Multi-agentic AI framework for end-to-end atomistic simulations

Autonomous multi-agent AI system coordinates specialized agents to perform complex materials property calculations from natural language prompts.

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Publication Details

Journal
Digital Discovery
Published
2025-12-09
DOI
https://doi.org/10.1039/d5dd00435g
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00

Funders

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article

Multi-agentic AI framework for end-to-end atomistic simulations

Digital Discovery
Machine Learning in Materials Science
article

Multi-agentic AI framework for end-to-end atomistic simulations

article en

Abstract

Autonomous multi-agent AI system coordinates specialized agents to perform complex materials property calculations from natural language prompts.

Digital DiscoveryVol. 5(1)
Argonne National Laboratory (US), University of Illinois Chicago (US)
U.S. Department of Energy, National Energy Research Scientific Computing Center, Office of Science, Basic Energy Sciences, Argonne National Laboratory, Lawrence Berkeley National Laboratory
Openalex Percentile: Top 51%
Machine Learning in Materials Science
DOIOpen Access PDFOpenAlex
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Multi-agentic AI framework for end-to-end atomistic simulations · Digital Discovery (2025) | TGRS Research Map | TGRS