El Agente Sólido: A New Age(nt) for Solid State Simulations
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arXiv
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| Format: | Preprint |
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2026
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| author | Kumar, Sai Govind Hari Zou, Yunheng Wang, Andrew Valdés-Hernández, Jesús Ko, Tsz Wai Yue, Nathan Leng, Olivia Xu, Hanyong Crebolder, Chris Aspuru-Guzik, Alán Bernales, Varinia |
| author_facet | Kumar, Sai Govind Hari Zou, Yunheng Wang, Andrew Valdés-Hernández, Jesús Ko, Tsz Wai Yue, Nathan Leng, Olivia Xu, Hanyong Crebolder, Chris Aspuru-Guzik, Alán Bernales, Varinia |
| contents | Quantum chemistry calculations are a key component of the materials discovery process. The results from first-principles explorations enable the prediction of material properties prior to experimental validation. Despite their impact, the practical use of first-principles methods remains limited by the expertise required to design, execute, and troubleshoot complex computational workflows. Even when workflows are successfully built, they are sometimes rigid and not adaptable to different use cases. Recent advances in large language models (LLMs) and agentic systems offer a pathway to flexibly automate these processes and lower barriers to entry. Here, we introduce El Agente Sólido, a hierarchical multi-agent framework for automating solid-state quantum chemistry workflows using the open-source Quantum ESPRESSO simulation package. The framework translates high-level scientific objectives expressed in natural language into end-to-end computational pipelines that include structure generation, input file construction, workflow execution, and post-processing analysis. El Agente Sólido integrates density functional theory with phonon calculations and machine-learning interatomic potentials to enable efficient and physically consistent simulations. Extensive benchmarking and case studies demonstrate that El Agente Sólido reliably executes a wide range of solid-state calculations, highlighting its potential to improve reproducibility and accelerate computational materials discovery |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_17886 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | El Agente Sólido: A New Age(nt) for Solid State Simulations Kumar, Sai Govind Hari Zou, Yunheng Wang, Andrew Valdés-Hernández, Jesús Ko, Tsz Wai Yue, Nathan Leng, Olivia Xu, Hanyong Crebolder, Chris Aspuru-Guzik, Alán Bernales, Varinia Materials Science Chemical Physics Quantum chemistry calculations are a key component of the materials discovery process. The results from first-principles explorations enable the prediction of material properties prior to experimental validation. Despite their impact, the practical use of first-principles methods remains limited by the expertise required to design, execute, and troubleshoot complex computational workflows. Even when workflows are successfully built, they are sometimes rigid and not adaptable to different use cases. Recent advances in large language models (LLMs) and agentic systems offer a pathway to flexibly automate these processes and lower barriers to entry. Here, we introduce El Agente Sólido, a hierarchical multi-agent framework for automating solid-state quantum chemistry workflows using the open-source Quantum ESPRESSO simulation package. The framework translates high-level scientific objectives expressed in natural language into end-to-end computational pipelines that include structure generation, input file construction, workflow execution, and post-processing analysis. El Agente Sólido integrates density functional theory with phonon calculations and machine-learning interatomic potentials to enable efficient and physically consistent simulations. Extensive benchmarking and case studies demonstrate that El Agente Sólido reliably executes a wide range of solid-state calculations, highlighting its potential to improve reproducibility and accelerate computational materials discovery |
| title | El Agente Sólido: A New Age(nt) for Solid State Simulations |
| topic | Materials Science Chemical Physics |
| url | https://arxiv.org/abs/2602.17886 |