aircraft fuel efficiency can be improved by unlocking the potential of aeroelasticity in the aeronautical design. However, same levels of safety of the ‘conventional design’ need to be guaranteed at all time. To do so, we propose to use bio-inspired structures that react to off-design changes in the dynamic or unsteady aerodynamics loads by morphing the geometry of the structure or the aerodynamic shape. By doing so, the morphed structure falls back within the design safety boundaries. It is foreseen that such solutions will be passive (i.e. no actuation required) and will morph their shape thanks to the intelligence embedded in the structural design.

Two morphing strategies will be explored: 1) the load bearing structure is designed with breaking points that collapse, in a controlled fashion, if the dynamic loads rise above a certain threshold. By doing so, the morphed structure falls back into a stable condition. It is foreseen that for this approach wing-span morphing will be explored, and 2) the aerofoil internal structure features auxetic or origami structures that, if loaded with off-design unsteady aerodynamic loads, passively morph the aerofoil shape. The resulting geometry produces unsteady aerodynamic loads that do not have a destabilizing effect on the aerostructure. The project is both numerical and experimental and the wind tunnel (WT) facilities of the UoL will be used.

The student will be required to review the literature related morphing for aeroelastic models [1 week], complete the conceptual and preliminary design of one of the two morphing solutions [2 weeks], manufacture and assemble it in the wind tunnel of the University of Liverpool [4 weeks], conduct an experimental campaign to validate it [2 weeks], and write a report [1 week].

42. Project Title: Design, manufacturing and experimental validation of a gust generator for aeroelastic model.

Supervisors: Dr Sebastiano Fichera, School of Engineering

Description: A deeper understanding of the aeroelastic behaviour of aeronautical linear and non-linear structures is becoming more and more important over the last decades. The path to the goal of having lighter and more efficient aircraft (i.e. maximise the payload) passes through the ability of controlling the flutter/LCO instabilities to a great extent.

Closely related to this research area, there is the ability to reduce the gust effects. Over the past years, two aeroelastic models have been built within the School of Engineering of the University of Liverpool to be used as experimental rigs for testing different control algorithms.

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Figure 1 – MODFLEX

Figure 2 - 2D Rig To push further this research, it is necessary now to extend the wind tunnel facility to accommodate a gust generator.

The gust generator will be composed mainly by two parallel aerofoils with rotating-slotted-cylinders (actuated through brushless motors) at the trailing edges and controlled in close-loop (by encoders) by a real-time system.

Figure 3 - gust generator [1]

The student will be required to review the literature related to gust generator for aeroelastic models [1 week], complete the conceptual and preliminary design of the gust generator [2 weeks], manufacture and assemble it in the wind tunnel of the University of Liverpool [4 weeks], conduct an experimental campaign to validate it [2 weeks], and write a report [1 week].

[1] D. M. Tang, P. G. a. Cizmas, and E. H. Dowell, “Experiments and analysis for a gust generator in a wind tunnel,” Journal of Aircraft, vol. 33, no. 1, pp. 139–148, Jan. 1996.

43. Project Title: Study of Pathological Airways using Computational Fluid Dynamics

Supervisors: Dr Sebastian Timme, School of Engineering, Andrew Kinshuck, Liverpool University Hospitals NHS Foundation Trust

Description: Airway stenosis is narrowing of the human airway which can result in severe breathing difficulty. Airway stenosis can occur at different levels including the larynx, trachea or bronchi. A specific condition known as subglottic stenosis occurs when there is a circumferential narrowing in the region of the upper trachea (and just below the vocal cords) known as the subglottis. Patients typically complain of worsening breathlessness especially during any 31 | P a g e

exertion. Diagnosis is made with imaging and endoscopic assessment. In the first instance endoscopic treatment is performed using laser and balloon dilatation to widen the airway. In severe cases the patient may require a tracheostomy to bypass the obstruction. In the long term the patient may require a resection of this part of the airway if it recurs following endoscopic treatment.

It is important to analyse the amount of narrowing (stenosis) and to assess the patient’s symptoms before embarking on invasive surgery. Understanding the relationship with airflow through the stenosis is relevant when planning the patient’s treatment. Computational fluid dynamics (CFD) will help determine the reasons for the patient’s symptoms and potentially what percentage of airway narrowing requires intervention. Patients have imaging (such as computerised tomography) of their airway as part of their workup to assess for underlying causes and level of stenosis. The images can be used to capture the geometry of the stenosis and airway and to form a three-dimensional image matrix. From this matrix, CFD simulation can be performed.

The student will explore the entire simulation chain including geometry reconstruction from imaging, meshing, solving and post-processing.

The project is a collaboration with Liverpool University Hospitals NHS Foundation Trust. A student would be able to attend the operating theatre to see the surgery and how the airway stenosis is treated and understand the symptoms and impact on the quality of life.

