Multi-agent systems for chemical engineering
a review and perspective
Sophia Rupprecht (TU Delft - ChemE/Process Systems Engineering)
Qinghe Gao (TU Delft - ChemE/Process Systems Engineering)
Tanuj Karia (TU Delft - ChemE/Process Systems Engineering)
Artur M. Schweidtmann (TU Delft - ChemE/Process Systems Engineering)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Large language model (LLM)-based multi-agent systems (MASs) are a recent but rapidly evolving technology with the potential to transform chemical engineering by decomposing complex workflows into teams of collaborative agents with specialized knowledge and tools. This review surveys the state-of-the-art of MASs within chemical engineering. While early studies demonstrate promising results, scientific challenges remain, including the design of tailored architectures, integration of heterogeneous data modalities, development of foundation models with domain-specific modalities, and strategies for ensuring transparency, safety, and environmental impact. As a young but fast-moving field, MASs offer exciting opportunities to rethink chemical engineering workflows.
help_outline