Accounting for corner flow unifies the understanding of droplet formation in microfluidic channels

Investigation of piezoelectric printing devices for oil-free and on-demand picolitre monodisperse droplet generation

Picolitre monodisperse droplet printing technology has important applications in biochemistry, such as accounting for quantitative analysis and single-cell analysis, and can be used for parallel high-throughput analysis of biomarkers and chemicals. However, commonly used droplet generation devices require complex control systems or customised microfluidic chips, making them costly and difficult for researchers to operate. Additionally, generating picolitre monodisperse droplets with microfluidic devices necessitates the introduction of an oil phase to block and separate the liquid. This requirement can reduce the throughput of the target droplets and cause cell contamination, hindering the adoption of this technology. By employing a common 1-mm-diameter capillary in the laboratory in combination with a piezoelectric transducer, we have achieved on-demand picolitre droplet printing of less than 100 pL in an oil-free environment. The device was found to be biocompatible with K562 cells. This approach is less costly, offers greater operational freedom, and is easier to integrate with other downstream assay modules or even handheld cell-printing devices. This study holds great potential for application in areas such as single-cell analysis, cell sampling, and pharmaceutical analysis.

Investigation of air bubble behaviour after gas embolism events induced in a microfluidic network mimicking microvasculature

Gas embolism is a medical condition that occurs when gas bubbles are present in veins or arteries, decreasing blood flow and potentially reducing oxygen delivery to vital organs, such as the brain. Although usually reported as rare, gas embolism can lead to severe neurological damage or death. However, presently, only limited understanding exists regarding the microscale processes leading to the formation, persistence, movement, and resolution of gas emboli, as modulated by microvasculature geometrical features and blood properties. Because gas embolism is initially a physico-chemical-only process, with biological responses starting later, the opportunity exists to fully study the genesis and evolution of gas emboli using in vitro microfluidic networks mimicking small regions of microvasculature. The microfluidics networks used in this study, which aim to mimic microvasculature geometry, comprise linear channels with T-, or Y-junction air inlets, with 20, 40, and 60 μm widths (arterial or venous), and a 30 μm width honeycombed network (arterial) with three bifurcation angles (30°, 60°, and 90°). Synthetic blood, equivalent to 46% haematocrit concentrations, and water were used to study the modulation of gas embolism-like events by liquid viscosity. Our study shows that (i) longer bubbles with lower velocity occur in narrower channels, e.g., with 20 μm width; (ii) the resistance of air bubbles to the flow increases with the higher haematocrit concentration; and lastly (iii) the propensity of gas embolism-like events in honeycomb architectures increases for more acute, e.g., 30°, bifurcation angles. A dimensionless analysis using Euler, Weber, and capillary numbers demarcated the conditions conducive to gas embolism. This work suggests that in vitro experimentation using microfluidic devices with microvascular tissue-like structures could assist medical guidelines and management in preventing and mitigating the effects of gas embolism.

Cost-Effective Droplet Generator for Portable Bio-Applications

The convenient division of aqueous samples into droplets is necessary for many biochemical and medical analysis applications. In this article, we propose the design of a cost-effective droplet generator for potential bio-chemical application, featuring two symmetric tubes. The new droplet generator revisits the relationship between capillary components and liquid flow rates. The size of generated droplets by prototype depends only on generator dimensions, without precisely needing to control external flow conditions or driving pressure, even when the relative extreme difference in flow rate for generating nL level droplets is over 57.79%, and the relative standard deviation (RSD) of the volume of droplets is barely about 9.80%. A dropper working as a pressure resource is used to verify the rapidity and robustness of this principle of droplet generation, which shows great potential for a wide range of droplet-based applications.

Capillary imbibition and flow of wetting liquid in irregular capillaries: A 100-year review

Capillary imbibition, such as plant roots taking up water, reservoir rocks absorbing brine and a tissue paper wiping stains, is pervasive occurred in nature, engineering and industrial fields, as well as in our daily life. This phenomenon is earliest modeled through the process that wetting liquid is spontaneously propelled by capillary pressure into regular geometry models. Recent studies have attracted more attention on capillary-driven flow models within more complex geometries of the channel, since a detailed understanding of capillary imbibition dynamics within irregular geometry models necessitates the fundamentals to fluid transport mechanisms in porous media with complex pore topologies. Herein, the fundamentals and concepts of different capillary imbibition models in terms of geometries over the past 100 years are reviewed critically, such as circular and non-circular capillaries, open and closed capillaries with triangular/rectangular cross-sections, and heterogeneous geometries with axial variations. The applications of these models with appropriate conditions are discussed in depth accordingly, with a particular emphasize on the capillary flow pattern as a consequence of capillary geometry. In addition, a universal model is proposed based on the dynamic wetting condition and equivalent cylindrical geometry to describe the capillary imbibition process in terms of various solid topologies. Finally, future research is suggested to focus on analyzing the dynamics during corner flow, the snap-off of wetting fluid, the capillary rise of non-Newtonian fluids and applying accurate physical simulation methods on capillary-driven flow processes. Generally, this review provides a comprehensive understanding of the capillary-driven flow models inside various capillary geometries and affords an overview of potential advanced developments to enhance the current understanding of fluid transport mechanisms in porous media.

