Systematic characterization of effect of flow rates and buffer compositions on double emulsion droplet volumes and stability

Enhanced CRISPR/Cas12a-based quantitative detection of nucleic acids using double emulsion droplets

Pairing droplet microfluidics and CRISPR/Cas12a techniques creates a powerful solution for the detection and quantification of nucleic acids at the single-molecule level, due to its specificity, sensitivity, and simplicity. However, traditional water-in-oil (W/O) single emulsion (SE) droplets often present stability issues, affecting the accuracy and reproducibility of assay results. As an alternative, water-in-oil-in-water (W/O/W) double emulsion (DE) droplets offer superior stability and uniformity for droplet digital assays. Moreover, unlike SE droplets, DE droplets are compatible with commercially available flow cytometry instruments for high-throughput analysis. Despite these advantages, no study has demonstrated the use of DE droplets for CRISPR-based nucleic acid detection. In our study, we conducted a comparative analysis to assess the performance of SE and DE droplets in quantitative detection of human papillomavirus type 18 (HPV18) DNA based on CRISPR/Cas12a. We evaluated the stability of SEs and DEs by examining size variation, merging extent, and content interaction before and after incubation at different temperatures and time points. By integrating DE droplets with flow cytometry, we achieved high-throughput and high-accuracy CRISPR/Cas12a-based quantification of target HPV18 DNA. The DE platform, when paired with CRISPR/Cas12a and flow cytometry techniques, emerges as a reliable tool for absolute quantification of nucleic acid biomarkers.

Design automation of microfluidic single and double emulsion droplets with machine learning

Droplet microfluidics enables kHz screening of picoliter samples at a fraction of the cost of other high-throughput approaches. However, generating stable droplets with desired characteristics typically requires labor-intensive empirical optimization of device designs and flow conditions that limit adoption to specialist labs. Here, we compile a comprehensive droplet dataset and use it to train machine learning models capable of accurately predicting device geometries and flow conditions required to generate stable aqueous-in-oil and oil-in-aqueous single and double emulsions from 15 to 250 μm at rates up to 12000 Hz for different fluids commonly used in life sciences. Blind predictions by our models for as-yet-unseen fluids, geometries, and device materials yield accurate results, establishing their generalizability. Finally, we generate an easy-to-use design automation tool that yield droplets within 3 μm (<8%) of the desired diameter, facilitating tailored droplet-based platforms and accelerating their utility in life sciences.

Grease the gears: how lubrication of syringe pumps impacts microfluidic flow precision

Pumps are indispensable for analytical applications and ensure controlled fluid movement. Syringe pumps are among today's most prevalent liquid delivery systems, especially for high-pressure, stable, low-flow-rate microfluidic applications. Due to moving mechanical parts of the assembly, regular maintenance is essential to ensure reliable operation and flow rates. However, lubrication of the mechanics is easily overlooked because the research focuses on novel analytical applications rather than on the maintenance of pumps. Here, we investigate the lubrication of the syringe pump guide rods with its effect on the flow rate stability after regular pump cleaning from contaminations. The guide rods of syringe pumps were thoroughly cleaned from any lubricant, and the flow rate for specified flowrates between 5 and 100 μL min-1 was measured, revealing tremendous flow rate fluctuations with a coefficient of variation (CV) value up to 0.34. In contrast, flow rate measurements of syringe pumps with lubricated guide rods show a five-fold smoother flow rate fluctuation depending on the specified flow rate with CV values below 0.07. These differences in flow rate's CV were most significant for pressure drops below 500 mbar, relevant for many lab-on-a-chip applications. In summary, we emphasize the awareness of lubricating moving parts of syringe pumps to achieve constant flow rates, minimize wear, and ensure the reliable operation of, for instance, accurate lab-on-a-chip workflows.

Versatility and stability optimization of flow-focusing droplet generators via quality metric-driven design automation

Droplet generation is a fundamental component of droplet microfluidics, compartmentalizing biological or chemical systems within a water-in-oil emulsion. As adoption of droplet microfluidics expands beyond expert labs or integrated devices, quality metrics are needed to contextualize the performance capabilities, improving the reproducibility and efficiency of operation. Here, we present two quality metrics for droplet generation: performance versatility, the operating range of a single device, and stability, the distance of a single operating point from a regime change. Both metrics were characterized in silico and validated experimentally using machine learning and rapid prototyping. These metrics were integrated into a design automation workflow, DAFD 2.0, which provides users with droplet generators of a desired performance that are versatile or flow stable. Versatile droplet generators with stable operating points accelerate the development of sophisticated devices by facilitating integration of other microfluidic components and improving the accuracy of design automation tools.

Flexible droplet transportation and coalescence via controllable thermal fields

Flexible droplet transportation and coalescence are significant for lots of applications such as material synthesis and analytical detection. Herein, we present an effective method for controllable droplet transportation and coalescence via thermal fields. The device used for droplet manipulation is composed of a glass substrate with indium tin oxide-made microheaers and a microchannel with two transport branches and a central chamber, and it's manipulated by sequentially powering the microheaters located at the bottom of microchannel. The fluid will be unevenly heated when the microheater is actuated, leading to the formation of thermal buoyancy convection and the decrease of interfacial tension of fluids. Subsequently, the microdroplets can be transported from the inlets of microchannel to the target position by the buoyancy flow-induced Stokes drag. And the droplet migration velocity can be flexibly adjusted by changing the voltage applied on the microheater. After being transported to the center of central chamber, the coalescence behaviors of microdroplets can be triggered if the microheater located at the bottom of central chamber is continuously actuated. The droplet coalescence is the combined effect of decreased fluid interfacial tension, the shortened droplet distance by buoyancy flow and the increased instability of droplet under the elevated temperature. The droplet coalescence efficiency is also related to the voltage of microheater, by increasing the voltage from 3.5 V to 7 V, the needed time for droplet coalescence dramatically decrease from 220s to 1.4 s. Finally, by the droplet coalescence-triggered calcium hydroxide precipitation reaction, we demonstrate the applicability of the droplet manipulation method on specific sample detection. Therefore, this approach used for droplet transportation and coalescence can be attractive for many droplet-based applications such as analytical detection.