Triangle

What do you know about the fellowship?

Let's explore the transformative power of our EPSRC fellowship as we delve into the following captivating work packages:

 

 WP1. High throughput materials discovery

 

 

 

The material discovery apparatus (MDA) takes a holistic approach to developing lanthanide series doped zirconates for thermal barrier coatings (TBCs), silicates for environmental barrier coatings (EBCs), and alumina for electrical insulators. The direct feed from the MDA to solution precusor plasma spray (SPPS) allows the rapid ceramic processing, both for discovery and production modes.  

 

mda

 
Schematic diagram of materials discovery apparatus functioned to dispense and mix different compositions, prior to thermal spraying.
 

 

 WP2. Microstructure and architecture development

 

 

The microstructural development of advanced coatings are tailored and fine-tuned to induce and achieve desirable thermal, environmental and electrical barrier properties. The use of axial high-speed, high-energy plasma spray enables the design of new coatings with unprecedented control over porosity, cracks, and voids from nanoscale to component level.  

 

 

sem images 

 
Back-scattered (BSE) images in optimising the microstructure of TBCs.
 

 

 WP3. Performance tests

 

 

 

The advanced performance tests include, but are not limited to, erosion resistance, calcia-magnesia-alumina-silica (CMAS) resistance, cyclic steam recession, burner rig testing, and furnace thermal cycling, guided by original equiment manufacturers (OEMs) and using in-house expertise.  Advanced coating characterisations are also conducted at Diamond Light Source (I-14), ISIS Neutron and Muon Source (ENGINX), and Australian Nuclear Science and Technology Organisation. 

 

steam recession

 
Steam-recession steam rig to test on EBC samples.
 

 

 WP4. Machine learning and modelling

 

 

 

The discovery apparatus is connected with graph neural network for making an informed decision for a new successful composition. The active learning models are incorporated into thermal spray to reduce the expensive optimisation. This not only saves the valuable time and costs, but also accelerates the development of new material compositions and their technological readiness.


 

 simulation

 
Machine learning on simulating the effect different radial injection approaches in thermal spray.
 

 

 WP5. Scoping studies

 

 

The scoping studies are targeted on new doped materials, additive manufacturing of ceramics, and post-deposition treatments that may be necessary for some industrial applications. 

 

scoping studiese

 
Machine learning on simulating the effect different radial injection approaches in thermal spray.
 

 

 

Centre of Excellence in Coatings and Surface Engineering
Faculty of Engineering
University of Nottingham

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