Quantitative Analysis of Drag Force for Task-Specific Micromachine at Low Reynolds Numbers

Author:

Wang Qiang,Wang Zhen

Abstract

Micromotors have spread widely in order to meet the needs of new applications, including cell operation, drug delivery, biosensing, precise surgery and environmental decontamination, due to their small size, low energy consumption and large propelling power, especially the newly designed multifunctional micromotors that combine many extra shape features in one device. Features such as rod-like receptors, dendritic biosensors and ball-like catalyzing enzymes are added to the outer surface of the tubular micromotor during fabrication to perform their special mission. However, the structural optimization of motion performance is still unclear. The main factor restricting the motion performance of the micromotors is the drag forces. The complex geometry of a micromotor makes its dynamic behavior more complicated in a fluid environment. This study aimed to design the optimum structure of tubular micromotors with minimum drag forces and obtain the magnitude of drag forces considering both the internal and external fluids of the micromotors. By using the computational fluid dynamics software Fluent 18.0 (ANSYS), the drag force and the drag coefficient of different conical micromotors were calculated. Moreover, the influence of the Reynolds numbers Re, the semi-cone angle δ and the ratios ξ and η on the drag coefficient was analyzed. The results show the drag force monotonically increased with Reynolds numbers Re and the ratio η. The extreme point of the drag curve is reached when the semi-cone angle δ is 8° and the ratio ξ is 3.846. This work provides theoretical support and guidance for optimizing the design and development of conical micromotors.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Comprehensive Understanding of Self-Propelled Janus Pt/Fe2O3 Micromotor Dynamics: Impact of Size, Morphology, and Surface Structure;The Journal of Physical Chemistry Letters;2023-10-27

2. Deep Learning-Based Approach for Optical Microrobot Tracking, Pose Prediction and Trapping Points Localisation;2023 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS);2023-10-09

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