14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon

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 hacka...

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Detalles Bibliográficos
Autores principales: Jablonka, Kevin Maik, Ai, Qianxiang, Al-Feghali, Alexander, Badhwar, Shruti, Bocarsly, Joshua D., Bran, Andres M., Bringuier, Stefan, Brinson, L. Catherine, Choudhary, Kamal, Circi, Defne, Cox, Sam, de Jong, Wibe A., Evans, Matthew L., Gastellu, Nicolas, Genzling, Jerome, Gil, María Victoria, Gupta, Ankur K., Hong, Zhi, Imran, Alishba, Kruschwitz, Sabine, Labarre, Anne, Lála, Jakub, Liu, Tao, Ma, Steven, Majumdar, Sauradeep, Merz, Garrett W., Moitessier, Nicolas, Moubarak, Elias, Mouriño, Beatriz, Pelkie, Brenden, Pieler, Michael, Ramos, Mayk Caldas, Ranković, Bojana, Rodriques, Samuel G., Sanders, Jacob N., Schwaller, Philippe, Schwarting, Marcus, Shi, Jiale, Smit, Berend, Smith, Ben E., Van Herck, Joren, Völker, Christoph, Ward, Logan, Warren, Sean, Weiser, Benjamin, Zhang, Sylvester, Zhang, Xiaoqi, Zia, Ghezal Ahmad, Scourtas, Aristana, Schmidt, K. J., Foster, Ian, White, Andrew D., Blaiszik, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: RSC 2023
Materias:
Chemistry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10561547/
https://www.ncbi.nlm.nih.gov/pubmed/38013906
http://dx.doi.org/10.1039/d3dd00113j

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