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Details of Grant 

EPSRC Reference: EP/P510208/1
Title: ENDURANCE: Graphene based coatings for durable wear resistance low cost position sensors
Principal Investigator: Choy, Professor K
Other Investigators:
Researcher Co-Investigators:
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Department: Institute for Materials Discovery
Organisation: UCL
Scheme: Technology Programme
Starts: 09 March 2016 Ends: 08 March 2017 Value (£): 49,365
EPSRC Research Topic Classifications:
Complex fluids & soft solids Materials Synthesis & Growth
EPSRC Industrial Sector Classifications:
Transport Systems and Vehicles
Related Grants:
Panel History:  
Summary on Grant Application Form
Developed by Prof. Choy, Aerosol Assisted Ion Deposition (AAID) is a novel, non-vacuum, cost effective and eco-friendly method for the non-line-of-sight deposition of both thin and thick coatings to 3D structure (non-conformal substrates) with control of structure and composition at the nanoscale. The fabrication of uniform graphene based nano-composite coatings, involves formulation of chemical precursors, which can be a solution or a suspension, and atomisation of the precursor to generate a finely charged aerosol. This allows control of the dynamics of droplets and their evaporation to form droplets consisting of polymeric ions, leading to the deposition of polymeric films incorporating with graphene based nanomaterials to form nanocomposite coatings with uniform and well-controlled structures in an open atmosphere.

Within the ENDURANCE project we will apply this technique for the development graphene based nanocomposite coatings on potentiometer wiper heads targeting excellent conductivity between 1 and 300 ohm/square and wear resistance.

Key challenges to be addressed in our research include:

(1) Graphene interfaces: Limited knowledge of wear properties for graphene to graphene material contacts - we will explore the relationships between graphene coating formulation, chemical / physical properties and the wear properties at graphene to graphene interfaces;

(2) Coating stability: Achieving complete polymerisation during cure thereby enabling long term coating stability - we will explore the relationships between graphene ink formulation and cure properties enabling optimisation of rapid and stable cure;

(3) Coating surfaces: Ensuring graphene is concentrated at the coating surface to enable the surface properties to be realized- we will assess the feasibility to utilise electrostatic (repulsion) and formulation density to promote surface aggregation of graphene;

(4) Coating adhesion: Graphene traditionally has poor adhesion to material surfaces thereby limited coating wear stability - we will explore coating formulations, substrate surface treatments and layer thickness to improve adhesion and wear performance; and

(5) Conductivity: High conductivity requires excellent connectivity between graphene layers which may be difficult to achieve - we will explore the addition of both conductive additives and surface treatments to promote coating conductivity.

Our research approach will follow three key phases (tasks):

Task 1. Formulation Screening: nano-composite ingredients will be screened (graphene, nano-tubes, surfactants, binders, cross linkers, solvents, lubricants etc...) using standard formulations to understand relationships between formulation, AAID processing, and coating properties and performance (adhesion, conduction, wear and cure)

Task 2. Coating formulation: different coating formulations will be investigated to achieve the target properties within the constraints of the material and processing requirements. A limited number of systems will be selected for further study.

Task 3. First generation ink development: selected coating formulations will undergo a number of development cycles to optimise consistency, reliability, wear, rheology, cure etc. Substrate chemical (etching) & physical surface modification strategies will be considered to improve coating adhesion. A tribometer test rig will be used to assess wear and coating adhesion.

We will also support investigation of graphene to graphene interface wear properties using statistical analysis methods (performance analysis) and analysis of wear samples to understand the wear mechanisms.
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