- Further development of a rapid coating assessment methodology.
- Utilise the new assessment criteria for durability evaluation of repellent surfaces to compare commercial non-stick coatings on aluminium alloy, titanium alloy and glass.
- Identify the modes of failure of the repellent surfaces as a function of substrate.
- Extend the assessment criteria methodology to include erosion and photochemical damage.
Previous work has developed a new approach to the assessment of the durability of repellent surfaces. This approach used a multi-variate analysis method to define a figure of merit based on considerations of surface roughness, surface energy and retention of these key characteristics under abrasive and aggressive chemical conditions. The measured properties of candidate coatings and surface treatments are measured using standard methods and protocols under this approach. The retention of the key performance indicator, i.e. repellence, as a function of exposure to a range of harsh mechanical and chemical conditions can then be determined. The normalised performance data are plotted in the form of a radar diagram.
This approach bridges the gap that currently exists between measurement of individual properties (repellence, abrasion resistance etc) and long-term functional assessment. It also enables a more rapid comparative assessment between candidate coatings and surface treatments and so can be used to screen candidate coatings for longer term field trials.
Previous work focussed on coating formulations developed at TWI on aluminium Q-panels. The proposed programme of work will expand and extend this approach. In addition to candidate TWI coatings, commercial hydrophobic (fluorocarbon and hydrocarbon) coatings and silanes will be applied to Ti-6Al-4V, 2XXX series aluminium, and glass. These substrates are representative of the materials used in the aerospace and solar photovoltaic industries.
Relevant Industry Sectors
Benefits to Industry
The project will establish a more holistic and accelerated test methodology than conventional functional assessment. This will enable industry to make better selection decisions and to validate these more rapidly than at present.
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