PhD, MPhil Chemical & process engineering

Filtration and washing of pharmaceutical products is classically undertaken empirically. This project will use nano-computed tomography (nano-CT), a high-resolution cross-sectional imaging technique to track the progress of washing at high resolution in real time.

This modelling and simulation study will investigate the complex processes that occur when foam, rather than water, is used as a carrier for fibres during papermaking, with a view towards reducing the overall water footprint of the paper production process.

This project aims to develop a new computational tool, combining molecular simulations and machine learning approaches, to predict the solubility of complex pharmaceutical molecules in a variety of solvents.

Focussed on the development of novel sorption systems for water remediation, the project combines materials development, characterisation and testing for a range of pollutants, including pharmaceuticals and heavy metal species.

Focussed on understanding the impact of teaching strategies within a chemical engineering programme to both evaluate current acquisition of industry-ready graduate attributes with a view to informing educational changes required to best support student development.

This project is to develop and assess modelling methods to obtain a deeper insight into the physico-chemical processes of biomass conversion.

This project will undertake studies on the processes and technology required to convert biomass waste into a range of hydrocarbons. This research project requires both modelling and experimental studies to analyse the waste to energy process and the fuel properties of hydrocarbons and chemicals produced.

The purpose of this project is to apply a formulation to polymeric turbulent boundary layer flows and, in this way, to make some first, yet decisive, steps in the physics and algorithmics of fully-coupled polymeric boundary layer turbulence.

The research is a co-operation with researchers at California Institute of Technology, and will pioneer superfluid flow-structure interactions with are of key importance in technological and astronomical applications.

Soils, catalysts, tablets, dunes: all are packings of particles. Whether a packing is stable or collapses is a key question in nature and industry. The project uses computational methods to explore what features of a packing’s microstructure makes it stable.

Many applications rely on structured films and membranes, such as selective filters, adsorbents, and biological systems. The project will use computer modelling to analyse how particles with complex interactions aggregate to form films with complex structure and complex time-evolution.

This project will utilise molecular dynamics simulation, exploiting the ARCHIE_WeSt supercomputer at Strathclyde to understand how the inhibitors interact with protein aggregates; how they interfere with the nucleation and growth pathway of the fibrils, and if aggregation can be reversed.

The project will focus on the applications of latest Small-angle X-ray scattering system in CMAC (EPSRC Centre of excellence in continuous manufacturing and crystallisation) to provide mechanistic understanding of interparticle interaction in dense system under repulsive or attractive interactions.

In this project, the student will be involved in an industrial funded project to develop and use spatially offset Raman spectroscopy (SORS) and spatially resolved diffuse reflectance spectroscopy (SR-DRS) for obtaining insight into sub-surface powder drying behaviour.

This project will combine recent theories for the influence of charge correlations on the structure of the electric double layer with a simple quantum description of charge transfer to to develop a new model for electrochemical reactions.

This ambitious project attempts to build a single, unified description of complex fluids that incorporates molecular-level detail but can be applied on a wide range of length and time scales that extends to the continuum scale.

This project aims to develop a new multi-scale simulation model to describe the entire synthesis process of bio-inspired silica materials. The model will then be used to design an ideal material for carbon capture applications.

This modelling and simulation study will investigate processes that occur when foam injection is used to displace fluids from an oil reservoir, and in particular what happens as the foam front changes direction as additional injection wells are brought online.

This project investigates how crystals nucleate and how fluid flows can be used to influence crystallisation, using cutting edge experimental facilities, including high speed high resolution imaging, Brownian microscopy, static and dynamic light scattering and small angle X-ray scattering.

This project will investigate behavioural and performance characteristics of students when working in Problem-Based and Enquiry-based learning activities in order to elucidate the link between the use of these approaches and the development of learner’s autonomy.

This project aims to enhance the understanding of point-source detection of microplastic fragments using spectrophotometry and chemometric methods.

The PhD study will explore conceptual, theoretical, and experimental approaches in biomass utilisation and thermochemical conversion to develop innovative energy solutions and/or processes as well as a circular economy concept for resource recovery.

Quantum Chemistry and Molecular Dynamics calculations will be carried out to explore the mechanism and kinetics of lignocellulosic biomass processing and the conversion of waste into valuable products.

In this project, an integrated system will be designed and developed to ensure efficient generation of liquid transportation fuels whilst maximising the value of biomass into value-added chemicals by controlling structure and functionality as they form.

The project involves the development of a pilot scale reactor with instrumentation that will enable the interrogation and optimisation an electroforming process. Both scientific and statistical techniques will be employed to interpret process data enabling process control.

This project aims to develop embedded optical fibre sensors for polymer electrolyte membrane fuel cells to characterise catalyst degradation mechanisms under realistic operating conditions.

This project aims to develop a new process for hydrogen production using biomass electrolysis.

This project aims to use molecular dynamics simulations to understand how the interaction between filler, coupling agent and polymer influence the composite properties.

This PhD project will explore the design, characterisation and application of exsolved materials for power-to-X energy conversion devices where X can be fuels, chemicals, heat or power, all essential for transitioning to a clean, sustainable energy economy.

This PhD project will develop reversible solid oxide cells based on a newly discovered class of materials, so called exsolved or emergent materials.

The project will investigate Machine Learning and Deep Learning approaches to extract and fuse multiple data streams from multi-sensor setups in chemical and pharmaceutical manufacturing through a combination of experimental work, data analytics and process simulation.

The project will explore the use of hybrid models that combine the advantages of data-driven and physics-based first principles models to enhance the performance of current models for crystal nucleation and growth in chemical and pharmaceutical manufacturing.

The project will contribute to the ongoing efforts in monitoring and improving air quality through the application of machine learning and deep learning algorithms for detection and characterisation of airborne microplastics and asbestos fibres.

The study will assess potential applications of Chemical & Process Engineering on circular nutrient metabolism with focus on urine utilization under the resources available and the constraints existing on Mars.

The study will focus on the current and future challenges of drinking water metabolism in cities to effectively respond in sustainable operational approaches and to support human well-being in urban environments.

The effect of hydrogen on soot formation is a focus of attention for this project since some future energy strategies involve blending hydrogen with conventional fuel. Understanding the effect of hydrogen addition may also help to elucidate the underlying mechanisms of soot formation.

We will develop an innovative technique to study crystal nucleation, using an optical tweezer to generate a localized shear flow in a crystallizing solution, thus triggering nucleation in a known position enabling direct measurement of the growing nucleus.