PhD Symposium

Is the Third Branch Optimal? Patient-Specific FSI Analysis of Triple-Branched Thoracic Endovascular Aortic Repair and Progressive Computational Planning and Evaluation of TEVAR

My PhD study focuses on the development and application of patient-specific computational simulations to investigate thoracic endovascular aortic repair (TEVAR). Using fluid-structure interaction (FSI) modelling, I evaluate haemodynamics and the structural biomechanical behaviour of the aorta following TEVAR under physiologically realistic conditions. In parallel, my current work involves the use of computational structural frameworks, such as finite element analysis, to model stent-graft deployment and facilitate surgical planning, with the aim of supporting treatment optimisation and improving preoperative decision-making. Together, this research seeks to enhance the understanding of endovascular repair and contribute towards more personalised vascular interventions.

Targeted Thrombolytics Using Red Blood Cell Derived Vesicles

Thrombosis is a pathological condition where a blood clot blocks a blood vessel supplying oxygen and nutrients to an organ, leading to life-threatening heart attacks, brain stroke, deep vein thrombosis and pulmonary embolisms. Rapid dissolution of the clot is thus a critical and a time-sensitive intervention. Thrombolytic drugs are a class of drugs that can break these blood clots, however their high risk of systemic bleeding and limited efficacy in complex clots significantly restricts their clinical use. Targeted delivery of thrombolytic agents may not only alleviate systemic side effects but also enhance the dissolution dynamics of blood clots. 
To that end, we propose the use of Red Blood Cell Vesicles (RBCVs) for the targeted delivery of a potent thrombolytic agent, streptokinase (SK). RBCVs are nanoparticles derived from the membranes of natural red blood cells conferring inherent biocompatibility and targetability to the system. RBCVs are further modified with a targeting peptide, cRGD, which allows the nanoparticles to specifically bind to activated platelets found only in blood clots. RBCV-cRGD-SK formulations have been evaluated in multiple human ex vivo blood clot models under static and flow conditions, demonstrating enhanced thrombolytic performance compared with free streptokinase.

The burden of antibody production in mammalian cells

To produce therapeutic antibodies (antibodies given to patients to treat specific diseases), mammalian cells are genetically engineered to produce the antibody protein. This involves inserting the antibody genes into the cell’s genome, growing the cells so they express the antibody, and then purifying the final product.

A major challenge arises during cell growth and antibody production: producing large amounts of antibody places a burden on the host cell. Cells have limited resources (such as energy, enzymes, and molecular building blocks), so antibody production competes with essential cellular processes like metabolism and growth. As a result, cell performance becomes suboptimal, often leading to slower growth and reduced product yield.

In my research, I have characterised this antibody-specific burden by showing that antibody expression reduces cell growth and that different antibody designs lead to variable product yields. I have also begun developing a genetic control system to reduce this burden. This system enables cells to sense their own production stress and adjust antibody expression accordingly. In principle, this creates a self-regulating response in individual cells, which may improve growth, reduce variability, and increase overall yield.

Synthetic cells with density-dependent sensing and collective gene activation

My PhD focuses on designing synthetic cells as novel therapeutic vectors for disease. Synthetic cells are mimics of living cells that are engineered with only the minimal components necessary to perform a specific function. In my PhD, I engineer sense-response functions into the synthetic cells by encapsulating DNA templates and cell-free expression machinery within a lipid membrane. Previous research into sense-response synthetic cells only engineer responses to molecules in the external environment, but not to other synthetic cells. I have engineered synthetic cells that respond to each other, leading to collective gene activation that is controlled by the proximity of synthetic cells within the population. 

Glycerol Electrochemical Oxidation towards Lactate Production using Multi-component Pt-based catalysts

Glycerol is a major by-product of biodiesel production. The aim of my PhD is to investigate its valorisation into value-added commodity chemicals, with a particular focus on lactate. However, lactate production via glycerol electrooxidation is complicated by the coexistence of Faradaic and non-Faradaic reaction pathways, which are difficult to decouple and control.

Engineering Control of Electrochemical Glycerol Oxidation

The growth of biodiesel production has generated a large surplus of crude glycerol, whose low market value and complex impurity profile pose major challenges for sustainable valorisation. Electrochemical glycerol oxidation (GOR) represents a promising route to convert glycerol into value-added chemicals using renewable electricity. However, its practical implementation is hindered by catalyst deactivation, complex reaction pathways, and strong sensitivity to operational conditions. These challenges are further intensified when considering crude glycerol feeds, which contain impurities that can poison electrocatalysts or alter interfacial reaction pathways. At present, few electrocatalysts have demonstrated long-term tolerance to such impurities under industrially relevant conditions.
The aim of my research is to develop and optimise process-level control strategies that can substantially improve catalyst stability and selectivity without relying on complex catalyst design. By using a custom-built electrochemical system with a rotating platinum electrode, I investigate the effects of controlled hydrodynamics and dynamic modulation of the electric potential on surface poisoning and reaction pathways. This work demonstrates how dynamic catalyst regeneration and hydrodynamic control can serve as powerful engineering levers for GOR and provides a practical framework for developing more robust electrochemical processes capable of valorising impure glycerol streams, bringing electrochemical glycerol upgrading closer to industrial implementation.

The production of Levoglucosan via non-pyrolytic pathways for a promising platform chemical

Levoglucosan anhydrous sugar platform chemical used in industry for a wide varity of applications including polymers, solvents and other sugar derivatives. It is currently produced via pyrolysis of cellulose-containing biomass, which leads to fast production, but is energy-intensive and releases harmful emissions. 

