A new technique for real-time microfluidic droplets characterisation

This research summary describes how Riccardo Zamboni, Annamaria Zaltron, Mathieu Chauvet, and Cinzia Sada developed a fully integrated opto-microfluidic platform to detect, label and enable droplets characterisation using microfluidics. The high reproducibility and portability of this fully integrated opto-microfluidic platform can revolutionise droplet characterisation.

Their work on “Real-time precise microfluidic droplets label-sequencing combined in a velocity detection sensor” was published in Nature Scientific Reports in September 2021.

ABSTRACT

Microfluidics can generate droplets to apply to a broad range of laboratory applications. However, the current imaging techniques used for droplet characterization are time-consuming and need large data storage. This project developed a new opto-microfluidic system for reliable and reproducible droplet labelling using optical waveguides in a Mach Zehnder’s configuration. The opto-microfluidic platform developed by the authors coupled a pressure controller and flow sensor to a pig-tailed He–Ne laser and substrate to successfully sequence, characterise, and label droplets. Due to the biocompatibility and chemical resistant nature of the a lithium niobate substrate used in their experiments, the system can be adapted to a wide range of applications, including lab-on-a-chip techniques.

If you would like to learn more about droplet generation, check this application note.

To learn more, watch the webinar by Leslie Labarre and Aurelie Vigne on droplet-based microfluidics!

INTRODUCTION | A real-time approach for droplet characterization

The integrated approach developed by the authors combines optical waveguides in a Mach-Zehnder interferometer (MZI) configuration to label droplets generated by microfluidics. The MZI configuration consists of an input light waveguide that splits into two arms crossing through a microfluidic channel. After passing through the channel, the two branches recombine into one, forming the output waveguide.

A photodiode collects the output light and transduces the signal to a Data Acquisition System (DAQ) for processing. The optical transmission (OT) intensity changes depending on the refraction of light from the droplet and surrounding phase (oil). Changes in the OT signal detects droplet movement through the channel. Thus, the device sequentially labels and analyses droplets’ length and velocity. 

The authors coupled a camera and a microscope to a pressure-driven microfluidics system. to compare both methods’ performance and reliability, synchronically.

AIM & OBJECTIVES

The proof of concept of this project aimed to:

• Overcome droplet labelling weaknesses of current imaging techniques while maintaining reliability of the acquired data.
• Create a fully integrated opto-microfluidic platform adapted to different laboratory applications and needs.

MATERIALS & METHODS | Estabilishing an opto-microfluidic system

The microfluidic setup is composed of the Elveflow OB1 MK3+ pressure controller connected to the Bronkhorst Coriolis flow sensor. The Elveflow OB1 MK3+  delivers nearly any pressure profile to a system.The in-series Bronkhorst Coriolis flow sensor measures the flow rate across devices. This combination allows both pressure and flow control. 

The pressure controller and flow sensor were coupled to a pig-tailed He–Ne laser with the MZI and a photodiode. Thus, the researchers could create specific and varied flow rates to test different configurations for droplet characterization.

A lithium-niobate substrate was integrated with the microfluidic circuit. The microfluidic system is composed of a cross-junction droplet generator connected to a straight channel. The MZI splits the light into two arms reaching two different parts of the channel.The photodiode collects the light exiting the waveguide and the signal is transduced to a data acquisition system (DAQ).

The droplets were produced by a cross-flow junction of three channels. MilliQ water was injected in the central channel with a varied flow rate of [10:55] μL/min. Hexadecane oil containing 3% SPAN80 was injected into the two perpendicular channels with a flow rate range of [10:125] μL/min.

Video 1: The optofluidic system and the MZI configuration. The microfluidic system is composed of a cross-junction droplet generator connected to a straight channel. The MZI splits the light into two arms reaching two different parts of the channel.The photodiode collects the light exiting the waveguide and the signal is transduced to a data acquisition system (DAQ).

To compare the microfluidic device performance with the imaging approach, a video camera and microscope were coupled to the system. The video simultaneously recorded droplet dynamics in the channel while the microscope allowed real time visualisation of the droplets. 

Video 2: The imaging approach. a video camera and microscope were coupled to the system. The video simultaneously recorded droplet dynamics in the channel while the microscope allowed real time visualisation of the droplets. 

Both the images from the standard system and the optical transmission (OT) signal from the MZI were analysed by an ad-hoc tracking software.

MATERIALS

• Lithium niobate (LN) substrate
• Mach Zehnder interferometer device
• Elveflow OB1 MK3+ pressure controller
• Bronkhorst coriolis flow sensor
• Millipore Milli-Q water
• Suspension of Hexadecane oil (Sigma Aldrich) containing 3% SPAN80 (Sigma Aldrich)
• Opto-fast camera acA800-510μm

KEY FINDINGS | Reliable and faster droplet characterization

By associating trigger times and OT signals with different configurations, the device could label even droplets with arbitrary shape, size, and speed. Also, differences in droplets’ composition generated different configurations, and droplets’ sizes variation showed different OT intensities.

Sequence of droplet passage was determined by the time interval between the two moments when a droplet crosses the two waveguide branches in the microfluidic channel. This way, the MZI platform provided data on length and velocity of the droplets.

To test the ability of the MZI to sequence rapidly flowing droplets, 43 emulsions with more than 100 droplets at varying flow rates were analysed. The MZI platform showed great ability to detect length and velocity of single droplets and emulsions, similar to the commonly used imaging technique. 

Is important to highlight that all results were validated by using a standard imaging system, simultaneously. This validation protocol confirmed that the MZI platform can be used independently of the imaging acquisition with the same reliability but better reproducibility and data processing time.

CONCLUSION | Droplet characterization by opto-microfluidics increases reproducibility

Compared to standard used imaging systems, the Integrated MZI method reliably detected droplets generated by microfluidics without the need for calibration (as needed for most electric-based techniques). By labelling velocity and length in real-time, the integrated system successfully optimises time and reproducibility of laboratory protocols.

Most importantly, the MZI can be easily integrated with microfluidic devices. Additionally, the waveguided MZI structure can be adapted for detection of smaller biological units – such as cells and particles -, which cannot be done with standard fiber-based devices.

“Notably, the working principle of the MZI detection does not depend on the intensity of the optical transmission signal, neither on the nature of the interaction, as long as the time instants mentioned above can be identified. Therefore, any liquids combinations can be detected as long as they provide a trigger signal which allows to distinguish the four instants between the different interactions of droplets with the two branches”, conclude the authors.

This article was written by Thais Langer.

References