Towards Fully Automated Molecular Simulations: Multi-Agent Framework for Simulation Setup and Force Field Extraction
By: Marko Petković, Vlado Menkovski, Sofía Calero
Potential Business Impact:
Lets computers discover new materials automatically.
Automated characterization of porous materials has the potential to accelerate materials discovery, but it remains limited by the complexity of simulation setup and force field selection. We propose a multi-agent framework in which LLM-based agents can autonomously understand a characterization task, plan appropriate simulations, assemble relevant force fields, execute them and interpret their results to guide subsequent steps. As a first step toward this vision, we present a multi-agent system for literature-informed force field extraction and automated RASPA simulation setup. Initial evaluations demonstrate high correctness and reproducibility, highlighting this approach's potential to enable fully autonomous, scalable materials characterization.
Similar Papers
ChemGraph: An Agentic Framework for Computational Chemistry Workflows
Chemical Physics
AI helps scientists discover new materials faster.
Build Your Personalized Research Group: A Multiagent Framework for Continual and Interactive Science Automation
Artificial Intelligence
AI helps scientists discover new things faster.
Multi-agent systems for chemical engineering: A review and perspective
Multiagent Systems
Teams of AI help design new chemicals faster.