Microfluidic Flow Research Articles

Mechanobiology studies of bladder tumor cells using laterally squeezing microfluidic flow cytometry

The deformability and uptake capability of cells are critical indicators of their biomechanical properties and functional behaviors, particularly in tumor heterogeneity and cancer research. Here, we introduce a microfluidic flow cytometry platform integrated with a laterally adjustable squeezing structure for the characterization of bladder tumor cells (including 5637 and EJ cell lines) and uroepithelial cells (SV-HUC-1 cell line). The deformability of these cell types under varying channel width conditions was clearly assessed using this platform. The results demonstrated that tumor cells exhibited higher deformability compared to uroepithelial cells, with the EJ cell line exhibiting the greatest difference. Furthermore, the relationship between the malignancy, deformability, and uptake capability of bladder cells was explored through co-cultivation experiments with 2 μm particles. As the malignancy increased, the cells became more deformable and exhibited stronger phagocytic capability with particles. Subsequently, the heterogeneity of tumor cells was investigated by analyzing the deformability of phagocytic and non-phagocytic subpopulations within EJ cells. The developed microfluidic platform offers a promising high-throughput method to assess the biomechanical and phagocytic characteristics of cells, providing valuable insights into tumor cell biology, and potentially improving clinical status of urinary cytology examinations for bladder cancer.

Long-Term Stable and Multifeature Microfluidic Impedance Flow Cytometry Based on a Constricted Channel for Single-Cell Mechanical Phenotyping.

The microfluidic impedance flow cytometer (m-IFC) using constricted microchannels is an appealing choice for the high-throughput measurement of single-cell mechanical properties. However, channels smaller than the cells are susceptible to irreversible blockage, extremely affecting the stability of the system and the throughput. Meanwhile, the common practice of extracting a single quantitative index, i.e., total cell passage time, through the constricted part is inadequate to decipher the complex mechanical properties of individual cells. Herein, this study presents a long-term stable and multifeature m-IFC based on a constricted channel for single-cell mechanical phenotyping. The blockage problem is effectively overcome by adding tiny xanthan gum (XG) polymers. The cells can pass through the constricted channel at a flow rate of 500 μL/h without clogging, exhibiting high throughput (∼240 samples per second) and long-term stability (∼2 h). Moreover, six detection regions were implemented to capture the multiple features related to the whole process of a single cell passing through the long-constricted channel, e.g., creep, friction, and relaxation stages. To verify the performance of the multifeature m-IFC, cells treated with perturbations of microtubules and microfilaments within the cytoskeleton were detected, respectively. It suggests that the extracted features provide more comprehensive clues for single-cell analysis in structural and mechanical transformation. Overall, our proposed multifeature m-IFC exhibits the advantages of nonclogging and high throughput, which can be extended to other cell types for nondestructive and real-time mechanical phenotyping in cost-effective applications.

A numerical approach to overcome the very-low Reynolds number limitation of the artificial compressibility for incompressible flows

We propose a numerical approach to solve a long-standing challenge which is the applicability of the artificial compressibility (AC) formulation for solving the incompressible Navier—Stokes equations at very-low Reynolds numbers. A wide range of engineering applications involves very-low Reynolds number flows in Micro-ElectroMechanical Systems (MEMS) and in the fields of chemical-, agricultural- and biomedical engineering. It is known that the already existing numerical methods using the AC approach fail to provide physically correct results at very-low Reynolds numbers (Re ≤ 1). To overcome the limitation of the AC method for these engineering applications, we propose a higher-order Neumann-type pressure outflow boundary condition treatment along with their up to fourth-order numerical approximations. We found that the numerical treatment of the pressure at the outlet boundary plays the main role in overcoming the limitation of the AC method at very-low Reynolds numbers (Re << 1). Therefore, we provide numerical evidence on the accuracy of the AC method beyond its previously reported limitations, e.g., the low Reynolds number Oseen flow (Re << 1) is first presented in this work. A third-order explicit total-variation diminishing (TVD) Runge–Kutta scheme has been employed with standard finite difference spatial discretisation schemes for improving the accuracy of the numerical solution. For modelling strongly viscous flows, the Reynolds number ranges from 10−1 to 10−4. Overall, we found that the accuracy limitation of the AC method below Re < 1 can be overcome with an accurate numerical treatment of the outlet pressure boundary condition instead of using high-order schemes in the governing equations. For the investigated Reynolds number range (10−1 ≤ Re ≤ 10−4), the obtained results show that the relative errors were smaller than 1% for the numerical simulations performed on the configurations of both the two- and three-dimensional, straight microfluidic channels. The imposition of high-order derivative Neumann-type pressure outflow boundary conditions reduced the maximum relative errors of the numerical solutions from 85% and 95% to below than 1% at the outlet section of the two- and three-dimensional, straight microfluidic channel flows, respectively. Taking the advantage of the numerical approach proposed here, two- and three-dimensional benchmark problems employed in the current investigation in comparison with analytical solutions available in the literature, clearly demonstrate that the artificial compressibility can be used beyond its previously known constraints for very-low Reynolds number incompressible flows.

