title: Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Creators: name: Zimmermann, Yoel
name: Bazgir, Adib
name: Afzal, Zartashia
name: Agbere, Fariha
name: Ai, Qianxiang
name: Alampara, Nawaf
name: Al-Feghali, Alexander
name: Ansari, Mehrad
name: Antypov, Dmytro
name: Aswad, Amro
name: Bai, Jiaru
name: Baibakova, Viktoriia
name: Biswajeet, Devi Dutta
name: Bitzek, Erik
name: Bocarsly, Joshua D.
name: Borisova, Anna
name: Bran, Andres M.
name: Brinson, L. Catherine
name: Calderon, Marcel Moran
name: Canalicchio, Alessandro
name: Chen, Victor
name: Chiang, Yuan
name: Circi, Defne
name: Charmes, Benjamin
name: Chaudhary, Vikrant
name: Chen, Zizhang
name: Chiu, Min-Hsueh
name: Clymo, Judith
name: Dabhadkar, Kedar
name: Daelman, Nathan
name: Datar, Archit
name: Jong, Wibe A. De
name: Evans, Matthew L.
name: Fard, Maryam Ghazizade
name: Fisicaro, Giuseppe
name: Gangan, Abhijeet Sadashiv
name: George, Janine
name: Gonzalez, Jose D. Cojal
name: Götte, Michael
name: Gupta, Ankur K.
name: Harb, Hassan
name: Hong, Pengyu
name: Ibrahim, Abdelrahman
name: Ilyas, Ahmed
name: Imran, Alishba
name: Ishimwe, Kevin
name: Issa, Ramsey
name: Jablonka, Kevin Maik
name: Jones, Colin
name: Josephson, Tyler R.
name: Juhasz, Greg
name: Kapoor, Sarthak
name: Kang, Rongda
name: Khalighinejad, Ghazal
name: Khan, Sartaaj
name: Klawohn, Sascha
name: Kuman, Suneel
name: Ladines, Alvin Noe
name: Leang, Sarom
name: Lederbauer, Magdalena
name: Sheng-Lun
name: , Liao
name: Liu, Hao
name: Liu, Xuefeng
name: Lo, Stanley
name: Madireddy, Sandeep
name: Maharana, Piyush Ranjan
name: Maheshwari, Shagun
name: Mahjoubi, Soroush
name: Márquez, José A.
name: Mills, Rob
name: Mohanty, Trupti
name: Mohr, Bernadette
name: Moosavi, Seyed Mohamad
name: Moßhammer, Alexander
name: Naghdi, Amirhossein D.
name: Naik, Aakash
name: Narykov, Oleksandr
name: Näsström, Hampus
name: Nguyen, Xuan Vu
name: Ni, Xinyi
name: O'Connor, Dana
name: Olayiwola, Teslim
name: Ottomano, Federico
name: Ozhan, Aleyna Beste
name: Pagel, Sebastian
name: Parida, Chiku
name: Park, Jaehee
name: Patel, Vraj
name: Patyukova, Elena
name: Petersen, Martin Hoffmann
name: Pinto, Luis
name: Pizarro, José M.
name: Plessers, Dieter
name: Pradhan, Tapashree
name: Pratiush, Utkarsh
name: Puli, Charishma
name: Qin, Andrew
name: Rajabi, Mahyar
name: Ricci, Francesco
name: Risch, Elliot
name: Ríos-García, Martiño
name: Roy, Aritra
name: Rug, Tehseen
name: Sayeed, Hasan M.
name: Scheidgen, Markus
name: Schilling-Wilhelmi, Mara
name: Schloz, Marcel
name: Schöppach, Fabian
name: Schumann, Julia
name: Schwaller, Philippe
name: Schwarting, Marcus
name: Sharlin, Samiha
name: Shen, Kevin
name: Shi, Jiale
name: Si, Pradip
name: D'Souza, Jennifer
name: Sparks, Taylor
name: Sudhakar, Suraj
name: Talirz, Leopold
name: Tang, Dandan
name: Taran, Olga
name: Terboven, Carla
name: Tropin, Mark
name: Tsymbal, Anastasiia
name: Ueltzen, Katharina
name: Unzueta, Pablo Andres
name: Vasan, Archit
name: Vinchurkar, Tirtha
name: Vo, Trung
name: Vogel, Gabriel
name: Völker, Christoph
name: Weinreich, Jan
name: Yang, Faradawn
name: Zaki, Mohd
name: Zhang, Chi
name: Zhang, Sylvester
name: Zhang, Weijie
name: Zhu, Ruijie
name: Zhu, Shang
name: Janssen, Jan
name: Li, Calvin
name: Foster, Ian
name: Blaiszik, Ben
Publisher: name: Maryland Shared Open Access Repository
Year: 2025
Subjects: subject: Condensed Matter - Materials Science
subject: Physics - Chemical Physics
subject: Computer Science - Machine Learning

description: 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.