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Motivation

Achieving reliable, high-performance fusion requires a predictive understanding of turbulence and instability dynamics at the tokamak edge, where fluctuations spread nonlocally and strongly influence pedestal structure, confinement, and the approach to disruptive events. These processes are difficult to diagnose experimentally and too computationally intensive to model in real time with first-principles simulations, motivating new approaches that blend physics-based modelling with mode...

The rapid adoption of Industrial Internet of Things (IIoT) technologies has transformed manufacturing, offering greater efficiency, real-time monitoring, and data-driven decision-making. However, this interconnectivity introduces significant cybersecurity vulnerabilities, leaving systems exposed to cyber-attacks. Traditional intrusion detection systems (IDS) often fall short in handling the real-time, large-scale data demands of IIoT and lack sustainability considerations, such as energy efficie...

The UK’s railway bridge asset stock represents over 80% well-aged (>50 years) infrastructure, often carrying loads beyond their original design capacity, hence in urgent need of a reliable real-time damage identification system. The current practice of visual inspection of bridges can be subjective and exposes the workforce to hazardous job sites. In recent years, there have been significant efforts in instrumenting bridges and assessing the condition of the bridge using direct measurements. The...

Layered double hydroxides (LDHs) are tuneable two-dimensional nanomaterials with demonstrated promise as platforms for the delivery of biological molecules via aerosol formulations. Their unique material properties—namely, adjustable particle size, plate-like morphology, and surface charge—enable enhanced penetration through biological barriers, optimised uptake by target cells, and control over release kinetics. In aerosol science, such material characteristics are critical for influencing depo...