Comprehensive overview of microfluidic flow sensors: principles, materials, and fabrication

Comprehensive overview of microfluidic flow sensors: principles, materials, and fabrication

Microscale Flow Control and Droplet Generation Using Arduino-Based Pneumatically-Controlled Microfluidic Device.

Microfluidics are crucial for managing small-volume analytical solutions for various applications, such as disease diagnostics, drug efficacy testing, chemical analysis, and water quality monitoring. The precise control of flow control devices can generate diverse flow patterns using pneumatic control with solenoid valves and a microcontroller. This system enables the active modulation of the pneumatic pressure through Arduino programming of the solenoid valves connected to the pressure source. Additionally, the incorporation of solenoid valve sets allows for multichannel control, enabling simultaneous creation and manipulation of various microflows at a low cost. The proposed microfluidic flow controller facilitates accurate flow regulation, especially through periodic flow modulation beneficial for droplet generation and continuous production of microdroplets of different sizes. Overall, we expect the proposed microfluidic flow controller to drive innovative advancements in technology and medicine owing to its engineering precision and versatility.

Dynamic detection of soluble intermediates during methanol electrooxidation

Methanol electrooxidation at a Pt band electrode is studied in a microfluidic flow cell (MFFC) with simultaneous electrochemical detection of formic acid at a down-stream sensor (detector) Pd electrode. Detection of formic acid at the Pd electrode is possible through either a fast voltammetry or a potential step procedure. In both cases, maximizing the detection signal (oxidation current) requires Pd oxide formation and reduction before detection. Pd oxide formation is needed to oxidize surface-bound carbonaceous species while Pd oxide reduction is needed to reactivate the electrode surface. Although formic acid alone is easily detected and provides a stable detection signal at the Pd sensor electrode, simultaneous formation of formaldehyde during methanol oxidation degrades the detection signal at the Pd electrode over time. We show that dynamic detection of sub-millimolar formic acid concentrations in 2M methanol is possible at a time resolution down to 2 s. Dynamic detection during methanol oxidation at platinum shows that production of soluble intermediates occurs at all potentials where an oxidation current is observed. Furthermore, a higher faradaic efficiency to formic acid occurs during the main methanol oxidation peak in the positive-going sweep compared to the negative-going sweep, and is higher still at potentials above 1V. This work shows that microfluidic flow cells can be used for fast and dynamic detection of soluble reaction intermediates by using down-stream electrodes with custom potential step or sweep sequences.

Discovering Variability in Population of T-Lymphocyte Subsets Present in Peripheral Blood of Patients Co-Infected by HIV and HBV Through Laboratory Medicine

An alarming number of 296 million individuals in Egypt have recently been diagnosed as HBV positive; because these two viruses share similar routes of transmission, about 10% of this population is also thought to be HIV positive. It is widely acknowledged that coinfection with HIV and HBV has a significant negative effect on the immune system and accelerates the loss of T-lymphocyte subpopulations, which are essential for immunological defense. This enlightening study, carried out in Cairo, Egypt, explores the complicated dynamics of T-cell subsets and carefully looks at the immunological effects and frequency of coinfection between HIV and HBV. Naturally, of the 35 patients in the cohort under examination, an impressive 8.4% had coinfections with HBV and HIV. Systematic immunophenotyping of several T-cell subsets, such as CD4+, CD8+, CD45RO, CD16+56, and CD45RA, was used in the study, and the results showed clear differences between coinfected and mono-infected peopleUsing trustworthy methods like microfluid inertial separation and flow cytometry has given researchers significant insights into the complex immunological circumstances connected to HIV/HBV coinfection. Interestingly, a significant decrease in CD4+ cells—a crucial marker of HIV progression—was observed in over 50% of the coinfected patients, suggesting an accelerated course of the illness in these individuals. Moreover, the study establishes the foundation for particular treatment strategies and adds to our scientific understanding coinfection dynamics. These therapies, based on the study’s detailed findings, can potentially improve patient outcomes despite this difficult coinfection setting. To manage the difficulties of HIV/HBV coinfection, the research emphasizes the importance of ongoing attention and the incorporation of cutting-edge diagnostic techniques, eventually advancing public health activities.

