||This symposium will provide a forum to identify current achievements and existing challenges in advanced and accelerated materials discovery and characterization of ceramic and glassy materials enabled by simulation and machine learning approaches. Computational techniques ranging from atomistic simulations to mesoscopic and continuum modeling, and innovative approaches in experimental data analysis for the study of ceramic materials, crystalline or amorphous, of all compositions will be considered. Contributions involving informatics approaches, machine learning, datamining, and design and optimization for materials discovery are also encouraged.
Topics include, but are not limited to:
• Informatics, machine learning, data mining approaches,
• First-principles studies of the structure and properties of ceramic materials,
• Molecular dynamics and Monte Carlo studies,
• Upscaling techniques and mesoscale modeling,
• Continuum modeling of ceramic materials,
• Breakthroughs in computational methods for ceramic materials.
This symposium is sponsored by the ACerS Glass & Optical Materials Division.