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Shrinking microbubbles with microfluidics: mathematical modelling to control microbubble sizes.

A Salari¹, V Gnyawali, I M Griffiths

¹Biomedical Engineering Graduate Program, Ryerson University, Toronto, Canada.

|November 15, 2017

Summary

This summary is machine-generated.

Researchers developed a microfluidic platform to create small microbubbles for medical uses. A new mathematical model predicts bubble size, aiding in engineering specific microbubble dimensions for clinical applications.

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Area of Science:

Biomedical Engineering
Fluid Dynamics
Materials Science

Background:

Microbubbles are valuable in medicine for drug delivery, oxygen transport, sonoporation, and ultrasound imaging.
Generating microbubbles smaller than 10 micrometers (<10 μm) using microfluidics is challenging, often requiring complex and expensive setups.
A novel microfluidic platform integrates flow-focusing with a vacuum system to shrink microbubbles to desired sub-10 μm sizes.

Purpose of the Study:

To develop a theoretical framework correlating microbubble size with input parameters in a microfluidic platform.
To establish a predictive model for microbubble generation and shrinkage under varying conditions.
To facilitate the engineering of specific microbubble sizes for medical applications.

Main Methods:

Characterization of microbubbles produced with varying lipid concentrations and solution interfacial tensions.
Monitoring microbubble size changes within the microfluidic channel under different vacuum pressures.
Development of a mathematical model based on the physics of the bubble shrinkage mechanism.

Main Results:

The study successfully characterized microbubble behavior under diverse experimental conditions.
A mathematical model was developed that accurately predicts microbubble sizes based on input parameters.
The model demonstrates good agreement with experimental data, validating its predictive capabilities.

Conclusions:

The developed mathematical model effectively predicts microbubble sizes generated by the microfluidic platform.
This theoretical framework is crucial for understanding and controlling microbubble dimensions.
The model will empower users to precisely engineer microbubbles for targeted medical applications.