A research team at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) has successfully ...

Following the success of large language models, the concept of large materials models as deep-learning computational models for materials design has attracted great interest. Nevertheless, the task of ...

A general-purpose LLM is fine-tuned with inorganic material knowledge datasets and used to predict the synthesizability and precursor compounds of hypothetical inorganic materials. Seoul National ...

Materials informatics applies data-driven strategies to materials R&D. Long before generative AI technology reached peak hype, it had a long history of success in this field. A common approach is to ...

(a) A feasible route for developing large materials models capable of describing the structure-property relationship of materials. The universal materials model of DeepH accepts an arbitrary material ...