El Agente Sólido
Purpose and distinctive contribution
Automate end-to-end solid-state quantum chemistry simulations.
Hierarchical agents translate natural-language objectives into Quantum ESPRESSO structure generation, inputs, execution and analysis, integrating DFT, phonons and machine-learning interatomic potentials.
This page describes the specific system in the cited study, not every capability of the wider El Agente platform.
Publication and full author credit
Sai Govind Hari Kumar; Yunheng Zou; Andrew Wang; Jesús Valdés-Hernández; Tsz Wai Ko; Nathan Yue; Olivia Leng; Hanyong Xu; Chris Crebolder; Alán Aspuru-Guzik; Varinia Bernales. (2026). El Agente Sólido: A New Age(nt) for Solid State Simulations. arXiv:2602.17886.
Publication or posting date: . Preprint; journal publication not independently verified.
Research roles and contributions
Prof. Varinia Bernales and Prof. Alán Aspuru-Guzik are credited as coauthors alongside the complete team above. Detailed conception, supervision, implementation, and maintainer roles have not been independently verified for this page and are not inferred from author order.
Software, artifacts, and limitations
Paper-linked research artifacts → Paper-linked benchmark results; not complete agent source. Availability evidence in the manuscript.
Capabilities are bounded by the tasks, tools, models, and evaluation conditions reported in the study. No universal speedup, reliability, or fully autonomous experimental capability is claimed here. Consult the linked manuscript’s methods and limitations before applying its results to a new workflow.