About the project
This project will develop high-throughput program scripts for 3D/4D microstructure analysis and feature tracking to accelerate alloy design based on our developed Track-Rex toolbox. Using advanced microstructure characterisation and deep learning, this project will create automated pipelines linking manufacturing, microstructure evolution, and materials performance, ultimately supporting impactful, interdisciplinary research.
Alloy design is critical for creating lighter, stronger, and more sustainable components for aerospace, transport, and energy systems. However, understanding and predicting the performance of advanced alloys requires analysing how their complex 3D and time-evolving (4D) microstructures form during manufacturing and change under service conditions. Modern characterisation techniques such as 3D Electron Backscatter Diffraction (3D EBSD), Lab Diffraction Contrast Tomography (LabDCT), and synchrotron X-ray tomography can capture unprecedented detail on grain growth, phase transformation, and defect evolution — but they generate terabyte-scale multimodal datasets that are challenging to reconstruct, segment, and interpret.
This project will address this bottleneck by building on the group’s open-source Track-Rex toolbox to create high-throughput, AI-assisted pipelines for 3D/4D microstructure reconstruction, segmentation, and feature tracking. Using deep learning and graph-based algorithms, the project will automate tasks that currently require extensive manual effort, enabling researchers to connect processing–structure–property (PSP) relationships faster and more reliably.
You will work closely with industrial partners contributing representative additive manufacturing (AM) alloy datasets and case studies, ensuring real-world relevance. We will obtain multimodal datasets (3D EBSD, LabDCT, synchrotron tomography) from in-house printed representative AM samples, project partners, and open repositories, such as Zenodo. Data will capture crystallographic, morphological, and defect information across scales.
This project offers access to state-of-the-art facilities at the University of Southampton, Henry Royce Institute, ESRF and Diamond Light Source, including advanced additive manufacturing labs, high-resolution microscopy, synchrotron partnerships, and the Iridis high-performance computing cluster.
