mlsanityData to 14 Oct 2026

Aitomia: Your Intelligent Assistant for AI-Driven Atomistic and Quantum Chemical Simulations

arXiv 2505.08195 ↗First posted 13 May 2025physics.comp-ph cs.AI cs.LGcited by 8

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Abstract (arXiv)

We have developed Aitomia - a platform powered by AI to assist in performing AI-driven atomistic and quantum chemical (QC) simulations. This evolving intelligent assistant platform is equipped with chatbots and AI agents to help experts and guide non-experts in setting up and running atomistic simulations, analyzing simulation results, and summarizing them for the user in both textual and graphical forms. Aitomia combines LLM-based agents with the MLatom platform to support AI-driven atomistic simulations as well as conventional quantum-chemical calculations, including DFT, semiempirical methods such as GFN2-xTB, and selected high-level wavefunction-based methods, through interfaces to widely used programs such as Gaussian, ORCA, PySCF, and xtb, covering tasks from ground-state and excited-state calculations to geometry optimization, thermochemistry, and spectra simulations. The multi-agent implementation enables autonomous execution of complex computational workflows, such as reaction enthalpy calculations. Aitomia was the first intelligent assistant publicly launched on cloud computing platforms for broad-scope atomistic simulations (Aitomistic Lab@XMU at https://atom.xmu.edu.cn and Aitomistic Hub at https://aitomistic.xyz). Aitomia lowers the barrier to performing atomistic simulations, thereby democratizing simulations and accelerating research and development in relevant fields.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 15 of its 60 references that are in the map. First posted on arXiv 13 May 2025.

Builds on

15 of 60 references.

References · 15

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3 more
  1. 2024CataLM: Empowering Catalyst Design Through Large Language Modelscited by 3
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 6.

8 papers.

Similar, not cited

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  1. 2026QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities
  2. 2025ChemGraph: An Agentic Framework for Computational Chemistry Workflows
  3. 2026An Agentic Orchestration of Atomistic Simulations
  4. 2026El Agente Quntur: A research collaborator agent for quantum chemistry
  5. 2026Science Done on a Machine by a Machine: AI Agents in Computational Chemistry
  6. 2024AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligence
  7. 2025Prospects for Using Artificial Intelligence to Understand Intrinsic Kinetics of Heterogeneous Catalytic Reactions
  8. 2026LLM-Guided Test-Time Discovery of Quantum-Chemical Approximation Algorithms