This tool is the competition version of the llm4lammps tool. The transformative role of Large Language Models (LLMs) in computational materials science is explored by mixing OpenAI's GPT-4 API with a LAMMPS simulation workflow. This tool aims to be a demonstration of what is possible with automated and streamlined research processes and shed light on the future of materials science discoveries. We hope that throughout the course of the competition, a variety of interesting LAMMPS simulations are thought up and run with minimal knowledge of LAMMPS itself. Instead users may rely on physics knowledge and the power of the large language models. 

Researchers should cite this work as follows:

• Ethan Holbrook, Saswat Mishra, Juan Carlos Verduzco Gastelum, William Zummo, Kat Nykiel, Alejandro Strachan (2024), "Large language model competition for LAMMPS," https://nanohub.org/resources/llm4lammpscomp. (DOI: 10.21981/3DDX-QX90).

  BibTex | EndNote

1. graphical user interface (GUI)
2. LAMMPS
3. large language models
4. machine learning and data science