LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Design of an optimized ECCA microchannel for particle manipulation utilizing dean flow coupled elasto-inertial method

Photo by edhoradic from unsplash

Abstract In this paper, an Eulerian-Lagrangian simulation was conducted to achieve optimal Expanded-Contracted Cavity Arrays microchannel. First, a new code was developed to solve the viscoelastic flow field, and then… Click to show full abstract

Abstract In this paper, an Eulerian-Lagrangian simulation was conducted to achieve optimal Expanded-Contracted Cavity Arrays microchannel. First, a new code was developed to solve the viscoelastic flow field, and then the particles were solved by adding appropriate forces to the OpenFOAM Lagrangian solver. This code was then validated for both Eulerian and Lagrangian models. Subsequently, the effect of different parameters such as flow rate, distance from the inlet, cavity depth and distance, and particle size were also studied to obtain the proper geometry for particle focusing. Finally, the selected channel was integrated with a straight channel to separate 4.8 and 13 μm particles. The results of current research can be used to find a proper design of an Expanded-Contracted Cavity Arrays channel to achieve precise focusing and efficient, continuous, and sheathless particle/cell separation, which is much worthy for applications such as high-speed cytometry, cell counting, sorting, and many biological applications.

Keywords: optimized ecca; ecca microchannel; design optimized; particle; design; microchannel particle

Journal Title: Advanced Powder Technology
Year Published: 2021

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.