Recent Developments in 3D Printing of Droplet-Based Microfluidics

Advances and Applications of Micro- and Mesofluidic Systems

Microfabrication technology has advanced scientific understanding and expanded our molecular control capabilities, enabling the development of 3D models in micrometer structures. The sizes of the fluidic channels are arranged in descending order, starting with the macro-, followed by the meso-, micro-, and nanoscale. These advances bring advantages and speed up biological and chemical experimental processes. Such miniaturized systems show significant advances, particularly in meso- and microreactors, through high-throughput screening. This work proposes a bibliometric analysis of the advances and applications of the Web of Science (WoS) database, analyzing the main highlights of the publications, indicators, and impact on knowledge production. In the past 20 years, approximately 3,934 documents published and cited, mainly by major world powers on micro- and mesofluidic systems, are increasingly expanding in the academic and industrial sectors.

A Simple Pump-Free Approach to Generating High-Throughput Microdroplets Using Oscillating Microcone Arrays

Droplet generation is crucial in various scientific and industrial fields, such as drug delivery, diagnostics, and inkjet printing. While microfluidic platforms enable precise droplet formation, traditional methods often require costly and complex setups, limiting their accessibility. This study introduces a simple, low-cost approach using an off-the-shelf unit and a 3D-printed reservoir. The device, equipped with a driver board, piezo-ring transducer, and a metal sheet with holes, generates oil-in-water (O/W) droplets with an average diameter of 4.62 ± 0.67 µm without external fluid pumps. Its simplicity, cost-effectiveness, and scalability make it highly suitable for both lab-on-chip and industrial applications, demonstrating the feasibility of large-scale uniform droplet production.

Advancing 3D printed microfluidics with computational methods for sweat analysis

The intricate tapestry of biomarkers, including proteins, lipids, carbohydrates, vesicles, and nucleic acids within sweat, exhibits a profound correlation with the ones in the bloodstream. The facile extraction of samples from sweat glands has recently positioned sweat sampling at the forefront of non-invasive health monitoring and diagnostics. While extant platforms for sweat analysis exist, the imperative for portability, cost-effectiveness, ease of manufacture, and expeditious turnaround underscores the necessity for parameters that transcend conventional considerations. In this regard, 3D printed microfluidic devices emerge as promising systems, offering a harmonious fusion of attributes such as multifunctional integration, flexibility, biocompatibility, a controlled closed environment, and a minimal requisite analyte volume-features that leverage their prominence in the realm of sweat analysis. However, formidable challenges, including high throughput demands, chemical interactions intrinsic to the printing materials, size constraints, and durability concerns, beset the landscape of 3D printed microfluidic devices. Within this paradigm, we expound upon the foundational aspects of 3D printed microfluidic devices and proffer a distinctive perspective by delving into the computational study of printing materials utilizing density functional theory (DFT) and molecular dynamics (MD) methodologies. This multifaceted approach serves manifold purposes: (i) understanding the complexity of microfluidic systems, (ii) facilitating comprehensive analyses, (iii) saving both cost and time, (iv) improving design optimization, and (v) augmenting resolution. In a nutshell, the allure of 3D printing lies in its capacity for affordable and expeditious production, offering seamless integration of diverse components into microfluidic devices-a testament to their inherent utility in the domain of sweat analysis. The synergistic fusion of computational assessment methodologies with materials science not only optimizes analysis and production processes, but also expedites their widespread accessibility, ensuring continuous biomarker monitoring from sweat for end-users.

An Experimental Study on Complete Droplet Rebound from Soft Surfaces: Critical Weber Numbers, Maximum Spreading, and Contact Time

Droplet impact on soft surfaces (PDMS) was experimentally studied with particular interest in the complete rebound of droplets. This study focuses on the effect of liquid viscosity and the elastic modulus of the substrate on the critical rebound Weber number, maximum spreading, and contact time. Specifically, the lower and upper critical Weber numbers increase with an increasing droplet viscosity. With decreasing PDMS elastic modulus, the upper critical Weber number increases, while the lower critical Weber number decreases. The PDMS elastic modulus does not significantly affect the maximum spreading time and contact time. An interesting phenomenon of discontinuous contact time was experimentally observed and was theoretically interpreted.

