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Exploring the Effects of Liquid Marbles' Deformation on Their Rolling Resistance.

Yukai SunMeirong ZhaoClarence Augustine Th TeeLe SongJinwei GuoJie PanChuntian LiuShiyu ZhangYelong Zheng
Published in: Langmuir : the ACS journal of surfaces and colloids (2023)
Liquid marbles (LMs) are nonwetting droplets manufactured by encapsulating droplets with micro- or nanoscale particles. These marbles are widely used as transport carriers for digital microfluidics due to their rapid displacement velocity and leak-free transport. An improved understanding of the resistance mechanism of rolling LMs is crucial for their transport and manipulation. In this study, we investigated the rolling resistance of LMs obtained with different powders and volumes using a high-speed camera. Our findings suggest that the deformation of liquid marbles would hinder their rolling by a resistance torque. To depict this resistance effect, we propose a theoretical model ( f ∼ λ ( ε - 1 2 Bo 1 / 2 ε 2 + 1 4 Bo ε 3 ) ) , where f is the rolling resistance of marbles, λ is the deflection coefficient, Bo is the Bond number, and (ε is the contact surface deformation) that accurately predicts the relationship between deformation and rolling resistance, which is supported by our experimental results. To further validate our theoretical model, we conducted three independent experiments: shape detection of prepared LMs, measuring the elastic force of LMs, and detecting the diffusive motion of the encapsulating particles. Furthermore, we discuss three factors that affect the rolling resistance: the volume of the marbles, the type and size of the encapsulating particles, and the substrate roughness. This comprehensive study not only generalizes the mechanism of deformation hindering the rolling of liquid marbles but also provides a theoretical framework to predict the relationship between the deformation and rolling resistance. These findings have practical implications for improving the manipulation efficiency and advancing the use of LMs as microfluidic carriers.
Keyphrases
  • high speed
  • magnetic resonance imaging
  • computed tomography
  • atomic force microscopy
  • high resolution
  • machine learning
  • magnetic resonance
  • single cell
  • sensitive detection
  • low cost