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Machine Learning Accelerated Design and Discovery of Rare-earth Phosphates as Next Generation Environmental Barrier Coatings

Sep 24, 2022
An integrated computational and experimental approach for data-driven materials design of next generation EBCs
An integrated computational and experimental approach for data-driven materials design of next generation EBCs

  • Algorithms are being developed to generate synthetic microstructures based on experimentally-obtained microstructures and simulation of generated microstructure for materials properties simulations. 

  • Experimental EBSD data is processed and fed into DREAM 3D software to generate 3D synthetic statically equivalent microstructure of the single component and multicomponent rare-earth phosphates.

  • Abaqus files based on model output from DREAM 3D are generated to calculate the macroscopic properties of various statistically representative synthetic microstructures.

  • Effect of CMAS penetration on the effective material properties are studied and the extent of property degradation is being determined.

Authors

Jie Lian, Rensselaer Polytechnic Institute

Additional Materials

U.S. National Science Foundation and NSF DMREF, Materials for Our Future

This material is based upon work supported by the U.S. National Science Foundation Award No. 2015237. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation. This site is maintained collaboratively by principal investigators with NSF DMREF awards, independent of the NSF.