Evaluation of GlassNet for physics‐informed machine learning of glass stability and glass‐forming ability
Evaluation of GlassNet for physics‐informed machine learning of glass stability and glass‐forming ability
Abstract Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch‐screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for …