Multimodal AI for Materials

Multimodal AI for Materials Explorer

The analysis covers publications from 2020 to 2025 and highlights the emerging research trends of generative and multimodal AI in Materials research. Publication data were derived from the Elsevier Scopus database.

The data is updated annually, with the latest update in June 2026. The reported numbers should be interpreted as indicators of overall trends rather than exact totals.

Fig. 1 · Proportion of multimodal AI, generative AI, and generative and multimodal AI publications in materials research

The “generative and multimodal AI” term refers to publications that matched both the “multimodal AI” and “generative AI” groups.

Fig. 2 · AI publications in materials research in property prediction and materials design

Increasing numbers of AI studies in property prediction and materials design.

Fig. 3 · Multimodal AI publications in materials research by data category

Publications match "Multimodal AI for materials" query and involve at least one of four materials data categories: composition, microstructure, processing, and testing & characterisation.

Fig. 4 · Relative proportion of the materials data categories in multimodal AI publications

Publications spanning multiple categories are counted in each.