Coupling Language Models with Physics-based Simulation for Synthesis of Inorganic Materials

ArXi:2606.00315v1 Announce Type: new Modern generative machine learning (ML) models can propose novel inorganic crystalline materials with targeted properties; however, synthesis planning of these materials remains difficult due to the complexity of the associated physical processes and limited availability of computational tools. We