44. Project Title: Artificial Muscle

Supervisors: Dr Ben Salem Bernard, Robotics - AI – Interactions, School of Engineering

IntroductionArtificial MuscleAn artificial muscle based on Shape Memory Alloys (SMA) is being developed in the School of Engineering under the supervision of Ben SALEM, with the aim of providing a precise and rapid actuation of a dexterous robotic manipulator. From 2018, a series of Artificial Muscle prototypes were developed using shape memory alloy actuators (see Fig. 1). You are encouraged to make some improvements to the last design of the Artificial Muscle as part of the preparatory work of your project. You are then invited to develop an effective actuator that, in the future, will be integrated within an agile robotic manipulator. Currently, version 5 of the actuator is being finalised.

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Fig 1 – Artificial Muscle Prototypes (Version 1 to 4)

Sensor TechnologyVarious sensor principles were investigated (resistive, optical, and ultrasounds). We have developed our own capacitive sensors that rely on sliding tubes at the core of the Artificial Muscle mechanical design. This variable capacity is used within a Monostable Multivibrator circuit. The drawback of this approach is the requirement for the artificial muscle to be actuated along a single axis. Work on sensor principles that will allow the Artificial Muscle to bend in many directions could be undertaken as furthering the development of version 6 of the actuator.

Synopsis Your work will be based on the improved engineering of the Artificial Muscle already developed. You will conceive, develop, build, and test a further improved design for the artificial muscle, over a minimum of two iterations. Once completed you will demonstrate your prototype, you will then implement an effective sensory technology to monitor and control the manipulator.

Remarks This project is research-driven, a demonstration to the industry is planned as well as a publication at a conference on Robotics. The successful student will either have their name in the acknowledgments or if appropriate as a co-author of any publications.

Work The student will play an active role in the research of the project and to contribute to academic research first hand. This project is an opportunity to combine principles from a variety of engineering and design disciplines and will encourage the student to rely on theoretical and experimental principles to produce an effective improvement to the Artificial Muscle leading to version 6 of the actuator.

Context This is an on-going research project in the area of Artificial Muscles. The work proposed in this internship will help further advance the design and the control of the Artificial Muscles being developed. Version 5 of the Artificial Muscle is currently being fabricated, and it is hoped that the summer intern will take over the project to make further progress.

How Lab space, access to the previous Artificial Muscles prototypes, and a networked PC with specialist software will be made available to the student for the duration of the project. At the start of the project there will be a launch meeting to agree on a detailed work plan for the project, including milestones. There will be weekly regular meetings to check on progress and discuss issues and challenges if any. At the end of the project arrangements will be made for the student to present and demonstrate their work to the project’s potential industry clients.

TRL 6 to 7 Technology prototype demonstration in an operational environment

COVID-19 Some parts of this project can be conducted remotely, although not an ideal arrangement, this would mitigate some of the restrictions, if any are still in place by summer 2021, due to COVID-19. If necessary, and in a worst case scenario, all the work

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can be remotely conducted, with simulations of the Artificial Muscle.

45. Project Title: LEARN - multi- LE vel A utonomy for R econfiguration & N avigation

Supervisors: Dr Ben Salem Bernard, Robotics - AI – Interactions, School of Engineering

Introduction We have been developing a system for IED localisation and other missions consisting of two modular sub-systems: an all-terrain robot coupled with a command and deployment Unmanned Aerial Vehicle (see fig.1). Robot and drone are autonomously reconfigurable according to the mission, context, and status. They autonomously assemble and disconnect via connecting terminals (for airlifting and dropping the robot up to 2mtrs). The overall project is about the development of up to 5 levels of autonomy control for reconfiguration and navigation of the robot (see fig. 2).

Fig 1 – Current robot and drone prototypes

Levels of autonomyThe robot as it currently stands features a level of autonomy that is 0 (i.e. remote controlled) and 1 (i.e. programmed) and 2 (i.e. semi-automated) for some functions. We propose to further the autonomy of the robot to level 3 (i.e. automated) and 4 (i.e. with agency) for most functions and to level 5 (i.e. with volution) for some navigation functions. For the purpose of this project, we are aiming to achieve level 3 and possibly level 4.

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Fig 2 – Five levels of autonomy for reconfiguration and navigation

Synopsis Your work will be based on developing a control algorithm and its implementation for the reconfiguration of the modular robot from 1 to 2 modules and the navigation of the robot with a level of autonomy 3 to 4 (see fig. 2).

Remarks This project is research-driven, a demonstration to the industry is planned as well as a publication at a conference on Robotics. The successful student will either have their name in the acknowledgments or if appropriate as a co-author of any publications.

