Chemical Engineering

This PhD project will develop sustainable, bio-based gas sensors for applications in environmental monitoring, healthcare and smart packaging. The research will explore renewable and low-impact materials, including bio-derived substrates, functional polymers and carbon-based sensing layers, combined with scalable printing and coating techniques. The student will investigate how material composition, device architecture and processing determine sensitivity, selectivity and stability when detecting gases such as ammonia, nitrogen dioxide and volatile organic compounds.

A central focus will be the complete life cycle of the sensors. The student will design devices for disassembly, recovery and recycling, investigating how substrates, electrodes and sensing materials can be separated and reused or safely biodegraded at the end of use. Working with collaborators in polymer chemistry and recycling, the project will connect device performance with biodegradation and recyclability assessments, establishing practical design principles for high-performance sensors that minimise resource consumption and electronic waste.

The successful candidates will join our team, which includes researchers from the Institute for Integrated Micro and Nano Systems, the School of Chemistry, and the wider College of Science and Engineering.

Before you apply: We strongly recommend that you contact the supervisor for this project before you apply.

https://eng.ed.ac.uk/sustainable-printable-electronics-research-group

• a 2:1 undergraduate degree (or equivalent).
• applicant's must meet the University’s English language requirements.

Applications are welcomed from self-funded students, or students who are applying for  scholarships from the University of Edinburgh or elsewhere

Funding may be available to Home students on a competitive basis. Candidates are invited to discuss potential funding opportunities.

Further information and other funding options.

Context

Reverse osmosis (RO) holds significant promise in alleviating global water scarcity through seawater desalination. But shortages of increasing frequency and intensity now demand treatment of unconventional waters beyond seawater, such as wastewater, to expand supply. RO is also increasingly deployed to treat industrial streams in microelectronics, pharmaceutical, and food & drink manufacturing, which must meet stringent water quality standards. In all cases, RO polyamide (PA) membranes – originally designed to reject charged (ionic) species in seawater – are increasingly challenged by small charge-neutral contaminants (SNC) that pass through largely unrejected. SNC include toxic disinfection by-products (e.g., nitrosamines) and organic pollutants (trihalomethanes, phenols, dioxanes, alcohols, ketones); their removal requires additional energy-intensive treatment stages. 

Answering the following two long-unresolved research questions (RQ) is key to shifting from a trial-and-error approach to rational membrane design, and achieving transformative improvements in SNC rejection: RQ1. What are the molecular-level mechanisms governing sorption and transport in RO membranes? RQ2. How can insights into sorption and transport be leveraged to efficiently search a vast library of possible membrane materials – the chemical design space – and discover highly selective, water-permeable membranes?

Objectives

We will tackle RQ1-2 through simulation and experiment to achieve our Overall Objective: to computationally discover new membrane materials for SNC removal by harnessing molecular dynamics (MD) simulation and machine learning (ML).

The project is structured along the following two Works Streams (WS) addressing RQ1-2. In WS1, MD simulation will elucidate molecular-level sorption and transport mechanisms, providing insights into the optimal membrane properties – pore sizes, interfacial chemistry – that boost selectivity. In WS2, a vast chemical design space formulated with insights from WS1 will be explored using a ML technique enabling computationally-efficient materials discovery. 

Research and Training

The successful applicant will conduct research in the School of Engineering at the University of Edinburgh, under the supervision of Dr Santiago Romero-Vargas Castrillón. The student will have access to a wide range of computational facilities. Educational and research opportunities afforded by this project include: 

• training in state-of-the-art molecular simulation techniques 

• close mentoring through regular meetings, as well as interactions with other investigators at the Institute of Multiscale Thermofluids (IMT) and the Institute for Infrastructure and Environment (IIE) at Edinburgh 

• the opportunity to attend national and international scientific conferences to disseminate your results 

• strong emphasis and support to publish research results in leading scientific journals, which will kickstart your career in academia or industry. 

This is a challenging and scientifically ambitious project, requiring a student who is dedicated and enthusiastic about asking, and tackling, fundamental questions. The successful applicant will have been awarded an undergraduate degree at the time of appointment (2:1 or above, preferably supported by an MSc) in chemical engineering, mechanical engineering, chemistry, physics, materials science, or a cognate field. A strong background in mathematics and physics is required, as well as interest in molecular simulation. Prior research experience in modelling and simulation is highly desirable.

We accept applications from qualified self-funded students. Qualified UK applicants (or those with EU settled status) may be supported to apply for highly competitive School of Engineering studentships.

Further information and other funding options.

Global context: By 2050 the global population is projected to reach nearly 10 billion, requiring an estimated 56% increase in food production compared to 2010, on less land, with fewer resources, and under mounting climate pressure. Crop protection products are essential to this challenge, safeguarding harvests from pests, weeds and disease. But manufacturing these agrochemicals sustainably is one of the industry's hardest unsolved problems. 

Scientific challenge: At the core of agrochemical manufacture lies filtration: separating solid crystalline product from the surrounding liquid. Many of these crystals grow as tiny rods, and their elongated shapes make them notoriously difficult to separate efficiently. Poor filtration means wasted product, wasted energy, and wasted water. Getting it right, can unlock cleaner, cheaper, more sustainable production at scale. 

This project: You will build particle-based physics simulations of rod-shaped crystals as they pack, flow and form filter cakes. Using fundamental physics, contact mechanics and hydrodynamics, you'll reveal exactly how rod geometry, orientation and packing govern filtration performance. From these insights, you'll help optimise the process itself, turning trial-and-error into predictive design. 

Why it matters: Your work will directly target UN Sustainable Development Goal 2: Zero Hunger, while cutting the energy and water footprint of manufacturing. You'll contribute to making a vital global industry genuinely sustainable. 

What you'll gain: 

• Expertise in computational modelling, soft-matter physics and particle simulation. 

• Expertise in written and verbal communication. 

• Real-world industrial relevance and collaboration. 

• Skills spanning coding, physics and chemical engineering, which are highly sought after in academia and industry.

We're looking for: A curious, motivated graduate in physics, chemical engineering, applied maths or a related field, with an appetite for problem solving.

Dixon, A., Hone, J., Melaugh, G. and Ness, C., 2026. Rheology of dense suspensions of granular spherocylinders by particle-based simulation. arXiv preprint arXiv:2607.28206. Ness, C., Seto, R. and Mari, R., 2022. The physics of dense suspensions. Annual Review of Condensed Matter Physics, 13(1), pp.97-117.

A UK 2:1 honours degree, or its international equivalent, in an appropriate subject, or relevant qualifications and experience.

There may be industry funding available for this project for Home applicants (UK & EU with settled/pre-settled status), please enquire.

Applications are welcomed from self-funded students, or students who are applying for scholarships form the University of Edinburgh or elsewhere.

Further information and other funding options.