Artificial intelligence and machine learning for process and policy design in the transition towards circular economy systems: advancements and opportunities

Novel computational techniques raised under the concept of artificial intelligence have vast applications in science and engineering. In this work, we review the most relevant frameworks and applications of artificial intelligence and machine learning oriented to the development of sustainable production and consumption systems using a bottom-up multi-scale approach. Firstly, we address frameworks for molecular and processing unit design and flowsheet design. Secondly, we assess methods proposed for the environmental and social assessment of superstructures. Finally, we also discuss the contributions and applications of artificial intelligence in the development of policies that support the shift of paradigm to the circular economy.

Authors

Institutions

Publication Details

Journal
Current Opinion in Chemical Engineering
Published
2025-11-29
DOI
https://doi.org/10.1016/j.coche.2025.101200
Citations
2
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
1.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial intelligence and machine learning for process and policy design in the transition towards circular economy systems: advancements and opportunities

Sidney Omelon, Edgar Martín-Hernández, Aurora del Carmen Munguía-López, Borja Hernández
2 citations
Current Opinion in Chemical Engineering
Machine Learning in Materials Science
1.04
article

Artificial intelligence and machine learning for process and policy design in the transition towards circular economy systems: advancements and opportunities

Sidney Omelon, Edgar Martín-Hernández, Aurora del Carmen Munguía-López, Borja Hernández
article en
2 citations

Abstract

Novel computational techniques raised under the concept of artificial intelligence have vast applications in science and engineering. In this work, we review the most relevant frameworks and applications of artificial intelligence and machine learning oriented to the development of sustainable production and consumption systems using a bottom-up multi-scale approach. Firstly, we address frameworks for molecular and processing unit design and flowsheet design. Secondly, we assess methods proposed for the environmental and social assessment of superstructures. Finally, we also discuss the contributions and applications of artificial intelligence in the development of policies that support the shift of paradigm to the circular economy.

Current Opinion in Chemical EngineeringVol. 51
Universidad Rey Juan Carlos (ES), McGill University (CA), University at Buffalo, State University of New York (US)
Openalex Percentile: Top 21%
Machine Learning in Materials Science
1.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.