Work The student will play an active role in the research of the project and to contribute to academic research first hand. This project is an opportunity to combine principles from a variety of engineering disciplines and will encourage the student to rely on theoretical principles and industry practices to produce an effective control algorithm for an autonomous robot.

Context This is an on-going research project on a Homogeneous omni-directional modular robot called PetRo that will be used for search and rescue and inspection of damaged structures. The robot and drone have been designed and fabricated and are currently undergoing testing. However, there is a need to develop and implement a control algorithm to deliver autonomy in the reconfiguration and navigation of the robot.

How Lab space, access to the robot, and a networked PC with specialist software will be made available to the student for the duration of the project. There will also be the opportunity to use a prototype model autonomous vehicle (controlled by a Jetson TX2 board and equipped with stereo, depth cameras, as well as LIDAR, and a variety of sensors) as a test platform.At the start of the project there will be a launch meeting to agree on a detailed work plan for the project, including milestones. There will be weekly regular meetings to check on progress and discuss issues and challenges if any. At the end of the project arrangements will be made for the student to present and demonstrate their work to the project’s potential industry clients.

TRL 4 to 5 Technology basic validation in a relevant environment

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COVID-19 Most parts of this project can be conducted remotely, although not an ideal arrangement, this would mitigate any restrictions, if any are still in place by summer 2021, due to COVID-19. If necessary, and in a worst case scenario, all the work can be remotely conducted, with simulations of the robot’s autonomy.

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46. Project Title: PetRo 6

Supervisors: Dr Ben Salem Bernard, Robotics - AI – Interactions, School of Engineering

Introduction PetRo is an omnidirectional Homogeneous Modular Robot (HMR) that has been developed in-house over the years. PetRo is self-assembling and throwable, implying that a number of isolated single modules are capable of regrouping and assembling into a desired configuration within the theatre of operations. This also implies that each module does not require particular handling, and that it is sufficiently robust to be literally thrown into the theatre of operation.We have been developing a series of homogeneous modular robots (HMR) called PetRo and have completed version 4 for testing (fig. 1). A task specific version has been designed, Version 5, for the replacement of overhead copper wires with fiber optics (fig. 1) with BT as a client. This project will focus on making improvements to the PetRo platform and deliver version 6 of the robot.

Fig 1 – PetRo 4 prototype and PetRo 5 CAD model

Connecting TerminalsThe design, modelling, fabrication of the Connecting terminals has been completed (fig. 2). It is a mechanism for the locking-in and securing of the assembly of robot modules, and of a robot module to a drone for airlifting, and then release at the theatre of operation. The design approach has focused on efficiency (power to release), safety (redundant mechanisms), and fast response (low-latency actuators). It should deliver a symmetrical mechanism (there are no male or female mechanisms). A current set of 2 prototypes has been partially fabricated and need to be completed.

Fig. 2 – Connecting terminal prototype (l. Single, r. coupled)

Sensor Hubs

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One of the features of the robot is the sensor hubs that attach to the core frame of the robot and can be replaced, allowing for a quick reconfiguration of the sensing capabilities of the robot for a variety of scenarios of operation. A current prototype has been partially fabricated and needs to be completed (fig. 3), alongside the development of a mission specific one for human presence detection.

Fig. 3 – Sensors hub and PetRo 4.20 CAD model The work will be on the improved design, modelling, fabrication and testing of the sensor hubs, as well as their attachment mechanism to the frame of the robot. The approach should focus on an effective combination of sensors for navigation, orientation, context awareness and event detection, and any specifics depending on the mission. The sensor data will be used for the control of the robot as well as for the mission performance as well as to perform system wide integrity checks.

Synopsis Your work will be on the design, modelling, fabrication and testing of any combination of:

● Improvements to the PetRo module mechanisms, body anatomy, and structural integrity

● Connecting terminals for the self-assembling of modules● Generic, and mission specific sensor hubs (including sensor data processing and

merger)● Control, autonomy and navigation

Remarks This project is research-driven, a demonstration to the industry is planned as well as a publication at a conference on Robotics. The successful student will either have their name in the acknowledgments or if appropriate as a co-author of any publications.

Work The student will play an active role in the research of the project and to contribute to academic research first hand. This project is an opportunity to combine principles from a variety of engineering disciplines and will encourage the student to rely on theoretical principles and practices to produce an effective autonomous HMR prototype.

Context This is an on-going research project on a Homogeneous omni-directional modular robot called PetRo that will be used for search and rescue and inspection of damaged structures. The robot will assemble with other modules as a key feature of its reconfigurability. It will also assemble with a drone for airlifting. However, there is a need to develop an improved version of the module, leading to PetRo 6.

How Lab space, access to the robot, and a networked PC with specialist software will be made available to the student for the duration of the project.

