Abstract
Droplet-based microfluidics is a powerful tool for high-throughput analysis of liquid samples with significant applications in biomedicine and biochemistry. Nevertheless, extracting content-rich information from single picolitre-sized droplets at high throughputs remains challenging due to the weak signals associated with these small volumes. Overcoming this limitation would be transformative for fields that rely on high-throughput screening, enabling broader multiparametric analysis. Here we present an integrated optofluidic platform that addresses this critical point by combining advanced hyperspectral imaging with self-referencing and measurement automation. With this approach our platform achieves high temporal and spectral resolution with shot-noise limited performance, allowing for the label-free interrogation of single droplet contents. To demonstrate the platform's capabilities, we first exploit its high temporal and spectral resolution to study rapid dynamic changes in the composition of a heterogeneous population of nanoparticles. Second, leveraging the platform's shot-noise limited performance and using a model DNA-AuNP sensor, we detect target DNA sequences down to 250 pM, thereby showcasing the platform's compatibility with demanding sensing applications. Finally, through measurement automation, we demonstrate multiplexed sample monitoring over hours. These findings show that our optofluidic platform not only helps to close the current gap in high-throughput droplet analysis, but also significantly advances the potential for content-rich characterization, ultimately enhancing the scope and effectiveness of high-throughput screening methods.
Published Version
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