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The article discusses a data-driven approach to improve the microstructure-property linkage in ceramic materials, focusing on the impact of inclusions on mechanical performance. By integrating synthetic Representative Volume Elements (RVEs) and machine learning techniques, the study aims to optimize material performance through enhanced understanding of microstructural features. The findings indicate that non-uniform inclusion distribution and variability in inclusion size negatively affect mechanical prope
- Author
- ali.fahem
- Language
- EN