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At the start of the project there will be a launch meeting to agree on a detailed work plan for the project, including milestones. There will be weekly regular meetings to check on progress and discuss issues and challenges if any. At the end of the project arrangements will be made for the student to present and demonstrate their work to the project’s potential industry clients.

TRL 5 to 6 Technology model or prototype demonstration in a relevant environment

COVID-19 Most parts of this project can be conducted remotely, although not an ideal arrangement, this would mitigate any restrictions, if any are still in place by summer 2021, due to COVID-19. If necessary, and in a worst case scenario, all the work can be remotely conducted and based on CAD modelling and simulation, without physical prototyping.

47. Project Title: Developing Techniques for Low Cost Rapid Manufacturing of Perovskite Solar Cells

Supervisors: Dr Amanda Jane Hughes – Mechanical Engineering, Dr Laurie Philips – Stephenson Institute of Renewable Energy, School of Engineering

Description: We are at a critical moment in the fight against climate change. It is essential that renewable alternatives for energy production are highly efficient, cheap to produce at large scale, and with short energy payback times. Metal-halide perovskites are a photovoltaic material that have seen a rapid rise in efficiency in recent years with the latest record at 25.2%, approaching the top values achieved by the market leading silicon solar cells. With their high efficiencies and suitability for low cost manufacturing methods, perovskites have shown great promise for sustainable solar and the challenge now is to transition into commercial production.

Perovskite structured materials have the general formula ABX3, and can have very different properties depending on the chemical mix used at the various sites; A (Cs, Rb, MA, FA), B (Pb, Sn), and X (I, Br, Cl), methylammonium lead iodide (MAPbI3) being the most well studied. Tunable properties provide huge opportunities not available for most thin-film solar absorbers, including the potential to stack perovskites with different bandgaps in a tandem cell to use more of the solar spectrum and beat the Shockley-Queisser limit. The most developed tandems are perovskite-silicon, which have reached an impressive efficiency (27.3% - Oxford PV), but still rely on an energy expensive manufacturing process to create the silicon. Perovskite-perovskite tandem devices would allow for the increased efficiency of multi-junction photovoltaics while retaining the benefits of the low-temperature processing.

During this project the student intern will join us in the lab as we investigate perovskite-perovskite tandem devices for fabrication using ink-jet printing, to enable their low cost large scale manufacturing. This work will focus on designing modified ink-jet printer components to suit the perovskite processing requirements and developing new perovskite solutions with optimum properties for printing.

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48. Project Title: 3D-printed Origami Solar Sails for Next Generation of CubeSats

Supervisors: Dr Stefania Soldini, Department Mechanical, Materials & Aerospace, School of Engineering

Description: Spacecraft deployable devices are generally large structures (i.e. solar arrays, antennas, ect) stowed before launch, and deployed in-space utilising origami-based designs. To save mass and costs, these large structures tend to be thin. Due to their high reflectivity, the Sun photon radiation causes undesired torque on spacecraft. Therefore, attitude maintenance is required to counteract its effect. Conversely, solar sails are deployable structures (“space mirrors”) specifically designed to enhance the effect of the sun’s radiation as a primary form of fuel-free propulsion thus helping to facilitate a longer mission. However, all such large devices are currently designed to maintain a fixed-shape once deployed and a single spacecraft usually mounts multiple deployable structures for different purposes.

We propose Additive Manufacturing (AM) for next and future generations of deployable origami-based devices for shape-changing CubeSats. A CubeSat mounting a 3D-printed morphing solar sail can potentially modulate the intensity of the radiation for different mission purposes (i.e. fuel-free control manoeuvres or regulating thermo-optical properties). The reconfiguration of a solar sail’s shape triggered by changes in the local sail reflectivity could in turn pave the way to new missions. The intensity of the Sun radiation forces is proportional to changes in the overall CubeSat area-to-mass ratio. Since the CubeSat mass is fixed, the controllability of the CubeSat depends on the overall reflective area exposed to the Sun. Theoretical studies have shown that reflectivity changes in a sail membrane can trigger a reshaped configuration in origami-based sails. The design and manufacturing flexibility offered by AM techniques, together with its capability of combining multiple materials (structural, photo-voltaic, conductive etc.) in a single pass, will enable new and more effective design of solar sails and, as a consequence, of the whole CubeSat.