Study of microfluidic heat transfer in 2D hydrophobic walls with different slip mechanisms

Numerous studies have shown that the gas at the solid-liquid interface in microflow can increase the slip length, reduce the flow resistance. However, the relationship between nanobubbles and fluid boundary slip is complicated, and the impact of nanobubble morphology must be considered. To investigate the combined effect of the bubble model on slip and heat transfer, we investigated the drag reduction and heat transfer effect of microfluidic flow on a 2D hydrophobic wall by theoretical derivation combined with numerical simulation. The comparison of the results revealed good agreement between the analytical solution and the numerical simulation results. It was shown that the gas slip generated by the rarefied gas significantly affected the flow heat transfer effect. Further analysis of the bubble meniscus shape revealed that minimizing the protruding angle of the meniscus is crucial for enhancing drag reduction. In addition, the simulation results also revealed that increasing the gas coverage fraction effectively reduces flow resistance while maintaining heat transfer performance. At the same time, the higher pressure enhanced the heat transfer effect while maintaining the stability of the drag reduction effect.

Rapid and specific detection of nanoparticles and viruses one at a time using microfluidic laminar flow and confocal fluorescence microscopy

Mainstream virus detection relies on the specific amplification of nucleic acids via polymerase chain reaction, a process that is slow and requires extensive laboratory expertise and equipment. Other modalities, such as antigen-based tests, allow much faster virus detection but have reduced sensitivity. In this study, we introduce an approach for rapid and specific detection of single nanoparticles using a confocal-based flow virometer. The combination of laminar flow in a microfluidic channel and correlated fluorescence signals emerging from both free dyes and fluorescently labeled primary antibodies provide insights into nanoparticle volumes and specificities. We evaluate and validate the assay using fluorescent beads and viruses, including SARS-CoV-2 with fluorescently labeled primary antibodies. Additionally, we demonstrate how hydrodynamic focusing enhances the assay sensitivity for detecting viruses at relevant loads. Based on our results, we envision the future use of this technology for clinically relevant bio-nanoparticles, supported by the implementation of the assay in a portable and user-friendly setup.

Periodic Flows in Microfluidics.

Microfluidics, the science and technology of manipulating fluids in microscale channels, offers numerous advantages, such as low energy consumption, compact device size, precise control, fast reaction, and enhanced portability. These benefits have led to applications in biomedical assays, disease diagnostics, drug discovery, neuroscience, and so on. Fluid flow within microfluidic channels is typically in the laminar flow region, which is characterized by low Reynolds numbers but brings the challenge of efficient mixing of fluids. Periodic flows are time-dependent fluid flows, featuring repetitive patterns that can significantly improve fluid mixing and extend the effective length of microchannels for submicron and nanoparticle manipulation. Besides, periodic flow is crucial in organ-on-a-chip (OoC) for accurately modeling physiological processes, advancing disease understanding, drug development, and personalized medicine. Various techniques for generating periodic flows have been reported, including syringe pumps, peristalsis, and actuation based on electric, magnetic, acoustic, mechanical, pneumatic, and fluidic forces, yet comprehensive reviews on this topic remain limited. This paper aims to provide a comprehensive review of periodic flows in microfluidics, from fundamental mechanisms to generation techniques and applications. The challenges and future perspectives are also discussed to exploit the potential of periodic flows in microfluidics.

