Print Email Facebook Twitter Machine learning and circular bioeconomy Title Machine learning and circular bioeconomy: Building new resource efficiency from diverse waste streams Author Tsui, To Hung (National University of Singapore; Campus for Research Excellence and Technological Enterprise (CREA) van Loosdrecht, Mark C.M. (TU Delft BT/Environmental Biotechnology) Dai, Yanjun (Shanghai Jiao Tong University) Tong, Yen Wah (National University of Singapore; Campus for Research Excellence and Technological Enterprise (CREA) Date 2023 Abstract Biorefinery systems are playing pivotal roles in the technological support of resource efficiency for circular bioeconomy. Meanwhile, artificial intelligence presents great potential in handling scientific tasks of high-dimensional complexity. This review article scrutinizes the status of machine learning (ML) applications in four critical biorefinery systems (i.e. composting, fermentation, anaerobic digestion, and thermochemical conversions) as well as their advancements against traditional modeling techniques of mechanistic approach. The contents cover their algorithm selections, modeling challenges, and prospective improvements. Perspectives are sketched to further inform collective efforts on crucial aspects. The multidisciplinary interchange of modeling knowledge will enable a more progressive digital transformation of sustainability efforts in supporting sustainable development goals. Subject BiorefineryMultiscale modelingResource recoverySupply chainSustainability To reference this document use: http://resolver.tudelft.nl/uuid:f65a75bc-c174-47b0-9f12-762a9f289cb1 DOI https://doi.org/10.1016/j.biortech.2022.128445 Embargo date 2023-06-05 ISSN 0960-8524 Source Bioresource Technology, 369 Bibliographical note Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type review Rights © 2023 To Hung Tsui, Mark C.M. van Loosdrecht, Yanjun Dai, Yen Wah Tong Files PDF 1_s2.0_S0960852422017783_main.pdf 1.37 MB Close viewer /islandora/object/uuid:f65a75bc-c174-47b0-9f12-762a9f289cb1/datastream/OBJ/view