Inertial cell sorting of microparticle-laden flows: An innovative OpenFOAM-based arbitrary Lagrangian–Eulerian numerical approach

微粒 分类 机械 惯性参考系 欧拉路径 计算机科学 经典力学 物理 应用数学 拉格朗日 数学 算法 光学
作者
Zahra Hashemi Shahraki,Mahdi Navidbakhsh,Robert A. Taylor
出处
期刊:Biomicrofluidics [American Institute of Physics]
卷期号:15 (1) 被引量:3
标识
DOI:10.1063/5.0035352
摘要

The need for cell and particle sorting in human health care and biotechnology applications is undeniable. Inertial microfluidics has proven to be an effective cell and particle sorting technology in many of these applications. Still, only a limited understanding of the underlying physics of particle migration is currently available due to the complex inertial and impact forces arising from particle–particle and particle–wall interactions. Thus, even though it would likely enable significant advances in the field, very few studies have tried to simulate particle-laden flows in inertial microfluidic devices. To address this, this study proposes new codes (solved in OpenFOAM software) that capture all the salient inertial forces, including the four-way coupling between the conveying fluid and the suspended particles traveling a spiral microchannel. Additionally, these simulations are relatively (computationally) inexpensive since the arbitrary Lagrangian–Eulerian formulation allows the fluid elements to be much larger than the particles. In this study, simulations were conducted for two different spiral microchannel cross sections (e.g., rectangular and trapezoidal) for comparison against previously published experimental results. The results indicate good agreement with experiments in terms of (monodisperse) particle focusing positions, and the codes can readily be extended to simulate two different particle types. This new numerical approach is significant because it opens the door to rapid geometric and flow rate optimization in order to improve the efficiency and purity of cell and particle sorting in biotechnology applications.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
zlololo发布了新的文献求助10
1秒前
1秒前
桐桐应助lee采纳,获得10
2秒前
善学以致用应助长京采纳,获得10
2秒前
mogekkko发布了新的文献求助10
2秒前
SS1988发布了新的文献求助10
2秒前
毛豆应助liu采纳,获得10
3秒前
zke完成签到,获得积分10
3秒前
要减肥的乐双完成签到 ,获得积分10
5秒前
赘婿应助伈X采纳,获得10
5秒前
6秒前
6秒前
elsa完成签到,获得积分10
6秒前
四文鱼发布了新的文献求助10
6秒前
7秒前
Caroline完成签到 ,获得积分10
7秒前
10秒前
10秒前
10秒前
躺平摆烂发布了新的文献求助10
11秒前
huangjober关注了科研通微信公众号
11秒前
11秒前
夕十发布了新的文献求助10
12秒前
扶好三四应助666采纳,获得20
12秒前
DYN完成签到 ,获得积分10
12秒前
Xx发布了新的文献求助20
13秒前
共享精神应助偷猪剑客采纳,获得10
13秒前
14秒前
chutong12345完成签到,获得积分10
14秒前
15秒前
16秒前
16秒前
17秒前
长京发布了新的文献求助10
17秒前
急急急完成签到,获得积分10
18秒前
19秒前
19秒前
笑傲完成签到,获得积分10
19秒前
小元发布了新的文献求助30
20秒前
YangShu关注了科研通微信公众号
20秒前
高分求助中
Востребованный временем 2500
Classics in Total Synthesis IV: New Targets, Strategies, Methods 1000
Mantids of the euro-mediterranean area 600
The Oxford Handbook of Educational Psychology 600
Injection and Compression Molding Fundamentals 500
Mantodea of the World: Species Catalog Andrew M 500
Insecta 2. Blattodea, Mantodea, Isoptera, Grylloblattodea, Phasmatodea, Dermaptera and Embioptera 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 内科学 物理 纳米技术 计算机科学 基因 遗传学 化学工程 复合材料 免疫学 物理化学 细胞生物学 催化作用 病理
热门帖子
关注 科研通微信公众号,转发送积分 3422098
求助须知:如何正确求助?哪些是违规求助? 3022549
关于积分的说明 8901291
捐赠科研通 2709910
什么是DOI,文献DOI怎么找? 1486230
科研通“疑难数据库(出版商)”最低求助积分说明 686963
邀请新用户注册赠送积分活动 682179