49. Project Title: Assessment of Immersive Environments in Flight Simulation

Supervisors: Prof Mark D White, Dr Wajih Memon, School of Engineering

Description: The qualification of a flight simulator for training purposes involves a number of objective and subjective assessments of the device prior to it being accepted as fit for purpose. Previous work undertaken in the Flight Science and Technology Research group in the School of Engineering has shown that meeting the qualification criteria contained within existing rotorcraft simulator standards does not necessarily guarantee production a device that is fit for purpose for training. The group is coordinating an international effort addressing the shortcomings of existing civil helicopter simulator qualification standards. In the current phase of work, the subjective assessment and the level of immersion a pilot feels in a simulator is being considered. At the final stage of the simulator qualification process a subjective evaluation of the simulator is undertaken by a pilot. One of the key influencing factors regarding the acceptance process is the level to which the pilot “engages” or is immersed in a virtual environment. There is little research available that quantifies the appropriate level of immersion, especially when using less complex simulator devices. This project would aim at integrating and assessing new VR technologies into the existing flight simulation environments to assess their impact on the level of immersion a pilot feels. The project will involve the design, testing and analysis of new simulation scenarios for rotorcraft flight simulators. The work would contribute to the ongoing research programme to develop new metrics to quantify the level of immersion and provide guidelines for future simulator qualification processes.

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50. Project Title: Beyond Programmable Matter

Supervisors: Dr Alfredo Leal (PDRA, with support by Dr Paolo Paoletti and Dr Sebastiano Fichera), School of Engineering

Description: Imagine hundreds of small units that can be programmed to selectively attach to each other to create a bigger functional device (a table, a chair, etc.) at a flick of your finger; this is what is known as programmable matter and it is akin to self-assembly processes that are at the basis of life in nature. Several recent theoretical results suggest that realising such “matter” is actually possible, but no convincing physical demo has been proposed yet. The supervisor is working on the EPSRC-funded BEST-Man project led by Dr Paoletti and has created the first proof-of-principle demo of a system capable of fully reconfiguring in 3D. However, additional functionalities (sensing, stiffness modulation etc) are lacking in the current proof-of-concept and the mechatronic design needs to be refined. For reference, similar projects are: M-Block (MIT), Kilobot (Harvard), Robot Pebbles (MIT), Millimotein (MIT), Catoms (Carnegie Mellon University/INRIA France).

The student will work alongside the researchers working on this project and will be required to a) design a new mechanical shell for the unit that allows proper placement of sensors and a novel actuation-by-deformation system [3 weeks], b) integrate the required sensors and actuators [3 weeks], c) write the control software [2 weeks] required to complete the final proof-of-principle demo [2 weeks]. Several of such devices will be designed using CAD first and then manufactured using 3D printing and PCB milling. The final demo will be a system composed of at least 5 devices capable of changing their collective shape from a cube to a pyramid and modulate the overall stiffness of the cube/pyramid.

51. Project Title: Automating road maintenance

Supervisors: Mr Christos Saant (PhD candidate, with Dr Paolo Paoletti and Sebastiano Fichera as support)

Description: The construction industry is changing, as the time- and labour-intensive construction and repair processes utilised nowadays are not sustainable in the long run. The next generation of construction processes requires a dramatic reduction in cost and time needed to perform operations, an improved labour safety, a more stringent quality control and a faster response time. Robots will play a big role in allowing the construction industry to meet their future performance and efficiency goals.

Within his PhD project, the supervisor is developing a device to autonomously repair minor road defects by integrating infrared heaters and a bespoke sealant deposition system onto a mobile robotic base. A proof-of-principle robot capable of repairing cracks and potholes has already been created, but it lacks infrared heating and the the range of materials that can be handled by the deposition system is still quite limited.

The student will work alongside the supervisor to design the next generation of autonomous road repair platforms. The project will involve performing a literature review of the existing approaches [2 weeks], designing the new platform using CAD [4 weeks], manufacturing the device [2 weeks] and testing its performance in a lab setting [2 weeks]. If successful, the outcome of this project will be integrated in the existing platform to create a demo where the robot will identify a crack, heat it and fill with a suitable sealant to prevent it becoming a pothole.

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52. Project Title: Soft robotic touch

Supervisors: Dr Paolo Paoletti and Dr Fichera (School of Engineering), Dr Shan Luo (Computer Science)

Description: Many of the challenges faced by robotics today deal with uncertainty in robot-robot, robot-human and robot-environment interaction; traditional robots struggle in these uncertain scenarios. Soft robots, manufactured either with compliant mechanisms or using compliant materials such as silicone elastomers, are an emerging approach to tackle modern challenges. Their inherent adaptability to the outer world may eradicate the need of complex control strategies for highly precise, thus safe, movements. Their “embodied intelligence”, where the mechanical response alleviates the burden traditionally associated to real-time feedback controllers, is revolutionising the field of robotics. However, modelling and control of such compliant actuators are still in their infancy when compared to stiff robotics, and this is mainly due to the lack of suitable soft sensors that can be integrated with these actuators.

