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 <strong>Large Language Model Agents for Atomistic Simulation Workflows</strong><br />
 <em>Jan Janssen (Max Planck Institute for Sustainable Materials)</em>
 
+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.
 
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