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Published on: April 12, 2019
Aitomia: An Agentic Framework for AI-Driven Atomistic and Quantum Chemical Simulations
Jinming Hu1, Hassan Nawaz1, Yi-Fan Hou1
1State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemistry, College of Chemistry and Chemicals Engineering, and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, Xiamen University, Xiamen 361005, China.
Abstract:
We present Aitomia, an agentic framework for AI-driven atomistic and quantum chemical (QC) simulations that helps experts and nonexperts alike set up and run calculations, analyze results, and summarize them in textual and graphical forms through natural language interaction. Built on the MLatom software ecosystem, Aitomia supports AI-driven atomistic simulations as well as conventional quantum-chemical calculations, including density functional theory, semiempirical methods such as GFN2-xTB, and selected high-level wave function-based methods, through interfaces to widely used programs such as Gaussian, ORCA, PySCF, and xtb, covering tasks from ground- and excited-state calculations to geometry optimization, thermochemistry, and spectra simulations. By autonomously executing computational workflows, Aitomia can deliver infrared spectra in seconds and reaction thermochemistry in minutes, with results close to experiment or high-level theoretical references while greatly reducing the manual effort required from users. Aitomia lowers the barrier to performing atomistic simulations, thereby democratizing simulations and accelerating research and development in the relevant fields.
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