Zero-power infrared switch with two-phase microfluidic flow and a 2D material thermal isolation layer

Wireless sensor nodes (WSNs) play an important role in many fields, including environmental monitoring. However, unattended WSNs face challenges in consuming power continuously even in the absence of useful information, which makes energy supply the bottleneck of WSNs. Here, we realized zero-power infrared switches, which consist of a metasurface and two-phase microfluidic flow. The metasurface can recognize the infrared signal from the target and convert it into heat, which triggers the two-phase microfluidic flow switch. As the target is not present, the switch is turned off. The graphene/MoS2/graphene 2D material heterostructure (thickness <2 nm) demonstrates an exceptionally high thermal resistance of 4.2 K/W due to strong phonon scattering and reduces the heat flow from the metasurface to the supporting substrate, significantly increasing the device sensitivity (the displacement of the two-phase microfluidic flow increases from ~1500 to ~3000 µm). The infrared switch with a pair of symmetric two-phase microfluidic flows can avoid spurious triggering resulting from environmental temperature changes. We realized WSNs with near-zero standby power consumption by integrating the infrared switch, sensors, and wireless communication module. When the target infrared signal appears, the WSNs are woken and show superb visual/auditory sensing performance. This work provides a novel approach for greatly lengthening the lifespan of unattended WSNs.

Functionalized monodisperse microbubble production: microfluidic method for fast, controlled, and automated removal of excess coating material

Functionalized monodisperse microbubbles have the potential to boost the sensitivity and efficacy of molecular ultrasound imaging and targeted drug delivery using bubbles and ultrasound. Monodisperse bubbles can be produced in a microfluidic flow focusing device. However, their functionalization and sequential use require removal of the excess lipids from the bubble suspension to minimize the use of expensive ligands and to avoid competitive binding and blocking of the receptor molecules. To date, excess lipid removal is performed by centrifugation, which is labor intensive and challenging to automate. More importantly, as we show, the increased hydrostatic pressure during centrifugation can reduce bubble monodispersity. Here, we introduce a novel automated microfluidic ’washing’ method. First, bubbles are injected in a microfluidic chamber 1 mm in height where they are left to float against the top wall. Second, lipid-free medium is pumped through the chamber to remove excess lipids while the bubbles remain located at the top wall. Third, the washed bubbles are resuspended and removed from the device into a collection vial. We demonstrate that the present method can (i) reduce the excess lipid concentration by 4 orders of magnitude, (ii) be fully automated, and (iii) be performed in minutes while the size distribution, functionality, and acoustic response of the bubbles remain unaffected. Thus, the presented method is a gateway to the fully automated production of functionalized monodisperse microbubbles.

Implementing microfluidic flow device model in utilizing dural substitutes as pulp capping materials for vital pulp therapy

Vital pulp therapy (VPT) has gained prominence with the increasing trends towards conservative dental treatment with specific indications for preserving tooth vitality by selectively removing the inflamed tissue instead of the entire dental pulp. Although VPT has shown high success rates in long-term follow-up, adverse effects have been reported due to the calcification of tooth canals by mineral trioxide aggregates, which are commonly used in VPT. Canal calcification poses challenges for accessing instruments during retreatment procedures. To address this issue, this study evaluated the mechanical properties of dural substitute intended to alleviate intra-pulp pressure caused by inflammation, along with assessing the biological responses of human dental pulp stem cells (hDPSC) and human umbilical vein endothelial cells (HUVEC), both of which play crucial roles in dental pulp. The study examined the application of dural substitutes as pulp capping materials, replacing mineral trioxide aggregate (MTA). This assessment was conducted using a microfluidic flow device model that replicated the blood flow environment within the dental pulp. Computational fluid dynamics simulations were employed to ensure that the fluid flow velocity within the microfluidic flow device matched the actual blood flow velocity within the dental pulp. Furthermore, the dural substitutes (Biodesign; BD and Neuro-Patch; NP) exhibited resistance to penetration by 2-hydroxypropyl methacrylate (HEMA) released from the upper restorative materials and bonding agents. Finally, while MTA increased the expression of angiogenesis-related and hard tissue-related genes in HUVEC and hDPSCS, respectively, BD and NP did not alter gene expression and preserved the original characteristics of both cell types. Hence, dural substitutes have emerged as promising alternatives for VPT owing to their resistance to HEMA penetration and the maintenance of stemness. Moreover, the microfluidic flow device model closely replicated the cellular responses observed in live pulp chambers, thereby indicating its potential use as an in vivo testing platform.

Multiresponsive Liquid Crystal Collagen Guides Mussel Byssus Formation.

