Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.

翻译：大语言模型（LLMs）如GPT-4引起了众多科学家的兴趣。近期研究表明，这些模型在化学和材料科学领域具有潜在应用价值。为探索这些可能性，我们组织了一场黑客马拉松。本文记录了该黑客马拉松中构建的项目。参与者将LLMs应用于多种场景，包括预测分子和材料性质、设计新型工具交互界面、从非结构化数据中提取知识，以及开发创新教育应用。这些主题的多样性以及能在两天内生成可运行原型的事实表明，LLMs将深刻影响我们领域的未来。丰富的创意与项目集合也证明，LLMs的应用不仅限于材料科学与化学，更有望为广泛学科领域带来潜在益处。