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Modeling oil/water emulsion separation in batch systems with population balances in the presence of surfactant

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  • معلومة اضافية
    • Contributors:
      Department of Chemical and Metallurgical Engineering; Chemical engineering; Aalto-yliopisto; Aalto University
    • بيانات النشر:
      Elsevier Ltd
    • الموضوع:
      2024
    • Collection:
      Aalto University Publication Archive (Aaltodoc) / Aalto-yliopiston julkaisuarkistoa
    • نبذة مختصرة :
      This study introduces a simplified model for batch gravitational separation of liquid–liquid dispersions, integrating a decantation model with a high order moment conserving method of classes in population balances (PBM-HMMC). The proposed model incorporates the dynamics of surfactants and their effect on droplet size distribution, emphasizing the crucial influence of surfactants on emulsion stability. Notably, while extensive literature exists on predicting interphases in batch separation with surfactants, the application of population balance methods to predict droplet size distribution evolution is scarcely addressed, which is a primary focus of this work. The model's accuracy is verified through comparison with independent experimental data, confirming its practical relevance. Furthermore, the research explores the impact of various parameters, including emulsion height, surfactant concentration and type, and droplet size distribution, on the separation process. ; Peer reviewed
    • File Description:
      application/pdf
    • ISSN:
      0009-2509
      1873-4405
    • Relation:
      Chemical Engineering Science; Volume 300; Mousavi, M, Bernad, A & Alopaeus, V 2024, ' Modeling oil/water emulsion separation in batch systems with population balances in the presence of surfactant ', Chemical Engineering Science, vol. 300, 120558 . https://doi.org/10.1016/j.ces.2024.120558; PURE UUID: 2531353f-0361-4cde-8b7d-3e53170c6732; PURE ITEMURL: https://research.aalto.fi/en/publications/2531353f-0361-4cde-8b7d-3e53170c6732; PURE LINK: http://www.scopus.com/inward/record.url?scp=85199958808&partnerID=8YFLogxK; PURE FILEURL: https://research.aalto.fi/files/154332136/CHEM_Mousavi_et_al_Modeling_oil-water_2024_Chemical_Engineering_Science.pdf; https://aaltodoc.aalto.fi/handle/123456789/130326; URN:NBN:fi:aalto-202408285887
    • الرقم المعرف:
      10.1016/j.ces.2024.120558
    • Rights:
      openAccess
    • الرقم المعرف:
      edsbas.E41C53B0