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Updated: Jul 3, 2026

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Aqueous Droplets Used as Enzymatic Microreactors and Their Electromagnetic Actuation
Published on: August 28, 2017
Laser-Emitting Droplet Assay for Enzymatic Evaluation Applications
Po-Hao Tseng1, Guocheng Fang2, Tian Zhou1
1School of Electrical and Electronics Engineering, Nanyang Technological University, 50 Nanyang Ave., Singapore 639798, Singapore.
ACS Nano
|July 1, 2026
Summary
We developed a laser-emitting droplet assay (LEDA) for real-time, label-free enzymatic activity monitoring. This ultrasensitive method significantly enhances biochemical analysis in complex biological samples.
Area of Science:
- Biochemistry
- Analytical Chemistry
- Microfluidics
Background:
- Accurate enzymatic activity analysis is crucial but challenging in complex biological settings.
- Existing methods often lack sensitivity or require labels, limiting real-time applications.
Purpose of the Study:
- To introduce a novel laser-emitting droplet assay (LEDA) for sensitive, real-time, label-free enzymatic activity detection.
- To demonstrate the application of LEDA in analyzing biological samples like saliva and milk.
Main Methods:
- Development of a platform using laser-emitting aqueous droplets as whispering-gallery-mode (WGM) microlasers.
- Monitoring enzymatic reactions via measurable shifts in laser signals induced by biochemical changes.
- Integration with microfluidic droplet technology for automated and scalable analysis.
Main Results:
- LEDA achieved a 90-fold sensitivity increase compared to conventional microlasers due to enhanced light-matter interactions.
- Successfully assessed α-amylase activity in saliva and protein concentration in milk samples.
- Distinct spectral signatures differentiated various sample types, showcasing analytical capability.
Conclusions:
- LEDA offers a highly sensitive, label-free approach for real-time enzymatic activity monitoring.
- The assay is adaptable for diverse biochemical analyses, including diagnostics and quality control.
- Integration with microfluidics promises automated, scalable, and ultrasensitive droplet-based analysis.

