Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

作者：Zimmermann, Yoel, Adib Bazgir, Zartashia Afzal, Fariha Agbere, Qianxiang Ai, Nawaf Alampara, Alexander Al‐Feghali, Mehrad Ansari, Dmytro Antypov, Amro Aswad, Bai, Jiaru, Viktoriia Baibakova, Devi Dutta Biswajeet, Erik Bitzek, Joshua D. Bocarsly, Anna S. Borisova, Andres M Bran, L. Catherine Brinson, Marcelo Calderón, Alessandro Canalicchio, Victor Chen, Yuan Chiang, Defne Çırcı, Benjamin Charmes, Vikrant Chaudhary, Zizhang Chen, Min–Hsueh Chiu, Judith Clymo, Kedar Dabhadkar, Nathan Daelman, Archit Datar, de Jong, Wibe A., Matthew L. Evans, Fard, Maryam Ghazizade, Giuseppe Fisicaro, Abhijeet Gangan, Janine George, Johan R. González-Moya, Götte, Michael, Ankur K. Gupta, Hassan Harb, Pengyu Hong, Ibrahim, Abdelrahman, Ilyas, Ahmed, Alishba Imran, Kevin Ishimwe, Ramsey Issa, Kevin Maik Jablonka, C. H. W. Jones, Tyler R. Josephson, Juhasz, Greg, Kapoor, Sarthak, Rongda Kang, Ghazal Khalighinejad, Khan, Sartaaj, Sascha Klawohn, Suneel Kuman, Alvin Noe Ladines, Leang, Sarom, Magdalena Lederbauer, Sheng-Lun, Liao, Hao Liu, Xuefeng Liu, Stanley Lo, Sandeep Madireddy, Piyush Ranjan Maharana, Shagun Maheshwari, Soroush Mahjoubi, J.A. Marquez, Rob Mills, Trupti Mohanty, Bernadette Mohr, Seyed Mohamad Moosavi, Alexander Moßhammer, Amirhossein D. Naghdi, Aakash Ashok Naik, Oleksandr Narykov, Hampus Näsström, Xuan Nguyen, Xinyi Ni, Dana O’Connor, Teslim Olayiwola, Federico Ottomano, Aleyna Beste Ozhan, Sebastian Pagel, Parida, Chiku, Jaehee Park, Vraj Patel, Elena Patyukova, Petersen, Martin Hoffmann, Luís Abegão Pinto, José M. Pizarro, Dieter Plessers, Trilochan Pradhan, Utkarsh Pratiush, Charishma Puli, Anquan Qin, Rajabi, Mahyar, Francesco Ricci, Elliot Risch, Martiño Ríos-García, Aritra Roy, Tehseen Rug, Hasan M. Sayeed, Markus Scheidgen, Mara Schilling-Wilhelmi, Marcel Schloz, Fabian Schöppach, Julia Schumann, Philippe Schwaller, Marcus Schwarting, Samiha Sharlin, Kevin Shen, Jiale Shi, Ping-Zhan Si, Jennifer D’Souza, Taylor D. Sparks, Suraj Sudhakar, Leopold Talirz, Dandan Tang, Olga Taran, Carla Terboven, Mark Tropin, Anastasiia Tsymbal, Katharina Ueltzen, Pablo A. Unzueta, Archit Vasan, Tirtha Vinchurkar, Trung D. Vo, Vogel, Gabriel, Christoph Völker, Jan Weinreich, Yang, Faradawn, Mohd Zaki, Chi Zhang, Sylvester Zhang, Weijie Zhang, Ruijie Zhu, Shang Zhu, Jan Janßen, Li, Calvin, Ian Foster, Ben Blaiszik · 发表于：arXiv (Cornell University) · 年份：2024 · DOI：10.48550/arxiv.2411.15221 · 被引用次数：4 · 研究领域：Biomedical and Engineering Education

Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hybrid locations, resulting in 34 team submissions. The submissions spanned seven key application areas and demonstrated the diverse utility of LLMs for applications in (1) molecular and material property prediction; (2) molecular and material design; (3) automation and novel interfaces; (4) scientific communication and education; (5) research data management and automation; (6) hypothesis generation and evaluation; and (7) knowledge extraction and reasoning from scientific literature. Each team submission is presented in a summary table with links to the code and as brief papers in the appendix. Beyond team results, we discuss the hackathon event and its hybrid format, which included physical hubs in Toronto, Montreal, San Francisco, Berlin, Lausanne, and Tokyo, alongside a global online hub to enable local and virtual collaboration. Overall, the event highlighted significant improvements in LLM capabilities since the previous year's hackathon, suggesting continued expansion of LLMs for applications in materials science and chemistry research. These outcomes demonstrate the dual utility of LLMs as both multipurpose models for diverse machine learning tasks and platforms for rapid prototyping custom applications in scientific research.