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Graphene-Metallic Based Moisture Fibre Sensors

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  • Full or part time
    Dr X Liu
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

There is a rising requirement to integrate the devices and textile together. The first generation smart textile is more focus on using traditional textile method to blending electrical components into the textile and insulate during washing to prevent damage. But these intergradation methods just rough supplementary technology not high integrated, at the expense of aesthetics and convenience. The new generation E-textile is amid to develop a real sense high-integrated technology: fibre based sensors and devices.

Graphene and sensors are a natural combination, as graphene’s large surface-to-volume ratio, unique optical properties, excellent electrical conductivity, high carrier mobility and density, high thermal conductivity and many other attributes can be greatly beneficial for sensor functions. The large surface area of graphene is able to enhance the surface loading of desired biomolecules, and excellent conductivity and small band gap can be beneficial for conducting electrons between biomolecules and the electrode surface.

This PhD project will combine the graphene and fibre by interfacial modification, to form hybrid sensors, which will be used as new generation wearable electronic device. The interaction between graphene and polymeric materials will be deeply study and the relationship with sensory of as-made sensor will be investigated as well.

Funding Notes

Funding covers tuition fees and annual maintenance payments of at least the Research Council minimum (currently £14,057) for eligible UK and EU applicants. EU nationals must have lived in the UK for 3 years prior to the start of the programme to be eligible for a full award (fees and stipend). Other EU nationals may be eligible for a fees-only award.

Applicants should have at least a 2.1 honours degree with deep knowledge in Materials and Chemistry, as well as computational skills. The focus of the project will be decided to suit the background and the strengths of the student.

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