Additive Manufacturing Applications in Biosensors Technologies

Three-dimensional (3D) printing technology, also known as additive manufacturing (AM), has emerged as an attractive state-of-the-art tool for precisely fabricating functional materials with complex geometries, championing several advancements in tissue engineering, regenerative medicine, and therapeutics. However, this technology has an untapped potential for biotechnological applications, such as sensor and biosensor development. By exploring these avenues, the scope of 3D printing technology can be expanded and pave the way for groundbreaking innovations in the biotechnology field. Indeed, new printing materials and printers would offer new possibilities for seamlessly incorporating biological functionalities within the growing 3D scaffolds. Herein, we review the additive manufacturing applications in biosensor technologies with a particular emphasis on extrusion-based 3D printing modalities. We highlight the application of natural, synthetic, and composite biomaterials as 3D-printed soft hydrogels. Emphasis is placed on the approach by which the sensing molecules are introduced during the fabrication process. Finally, future perspectives are provided.

High throughput microfluidic nanobubble generation by microporous membrane integration and controlled bubble shrinkage

Microfluidics has recently been proposed as a viable method for producing bulk nanobubbles for use in various applications. The portability, compact size, and capacity to precisely control fluids on a small scale are a few of the benefits of microfluidics that may be exploited to create customized bulk nanobubbles. However, despite the potential of microfluidic nanobubble generation, low throughput and limited nanobubble concentration remain challenging for microfluidics. Here, we integrate a microporous silicon membrane into a polydimethylsiloxane microfluidic chip to generate bulk nanobubbles in the 100-140 nm diameter range with a concentration of up to 108 mL-1. We investigate the nanobubble size and morphology using several characterisation techniques, including transmission electron microscopy, resonance mass measurement, dynamic light scattering, and the Tyndall effect. This new nanobubble generation technique can increase nanobubble concentration by ∼ 23 times compared to earlier microfluidic nanobubble generation platforms, which should increase the feasibility of translation to medical applications.

Role of three-dimensional cell culture in therapeutics and diagnostics: an updated review

Drug development and testing are a tedious and expensive process with a high degree of uncertainty in the clinical success and preclinical validation of manufactured therapeutic agents. Currently, to understand the drug action, disease mechanism, and drug testing, most therapeutic drug manufacturers use 2D cell culture models to validate the drug action. However, there are many uncertainties and limitations with the conventional use of 2D (monolayer) cell culture models for drug testing that are primarily attributed due to poor mimicking of cellular mechanisms, disturbance in environmental interaction, and changes in structural morphology. To overcome such odds and difficulties in the preclinical validation of therapeutic medications, newer in vivo drug testing cell culture models with higher screening efficiencies are required. One such promising and advanced cell culture model reported recently is the "three-dimensional cell culture model." The 3D cell culture models are reported to show evident benefits over conventional 2D cell models. This review article outlines and describes the current advancement in cell culture models, their types, significance in high-throughput screening, limitations, applications in drug toxicity screening, and preclinical testing methodologies to predict in vivo efficacy.

Rapid microfluidics prototyping through variotherm desktop injection molding for multiplex diagnostics

In this work, we demonstrate an inexpensive method of prototyping microfluidics using a desktop injection molding machine. A centrifugal microfluidic device with a novel central filling mechanism was developed to demonstrate the technique. We overcame the limitations of desktop machines in replicating microfluidic features by variotherm heating and cooling the mold between 50 °C and 110 °C within two minutes. Variotherm heating enabled good replication of microfeatures, with a coefficient of variation averaging only 3.6% attained for the measured widths of 100 μm wide molded channels. Using this methodology, we produced functional polystyrene centrifugal microfluidic chips, capable of aliquoting fluids into 5.0 μL reaction chambers with 97.5% accuracy. We performed allele-specific loop-mediated isothermal amplification (AS-LAMP) reactions for genotyping CYP2C19 alleles on these chips. Readouts were generated using optical pH sensors integrated onto chips, by drop-casting sensor precursor solutions into reaction chambers before final chip assembly. Positive reactions could be discerned by decreases in pH sensor fluorescence, thresholded against negative control reactions lacking the primers for nucleic acid amplification and with time-to-results averaging 38 minutes. Variotherm desktop injection molding can enable researchers to prototype microfluidic devices more cost-effectively, in an iterative fashion, due to reduced costs of smaller, in-house molds. Designs prototyped this way can be directly translated to mass production, enhancing their commercialization potential and positive impacts.