In this project, ionic liquids have been looked at as an alternative to producing levoglucosan via a wet chemical process with the final aim of integration into the ionosolv biomass pulping process developed by the Hallett group. Other potential advantages are a less energy-intensive process and fewer harmful by-products.

Ionic liquids can create a catalytic environment for levoglucosan production, and with the aid of various additives, optimisation of this production has been observed. Crucially, ionic liquids are recoverable, meaning less waste and ideally lower cost.  

Mg-Mediated dual-templated approach to active Fe-N-C catalysts from zinc adeninate framework

My PhD focuses on developing low-cost, platinum-free catalysts for the oxygen reduction reaction (ORR), the key cathode reaction in fuel cells. Although platinum-group catalysts deliver excellent ORR activity, they are expensive and scarce, so my work develops iron–nitrogen–carbon (Fe–N–C) single-atom catalysts as a practical replacement, where isolated Fe sites (Fe–Nₓ moieties) are embedded in an N-doped carbon framework. My aim is to create catalysts that are highly active, have a high density of accessible active sites, and remain stable under realistic operating conditions. To achieve this, I develop synthesis strategies that tune the pore structure and the local coordination environment of the iron sites, maximizing site density and utilization while suppressing the formation of inactive iron nanoparticles. I then combine advanced materials characterization with a wide range of electrochemical testing, moving from idealized screening methods to more practical, fuel-cell evaluations at high current densities. Ultimately, this research aims to enable affordable, scalable fuel-cell technologies for clean energy applications.

Crystal Regeneration Post-Breakage: From Parametric Study to Industrial Applications

Crystallisation is widely used in industrial processes, including pharmaceuticals, food, fine chemicals, and agrochemicals production. While many aspects of crystallisation (e.g., nucleation, growth, dissolution) are well-studied, the post-breakage behaviour of crystals remains under-researched, despite breakage being a common occurrence.

In my PhD, I perform experiments using paracetamol crystals and video imaging to explore a unique phenomenon called ‘crystal regeneration’, which describes the rapid growth of broken crystals into their pre-breakage shape. Initially, I demonstrated the applicability of regeneration in various solvents (ethanol, acetone, tetrahydrofuran) and compared the trends. I also demonstrated regeneration of crystals with multiple breakage sites, which resulted in a multiplied growth rate compared to a single breakage site. Then, by assessing the effects of temperature and concentration, I formulated the growth kinetics of regeneration, confirming significantly faster rates compared to regular crystal growth. Subsequently, I compared growth trends of broken and unbroken crystal pairs in the same setup, and used these results to quantify regeneration’s potential to improve industrial process productivity. Currently, I am testing different stirrers in a multi-crystal setup to integrate regeneration into industrial processes. These results are promising for enhancing the accuracy of crystallisation models and optimising industrial processes.

Design for functions via frontal photopolymerisation

Autonomous and origami-inspired material design has emerged as a powerful strategy for creating complex, functional structures, spanning multiple lengths and timescales, with applications ranging from soft robotics and biomedical devices to adaptive architectural components. Frontal photopolymerization (FPP) has emerged as a versatile and scalable approach to generate planar, multilevel and gradient polymer networks. FPP is a class of photopolymerization processes for which, under conditions of strong light attenuation and limited mass and diffusion processes, a sharp traveling solidification front develops and propagates into the liquid monomer. While the spatiotemporal evolution of FPP networks can become complex, and even autocatalytic for highly exothermic processes, a range of photopolymer systems exhibit surprisingly simple kinetics with time-invariant, propagating, conversion profiles. Here, we examine the spatiotemporal response and kinetics of asymmetric networks fabricated by FPP, focusing on the evolution of pattern curvature over time. We then design autonomous functional structures, able to perform directional jump, underwater ‘push’ and switch configuration driven by the response of asymmetric FPP networks.

Beyond Breakthrough Curves: 4D X‑ray CT Insights into Adsorption, Dispersion, and Heat Transfer

My PhD investigates gas adsorption and transport phenomena inside packed bed systems by combining classical adsorption experiments with X ray computed tomography (CT). Earlier CT studies were mainly proof-of-concept demonstrations, showing that adsorption could be imaged but offering limited quantitative or system-relevant insight. In my work, I build on these foundations and use time-resolved X-ray CT to obtain detailed, spatially resolved adsorption data within packed beds under realistic operating conditions.

From these measurements, I advanced the digital adsorption method and extended it to binary mixtures and weakly adsorbing species. This enabled the experimental identification of complex adsorption behaviour, including heat-induced roll-up phenomena, which had not previously been experimentally observed inside packed beds. I also used this framework to provide new experimental inside into the relationship between internal adsorption dynamics, dispersion, and heat effects.

Overall, my work moves beyond proof of concept imaging and delivers new experimental tools and insights that make internal adsorption and transport behaviour accessible for more realistic reactor modelling and design.

Closed-Loop Bayesian Optimisation for the Synthesis of Amine-Grafted Resins for Direct Air Capture

My PhD is on developing a closed-loop Bayesian optimisation workflow to synthesise polymeric adsorbents for the direct air capture of CO2. Our motivation is that current DAC adsorbent research focuses on expensive and hard-to-synthesise materials (e.g., MOFs). We focus on inexpensive polymeric materials, which are readily available and easy to scale up. In a multi-objective Bayesian optimisation framework, we are exploring the trade-off between the CO2 uptake and adsorption kinetics at atmospheric conditions by varying three synthesis parameters of these amine-grafted polymeric adsorbents. This work includes setting up the robotic synthesis platform and automated characterisation via TGA adsorption measurements, as well as the data treatment for Bayesian optimisation.