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Ping Xiao

Top university

9 months ago

High-throughput Making, Characterising and Testing of Environmental Barrier Coatings for Data-Centric Innovation (PhD) The University of Manchester in United Kingdom

Degree Level

PhD

Field of study

Machine Learning

Funding

Funded PhD Project (Students Worldwide)

Deadline

Expired

Country flag

Country

United Kingdom

University

The University of Manchester

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Keywords

Machine Learning
Chemistry
Mechanical Engineering
Chemical Engineering
Materials Science
Digital Twin Technology

About this position

This fully funded PhD opportunity at The University of Manchester, in partnership with the Henry Royce Institute and Rolls-Royce, focuses on the rapid development and optimisation of environmental barrier coatings (EBCs) for ceramic matrix composite (CMC) components in next-generation aero-engines. The project is part of cohort 3 of the EPSRC CDT in Developing National Capability for Materials 4.0, offering a unique interdisciplinary research environment and industrial collaboration.

Silicon carbide-based ceramic matrix composites (SiC-SiC CMCs) are revolutionising aeroengine design by replacing traditional nickel-based superalloys, thanks to their superior high-temperature mechanical properties and significantly lower density. However, these advanced materials require robust EBCs to protect against steam corrosion in the harsh gas-turbine environment. Without effective EBCs, CMC components degrade rapidly, limiting their operational lifespan. Current state-of-the-art EBCs use ytterbium disilicate applied via air plasma spraying (APS), but this project will explore electrophoretic deposition (EPD) as a cost-effective, versatile alternative that allows precise control over coating chemistry and microstructure.

Led by Professors Ping Xiao and Philip Withers, the research will build on recent advances in EPD of ytterbium disilicates, developed at Manchester, to manufacture EBCs with superior performance compared to APS coatings. The student will develop high-throughput methods for making, characterising, and testing a wide range of EBC compositions and powders, enabling a data-centric approach to materials innovation. Fast characterisation and mechanical testing techniques will be established to support rapid screening and optimisation.

A key aspect of the project is the integration of digital twinning and machine learning to model the relationships between EPD processing conditions, microstructural features, mechanical behaviour, and overall coating performance. This approach aims to accelerate the discovery of optimal formulations and processing parameters, setting new standards for the development of advanced coatings in aerospace and beyond.

The successful candidate will join a large, collaborative research team and work closely with Rolls-Royce, gaining exposure to industrial challenges and cutting-edge materials research. The studentship covers full tuition fees (for both home and international students), a tax-free stipend of at least £20,780, London allowance if applicable, and a research training support grant. Up to 30% of studentships are available to outstanding international applicants, and early applications are encouraged.

Applicants should have a strong background in materials science, chemical engineering, mechanical engineering, chemistry, or a related field. Experience with experimental research, data analysis, or machine learning is advantageous. The CDT is committed to equality, diversity, and inclusion, and welcomes applications from underrepresented groups.

To apply, visit the University of Manchester postgraduate application portal, select Postgraduate Research, the 2026/27 academic year, and CDT in Materials 4.0. For technical queries, contact Prof Ping Xiao at [email protected]. For general enquiries, email [email protected]. The application deadline is March 3, 2026.

For further reading, see the related publication: https://www.sciencedirect.com/science/article/pii/S0010938X25001805.

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants should hold or expect to obtain a first-class or upper second-class degree (or international equivalent) in materials science, chemical engineering, mechanical engineering, chemistry, or a closely related discipline. Experience in experimental research, data analysis, or machine learning is desirable. Candidates of all nationalities are welcome; up to 30% of studentships can be awarded to outstanding international applicants. English language proficiency is required as per University of Manchester standards.

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Professors

Professor at EPSRC CDT in Developing National Capability for Materials 4.0, with the Henry Royce Institute

University Name
Country flag

United Kingdom

Research Interests

Materials Chemistry

Condensed Matter Physics

High-temperature Materials

Materials Science

Mechanical Characterisation Of Materials For Compact Fusion Energy

Professor at EPSRC CDT in Developing National Capability for Materials 4.0, with the Henry Royce Institute

University Name
Country flag

United Kingdom

Research Interests

Mechanical Engineering

Chemical Engineering

Materials Science

Chemistry

Tem