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A Machine Learning Model for Oxygen Diffusion in Silica Thermally Grown Oxide Layers as a Function of Additive Content for Environmental Barrier Coating Life Modeling

Completed TRL 2 (started at 1, targeting 2)

Description

We propose to develop a machine learning model to correlate the presence of additives in the oxide corrosion layer of an environmental barrier coating to oxygen diffusivity, and use this as a proxy to estimate the effect of the coating formulation to aging lifetime.

Benefits

The proposed model would allow us to optimize environmental barrier coating formulations to decrease further oxygen diffusion through the oxide corrosion layer and therefore reduce further aging. This will increase the service life of turbine engine hot section components.

Details

Technology areaMaterials, Structures, Mechanical Systems, and Manufacturing > Materials > Coatings
ProgramCenter Innovation Fund: GRC CIF (GRC CIF)
Lead organizationGlenn Research Center, Cleveland, OH
Start date2023-10-01
End date2024-09-30

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