PhD Studentship: Electromagnetic Sensing for High-Temperature Microstructural EvolutionUniversity
This PhD redefines electromagnetic sensing by moving beyond magnetic permeability-dominated approaches to establish a conductivity-driven eddy-current framework for tracking microstructural evolution at high temperature.
The transition towards smarter, lower-carbon manufacturing demands new ways to understand and monitor how materials evolve during processing. This PhD project addresses a fundamental and timely challenge in electromagnetic (EM) sensing: how to quantitatively link electrical conductivity–dominated eddy current responses to microstructural evolution during high-temperature processing.
Conventional EM approaches for microstructure monitoring are often dominated by magnetic permeability effects and are therefore restricted to ferromagnetic materials below the Curie temperature. As a result, large regions of materials processing — including high-temperature steel processing, non-ferromagnetic alloys, and multi-material systems — remain poorly accessible to existing EM techniques. This project intentionally moves beyond that paradigm.
The research will focus on kHz–MHz eddy current sensing frameworks in which electrical conductivity is the primary sensing mechanism. This enables monitoring not only in steels above the Curie point, but also in non-ferromagnetic and weakly magnetic alloy systems, where phase transformations, grain evolution, precipitation, solute redistribution, or defect evolution modify electrical transport properties. While magnetic permeability effects will not be excluded where relevant, the central aim is to establish a robust, physically grounded conductivity-dominated sensing framework applicable across alloy systems and processing routes.
The project is fundamentally interdisciplinary, combining electromagnetism, materials physics, and metallurgy. The successful candidate will investigate how microstructural features — such as phase fraction, grain size, defect density, and thermal history — govern conductivity at elevated temperatures, and how these changes manifest in eddy current sensor responses. This will involve both experimental work and analytical interpretation, linking EM signals directly to underlying physical mechanisms.
Key research themes include:
Design and optimisation of kHz–MHz eddy current sensors suitable for high-temperature environments
Experimental studies linking microstructural evolution to electrical conductivity during thermal processing
Signal analysis and feature extraction from complex, temperature-dependent EM data
Integration of sensing data with metallurgical characterisation and physical interpretation
Development of transferable EM sensing principles beyond steels, towards broader alloy classes
The project will be based within the Advanced Steel Research Centre (ASRC) at WMG, an internationally recognised environment for steel metallurgy, electromagnetic sensing, and high-temperature experimentation. It will run alongside the major UK research programme Frontiers in Electromagnetic Non-Destructive Evaluation Research (FENDER), involving multiple universities and over 20 industrial partners. Relevant industrial partners include British Steel, Tata Steel Europe, Primetals Technologies, ETher NDE, Advanced Engineering Solutions, Rolls-Royce, EDF Energy, and the National Nuclear Laboratory. FENDER aims to bring game-changing ideas to EM NDE by harnessing advances in electronics, signal processing, modelling, and data science, positioning EM sensing at the heart of future Industry 4.0 manufacturing, advanced materials processing, and circular-economy technologies.
This PhD is ideal for candidates with a strong background in Physics, Materials Science, Electrical Engineering, or related disciplines, who are motivated by fundamental questions and experimental research. It will particularly appeal to students interested in electromagnetism, transport properties, phase transformations, and sensing science, and who wish to develop expertise that is both intellectually deep and highly transferable across materials, industries, and future research careers.