Fast liquid–liquid dispersion for low volumina in an active micromixer — AI-based investigation.
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| Title: | Fast liquid–liquid dispersion for low volumina in an active micromixer — AI-based investigation. |
|---|---|
| Authors: | Burke, Inga1 (AUTHOR) inga.burke@tu-dortmund.de, Brockerhoff, Lucas1 (AUTHOR), Kockmann, Norbert1 (AUTHOR) |
| Source: | Chemical Engineering & Processing. Sep2025, Vol. 215, pN.PAG-N.PAG. 1p. |
| Subjects: | Artificial intelligence, Image recognition (Computer vision), Gear pumps, Energy dissipation, High temperatures |
| Abstract: | Miniaturized equipment offers many benefits for mixing and liquid–liquid dispersion processes, such as fast and controllable mixing, high surface-to-volume ratio, and lower specific energy consumption. Rapidly changing product mixtures, as can be found in cosmetics industry, require special knowledge of the performance of the mixing and emulsification processes. Here, the droplet size distribution (DSD) is important to define the quality, consistency, and stability of the product and is often regarded as a critical quality attribute. In this work, a modified microstructured annular gear pump is examined as an active mixer for emulsification processes. The active micromixer has the benefit that the mixing power can be freely adjusted, independently of the volumetric flow rate, which enables performance investigation of the DSD based on the specific energy dissipation rate. Important process parameters, such as volumetric flow rate (0.5 to 1.5 mL ⋅ min-1), rotor speed (6000 to 12000 min-1) , and mass fraction of the dispersed phase (10 to 18.4 w% of the oil phase) are examined to investigate their effects on the DSD. For this, an AI-based image recognition is used for emulsion characterization. This methodology provides real-time monitoring and the opportunity to define operation ranges for rapid optimization of rotor, housing, geometry of mixing devices, and further process conditions such as volumetric flow rate for liquid–liquid mixing. [Display omitted] • Rapid dispersion in continuous-flow micromixer. • Near real-time measurement of emulsification and process control. • AI-based analysis for rapid process characterization. • Continuous emulsification at elevated temperature. [ABSTRACT FROM AUTHOR] |
| Copyright of Chemical Engineering & Processing is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 185834742 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Fast liquid–liquid dispersion for low volumina in an active micromixer — AI-based investigation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Burke%2C+Inga%22">Burke, Inga</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> inga.burke@tu-dortmund.de</i><br /><searchLink fieldCode="AR" term="%22Brockerhoff%2C+Lucas%22">Brockerhoff, Lucas</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kockmann%2C+Norbert%22">Kockmann, Norbert</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Chemical+Engineering+%26+Processing%22">Chemical Engineering & Processing</searchLink>. Sep2025, Vol. 215, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Image+recognition+%28Computer+vision%29%22">Image recognition (Computer vision)</searchLink><br /><searchLink fieldCode="DE" term="%22Gear+pumps%22">Gear pumps</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+dissipation%22">Energy dissipation</searchLink><br /><searchLink fieldCode="DE" term="%22High+temperatures%22">High temperatures</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Miniaturized equipment offers many benefits for mixing and liquid–liquid dispersion processes, such as fast and controllable mixing, high surface-to-volume ratio, and lower specific energy consumption. Rapidly changing product mixtures, as can be found in cosmetics industry, require special knowledge of the performance of the mixing and emulsification processes. Here, the droplet size distribution (DSD) is important to define the quality, consistency, and stability of the product and is often regarded as a critical quality attribute. In this work, a modified microstructured annular gear pump is examined as an active mixer for emulsification processes. The active micromixer has the benefit that the mixing power can be freely adjusted, independently of the volumetric flow rate, which enables performance investigation of the DSD based on the specific energy dissipation rate. Important process parameters, such as volumetric flow rate (0.5 to 1.5 mL ⋅ min-1), rotor speed (6000 to 12000 min-1) , and mass fraction of the dispersed phase (10 to 18.4 w% of the oil phase) are examined to investigate their effects on the DSD. For this, an AI-based image recognition is used for emulsion characterization. This methodology provides real-time monitoring and the opportunity to define operation ranges for rapid optimization of rotor, housing, geometry of mixing devices, and further process conditions such as volumetric flow rate for liquid–liquid mixing. [Display omitted] • Rapid dispersion in continuous-flow micromixer. • Near real-time measurement of emulsification and process control. • AI-based analysis for rapid process characterization. • Continuous emulsification at elevated temperature. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Chemical Engineering & Processing is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.cep.2025.110362 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Image recognition (Computer vision) Type: general – SubjectFull: Gear pumps Type: general – SubjectFull: Energy dissipation Type: general – SubjectFull: High temperatures Type: general Titles: – TitleFull: Fast liquid–liquid dispersion for low volumina in an active micromixer — AI-based investigation. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Burke, Inga – PersonEntity: Name: NameFull: Brockerhoff, Lucas – PersonEntity: Name: NameFull: Kockmann, Norbert IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 02552701 Numbering: – Type: volume Value: 215 Titles: – TitleFull: Chemical Engineering & Processing Type: main |
| ResultId | 1 |