Figure 1 Fig. 1 Spectrum of soft robots approaches grading from mostly stiff with a few selectively compliant elements (left) to entirely soft (right), from SCIENCE ROBOTICS 2016.

The Royal Society-sponsored project “Flex-Handle” led by Paoletti explores how advanced manufacturing and materials can be exploited to create the required soft sensors, with particular focus on tactile sensors capable of augmenting soft robots with the sense of touch. The student will contribute to this project by designing, manufacturing and testing new sensors to be embedded in soft actuators. More specifically, the student will be asked to complete a literature review on soft-sensors [2 weeks], use CAD to design an actuator with integrated sensing [3 weeks] and manufacture the designed actuator [2 weeks]. A final demo where the actuator performs a pick-and-place task with fabric while collecting data via the integrated sensors will be set up to showcase results [3 weeks].

53. Project Title: Vortex breakdown in pipe flow with growing swirl of fluids with shear-dependent viscosity

Supervisors: Dr David JC Dennis, Department Mechanical, Materials & Aerospace, School of Engineering

Description: Vortex breakdown of swirling flows – the formation of a stagnation point upstream of a region of near-stagnant recirculating flow – has fascinated and intrigued many since its discovery over 60 years ago. One of the key reasons for such continued study is the inherent artistic beauty embedded within it ( https://youtu.be/b0TylIqcEsQ), coupled with the non-trivial fluid dynamics at play. Vortex breakdown in swirling pipe flow was recently investigated experimentally and numerically using a Newtonian fluid [Dennis, D.J.C., Seraudie, C. and Poole, R.J., 2014. Controlling vortex breakdown in swirling pipe flows: experiments and simulations. Physics of Fluids, 26(5), p.053602, https://doi.org/10.1063/1.4875486] and for fluids with shear-dependent viscosity [Thornhill, T.O., Petit, T., Poole, R.J. and Dennis, D.J.C., 2018. Vortex breakdown in swirling pipe flow of fluids with shear-dependent viscosity. Physics

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of Fluids, 30(11), p.114107, https://doi.org/10.1063/1.5057409.]. The work using shear-dependent viscosity fluids revealed a new scaling using a Reynolds number with a viscosity based on a shear rate dependent on the rotational speed of the pipe (rather than the bulk flow), making it possible to very easily predict (with reasonable accuracy) the critical swirl ratio required to induce vortex breakdown, and the size of the recirculation bubble, for any fluid with shear-dependent viscosity.

In the proposed project the EPSRC Vacation intern will extend the work on shear-dependent fluids by numerically simulating flows with growing swirl, which have not yet been studied. They will be using Fluent CFD software in ANSYS Workbench to simulate a wide range of fluids in order to test the new Reynolds number scaling. If work progresses well, there may also be the opportunity to validate the simulations by performing experiments in the fluids laboratory. The project would suit a student interested in fluid mechanics and numerical simulations."

54. Project Title: Multifocal soft contact lenses design

Supervisors: Dr Ahmed Abass Description: Multifocal soft contact lenses are medical devices used to correct the eye refractive error through different power prescriptions with one lens. Unlike multifocal spectacle lenses which are used in multifocal glasses, multifocal soft contact lenses should be designed to fit the user’s eye beside being able to correct his vision at different distances. Multifocal versions of contact lenses are designed to permit more than one lens power to be able to correct the user’s vision at multi-distances after he loses the capability to naturally change the focus of his eyes because of age (presbyopia).

In this project, students will design the geometry and select the materials of a range of Multifocal contact lenses then test their optical power before and after the fitting process. The product design process will be carried out by a MATLAB software code, however, the process of fitting contact lenses to human eyes will be simulated by Abaqus finite element software where the 3D change in the shape of contact lenses can be monitored and recorded. The student will then use knowledge gained from this exercise to obtain correction factors, in terms of positions and angles, that can be used to take the position of the visual axis and the deflection of multifocal soft contact lenses in account when designing multifocal contact lenses.

Dr Abass (ORCID iD) uses his supervision to educate his students on how to be independent learners, develop their research skills quickly and requiring less support gradually towards the end of their work. Several of Dr Abass’ UG students are either first or co-authors in Q1 journal papers benefited from their projects.

55. Project Title: Simulating wrist motion in ex vivo specimens

Supervisors: Joanna Glanville (PhD student - School of Engineering)Co-supervisors: Dr Sebastiano Fichera (School of Engineering); Dr Karl Bates (Institute of Life Course & Medical Sciences)

Description: Cadaveric material has proved to be an invaluable resource for the development and validation of joint replacement prostheses. However, one must be cautious when extrapolating conclusions drawn from ex vivo studies to live human joints. For this reason, it can be advantageous for cadaveric studies to mimic in vivo conditions as closely as possible. For example, movement of a joint specimen better reflects human physiology when achieved via

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the simulation of anatomical muscle contractions. Hence, many research groups are using motion simulating devices to manipulate their specimens in this manner.

