A review of large language models and autonomous agents in chemistry

MC Ramos, CJ Collison, AD White - Chemical Science, 2025 - pubs.rsc.org
Large language models (LLMs) have emerged as powerful tools in chemistry, significantly
impacting molecule design, property prediction, and synthesis optimization. This review …

Matsciml: A broad, multi-task benchmark for solid-state materials modeling

KLK Lee, C Gonzales, M Nassar, M Spellings… - arxiv preprint arxiv …, 2023 - arxiv.org
We propose MatSci ML, a novel benchmark for modeling MATerials SCIence using Machine
Learning (MatSci ML) methods focused on solid-state materials with periodic crystal …

Quokka: An open-source large language model chatbot for material science

X Yang, SD Wilson, L Petzold - arxiv preprint arxiv:2401.01089, 2024 - arxiv.org
This paper presents the development of a specialized chatbot for materials science,
leveraging the Llama-2 language model, and continuing pre-training on the expansive …

Actionie: Action extraction from scientific literature with programming languages

X Zhong, Y Du, S Ouyang, M Zhong, T Luo… - Proceedings of the …, 2024 - aclanthology.org
Extraction of experimental procedures from human language in scientific literature and
patents into actionable sequences in robotics language holds immense significance in …

Matexpert: Decomposing materials discovery by mimicking human experts

Q Ding, S Miret, B Liu - arxiv preprint arxiv:2410.21317, 2024 - arxiv.org
Material discovery is a critical research area with profound implications for various
industries. In this work, we introduce MatExpert, a novel framework that leverages Large …