SOURCE-LINKED INTELLIGENCE
El Agente Potente: High-Throughput Agentic Atomistic Simulations
Foundational machine-learning interatomic potentials (MLIPs) are transforming atomistic simulations by achieving near-ab initio accuracy across large chemical spaces at a fraction of the computational cost. A central challenge in using these tools for high-throughput property calculations is translating high-level scientific intent into adaptive simulation campaigns without compromising workflow rigour. We introduce El Agente Potente, an agentic system that combines typed execution graphs with a complementary coding mode for MLIPs-driven atomistic simulations. Typed execution graphs provide st
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-13T23:20:21.000Z
First collected: 2026-09-20T12:21:05.240Z. This is not the publication date.