"PhD Studentship: Surface and Suspension Dynamics in the Alignment of Recycled Fibres"

The composites industry is under increasing pressure to transition towards a truly circular economy. As growing demand continues to widen the supply gap, we must recover untapped value that would otherwise be lost to landfilling and incineration, which are resource-intensive and environmentally damaging end-of-life pathways. Where recycled fibres are used, they are often downcycled as fillers and low-value reinforcements in their short and randomly aligned form. A key challenge to the effective reintegration of recycled carbon and glass fibres into high-performance products lies in achieving scalable and energy-efficient fibre alignment from irregular, reclaimed feedstocks. Fibre surface attributes and suspension behaviour in alignment systems play vital roles in determining the alignment efficiency, process stability, and the downstream consolidation and performance of remanufactured composites.

This fully-funded PhD project fits within a wider research programme with industrial partners and an interdisciplinary team working on the development of cross-platform alignment technologies that integrate material science, process engineering and sustainability analysis to deliver scalable solutions for circular composites manufacturing. The successful candidate will contribute to this broader vision by investigating the surface characteristics and suspension dynamics of recycled short fibres used in alignment processes.

Collaborative links with Gen 2 Carbon, Sigmatex and Teijin Europe in the parent project provide exciting opportunities for knowledge-exchange activities and technical site visits throughout the project.

Project Objectives

1. Characterise the surface properties of reclaimed carbon and glass fibres from different sources and with varying processing histories.
2. Investigate suspension behaviour, including fibre dispersion, settling and agglomeration tendencies under varying conditions.
3. Study the influence of suspension properties on alignment efficiency, consolidation behaviour, and interfacial compatibility with traditional composite matrices.
4. Explore complementary computational fluid dynamics-discrete element method (CFD-DEM) simulations as a tool to predict fibre-fluid interactions and inform experimental design.

Early application is advised as the position will be filled once a suitable candidate is identified.

Further information

Note that only applications received via the University’s online system will be considered. All applications should include the following documents:

• 2–3-page research proposal
• 1-page motivation letter/personal statement
• Curriculum vitae
• Degree transcripts/certificates

The University of Edinburgh is committed to equality of opportunity for all its staff and students and promotes a culture of inclusivity. Details: www.ed.ac.uk/equality-diversity

Principal Supervisor: Dr Wini Obande

Eligibility

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.

We welcome applications from enthusiastic, self-driven and resourceful candidates with a first-class or upper 2:1 UK Honours degree (or international equivalent) in one of the following disciplines:

• Chemical/Mechanical Engineering
• Computational/Experimental Physics
• Polymer/Physical Chemistry
• Any closely related disciplines to the above

Other Essential Requirements:

• 3D CAD proficiency, ideally using Solid Edge, Creo, or SolidWorks.
• Demonstrable experimental laboratory competence and analytical skills.
• University of Edinburgh English-language entry requirements apply.

Desirable Requirements:

• MSc/MEng (or equivalent) in a related field.
• Design of Experiments (DoE) and statistical modelling experience.
• Experience with DES or process modelling tools.
• Familiarity with LCA or cost-carbon analysis (or willingness to learn).
• Some coding experience, ideally in Python or MATLAB.

Tuition fees and stipend are available for Home & International students. Applications are also welcome from self-funded students, or students who are applying for scholarships from the university or elsewhere.

Informal Enquiries: W.Obande@ed.ac.uk