Marine mussels fabricate tough collagenous fibers known as byssal threads to anchor themselves. Threads are produced individually in minutes via secretion of liquid crystalline (LC) collagenous precursors (preCols); yet the physical and chemical parameters influencing thread formation remain unclear. Here, we characterized the structural anisotropy of native and artificially induced threads using quantitative polarized light microscopy and transmission electron microscopy to elucidate spontaneous vs regulated aspects of thread assembly, discovering that preCol LC phases form aligned domains of several hundred microns, but not the cm-level alignment of native threads. We then explored the hypothesized roles of mechanical shear, pH, and metal ions on thread formation through in vitro assembly studies employing a microfluidic flow focusing device using purified preCol secretory vesicles. Our results provide clear evidence for the role of all three parameters in modulating the structure and properties of the final product with relevance for fabrication of collagenous scaffolds for tissue engineering applications.

Simultaneous effects of capillary number, viscosity ratio, and contraction ratio on droplet dynamics in contraction microchannel

Abstract In droplet-based microfluidic systems, fluid properties, flow conditions, and channel geometry play crucial roles in the movement and manipulation of droplets. This study employs a three-dimensional numerical simulation method to investigate droplet dynamics in a contraction microchannel under the simultaneous influence of different factors, such as capillary number (Ca), viscosity ratio (λ), and contraction ratio (C). Specifically, a theoretical model is introduced for predicting the transition of droplets from trap to squeeze, and it is observed to be 〖Ca〗_I = f(C,λ). Meanwhile, droplet dynamics are investigated for the transition from squeeze to breakup for finding critical capillary number value (CaII). In addition, the critical viscosity ratio for the process from squeeze to breakup has been figured out by numerical results for a wide range of contraction ratios. Eventually, droplet dynamics including deformation, velocity ratio, and breakup during contraction microchannel are also quantitatively studied under the factors above.

Separation of Surface Grafted Microparticles via Light and Temperature

Separation of equally sized particles distinguished solely by interfacial properties remains a highly challenging task. Herein, a particle fractioning method is proposed, which is suitable to differentiate between polymer‐grafted microparticles that are equal in size. The separation relies on the combination of a pressure driven microfluidic flow, together with simultaneous light illumination and temperature control. Heating the solution forces thermo‐responsive surface grafts to undergo a volume phase transition and therefore locally changing the interfacial properties of the microparticles. Light illumination induces the phoretic/osmotic activity of the microparticles and lifts them into a higher plane, where hovering particles experience a different shear stress proportional to the height. The light‐induced hovering height depends on the interfacial properties, and this complex interaction leads to different movements of the microparticles as a function of their surface grafting. The concepts are visualized in experimental studies, where the complex physical principle provides a simple method for fractioning a binary mixture with at least one thermo‐responsive polymer graft.

Magnetically Guided Microcatheter for Targeted Injection of Magnetic Particle Swarms.

The initial delivery of small-scale magnetic devices such as microrobots is a key, but often overlooked, aspect for their use in clinical applications. The deployment of these devices within the dynamic environment of the human body presents significant challenges due to their dispersion caused by circulatory flows. Here, a method is introduced to effectively deliver a swarm of magnetic nanoparticles in fluidic flows. This approach integrates a magnetically navigated robotic microcatheter equipped with a reservoir for storing the magnetic nanoparticles. The microfluidic flow within the reservoir facilitates the injection of magnetic nanoparticles into the fluid stream, and a magnetic field gradient guides the swarm through the oscillatory flow to a target site. The microcatheter and reservoir are engineered to enable magnetic steering and injection of the magnetic nanoparticles. To demonstrate this approach, experiments are conducted utilizing a spinal cord phantom simulating intrathecal catheter delivery for applications in the central nervous system. These results demonstrate that the proposed microcatheter successfully concentrates nanoparticles near the desired location through the precise manipulation of magnetic field gradients, offering a promising solution for the controlled deployment of untethered magnetic micro-/nanodevices within the complex physiological circulatory systems of the human body.

Submegahertz Nucleation of Plasmonic Vapor Microbubbles near a Solid Vertical Boundary.

