AI Framework for Analyzing Molecular Dynamics Simulations
Published:Dec 30, 2025 10:36
•1 min read
•ArXiv
Analysis
This paper introduces VisU, a novel framework that uses large language models to automate the analysis of nonadiabatic molecular dynamics simulations. The framework mimics a collaborative research environment, leveraging visual intuition and chemical expertise to identify reaction channels and key nuclear motions. This approach aims to reduce reliance on manual interpretation and enable more scalable mechanistic discovery in excited-state dynamics.
Key Takeaways
- •VisU framework automates the analysis of nonadiabatic molecular dynamics simulations.
- •It uses a Mentor-Engineer-Student paradigm to mimic a collaborative research environment.
- •The framework leverages visual intuition and chemical expertise.
- •It aims to reduce manual interpretation and enable scalable mechanistic discovery.
Reference
“VisU autonomously orchestrates a four-stage workflow comprising Preprocessing, Recursive Channel Discovery, Important-Motion Identification, and Validation/Summary.”