Shape-based separation of micro-/nanoparticles in liquid phases

Behdani, Behrouz; Monjezi, Saman; Carey, Mason J.; Weldon, Curtis G.; Zhang, Jie; Wang, Cheng; Park, Joontaek

doi:10.1063/1.5052171

Cited by 26 publications

(12 citation statements)

References 144 publications

(168 reference statements)

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“…Advances in microfluidics have resulted in robust and high-throughput methods for micrometer-scale segregation. These techniques rely on external force fields ( 7 , 8 ), sorting based on fluorescence ( 9 ), intricate separator geometries ( 10 – 18 ), or carriers with non-Newtonian behavior ( 19 ). An alternative approach toward microscale separation is to leverage the long-range hydrodynamic interactions emerging from fluid–structure coupling ( 20 , 21 ).…”

mentioning

confidence: 99%

Universal motion of mirror-symmetric microparticles in confined Stokes flow

Georgiev

Toscano

Uspal

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

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Comprehensive understanding of particle motion in microfluidic devices is essential to unlock additional technologies for shape-based separation and sorting of microparticles like microplastics, cells, and crystal polymorphs. Such particles interact hydrodynamically with confining surfaces, thus altering their trajectories. These hydrodynamic interactions are shape dependent and can be tuned to guide a particle along a specific path. We produce strongly confined particles with various shapes in a shallow microfluidic channel via stop flow lithography. Regardless of their exact shape, particles with a single mirror plane have identical modes of motion: in-plane rotation and cross-stream translation along a bell-shaped path. Each mode has a characteristic time, determined by particle geometry. Furthermore, each particle trajectory can be scaled by its respective characteristic times onto two master curves. We propose minimalistic relations linking these timescales to particle shape. Together these master curves yield a trajectory universal to particles with a single mirror plane.

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mentioning

confidence: 99%

Universal motion of mirror-symmetric microparticles in confined Stokes flow

Georgiev

Toscano

Uspal

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

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“…Additionally, DLD may be employed for separation of particles and cells by their shape involving two types of phenomena: differences in length scale and differences in transport properties [328]. For instance, Beech et al combined size-based sorting with the isolation of cells regarding their susceptibility to shear stress ( Figure 17) [329].…”

Section: Deterministic Lateral Displacementmentioning

confidence: 99%

Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches

Voronin

Kozlova

Verkhovskii

et al. 2020

IJMS

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Flow cytometry nowadays is among the main working instruments in modern biology paving the way for clinics to provide early, quick, and reliable diagnostics of many blood-related diseases. The major problem for clinical applications is the detection of rare pathogenic objects in patient blood. These objects can be circulating tumor cells, very rare during the early stages of cancer development, various microorganisms and parasites in the blood during acute blood infections. All of these rare diagnostic objects can be detected and identified very rapidly to save a patient’s life. This review outlines the main techniques of visualization of rare objects in the blood flow, methods for extraction of such objects from the blood flow for further investigations and new approaches to identify the objects automatically with the modern deep learning methods.

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“…The fast developing nonlinear technique in biomicrofluidics is promising to precisely control the motion of particles and cells for focusing, 1 concentration, 2 and separation. 3 Recently, the inertial effects and non-Newtonian fluids 4,5 are getting much attention for their capabilities to achieve an extreme throughput continuously without the need for external forces. 6 Therefore, some fundamental issues such as the number of stable equilibrium positions and the effect of rheology on the inertial migration in the channel will be crucial for the development of biomicrofluidic chips and medical particles/cell diagnostics.…”

Section: Introductionmentioning

confidence: 99%

Influence of non-Newtonian power law rheology on inertial migration of particles in channel flow

Lin

Chen

et al. 2020

Biomicrofluidics

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In this paper, the inertial migration of particles in the channel flow of power-law fluid is numerically investigated. The effects of the power-law index (n), Reynolds number (Re), blockage ratio (k), and channel aspect ratio (AR) on the inertial migration of particles and equilibrium position are explored. The results show that there exist two stages of particle migration and four stable equilibrium positions for particles in the cross section of a square channel. The particle equilibrium positions in a rectangular channel are much different from those in a square channel. In shear-thinning fluids, the long channel face equilibrium position and two kinds of particle trajectories are found at low Re. With increasing Re, the short channel face equilibrium position turns to be stable, multiequilibrium positions, and three kinds of particle trajectories along the long wall start to form. Only two stable equilibrium positions exist in shear-thickening fluids. The equilibrium positions are getting closer to the channel centerline with increasing n and k and with decreasing Re. The inertial focusing length L 2 in the second stage of particle migration is much longer than inertial focusing length L 1 in the first stage. In the square channel, L 2 is decreased with increasing Re and k and with decreasing n. In the rectangular channel, L 2 is the shortest in the shear-thinning fluid.

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Shape-based separation of micro-/nanoparticles in liquid phases

Cited by 26 publications

References 144 publications

Universal motion of mirror-symmetric microparticles in confined Stokes flow

Universal motion of mirror-symmetric microparticles in confined Stokes flow

Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches

Influence of non-Newtonian power law rheology on inertial migration of particles in channel flow

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