Amiri Roodan Venoos, Gómez-Pastora Jenifer, Karampelas Ioannis H, González-Fernández Cristina, Bringas Eugenio, Ortiz Inmaculada, Chalmers Jeffrey J, Furlani Edward P, Swihart Mark T
Department of Chemical and Biological Engineering, University at Buffalo, The State University of New York, Buffalo, New York 14260, USA.
William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, 315 Koffolt Laboratories, 151 West Woodruff Avenue, Columbus, Ohio 43210, USA.
Soft Matter. 2020 Oct 28;16(41):9506-9518. doi: 10.1039/d0sm01426e.
We present a numerical model that describes the microfluidic generation and manipulation of ferrofluid droplets under an external magnetic field. We developed a numerical Computational Fluid Dynamics (CFD) analysis for predicting and optimizing continuous flow generation and processing of ferrofluid droplets with and without the presence of a permanent magnet. More specifically, we explore the dynamics of oil-based ferrofluid droplets within an aqueous continuous phase under an external inhomogeneous magnetic field. The developed model determines the effect of the magnetic field on the droplet generation, which is carried out in a flow-focusing geometry, and its sorting in T-junction channels. Three-channel depths (25 μm, 30 μm, and 40 μm) were investigated to study droplet deformation under magnetic forces. Among the three, the 30 μm channel depth showed the most consistent droplet production for the studied range of flow rates. Ferrofluids with different loadings of magnetic nanoparticles were used to observe the behavior for different ratios of magnetic and hydrodynamic forces. Our results show that the effect of these factors on droplet size and generation rate can be tuned and optimized to produce consistent droplet generation and sorting. This approach involves fully coupled magnetic-fluid mechanics models and can predict critical details of the process including droplet size, shape, trajectory, dispensing rate, and the perturbation of the fluid co-flow for different flow rates. The model enables better understanding of the physical phenomena involved in continuous droplet processing and allows efficient parametric analysis and optimization.
我们提出了一个数值模型,该模型描述了在外部磁场作用下铁磁流体微滴的微流控生成与操控。我们开发了一种数值计算流体动力学(CFD)分析方法,用于预测和优化有无永磁体情况下铁磁流体微滴的连续流动生成与处理。更具体地说,我们研究了在外部非均匀磁场作用下,水连续相中油基铁磁流体微滴的动力学。所开发的模型确定了磁场对液滴生成的影响,液滴生成是在流动聚焦几何结构中进行的,以及其在T型结通道中的分选。研究了三种通道深度(25μm、30μm和40μm),以研究磁力作用下的液滴变形。在这三种通道深度中,30μm的通道深度在所研究的流速范围内显示出最稳定的液滴生成。使用具有不同磁性纳米颗粒负载量的铁磁流体来观察不同磁力与流体动力比值下的行为。我们的结果表明,这些因素对液滴尺寸和生成速率的影响可以进行调整和优化,以实现稳定的液滴生成与分选。这种方法涉及完全耦合的磁流体力学模型,可以预测该过程的关键细节,包括不同流速下的液滴尺寸、形状、轨迹、分配速率以及流体共流的扰动。该模型有助于更好地理解连续液滴处理过程中涉及的物理现象,并允许进行有效的参数分析和优化。