MatBind: A Shared Embedding Space for Multimodal Materials Characterization
Fully characterizing a crystalline material requires integrating heterogeneous data sources -- atomic structures, diffraction patterns, electronic density of states, and natural language -- each of which captures a different facet of the same physical object. In practice, however, these modalities are stored and analyzed in isolation, making it difficult to relate or query materials across representational boundaries. We present MatBind, a contrastive learning framework that aligns four materials modalities -- crystal structure, powder X-ray diffraction (pXRD) simulated from structures, density of states (DOS), and text -- into a unified embedding space using crystal structure as the cent...
| Authors | Le Yang, Anoop K. Chandran, Jona Östreicher et al. |
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| Primary category | cs.LG |
| Published | 9 July 2026 |
| Last updated at source | 9 July 2026 |
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