Presently, the supervisors are developing a motion simulator which will animate cadaveric wrist joints. This is achieved through individually loading the tendons of five muscles which act to control the joint. In order to produce a target wrist motion using this device, it is necessary to pre-program the specific displacements of each tendon. An alternate system would be to calculate, in real-time, the required tendon manipulations to move the wrist from its current angle to a desired angle. The latter method would facilitate production of repeatable motions across multiple wrist specimens, as joint trajectories could be uniformly specified.

This project aims to investigate the incorporation of real-time motion capture data into the control of a wrist motion simulating device. The student will conduct a literature review of existing simulators [2 weeks], develop an algorithm for the production of a specific wrist movement trajectory (or trajectories) [5 weeks], test the efficacy of their control strategy using a mock wrist [2 weeks], and write a final project report [1 week].

56. Project Title: Modelling solidification dynamics to improve alloy strength using Laser Powder Bed Fusion (LPBF)

Supervisors: Dr M Patel and Richard Woods

Description: Additive manufacturing has transformed the way we produce components with improved mechanical properties and minimal waste. One method of 3D printing is Laser Powder Bed Fusion (LPBF), using a laser to fuse raw metallic alloy powder into desired component designs. Thermodynamically this process is differs from conventional melting and casting because of fast non-equilibrium thermal process. Thus, limiting the use of conventional alloy powders, requiring new alloy compositions that will produce desired microstructure and mechanical properties. Selection Microstructure Selection (SMS) map is a tool used to predict the microstructure evolution of alloy compositions during solidification. The microstructure of solidified metal has important consequences with regards to the strength characteristics, generally finer grain structures lead to improved strength. A SMS map will enable the user to tailor the processing conditions ensuring the alloy meets their specific needs, depending on which application the alloy is to be used in, such as aerospace or automotive etc.

While we have the analytical framework of models to produce the SMS, more work is required to develop sophisticated tools to solve these analytical equations. This project is suited to any student who has an interest in coding of mathematical simulations which can be verified experimentally. Any student who wishes to partake in this project should have experience using MATLAB, other languages/programmes may be taken into account.

For this project the student will be tasked with creating a programme from the given mathematical equations to produce a SMS map, for a given alloy and processing parameters. The programme will then be tested by processing known alloys and characterising their microstructure experimentally, adjusting the code accordingly. This will give the student a good understanding of how to work in a research environment as a part of a research team, where skills are shared throughout towards an end goal.

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57. Project Title: An investigation of teledentistry: current and future applications, and implications for access to oral care.

Supervisors: Isobel Leason

Description: Teledentistry is the remote facilitating of dental treatment, guidance, and education via the use of information technology instead of direct face-to-face contact with patients. Whilst uptake of teledentistry was previously slow, it has become a critical tool since the COVID-19 pandemic and it’s uses are rapidly evolving.

There are inequities in the provision of oral healthcare, and many face challenges in accessing public dental health care options. Groups such as the older population; children and young adults; and neurodiverse, and physically disabled individuals; may be subjected to systemic health inequalities and exclusions. Teledentistry has the potential to expand access to oral health care and increase provision of oral health care to excluded groups. However, the use of technology and nature of interactions may exclude some individuals further. Furthermore, the rapid adoption of teledentistry means that there has been limited investigation into patient experiences, and the design requirements of teledentistry solutions. There is a need to take a patient-centred approach, reflecting on current implementations of teledentistry, and investigating the advantages and potential barriers that teledentistry presents to different patient groups.

The aim of this project will be to first investigate how and where teledentistry has been applied, then to use an inclusive design perspective to identify insights into the potential opportunities and challenges in applications of teledentistry to address oral health inequalities.

The student will be directly supervised by PhD student Isobel Leason, a 1st year PhD student with a background in Product Design Engineering with experience working in oral healthcare technologies. The student may also work with Dr Farnaz Nickpour and other members of The Inclusionaries Lab for human-centred design research and innovation (https://inclusionaries.com/).

References:

Jaffe, D.H., et al, 2020. Health Inequalities in the Use of Telehealth in the United States in the Lens of COVID-19. Population Health Management 23, 368–377.. doi:10.1089/pop.2020.0186

Estai, M., et al, 2020. Teledentistry as a novel pathway to improve dental health in school children: a research protocol for a randomised controlled trial. BMC Oral Health 20.. doi:10.1186/s12903-019-0992-1

Da Costa, et al, 2020. How Has Teledentistry Been Applied in Public Dental Health Services? An Integrative Review. Telemedicine and e-Health 26, 945–954.. doi:10.1089/tmj.2019.0122

58. Project Title: The future of data collection in hospice healthcare experiences and its potential impact

Supervisors: Andrew Tibbles

Description: There is now a myriad of ways that we can gather healthcare data from a person. Through ambient, wearable and implantable technologies medical professionals can create a richer, clearer picture when giving a diagnosis. The increasingly growing field has demonstrated that it is able to be commercially viable and desirable, increasing efficiency and decreasing costs while allowing hospital admissions to be reduced.

