Literature DB >> 24407661

Direct numerical simulation of AC dielectrophoretic particle-particle interactive motions.

Ye Ai1, Zhenping Zeng2, Shizhi Qian3.   

Abstract

Under an AC electric field, individual particles in close proximity induce spatially non-uniform electric field around each other, accordingly resulting in mutual dielectrophoretic (DEP) forces on these particles. The resulting attractive DEP particle-particle interaction could assemble individual colloidal particles or biological cells into regular patterns, which has become a promising bottom-up fabrication technique for bio-composite materials and microscopic functional structures. In this study, we developed a transient multiphysics model under the thin electric double layer (EDL) assumption, in which the fluid flow field, AC electric field and motion of finite-size particles are simultaneously solved using an Arbitrary Lagrangian-Eulerian (ALE) numerical approach. Numerical simulations show that negative DEP particle-particle interaction always tends to attract particles and form a chain parallel to the applied electric field. Particles usually accelerate at the first stage of the attractive motion due to an increase in the DEP interactive force, however, decelerate until stationary at the second stage due to a faster increase in the repulsive hydrodynamic force. Identical particles move at the same speed during the interactive motion. In contrast, smaller particles move faster than bigger particles during the attractive motion. The developed model explains the basic mechanism of AC DEP-based particle assembly technique and provides a versatile tool to design microfluidic devices for AC DEP-based particle or cell manipulation.
Copyright © 2013 Elsevier Inc. All rights reserved.

Keywords:  Arbitrary Lagrangian–Eulerian (ALE); Dielectrophoresis; Microfluidics; Particle assembly; Particle chaining

Year:  2013        PMID: 24407661     DOI: 10.1016/j.jcis.2013.11.034

Source DB:  PubMed          Journal:  J Colloid Interface Sci        ISSN: 0021-9797            Impact factor:   8.128


  8 in total

1.  Expanding the flexibility of dynamics simulation on different size particle-particle interactions by dielectrophoresis.

Authors:  Sheng Hu; Rongrong Fu
Journal:  J Biol Phys       Date:  2018-10-26       Impact factor: 1.365

2.  Comparing machine learning and deep learning regression frameworks for accurate prediction of dielectrophoretic force.

Authors:  Sunday Ajala; Harikrishnan Muraleedharan Jalajamony; Midhun Nair; Pradeep Marimuthu; Renny Edwin Fernandez
Journal:  Sci Rep       Date:  2022-07-13       Impact factor: 4.996

Review 3.  A review of polystyrene bead manipulation by dielectrophoresis.

Authors:  Qiaoying Chen; Yong J Yuan
Journal:  RSC Adv       Date:  2019-02-08       Impact factor: 4.036

4.  Elucidating the Mechanisms of Two Unique Phenomena Governed by Particle-Particle Interaction under DEP: Tumbling Motion of Pearl Chains and Alignment of Ellipsoidal Particles.

Authors:  Yu Zhao; Jozef Brcka; Jacques Faguet; Guigen Zhang
Journal:  Micromachines (Basel)       Date:  2018-06-01       Impact factor: 2.891

5.  Numerical Investigation of DC Dielectrophoretic Deformable Particle⁻Particle Interactions and Assembly.

Authors:  Xiang Ji; Li Xu; Teng Zhou; Liuyong Shi; Yongbo Deng; Jie Li
Journal:  Micromachines (Basel)       Date:  2018-05-25       Impact factor: 2.891

6.  Deformability-Based Electrokinetic Particle Separation.

Authors:  Teng Zhou; Li-Hsien Yeh; Feng-Chen Li; Benjamin Mauroy; Sang Woo Joo
Journal:  Micromachines (Basel)       Date:  2016-09-20       Impact factor: 2.891

7.  A Continuous Cell Separation and Collection Approach on a Microfilter and Negative Dielectrophoresis Combined Chip.

Authors:  Qiong Wang; Xiaoling Zhang; Danfen Yin; Jinan Deng; Jun Yang; Ning Hu
Journal:  Micromachines (Basel)       Date:  2020-11-26       Impact factor: 2.891

8.  Deep-Learning Based Estimation of Dielectrophoretic Force.

Authors:  Sunday Ajala; Harikrishnan Muraleedharan Jalajamony; Renny Edwin Fernandez
Journal:  Micromachines (Basel)       Date:  2021-12-28       Impact factor: 2.891

  8 in total

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