
The traditional paradigm of material discovery, which often relied on serendipity and decades of labor-intensive laboratory experimentation, has undergone a radical transformation as artificial intelligence streamlines the identification of stable crystalline structures. In the current landscape starting in 2026, researchers no longer spend years synthesizing failed compounds; instead, deep learning architectures like Graph Neural Networks predict the thermodynamic stability of










