PhD in Physics

Lateral flow assays (LFAs) are widely used in community and clinical contexts because they are rapid, low-cost and user-friendly. However, conventional LFAs often lack the sensitivity required to detect low-abundance biological targets at early stages, especially in decentralised or resource-constrained environments. Addressing this sensitivity gap without introducing external instrumentation is a major challenge in the development of next-generation diagnostic technologies. This PhD project will engineer enhanced LFAs by integrating plasmonic amplification using gold nanostars (AuNS) with a power-free electrokinetic analyte focusing mechanism. Gold nanostars, as previously developed and optimised by Prof Nguyen TK Thanh's group for signal amplification in diagnostic systems possess highly branched morphologies that generate strong plasmonic responses suitable for boosting optical readout signals. In parallel, recent work from Dr Bolognesi's group has demonstrated the potential of salt gradient-driven electrokinetic focusing strategies (called diffusiophoresis) for selective concentration of colloids in confined geometries without external power supply. Building on these advances, the student will design LFA architectures that harness diffusiophoresis focusing to drive biomarker accumulation at the detection line while leveraging nanostar-enhanced signal output to achieve high sensitivity within short assay times. The student will gain expertise in nanomaterial synthesis, surface functionalisation and colloid and interface science, developing protocols for tailoring AuNS morphology and surface chemistry for enhanced stability and bio-recognition performance. They will be trained in advanced characterisation techniques including electron and optical microscopy, UV-Vis and scattering-based spectroscopy, X-ray diffraction, dynamic light scattering and image-based signal quantification methods. They will also acquire practical skills in lateral flow device design, paper-based microfluidic fabrication, assay optimisation and Python-based data analysis. The project offers a highly interdisciplinary training pathway that spans materials chemistry, diagnostics engineering, soft matter physics and translational analytical science. The student will join a collaborative, interdisciplinary and supportive research environment, working closely with experts in nanoparticle design, bioassay engineering and microfluidics. Access to state-of-the-art laboratories at UCL Chemistry and Royal Institution facilities will support all stages of the project.