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Flow-resistance analysis of nano-confined fluids inspired from liquid nano-lubrication: A Review
College of Chemical Engineering, State Key Laboratory of Materials-Oriented Chemical Engineering, Nanjing Tech University, Nanjing .
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.
College of Chemical Engineering, State Key Laboratory of Materials-Oriented Chemical Engineering, Nanjing Tech University.
College of Chemical Engineering, State Key Laboratory of Materials-Oriented Chemical Engineering, Nanjing Tech University.
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2017 (English)In: Chinese Journal of Chemical Engineering, ISSN 1004-9541, E-ISSN 2210-321X, Vol. 25, no 11, 1552-1562 p.Article in journal (Refereed) Published
Abstract [en]

 How to reduce flow resistance of nano-confined fluids to achieve a high flux is a new challenge for modern chemical engineering applications, such as membrane separation and nanofluidic devices. Traditional models are inapplicable to explain the significant differences in the flow resistance of different liquid–solid systems. On the other hand, friction reduction in liquid nano-lubrication has received considerable attention during the past decades. Both fields are exposed to a common scientific issue regarding friction reduction during liquid–solid relative motion at nanoscale. A promising approach to control the flow resistance of nano-confined fluids is to reference the factors affecting liquid nano-lubrication. In this review, two concepts of the friction coefficient derived from fluid flow and tribology were discussed to reveal their intrinsic relations. Recent progress on low or ultra-low friction coefficients in liquid nano-lubrication was summarized based on two situations. Finally, a new strategy was introduced to study the friction coefficient based on analyzing the intermolecular interactions through an atomic force microscope (AFM), which is a cutting-point to build a new model to study flow-resistance at nanoscale.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 25, no 11, 1552-1562 p.
National Category
Tribology
Research subject
Machine Elements
Identifiers
URN: urn:nbn:se:ltu:diva-64730DOI: 10.1016/j.cjche.2017.05.005OAI: oai:DiVA.org:ltu-64730DiVA: diva2:1118892
Note

Validerad;2017;Nivå 2;2017-12-05 (andbra)

Available from: 2017-07-03 Created: 2017-07-03 Last updated: 2017-12-05Bibliographically approved

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