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The student will aim to produce a critical mapping review using developing methodological practice with further outcomes to be development of speculative hospice care experience scenarios that demonstrate the integration of these technologies into a wider future society and a SWOT analysis of each of these scenarios and establish further work.

The student does not need to be physically present in the University for this brief and can be achieved remotely. Knowledge of Speculative and Critical Design desirable but not essential. The student will be directly supervised by PhD student Andrew Tibbles, 1st year PhD student with a background in Product Design, Advanced Manufacturing CAD/CAM and Speculative Design. The student may also work with Dr Farnaz Nickpour and the Inclusionaries Lab for human-centred design research and innovation (https://inclusionaries.com/).

Sources:

Indrakumari, R. et al., 2020. The growing role of Internet of Things in healthcare wearables. Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach, pp.163–194.

Min Wu, P.D.and J.L., 2021. Wearable Technology Applications in Healthcare: A Literature Review. HIMSS. Available at: https://www.himss.org/resources/wearable-technology-applications-healthcare-literature-review.

GlobalData, August 2019. Wearable Technology in Healthcare. Available at:

http://www.tauli.cat/institut/wp-content/uploads/2020/06/wearables-GlobalData_WearableTechnologyinHealthcare_220819.pdf

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SCHOOL OF ENVIRONMENTAL SCIENCES

Department of Earth, Ocean and Ecological Sciences

59. Project Title: The stability of ferromagnetic droplets

Supervisors: Dr Greig Paterson, Department of Earth, Ocean and Ecological Sciences

Description: Magnetic nanoparticles are widely found in nature and their abundance and properties yield valuable insight into the workings of the natural world. Inspired by nature, these nanoparticles are now being widely studied for applications in industry, medicine, and biotechnology. Such tiny particles, however, are so small that they are typically unable to remember any magnetic field that they experience, a phenomenon known as superparamagnetism. As such, uses of these nanoparticles has been limited to applications using very strong magnetic fields.

Recent work, however, has shown that when magnetite nanoparticles are arranged around the surface of an oil droplet, the interaction of multiple nanoparticles produces a magnetic memory. That is, when the field is switched off, the droplets remain magnetic. These droplets therefore have huge potential for use in deformable magnetic storage, programable liquids, microfluid mixing/separation, among others. However, the mechanism behind this memory is not well known and for how long the memory lasts has never been investigated.

In this project, we will model the fundamental physics (known as micromagnetic modeling) behind how individual grains become magnetized to explore the fidelity of the magnetic memory of different configurations of nanoparticles. This will be the first attempt to model and explain the mechanisms behind this intriguing and potentially useful phenomenon.

The models will simulate the experiments of recent research that experimentally demonstrated that magnetic liquid droplets could retain a magnetic memory and establish the longevity of this memory. Droplet morphology will be investigated and novel approaches to improving magnetic memory will be explored.

The models will be run with existing code called MERRILL and computer competency is required for preparing model inputs and analyzing outputs. Programing experience is favorable, and some familiarity with Linux/unix would be useful.

60. Project Title: The transport of molten droplets in an air stream

Supervisors: Dr Thomas J. Jones

Description: The jetting of molten droplets in an air stream is important for a wide variety of manufacturing processes and industries (e.g. cement, food, cosmetics). During transport, these molten droplets have the potential to stretch into elongate fibres, relax to more spherical shapes and/or break apart before cooling to below their glass transition. Despite the complex array of physical processes operating, the resultant size and morphology of the cooled clasts must be accurately controlled to meet the specific requirements of each manufacturing need. The transport of molten drops is also ubiquitous during volcanic eruptions of low viscosity (< 10 3 Pa s) magma. In this

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case, the morphology and sizes of erupted material left in the deposits can be used in a ‘forensic’ manner to uncover the conditions of past eruptions (e.g. differential gas-droplet velocities).

Recent analogue experiments have quantified the timescales of molten droplet deformation and break up during a volcanic eruption. In this internship you will integrate these new experimental results into a thermal model for droplet cooling during transport. An assessment of the interacting timescales will help us better understand the spectrum of clast morphologies and sizes produced. Strong numerical and modelling (Matlab) skills would be advantageous for this internship. If Covid restrictions allow, it may be possible to perform some supporting laboratory experiments.

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