Simulation-Powered Computational Linguistics
for Materials Foundation Models

SimuLingua delivers an open, multimodal Scientific Foundation Model (SciFM) for materials that unifies text, structures, images and simulation data to accelerate discovery across design–simulate–validate loops. Paired with a physics-in-the-loop generative engine and an AI-accelerated multi-scale simulation pipeline (DFT → phase-field → CFD/FEM), it creates a closed discovery loop: the model proposes promising candidates, fast surrogates verify plausibility and performance, and new data continuously flows back through a FAIR knowledge graph. A natural language interface lets domain experts query the KG, launch virtual experiments and steer multi-objective inverse design.