On-demand droplet formation at a T-junction: modelling and validation

Droplet microfluidics have found increasing applications across many fields. While droplet generation at a T-junction is a common method, its reliance on trial-and-error operation imposes undesirable constraints on its performance and applicability. In this study, we demonstrate a simple method for on-demand droplet formation at a T-junction with precise temporal control over individual droplet formation. Based on experimental observations, we also develop a physical model to describe the relationships among pressures, droplet generation, device geometry, and interfacial properties. Experimental validation demonstrates excellent performance of the model in predicting the pressure thresholds for switching droplet generation on and off. To address parameter uncertainties arising from real-world complexities, we show that monitoring droplet generation frequency provides a rapid, in situ approach for optimising experimental conditions. Our findings offer valuable guidelines for the design and automation of robust droplet-on-demand microfluidic systems, which can be readily implemented in conventional laboratories for a broad range of applications.

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Publication Details

Journal
Microsystems & Nanoengineering
Published
2025-05-19
DOI
https://doi.org/10.1038/s41378-025-00950-2
Citations
4
Primary Topic
Innovative Microfluidic and Catalytic Techniques Innovation
Type
article
Field-Weighted Citation Impact
2.70

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article

On-demand droplet formation at a T-junction: modelling and validation

Huabing Yin, Hongyu Zhao, Jonathan M. Cooper, William A. Mills et al.
4 citations
Microsystems & Nanoengineering
Innovative Microfluidic and Catalytic Techniques Innovation
2.70
article

On-demand droplet formation at a T-junction: modelling and validation

Huabing Yin, Hongyu Zhao, Jonathan M. Cooper, William A. Mills, Liang Peng, Andrew Glidle, Bei Li
article en
4 citations

Abstract

Droplet microfluidics have found increasing applications across many fields. While droplet generation at a T-junction is a common method, its reliance on trial-and-error operation imposes undesirable constraints on its performance and applicability. In this study, we demonstrate a simple method for on-demand droplet formation at a T-junction with precise temporal control over individual droplet formation. Based on experimental observations, we also develop a physical model to describe the relationships among pressures, droplet generation, device geometry, and interfacial properties. Experimental validation demonstrates excellent performance of the model in predicting the pressure thresholds for switching droplet generation on and off. To address parameter uncertainties arising from real-world complexities, we show that monitoring droplet generation frequency provides a rapid, in situ approach for optimising experimental conditions. Our findings offer valuable guidelines for the design and automation of robust droplet-on-demand microfluidic systems, which can be readily implemented in conventional laboratories for a broad range of applications.

Microsystems & NanoengineeringVol. 11(1)
Glasgow School of Art (GB), Jilin University (CN), Chinese Academy of Sciences (CN), Changchun Institute of Optics, Fine Mechanics and Physics (CN), University of Glasgow (GB), University of Edinburgh (GB)
University of Glasgow, Chinese Academy of Sciences, Engineering and Physical Sciences Research Council, Natural Environment Research Council, Innovate UK, James Watt School of Engineering, University of Glasgow
Openalex Percentile: Top 10%
Innovative Microfluidic and Catalytic Techniques Innovation
2.70
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