DARWIN 1.5: Large Language Models as Materials Science Adapted Learners

Understand

Materials discovery and design aim to find compositions and structures with desirable properties over highly complex and diverse physical spaces.

• Traditional solutions, such as high-throughput simulations or machine learning, often rely on complex descriptors, which hinder generalizability and transferability across different material systems.
• Moreover, These descriptors may inadequately represent macro-scale material properties, which are influenced by structural imperfections and compositional variations in real-world samples, thus limiting their practical applicability.
• To address these challenges, we propose DARWIN 1.5, the largest open-source large language model tailored for materials science.