SYMPOSIUM 40 – Modeling, Simulations and Data-Driven Approaches of Glass and Amorphous Materials

Modeling and simulation play an increasingly important role in advancing glass science, particularly for understanding the complex structures, properties, and behaviors of glasses, ceramics, amorphous, and nanostructured materials. This symposium will highlight recent advances in computational modeling, simulations, and data-driven approaches for glass science and engineering, including first-principles, classical, mesoscale, and machine-learning-based methods. Topics of interest include composition–property modeling, glass structure prediction, machine-learned interatomic potentials, accelerated glass simulations, AI-guided glass design and optimization, additive manufacturing and 3D printing of glasses, image processing and data analytics, and numerical approaches that support interpretation and validation of experimental data from techniques such as diffraction, spectroscopy, and solid-state NMR. The symposium also welcomes studies focused on understanding the fundamental nature of glass formation and the glassy state through integrated computational and experimental approaches.

Session Topics:

Coming later

Symposium Organizer(s):

Jincheng Du, University of North Texas, USA
Xiaonan Lu, Pacific Northwest National Laboratory, USA

Point(s) of Contact:

Jincheng Du; jincheng.du@unt.edu

Division Sponsor(s):

Glass and Optical Materials Division