14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Abstrak
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.
Topik & Kata Kunci
Penulis (53)
Kevin Maik Jablonka
Qianxiang Ai
Alexander Al-Feghali
Shruti Badhwar
Joshua D. Bocarsly
Andres M Bran
Stefan Bringuier
L. Catherine Brinson
Kamal Choudhary
Defne Circi
Sam Cox
Wibe A. de Jong
Matthew L. Evans
Nicolas Gastellu
Jerome Genzling
María Victoria Gil
Ankur K. Gupta
Zhi Hong
Alishba Imran
Sabine Kruschwitz
Anne Labarre
Jakub Lála
Tao Liu
Steven Ma
Sauradeep Majumdar
Garrett W. Merz
Nicolas Moitessier
Elias Moubarak
Beatriz Mouriño
Brenden Pelkie
Michael Pieler
Mayk Caldas Ramos
Bojana Ranković
Samuel G. Rodriques
Jacob N. Sanders
Philippe Schwaller
Marcus Schwarting
Jiale Shi
Berend Smit
Ben E. Smith
Joren Van Herck
Christoph Völker
Logan Ward
Sean Warren
Benjamin Weiser
Sylvester Zhang
Xiaoqi Zhang
Ghezal Ahmad Zia
Aristana Scourtas
KJ Schmidt
Ian Foster
Andrew D. White
Ben Blaiszik
Akses Cepat
- Tahun Terbit
- 2023
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