From dynamic self-organization to avalanching instabilities in soft-granular threads

We study the dynamics of threads of monodisperse droplets, including droplet chains and multi-chains, in which the droplets are interconnected by capillary bridges of another immiscible liquid phase. This system represents wet soft-granular matter - a class of granular materials in which the grains are soft and wetted by thin fluid films-with other examples including wet granular hydrogels or foams. In contrast to wet granular matter with rigid grains (e.g., wet sand), studied previously, the deformability of the grains raises the number of available metastable states and facilitates rearrangements which allow for reorganization and self-assembly of the system under external drive, e.g., applied via viscous forces. We use a co-flow configuration to generate a variety of unique low-dimensional regular granular patterns, intermediate between 1D and 2D, ranging from linear chains and chains with periodically occurring folds to multi-chains and segmented structures including chains of finite length. In particular, we observe that the partially folded chains self-organize via limit cycle of displacements and rearrangements occurring at a frequency self-adapted to the rate of build-up of compressive strain in the chain induced by the viscous forces. Upon weakening of the capillary arrest of the droplets, we observe spontaneous fluidization of the quasi-solid structures and avalanches of rearrangements. We identify two types of fluidization-induced instabilities and rationalize them in terms of a competition between advection and propagation. While we use aqueous droplets as the grains we demonstrate that the reported mechanisms of adaptive self-assembly apply to other types of soft granular systems including foams and microgels. We discuss possible application of the reported quasi-1D compartmentalized structures in tissue engineering, bioprinting and materials science.

A portable droplet generation system for ultra-wide dynamic range digital PCR based on a vibrating sharp-tip capillary

Monodisperse droplet has been widely used as a versatile tool in different disciplines including biosensing. Existing methods still struggle to balance the droplet generation performance with system simplicity. Here we introduce a novel droplet generation scheme based on the acoustic streaming generated from a vibrating sharp-tip capillary. The unique fluid pattern enables efficient droplet generation without any external pressure sources. This method achieved real-time modulation of droplet size over an ultra-wide range (6.77-661 μm), high throughput (up to 5000 droplets/s), and good monodispersity (<4%) with a power consumption below 60 mW. This method has enabled a multi-volume digital PCR with a dynamic range of ~6 orders of magnitude and multiplexing capability. It has also enabled a simple protocol to produce cell-laden alginate microcapsules in variable sizes with excellent biocompatibility. Overall, the present method combines high performance with small footprint and portability, which will be especially valuable for droplet applications requiring variable droplet size and performed in resource-limited settings.

Integration of capillary-hydrodynamic logic circuitries for built-in control over multiple droplets in microfluidic networks

Here, we show the successful implementation of advanced sequential logic in droplet microfluidics, whose principles rely on capillary wells establishing stationary states, where droplets can communicate remotely via pressure impulses, influencing each other and switching the device states. All logic operations perform spontaneously due to the utilization of nothing more than capillary-hydrodynamic interactions, inherent for the confined biphasic flow. Our approach offers integration feasibility allowing to encode unprecedentedly long algorithms, e.g., 1000-droplet counting. This work has the potential for the advancement of liquid computers and thereby could participate in the development of the next generation of portable microfluidic systems with embedded control, enabling applications from single-cell analysis and biochemical assays to materials science.

Droplet shape control using microfluidics and designer biosurfactants

Many uses of emulsion droplets require precise control over droplet size and shape. Here we report a 'shape-memorable' micro-droplet formulation stabilized by a polyethylene glycol (PEG)-modified protein -surfactant, the droplets are stable against coalescence for months and can maintain non-spherical shapes for hours, depending on the surface coverage of PEGylated protein. Monodisperse droplets with aspect ratios ranging from 1.0 to 3.4 were controllably synthesized with a flow-focusing microfluidic device. Mechanical properties of the interfacial protein network were explored to elucidate the mechanism behind the droplet shape conservation phenomenon. Characterization of the protein film revealed that the presence of a PEG layer at interfaces alters the mechanical responses of the protein film, resulting in interfacial networks with improved strength. Taking advantage of the prolonged stabilization of non-spherical droplets, we demonstrate functionalization of the droplet interface with accessible biotins. The stabilization of micro-droplet shape with surface-active proteins that also serve as an anchor for integrating functional moieties, provides a tailorable interface for diverse biomimetic applications.

Machine learning enables design automation of microfluidic flow-focusing droplet generation

Droplet-based microfluidic devices hold immense potential in becoming inexpensive alternatives to existing screening platforms across life science applications, such as enzyme discovery and early cancer detection. However, the lack of a predictive understanding of droplet generation makes engineering a droplet-based platform an iterative and resource-intensive process. We present a web-based tool, DAFD, that predicts the performance and enables design automation of flow-focusing droplet generators. We capitalize on machine learning algorithms to predict the droplet diameter and rate with a mean absolute error of less than 10 μm and 20 Hz. This tool delivers a user-specified performance within 4.2% and 11.5% of the desired diameter and rate. We demonstrate that DAFD can be extended by the community to support additional fluid combinations, without requiring extensive machine learning knowledge or large-scale data-sets. This tool will reduce the need for microfluidic expertise and design iterations and facilitate adoption of microfluidics in life sciences.

Scalable microfluidic droplet on-demand generator for non-steady operation of droplet-based assays

We developed a microfluidic droplet on-demand (DoD) generator that enables the production of droplets with a volume solely governed by the geometry of the generator for a range of operating conditions. The prime reason to develop this novel type of DoD generator is that its robustness in operation enables scale out and operation under non-steady conditions, which are both essential features for the further advancement of droplet-based assays. We first detail the working principle of the DoD generator and study the sensitivity of the volume of the generated droplets with respect to the used fluids and control parameters. We next compare the performance of our DoD generator when scaled out to 8 parallel generators to the performance of a conventional DoD generator in which the droplet volume is not geometry-controlled, showing its superior performance. Further scale out to 64 parallel DoD generators shows that all generators produce droplets with a volume between 91% and 105% of the predesigned volume. We conclude the paper by presenting a simple droplet-based assay in which the DoD generator enables sequential supply of reagent droplets to a droplet stored in the device, illustrating its potential to be used in droplet-based assays for biochemical studies under non-steady operation conditions.