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We use a macromodel of a flow-driven deterministic lateral displacement (DLD) microfluidic system to investigate conditions leading to size-separation of suspended particles. This model system can be easily reconfigured to establish an…

Fluid Dynamics · Physics 2016-04-27 Siqi Du , German Drazer

The Discrete Particle Method (DPM) is used to model granular flows down an inclined chute. We observe three major regimes: static piles, steady uniform flows and accelerating flows. For flows over a smooth base, other (quasi-steady) regimes…

Soft Condensed Matter · Physics 2011-08-26 Thomas Weinhart , Anthony Thornton , Stefan Luding , Onno Bokhove

We investigate the effect of particle volume fraction on the efficiency of deterministic lateral displacement (DLD) devices. DLD is a popular passive sorting technique for microfluidic applications. Yet, it has been designed for treating…

Soft Condensed Matter · Physics 2015-10-27 Rohan Vernekar , Timm Krüger

The dynamics of dense particle packings near the jamming transition is characterized by correlated particle motion. The growth of dynamical heterogeneities, or strong spatial variations in the motion of the particles constituting the…

Soft Condensed Matter · Physics 2024-09-12 Rajkumar Biswas , Anoop Mutneja , Smarajit Karmakar , Ranjini Bandyopadhyay

In this work, we use the standard deviation of image pixel intensity to analyse the speed, direction and surface-interaction of microparticles in fluid. First, we present an analytical model for estimating the total variance in the image…

Applied Physics · Physics 2019-04-10 Harish Sasikumar , Manoj M. Varma

Pinched flow fractionation is shown to be an efficient and selective way to quickly separate particles by size in a very polydisperse semi-concentrated suspension. In an effort to optimize the method, we discuss the quantitative influence…

Fluid Dynamics · Physics 2012-04-17 Aparna Srivastav , Thomas Podgorski , Gwennou Coupier

Dissipative particle dynamics (DPD) is a relatively new technique which has proved successful in the simulation of complex fluids. We caution that for the equilibrium achieved by the DPD simulation of a simple fluid the temperature depends…

Statistical Mechanics · Physics 2009-10-30 C. A. Marsh , J. M. Yeomans

Inspired by numerous lab on a chip, biomedical and bioengineering applications such as cell sorting, focusing, trapping, and filtering of particles, manipulation of micron sized particle trajectories has been of significant interest in the…

Fluid Dynamics · Physics 2026-03-18 Partha Kumar Das

Flowing granular materials segregate due to differences in particle size (driven by percolation) and density (driven by buoyancy). Modelling the segregation of mixtures of large/heavy particles and small/light particles is challenging due…

Soft Condensed Matter · Physics 2021-05-18 Yifei Duan , Paul B. Umbanhowar , Julio M. Ottino , Richard M. Lueptow

The ability to separate and analyze chemical species with high resolution, sensitivity, and throughput is central to the development of microfluidics systems. Deterministic lateral displacement (DLD) is a continuous separation method based…

Fluid Dynamics · Physics 2014-04-15 Timothy J. Bowman , German Drazer , Joelle Frechette

Introduced more than fifty years ago, dynamic light scattering is routinely used to determine the size distribution of colloidal suspensions, as well as of macromolecules in solution, such as proteins, nucleic acids, and their complexes.…

Plastic deformation In crystalline materials is controlled by the motion and interactions of dislocations [AND 17]. Discrete Dislocation Dynamics (DDD) simulations have now existed for about 25 years to investigate plastic flow at the…

Materials Science · Physics 2020-01-07 Sylvain Queyreau

Integration of physics principles with data-driven methods has attracted great attention in recent few years. In this study, a physics-informed dynamic mode decomposition (piDMD) method, where the mass conservation law is integrated with a…

Fluid Dynamics · Physics 2023-11-07 Dandan Li , Bidan Zhao , Shuai Lu , Junwu Wang

Dip-coating consists in withdrawing a substrate from a bath to coat it with a thin liquid layer. This process is well-understood for homogeneous fluids, but heterogeneities such as particles dispersed in the liquid lead to more complex…

Soft Condensed Matter · Physics 2022-03-02 Deok-Hoon Jeong , Michael Ka Ho Lee , Virgile Thiévenaz , Martin Z. Bazant , A. Sauret

Dynamic Mode Decomposition (DMD) is a data-driven and model-free decomposition technique. It is suitable for revealing spatio-temporal features of both numerically and experimentally acquired data. Conceptually, DMD performs a…

Fluid Dynamics · Physics 2020-12-18 Tim Krake , Stefan Reinhardt , Marcel Hlawatsch , Bernhard Eberhardt , Daniel Weiskopf

The interaction of multiple fluids through a heterogeneous pore space leads to complex pore-scale flow dynamics, such as intermittent pathway flow. The non-local nature of these dynamics, and the size of the 4D datasets acquired to capture…

The study of macro continuous flow has a long history. Simultaneously, the exploration of heat and mass transfer in small systems with a particle number of several hundred or less has gained significant interest in the fields of statistical…

Fluid Dynamics · Physics 2024-03-13 Aiguo Xu , Dejia Zhang , Yanbiao Gan

Dynamic mode decomposition (DMD) has proven to be a valuable tool for the analysis of complex flow-fields but the application of this technique to flows with moving boundaries is not straightforward. This is due to the difficulty in…

Fluid Dynamics · Physics 2020-07-28 Karthik Menon , Rajat Mittal

In conventional Deterministic Lateral Displacement (DLD), the migration behavior of a particle of specific size is determined by the critical diameter (Dc), which is predefined by the device's geometry. In contrast to the typical approach…

Fluid Dynamics · Physics 2024-01-17 Ali Kheirkhah Barzoki , Amir Shamloo

Differentiable particle filters provide a flexible mechanism to adaptively train dynamic and measurement models by learning from observed data. However, most existing differentiable particle filters are within the bootstrap particle…

Artificial Intelligence · Computer Science 2021-11-11 Xiongjie Chen , Hao Wen , Yunpeng Li