Laser triggered and photothermally induced vapor bubbles have emerged as promising approaches to facilitate optomechanical energy conversion for numerous applications in microfluidics and nanofluidics. Here, we report an observation of spontaneously triggered periodic nucleation of plasmonic vapor bubbles near a rigid sidewall with readily tuned nucleation frequency from 0.8kHz to over 200kHz. The detailed collapsing process of the vapor bubbles was experimentally and numerically investigated. We find that the lateral migration of residual bubbles toward the sidewall refreshes the laser spot area, terminates the subsequent steady bubble growth, and leads to the repeatable bubble nucleation. A mathematic model regarding the Kelvin impulses was derived. It shows that the competition between the rigid boundary induced Bjerknes force and laser irradiation caused thermal Marangoni force on collapsing bubbles governs the process. The model also leads to a criterion of γζ<0.34 for repeatable bubble nucleation, where γ is the normalized distance and ζ thermal Marangoni coefficient. This study demonstrates nucleation of violent vapor bubbles at extreme high frequencies, providing an approach to remotely realize strong localized flows in microfluidics and nanofluidics.

Comparison of Multiple Machine Learning Models for the Classification of Cell States Based on Impedance Features

Abstract Microfluidic impedance flow cytometry (IFC) enables high-throughput single-cell analysis in label-free manner. Tens of thousands of cells can be measured in several minutes under multiple frequencies, which give rise to impedance features with rich information ideal for machine learning (ML)-based cell classification. Conventional data processing approach for IFC typically exploits the scattered distribution of the measured cells which correlates the impedance features (e.g., the impedance amplitude and phase at different frequencies, the amplitude ratio between high to low frequencies) and exhibits resolved cell clusters in scatter plot. By manually gating on the distributed dots plot, the cell subgroups get mapped to different cell type or cellular states. ML-based data processing for IFC not only reduces the human workload, and more importantly, it also eliminates the human interference to manual gating strategy, and thus potentially leading to more concise and accurate cell classification results. Here, we demonstrate the ML-based classification of different cell states for tumor cells subject to anticancer drug treatment. IFC-measured impedance data of H1650 cells and Hela cells under drug-induced mitosis block state and apoptosis state have been applied for ML-based cell state identification. Three machine learning models, including the random forest (RF), support vector machine (SVM) and K-nearest neighbours (KNN) have been trained for impedance features extracted from cell signals at both 500 kHz and 10 MHz. In comparison, the RF model give rise to the highest classification accuracies among all trained models here. For H1650 cells, 84.01% and 85.96% accuracies have been respectively achieved for G1/S state vs. apoptosis and G2/M vs. apoptosis. For the classification between G2/M vs. apoptosis for the paclitaxel-treated Hela cells, the RF model produces high accuracy of 98.70%.

Optimization of Lipid-Based Nanoparticles Formulation Loaded with Biological Product Using A Novel Design Vortex Tube Reactor via Flow Chemistry.

Lipid-based nanoparticles (LNPs) is increasingly recognized for their potential in drug delivery, offering protection to hydrophobic drugs from degradation. Industrial synthesis of LNPs, exemplified by Pfizer-BioNTech and Moderna mRNA vaccines, utilizes flow chemistry or microfluidics, showcasing its scalability. This study explores the utilization of a novel design reactor, the vortex tube reactor, within flow chemistry for LNPs synthesis, aiming to optimize its conditions and compare them with batch synthesis. LNPs were synthesized using the vortex tube reactor, incorporating bovine serum albumin (BSA) as a model drug in the aqueous phase, alongside 1.2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and cholesterol in the organic phase. Design of experiments (DoE), specifically Box-Behnken design, was employed to optimize parameters, including X1: the flow rate ratio (10-100 mL/min), X2: the aqueous-to-organic volumetric ratio (1:1-10:1), and X3: the number of reactor units (1-5 units). Responses evaluated encompassed physical properties and productivity. Optimized conditions were determined by minimizing particle size (Y1), polydispersity index (Y2), and zeta potential (Y3), while maximizing entrapment efficiency (Y4), drug loading (Y5), and productivity (Y5). Results indicated that optimal conditions were achieved at X1 of 100 mL/min, X2 of 5.278, and X3 of 1 unit. LNPs synthesized under these conditions exhibited favorable physical properties and productivity, with uniformity maintained across batches. The vortex tube reactor demonstrated superiority over batch synthesis, yielding smaller particles (166.23 ± 0.98 nm), more uniform nanoparticles (PDI 0.17 ± 0.01), and higher entrapment (67.75 ± 1.55%) and loading capacities (36.39 ± 0.83%), indicative of enhanced productivity (313.4 ± 12.88 mg/min). This study elucidates the potential of flow chemistry, particularly utilizing the vortex tube reactor, for large-scale LNPs formulation, offering insights into parameter relationships and advancing nanoparticle synthesis for drug delivery applications.