Amorphous Fortress

Amorphous materials research, particularly focusing on what's termed the "Amorphous Fortress," aims to understand and predict the structure and emergent behavior of disordered systems. Current research utilizes machine learning, specifically diffusion models and deep neural networks, to analyze and generate atomic structures from experimental data (like XANES spectra) or to predict crystallization pathways from amorphous precursors. This work is significant because it bridges the gap between materials characterization and structure prediction, enabling the design of novel materials with tailored properties and offering insights into complex phenomena like glass transitions and interfacial thermal resistance in heterostructures.