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Developing Novel Tools for Analysis of Local Order Using Total Scattering Data

✓ Fully Funded 🎓 Artificial Intelligence 🎓 Materials Science 🎓 Physical Chemistry machine learning data analysis total scattering local structure materials characterization software development x-ray scattering neutron scattering

Explore the atomic-scale structure of materials by developing integrated tools that simplify total scattering data analysis. Use machine learning and collaborate with national UK facilities to push boundaries in metallurgy and materials science.

AI-generated overview

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Why This Research Matters

Materials properties such as radiation tolerance, electrical conductivity, and mechanical strength depend on local atomic arrangements. This research simplifies access to total scattering techniques, enabling broader use in key sectors like energy and structural materials. By advancing analysis methods, it fosters discovery and optimization of materials with enhanced performance and durability.

Metallurgy Characterisation Total Scattering Local Structure

Project Description

Project Overview

Total scattering is an advanced X-ray and Neutron scattering technique providing atomic-scale insights into material structures. This technique's potential is limited by the complexity of data processing and analysis, especially in metallurgical systems. The project seeks to develop novel tools that integrate diverse software suites to streamline this workflow, making the technique more accessible.

What You Will Do

The project involves coding, data curation, and practical experiments at UK national X-ray and Neutron facilities including ISIS Neutron and Muon Source and Diamond Light Source. It combines method development with machine learning to enhance analysis quality and user guidance through software integration. Collaboration with the STFC Scientific Computing team and the Royce Institute Materials 4.0 CDT cohort provides a rich environment for interdisciplinary research.

Expected Outcomes

The deliverables include a coherent analytical workflow tool that facilitates information transfer between software suites, a curated dataset, and machine learning methods to boost analysis. This will lower barriers for new users and unlock novel materials exploration areas by expanding total scattering applications.

Why This Matters

Understanding short-range order and local structure in materials can influence properties such as radiation damage tolerance, electrical resistivity, and strengthening capability. By simplifying total scattering analysis, this research enables wider adoption of the technique, benefiting materials science sectors including energy, batteries, and structural materials.

Entry Requirements

Background in Material Science, Chemistry, Physics, or Computer Science

How to Apply

Applications are processed through the University of Sheffield's postgraduate application system at https://www.sheffield.ac.uk/postgradapplication/login.do. For general enquiries contact doctoral-training@royce.ac.uk; for application queries contact Rebecca Milner at rebecca.milner@sheffield.ac.uk; for technical queries contact Dr Lewis Owen at lewis.owen@sheffield.ac.uk.

Eligibility

UK/Home
EU
International

Supervisor Profile

DL
Dr Lewis Owen
University of Sheffield
1212 Citations
15 h-index
Google Scholar

Dr Lewis Owen is a Senior Lecturer in Metallurgy Characterisation at the University of Sheffield. His research focuses on total scattering techniques to study local atomic structure and short-range order in complex materials, especially high-entropy alloys. He combines experimental scattering methods with data analysis and machine learning to advance understanding of materials properties. Dr Owen is recognized for his impactful work documented in respected materials science journals.

Key Publications

2017 367 citations
An assessment of the lattice strain in the CrMnFeCoNi high-entropy alloy
2018 190 citations
Lattice distortions in high-entropy alloys
2021 98 citations
An assessment of the thermal stability of refractory high entropy superalloys
2020 78 citations
The effect of Al on the formation and stability of a BCC–B2 microstructure in a refractory metal high entropy superalloy system
2016 73 citations
A new approach to the analysis of short-range order in alloys using total scattering

Research Contributions

Detailed analysis of lattice strain and distortions in high-entropy alloys.
Provides fundamental understanding of the mechanical behavior and stability of multi-component alloy systems.
Development and application of total scattering and reverse Monte Carlo modeling to analyze short-range order in alloys.
Enables more precise characterization of complex material structures, improving materials design.
Studies on the thermal stability and phase transformations in refractory high entropy superalloys.
Informs the development of materials with enhanced high temperature performance for industrial applications.

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