PhD Studentship: Catalyst Selection for the CVD Growth of Carbon Nanotubes

Application deadline: All year round
Research theme: Nanomaterials

This 4-year PhD project is fully funded for home students. The successful candidate will receive an annual tax-free stipend based on the UKVI stipend (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend to increase each year.

If you are an overseas student, we may be able to provide full funding. Please contact the main supervisor, Dr Bissett - mark.bissett@manchester.ac.uk, to discuss this.

Project Overview

Carbon nanotubes (CNTs) are critical components in advanced technologies, particularly as conductive additives in lithium-ion battery (LiB) electrodes. With the exponential growth in demand for high-performance batteries, the need for scalable, high-quality CNT production has never been greater. Chemical vapour deposition (CVD) remains a leading method for CNT synthesis, yet the role of catalyst composition in controlling CNT morphology and purity is still not fully understood.

This PhD project, in collaboration with Innospec, aims to investigate how different catalysts influence CNT growth, structure, and performance. Specifically, the study will compare different CNT catalysts, evaluating their impact on CNT morphology, chemical composition, and electrochemical performance in Li-ion cells.

Innospec is a global surface science company that provides speciality chemicals to a wide range of markets including fuels, home care, personal care, agrochemicals, and oilfields. Innospec employs 2,400 employees in 22 countries with manufacturing and research sites in Europe and the Americas. Innospec’s major research centre is in Ellesmere Port with the focus on new product discovery for all of its Business Units with a growing emphasis on electrification and biotechnology applications.

Key Objectives

• Synthesize CNTs via CVD using varied catalyst formulations and growth conditions.
• Characterize CNTs using Raman spectroscopy, SEM/TEM, and elemental analysis.
• Investigate the influence of catalyst impurities (e.g. Fe, S) on CNT purity and structure.
• Evaluate CNTs as conductive additives in standard Li-ion battery electrodes.
• Apply AI/machine learning to optimise experimental design and growth parameters.

Training and Facilities

The successful candidate will benefit from access to world-class facilities at the National Graphene Institute (NGI) and the Henry Royce Institute (HRI), including advanced microscopy, spectroscopy, and battery testing equipment. You will also spend time working directly with Innospec, gaining valuable industrial experience and insight into catalyst development and applications.

We are seeking a highly motivated candidate with:

• A first-class or upper second-class degree (or equivalent) in Materials Science, Chemistry, Physics, Chemical Engineering, or a related discipline.
• Experience in nanomaterials synthesis and characterization is desirable.
• Interest in energy storage technologies and machine learning applications in materials science.
• Strong analytical and problem-solving skills, and the ability to work independently and collaboratively.

To apply, please contact the supervisors Dr Bissett - mark.bissett@manchester.ac.uk and Prof Kinloch - ian.kinloch@manchester.ac.uk. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.

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