About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Artificial Intelligence Applications in Integrated Computational Materials Engineering (AI-ICME)
|
| Presentation Title |
Large Language Model Agents for Atomistic Simulation Workflows |
| Author(s) |
Jan Janssen, Joerg Neugebauer |
| On-Site Speaker (Planned) |
Jan Janssen |
| Abstract Scope |
Large language models (LLMs) are powerful tools for scientific research, particularly in interdisciplinary fields such as materials science, where they can bridge the gap between theory and experimentation. We have explored the potential of LLMs in designing new materials through atomistic simulations. Although LLMs face challenges such as complex Python programming and generating accurate responses, these issues could be overcome by integrating an agentic approach with simulation workflows in the pyiron framework. Our pyiron framework allows LLMs to calculate material properties and perform inverse design, identifying alloy compositions that meet specific criteria. The study highlights the importance of linking research data to scientific workflows to simplify processes for LLMs and researchers alike. The LangSim interface, which combines language and simulation, has been developed to facilitate this integration and is available on GitHub, thereby enhancing the synergy between LLMs and scientific workflows in materials science. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Computational Materials Science & Engineering, Sustainability, ICME |