Bioprinting the future using light: A review on photocrosslinking reactions, photoreactive groups, and photoinitiators

Light-based bioprinting is a type of additive manufacturing technologies that uses light to control the formation of biomaterials, tissues, and organs. It has the potential to revolutionize the adopted approach in tissue engineering and regenerative medicine by allowing the creation of functional tissues and organs with high precision and control. The main chemical components of light-based bioprinting are activated polymers and photoinitiators. The general photocrosslinking mechanisms of biomaterials are described, along with the selection of polymers, functional group modifications, and photoinitiators. For activated polymers, acrylate polymers are ubiquitous but are made of cytotoxic reagents. A milder option that exists is based on norbornyl groups which are biocompatible and can be used in self-polymerization or with thiol reagents for more precision. Polyethylene-glycol and gelatin activated with both methods can have high cell viability rates. Photoinitiators can be divided into types I and II. The best performances for type I photoinitiators are produced under ultraviolet light. Most alternatives for visible-light-driven photoinitiators were of type II, and changing the co-initiator along the main reagent can fine-tune the process. This field is still underexplored and a vast room for improvements still exist, which can open the way for cheaper complexes to be developed. The progress, advantages, and shortcomings of light-based bioprinting are highlighted in this review, with special emphasis on developments and future trends of activated polymers and photoinitiators.

Ultrahigh-Throughput Enzyme Engineering and Discovery in In Vitro Compartments

Novel and improved biocatalysts are increasingly sourced from libraries via experimental screening. The success of such campaigns is crucially dependent on the number of candidates tested. Water-in-oil emulsion droplets can replace the classical test tube, to provide in vitro compartments as an alternative screening format, containing genotype and phenotype and enabling a readout of function. The scale-down to micrometer droplet diameters and picoliter volumes brings about a >107-fold volume reduction compared to 96-well-plate screening. Droplets made in automated microfluidic devices can be integrated into modular workflows to set up multistep screening protocols involving various detection modes to sort >107 variants a day with kHz frequencies. The repertoire of assays available for droplet screening covers all seven enzyme commission (EC) number classes, setting the stage for widespread use of droplet microfluidics in everyday biochemical experiments. We review the practicalities of adapting droplet screening for enzyme discovery and for detailed kinetic characterization. These new ways of working will not just accelerate discovery experiments currently limited by screening capacity but profoundly change the paradigms we can probe. By interfacing the results of ultrahigh-throughput droplet screening with next-generation sequencing and deep learning, strategies for directed evolution can be implemented, examined, and evaluated.

Advances in Integration, Wearable Applications, and Artificial Intelligence of Biomedical Microfluidics Systems

Microfluidics attracts much attention due to its multiple advantages such as high throughput, rapid analysis, low sample volume, and high sensitivity. Microfluidics has profoundly influenced many fields including chemistry, biology, medicine, information technology, and other disciplines. However, some stumbling stones (miniaturization, integration, and intelligence) strain the development of industrialization and commercialization of microchips. The miniaturization of microfluidics means fewer samples and reagents, shorter times to results, and less footprint space consumption, enabling a high throughput and parallelism of sample analysis. Additionally, micro-size channels tend to produce laminar flow, which probably permits some creative applications that are not accessible to traditional fluid-processing platforms. The reasonable integration of biomedical/physical biosensors, semiconductor microelectronics, communications, and other cutting-edge technologies should greatly expand the applications of current microfluidic devices and help develop the next generation of lab-on-a-chip (LOC). At the same time, the evolution of artificial intelligence also gives another strong impetus to the rapid development of microfluidics. Biomedical applications based on microfluidics normally bring a large amount of complex data, so it is a big challenge for researchers and technicians to analyze those huge and complicated data accurately and quickly. To address this problem, machine learning is viewed as an indispensable and powerful tool in processing the data collected from micro-devices. In this review, we mainly focus on discussing the integration, miniaturization, portability, and intelligence of microfluidics technology.

