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Meeting MS&T21: Materials Science & Technology
Symposium Materials Informatics for Images and Multi-dimensional Datasets
Presentation Title Characterization of Additively Manufactured ZrB2-SiC Ultra High Temperature Ceramics via X-ray Microtomography
Author(s) Pratish R. Rao, Jonghyun Park, Jeremy Watts, William Fahrenholtz, Gregory Hilmas, David Lipke
On-Site Speaker (Planned) Pratish R. Rao
Abstract Scope Additively manufactured (AM) zirconium diboride-silicon carbide (ZrB2-SiC) composites are being considered as potential Brayton Cycle based heat exchangers materials, with supercritical CO2 as the working fluid, operating at temperatures as high as 1100 oC and pressures up to 250 bar. An extensive understanding of microstructure is thus critical in refining the processing parameters, resulting in fabrication of the components with long term durability. X-ray micro-computed tomography has been employed to quantitatively study the microstructural features of ZrB2-SiC systems. In this research, X-ray microtomography imaging was employed as a nondestructive characterization technique to analyze the microstructural aspects of the additively manufactured ceramic components. Statistical analysis was performed on 2D microtomographic projections of ZrB2-SiC (70-30 vol.%) sintered bodies to understand the interplay between processing parameters and the ensuing microstructure. The analysis of X-ray microtomography provided information on pore sizes and distribution, geometry and the allowable tolerances for longstanding durability under thermomechanical loading.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

Building a Database of Fatigue Fracture Images to train a CNN
Characterization of Additively Manufactured ZrB2-SiC Ultra High Temperature Ceramics via X-ray Microtomography
Graph Neural Networks for an Accurate and Interpretable Prediction of the Properties of Polycrystalline Materials
Machine Learning and Image Processing Techniques for Materials Evaluation
Machine Learning Ferroelectrics: Bayesianity, Parsimony, and Causality
Multivariate Statistical Analysis (MVSA) for Hyperspectral Images
Now On-Demand Only - Computational or Experimental? Interpreting X-ray Absorption and Diffraction Contrast for Massive Non-destructive 3D Grain Mapping of Metals in Laboratory CT
Open-source Hyper-dimensional Materials Analytics Using Hyperspy
Quantitative Comparisons of 2D Microstructures with the Wasserstein Metric
Spatial and Statistical Representation of Strain Localization as a Function of the 3D Microstructure Using Multi-modal and Multi-scale Data Merging
Training Deep-learning Models with 3D Microstructure Images to Predict Location-dependent Mechanical Properties in Additive Manufacturing
Understanding Degradation and Failure Mechanisms by Multiscale and Multiresolution Electron Microscopy

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