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Published on: February 17, 2019
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New insights into antibubble formation by single drop impact on a same-liquid pool
1Department of Food Science, College of Agriculture and Veterinary Medicine, United Arab Emirates University, Al Ain 15551, United Arab Emirates.
Journal of Colloid and Interface Science
|February 9, 2024
Summary
Secondary drops (SDs) from falling drops can create antibubbles. This study reveals new formation mechanisms and predicts antibubble size and probability using parameters like falling-drop height and surfactant concentration.
Area of Science:
- Fluid dynamics
- Surface science
- Colloid and interface science
Background:
- Secondary drops (SDs) are formed when falling drops impact a liquid bath.
- These SDs can potentially generate antibubbles, which are bubbles within a bubble.
- Understanding antibubble formation is crucial for various applications.
Purpose of the Study:
- To identify mechanisms of antibubble formation from secondary drops.
- To predict the size and formation probability (PAb) of antibubbles.
- To explore the influence of parameters like falling-drop height and surfactant concentration.
Main Methods:
- Generating secondary drops using a stable pulseless microfluidic pump.
- Recording drop impacts with a high-speed camera.
- Analyzing SD and antibubble formation, size, and probability based on falling-drop height (HFD) and dimensionless parameters (e.g., Weber number).
Main Results:
- New antibubble formation mechanisms from SDs were identified.
- Increased falling-drop height, impact velocity (U), and Weber number (We) led to larger SDs and antibubbles but fewer SDs.
- Antibubble formation probability showed distinct peaks related to HFD, U, and We, influenced by surfactant concentration.
Conclusions:
- Surfactant concentration plays a critical role in antibubble formation, with an optimal range for enhanced probability.
- Artificial neural modeling successfully predicted antibubble formation.
- Findings offer insights for controlled antibubble generation.
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