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Imaging and Quantification of the Area of Fast-Moving Microbubbles Using a High-Speed Camera and Image Analysis
Published on: September 5, 2020
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Mechanisms of single bubble cleaning.
Fabian Reuter1, Robert Mettin1
1Christian Doppler Laboratory for Cavitation and Micro-Erosion, Drittes Physikalisches Institut, Georg-August-Universität Göttingen, Friedrich-Hund-Platz 1, 37077 Göttingen, Germany.
Ultrasonics Sonochemistry
|July 19, 2015
Summary
Laser-induced bubble collapse near a solid surface effectively removes micro-particles through rapid liquid flows. Optimal cleaning occurs at a specific bubble stand-off distance, minimizing surface damage.
Area of Science:
- Physics of fluids
- Surface science
- Acoustics
Background:
- Surface-attached particles pose challenges in various industrial and scientific applications.
- Controlling particle removal without damaging sensitive surfaces is crucial.
Purpose of the Study:
- To investigate the dynamics of laser-induced bubble collapse near a solid boundary.
- To evaluate the effectiveness of this phenomenon for removing surface-attached micro-particles.
- To determine the optimal conditions for particle removal while minimizing substrate damage.
Main Methods:
- Generating individual bubbles using nanosecond Nd:YAG laser pulses near contaminated glass plates.
- Analyzing bubble dynamics via synchronous high-speed recordings.
- Characterizing cleaned areas and bubble dynamics using the non-dimensional stand-off parameter γ (gamma).
Main Results:
- Bubble collapse near a solid boundary generates a liquid jet, leading to particle removal.
- Optimal cleaning is observed at a stand-off parameter γ ≈ 0.7.
- Three distinct cleaning regimes were identified based on the stand-off distance γ, involving vortex flows, jet impact, and bubble wall oscillations.
- Cleaning effectiveness decreases for γ > 3.5, with no cleaning observed beyond this threshold.
Conclusions:
- Laser-induced bubble collapse is a viable method for removing surface-attached micro-particles.
- The non-dimensional stand-off parameter γ is critical for optimizing particle removal efficiency and minimizing surface damage.
- The study suggests a trade-off between cleaning potential and damage risk that can be managed by optimizing γ.
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