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Organisationseinheit der BAM
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.
A thorough characterization of base materials is the prereq- uisite for further research. In this paper, the characterization data of the reference materials (CEM I 42.5 R, limestone pow- der, calcined clay and a mixture of these three components) used in the second funding phase of the priority program 2005 of the German Research Foundation (DFG SPP 2005) are presented under the aspects of chemical and min- eralogical composition as well as physical and chemical properties. The data were collected based on tests performed by up to eleven research groups involved in this cooperative program.
Chapter 6: Case studies
(2023)