Directional self-migration of droplets on an inclined surface driven by wettability gradient

In the current study, the anti-gravity directional self-migration of droplets on an inclined surface driven by wettability gradient (ω) was investigated using a front-tracking method. A unified mechanical model of droplet motion on an inclined wettability gradient wall was derived, considering the driving force generated by ω (Fd), gravity (G), and flow resistance (Ff). The model demonstrates that ω, G, and inclination angle (α) are key parameters affecting droplet motion. By varying ω, Bond number (Bo), and α, the droplet dynamic characteristics were analyzed, and a real-time Capillary number (Ca) was introduced to measure the droplet migration speed. The results indicate that a larger ω generates a greater Fd, leading to faster migration and more pronounced spreading. When the ratio of the channel width to the droplet diameter is 0.7, the droplet can cross three regions, obtaining double Fd, and Ca curve exhibits a bimodal structure. When the ratio of the channel width to the droplet diameter is 1.2, the droplet slides and spreads in the middle region without ω, resulting in a trimodal Ca curve. A larger Bo implies a stronger gravity effect, reducing the net driving force for upward migration and slowing the migration speed. At α=30° and ω=0.54, Bo reaches its critical value at 0.5, where G exceeds Fd, causing the droplet to slide downward along the wall. α affects droplet motion by controlling the gravitational component along the wall (Gx). A larger α results in a smaller net driving force for upward migration, reducing the migration speed.

Authors

Institutions

Publication Details

Journal
Physics of Fluids
Published
2024-09-01
DOI
https://doi.org/10.1063/5.0228546
Citations
6
Primary Topic
Fluid Dynamics and Heat Transfer
Type
article
Field-Weighted Citation Impact
2.25

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Directional self-migration of droplets on an inclined surface driven by wettability gradient

Yuan Tian, Shuting Zhao, Zhaoqing Ke, Ying Zhang et al.
6 citations
Physics of Fluids
Fluid Dynamics and Heat Transfer
2.25
article

Directional self-migration of droplets on an inclined surface driven by wettability gradient

Yuan Tian, Shuting Zhao, Zhaoqing Ke, Ying Zhang, Yao Liu, D.C. Sun
article en
6 citations

Abstract

In the current study, the anti-gravity directional self-migration of droplets on an inclined surface driven by wettability gradient (ω) was investigated using a front-tracking method. A unified mechanical model of droplet motion on an inclined wettability gradient wall was derived, considering the driving force generated by ω (Fd), gravity (G), and flow resistance (Ff). The model demonstrates that ω, G, and inclination angle (α) are key parameters affecting droplet motion. By varying ω, Bond number (Bo), and α, the droplet dynamic characteristics were analyzed, and a real-time Capillary number (Ca) was introduced to measure the droplet migration speed. The results indicate that a larger ω generates a greater Fd, leading to faster migration and more pronounced spreading. When the ratio of the channel width to the droplet diameter is 0.7, the droplet can cross three regions, obtaining double Fd, and Ca curve exhibits a bimodal structure. When the ratio of the channel width to the droplet diameter is 1.2, the droplet slides and spreads in the middle region without ω, resulting in a trimodal Ca curve. A larger Bo implies a stronger gravity effect, reducing the net driving force for upward migration and slowing the migration speed. At α=30° and ω=0.54, Bo reaches its critical value at 0.5, where G exceeds Fd, causing the droplet to slide downward along the wall. α affects droplet motion by controlling the gravitational component along the wall (Gx). A larger α results in a smaller net driving force for upward migration, reducing the migration speed.

Physics of FluidsVol. 36(9)
Jiujiang University (CN), Nanchang University (CN), Centre for Sustainable Energy (GB), Sustainable Development Institute (US), Education Department of Jiangxi Province (CN), China Shenhua Energy (China) (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangxi Province
Openalex Percentile: Top 13%
Fluid Dynamics and Heat Transfer
2.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.