Deep Learning-Assisted Droplet Digital PCR for Quantitative Detection of Human Coronavirus

Since coronavirus disease 2019 (COVID-19) pandemic rapidly spread worldwide, there is an urgent demand for accurate and suitable nucleic acid detection technology. Although the conventional threshold-based algorithms have been used for processing images of droplet digital polymerase chain reaction (ddPCR), there are still challenges from noise and irregular size of droplets. Here, we present a combined method of the mask region convolutional neural network (Mask R-CNN)-based image detection algorithm and Gaussian mixture model (GMM)-based thresholding algorithm. This novel approach significantly reduces false detection rate and achieves highly accurate prediction model in a ddPCR image processing. We demonstrated that how deep learning improved the overall performance in a ddPCR image processing. Therefore, our study could be a promising method in nucleic acid detection technology.

Micro-injection Molded Droplet Generation System for Digital PCR Application

Sensitive, effective, and quantitative analysis of infectious pathogens is an important task for the prevention of human health threats. Herein, we present an advanced approach to producing gene-encapsulated microdroplets for quantitative analysis using a micropatterned metal mold and injection molding technique with an automatically operated system. An injection molded microdroplet generation device was successfully fabricated with a minimum channel width of 30 μm and optimized to produce 100 μm diameter droplets. The optimized microchannel design and flow rate also enable the production of stable numbers of microdroplets (~ 16,000 droplets). To verify the applicability of our device and system to droplet-based digital PCR analysis, Escherichia coli (E. coli) O157:H7 was selected as a model bacterial pathogen, and the stx2 gene was amplified in the microdroplets. The generated microdroplets exhibit both chemical and mechanical stability, and our results are similar to those obtained by a commercially available method. Accordingly, the usefulness of the microdroplet generative device and system is confirmed as a simple, fast, and reliable tool for the quantitative molecular analysis of infectious diseases.

Research progress on detection techniques for point-of-care testing of foodborne pathogens

The global burden of foodborne disease is enormous and foodborne pathogens are the leading cause of human illnesses. The detection of foodborne pathogenic bacteria has become a research hotspot in recent years. Rapid detection methods based on immunoassay, molecular biology, microfluidic chip, metabolism, biosensor, and mass spectrometry have developed rapidly and become the main methods for the detection of foodborne pathogens. This study reviewed a variety of rapid detection methods in recent years. The research advances are introduced based on the above technical methods for the rapid detection of foodborne pathogenic bacteria. The study also discusses the limitations of existing methods and their advantages and future development direction, to form an overall understanding of the detection methods, and for point-of-care testing (POCT) applications to accurately and rapidly diagnose and control diseases.

Emerging 3D printing technologies and methodologies for microfluidic development

This review paper examines recent (mostly 2018 or later) advancements in 3D printed microfluidics. Microfluidic devices are widely applied in various fields such as drug delivery, point-of-care diagnosis, and bioanalytical research. In addition to soft lithography, 3D printing has become an appealing technology to develop microfluidics recently. In this work, three main 3D printing technologies, stereolithography, fused filament deposition, and polyjet, which are commonly used to fabricate microfluidic devices, are thoroughly discussed. The advantages, limitations, and recent microfluidic applications are analyzed. New technical advancements within these technology frameworks are also summarized, which are especially suitable for microfluidic development. Next, new emerging 3D-printing technologies are introduced, including the direct printing of polydimethylsiloxane (PDMS), glass, and biopolymers. Although limited microfluidic applications based on these technologies can be found in the literature, they show high potential to revolutionize the next generation of 3D-printed microfluidic apparatus.