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dc.contributor.author Cruz-Olivares, Julian
dc.contributor.author Pérez Alonso, Israel Andy
dc.contributor.author Martín del Campo López, Eduardo
dc.contributor.author ROMAN GUERRERO, ANGELICA
dc.contributor.author Báez González, Juan Gabriel
dc.contributor.author Pérez-Alonso, César
dc.date.accessioned 2026-08-06T23:07:18Z
dc.date.available 2026-08-06T23:07:18Z
dc.date.issued 2026-06-24
dc.identifier.issn 2675-5459
dc.identifier.uri http://hdl.handle.net/20.500.11799/144295
dc.description Artículo sobre IA es
dc.description.abstract The convergence of Chemical Engineering 5.0 and Agentic Artificial Intelligence (AI) marks a paradigm shift in the chemical industry. Unlike traditional AI, intelligent agents do not just analyze data; they reason, plan, execute complex tasks in closed-loop systems. Today, this technology optimizes operational efficiency in chemical plants through advanced predictive maintenance and autonomous real-time tuning of process variables, drastically reducing energy consumption and carbon footprints. In the near future, Agentic AI will be the cornerstone of Self-Driving Labs, where multi-agent systems will independently design new catalysis and materials by integrating molecular simulation and robotic experimentation without constant human intervention. This evolution toward a human-centric industry’ will allow engineers to shift into strategic and ethical oversight roles, while agents manage supply chain resilience and industrial symbiosis. Therefore, the primary goal of this work is to demonstrate how Agentic AI is not merely a computational tool, but an essential autonomous collaborator for achieving sustainability and mass customization that defines the era of Chemical Engineering 5.0. es
dc.language.iso eng es
dc.publisher South Florida Journal of Development es
dc.rights openAccess es
dc.rights.uri http://creativecommons.org/licenses/by/4.0 es
dc.subject Chemical Engineering 5.0 es
dc.subject Agentic Artificial Intelligence es
dc.subject Sustainability es
dc.subject Self-Driving Labs es
dc.subject.classification INGENIERÍA Y TECNOLOGÍA es
dc.title Agentic AI in Chemical Engineering 5.0: Current Landscape and Future Outlook es
dc.type Artículo es
dc.provenance Científica es
dc.road Dorada es
dc.organismo Química es
dc.cve.CenCos 20401 es
dc.relation.vol 7
dc.validacion.itt Si es


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  • Título
  • Agentic AI in Chemical Engineering 5.0: Current Landscape and Future Outlook
  • Autor
  • Cruz-Olivares, Julian
  • Pérez Alonso, Israel Andy
  • Martín del Campo López, Eduardo
  • ROMAN GUERRERO, ANGELICA
  • Báez González, Juan Gabriel
  • Pérez-Alonso, César
  • Fecha de publicación
  • 2026-06-24
  • Editor
  • South Florida Journal of Development
  • Tipo de documento
  • Artículo
  • Palabras clave
  • Chemical Engineering 5.0
  • Agentic Artificial Intelligence
  • Sustainability
  • Self-Driving Labs

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