Search Results (309)

Background/Objectives: This study addresses the need for scalable and predictive strategies linking mixing conditions to nanocarrier properties by developing and analyzing a coaxial jet antisolvent process for the continuous production of pharmaceutical nanocarriers. Methods: A single experimental platform was used to generate both curcumin-based nanoparticles and nanoliposomes, enabling direct comparison of how mixing regime and formulation variables influence product characteristics. Results: Fluid-dynamic behavior was first characterized using tracer and micromixing experiments, revealing a strong dependence of mixing time on flow conditions, with characteristic mixing times decreasing from >1000 ms under laminar conditions to approximately 10–30 ms in turbulent regimes. Nanoparticles and liposomes obtained under optimized conditions exhibited mean sizes in the range of 120–250 nm, with polydispersity indices typically below 0.2 under optimized turbulent conditions. To rationalize these observations, a computational framework was implemented, combining Reynolds-averaged computational fluid dynamics with a population balance formulation solved by the method of moments. The model provided spatially resolved insight into solvent exchange, supersaturation development, and nucleation–growth dynamics, showing good agreement with experimental trends and capturing the effect of mixing conditions on particle size across different regimes. Conclusions: Although simplified, the modeling approach establishes the basis for future extensions toward full population-balance distribution simulations capable of predicting complete particle size distributions, highlighting the ability of the coaxial jet mixer to control supersaturation and particle formation through tunable hydrodynamic conditions. This capability makes the system particularly attractive compared to conventional batch or less controllable mixing technologies, enabling a more rational and scalable design of pharmaceutical nanocarriers, with good encapsulation performance as discussed in the main text. Full article

The development of high-throughput technologies for the separation and labeling of extracellular vesicles (EVs) from whole blood is critical for downstream EV detection and analysis. However, conventional EV separation and labeling workflows are typically labor-intensive and inefficient, requiring multiple sequential processing steps. Here, we present a microfluidic platform that integrates negative magnetophoresis-based separation with mixing-enhanced on-chip labeling. The chip adopts a vertical flow channel architecture in combination with a Halbach-array magnetic field configuration, thereby overcoming the throughput limitations inherent to traditional horizontal microchannels. Parallel channels can be freely arranged above on the magnetic array to achieve ultra-high throughput processing, achieving a cell removal efficiency of 99.97% at a blood-to-sheath flow ratio of 1:5. Furthermore, by incorporating a narrow-wide channel design synergized with a herringbone–Tesla micromixer structure, the platform achieves a labeling efficiency of 91.8% within 2 min, approaching the performance of conventional 20 min incubation. This system offers both high-throughput and integration capabilities, providing a powerful technical platform for EV-related life science research. Full article

Background/Objectives: The question addressed in the current work is to develop a simulation of a pharmaceutical process (DNA encapsulation within lipid nanoparticles using a microfluidic micromixer) which will be of utility to the end users (laboratory-scale formulation development). The simulation and the microfluidic approach also address sustainability issues, such as reducing the environmental impact of the process itself, and reducing the need for physical testing. The paper details the implementation and validation, taking into account key performance indicators and control parameters. Methods: The main method applied for simulation development is a novel multi-agent approach to incorporate stochastic probabilistic behavior, combined with theoretical definitions from the process experts and relevant literature, and data/results from laboratory-scale experiments with different parameter configurations. Results: The simulation was implemented as a representation of the real physical process, reproducing the relationships between process parameters (flow rates) and experimental key performance indicators (capsule diameter, poly dispersion index, encapsulation efficiency). The simulation results demonstrated a general agreement with the empirical results and provided useful predictive insights for the laboratory experiments. Conclusions: The simulation has potential as a support tool for laboratory experiments to reduce physical testing and indicate the most promising configurations on which to focus, with potential savings in time, resources and other costs. Full article

Lipid-based delivery systems (LDS), including lipid nanoparticles (LNPs) and liposomes, have become indispensable tools in modern biomedicine owing to their biocompatibility, capacity to encapsulate diverse therapeutic agents, and potential for targeted delivery. Despite their clinical success, conventional batch-based manufacturing methods are hindered by variability, limited scalability, and complex processing steps, slowing their broader translation. Microfluidic technologies offer a transformative solution by enabling precise fluid handling, rapid mixing, and reproducible production of LDS with tunable physicochemical attributes such as particle size, lamellarity, and drug-loading efficiency. This review highlights advances in microfluidic design strategies, including hydrodynamic flow focusing, staggered herringbone mixers, and toroidal micromixers, and evaluates how critical parameters such as flow rate, solvent composition, and lipid concentration influence LDS performance. Furthermore, we discuss the application of microfluidics in drug delivery, nucleic acid therapeutics, and vaccine platforms, underscoring its role in improving scalability, quality control, and clinical translation. Finally, we examine current challenges, including throughput limitations and solvent handling, while outlining future directions for integrating emerging materials and additive manufacturing to optimize LDS fabrication. Collectively, microfluidic platforms provide a promising pathway for next-generation lipid nanomedicines with enhanced precision, reproducibility, and therapeutic efficacy. Full article

As a multiple-energy carrier, hydrogen can facilitate the transition to a low-carbon future, and coupling renewable energy sources with hydrogen-power generation systems (e.g., gas turbines) can markedly enhance gas turbine combined cycles (GTCCs) power generation regarding cleanliness and flexibility. Conventional gas turbines fuel the natural gas–hydrogen mixture and encounter issues like unstable combustion and elevated nitrogen oxide (NO_x) emissions. Initially, the alterations in combustion characteristics resulting from the fuel transition are analyzed, and the principal technical challenges of hydrogen-mixed combustion are summarized. It is found that hydrogen exhibits a laminar flame speed approximately 7–10 times higher than that of methane, and a hydrogen blending ratio beyond 30% significantly increases the risk of flashback and thermoacoustic oscillations. The existing technical proficiencies of advanced hydrogen combustion strategies are delineated to offer decision-making assistance for the industry. For instance, micromix combustors can achieve NOx emissions below 20 ppm even with 100% hydrogen, while axial staging technology expands the stable operating range to 25–106% load. Additionally, current research on hydrogen-fueled gas turbines primarily focuses on enhancing traditional combustor designs. Conversely, the focus on the overall alteration of gas turbines has been relatively restricted. It further examines component failure issues arising from elevated temperatures and material hydrogen embrittlement, highlighting that X80 pipeline steel experiences a 17-fold increase in hydrogen embrittlement index when the hydrogen blending ratio rises from 1% to 20%, as well as safety concerns related to fuel transitions from conventional gas turbines to hydrogen gas turbines, offering technical references for the comprehensive optimization of hydrogen-fueled gas turbines. Full article

An experimental investigation was conducted to evaluate the thermal conductivity (TC) and local heat-transfer coefficients (LHTCs) of nanofluids containing alumina (Al₂O₃), hematite (Fe₂O₃), and copper oxide (CuO) nanoparticles dispersed in deionized water. A newly developed non-invasive LHTC probe was integrated into the inner wall of the test section to enable direct quantification of interfacial heat-transfer performance. The measurements were conducted under laminar and turbulent flow conditons across Reynolds numbers ranging from 1000 to 10,000. The selected nanoparticles were chosen based on their high intrinsic thermal conductivity, cost effectiveness, and, in the case of Fe₂O₃, magnetic recoverability. The nanoparticles enhanced both TC and LHTCs through improved thermophysical propoerties and possible interfacial effects. Maximum TC enhancements of 19%, 21%, and 25% were achieved for Al₂O₃/distilled water (DW), Fe₂O₃/DW, and CuO/DW nanofluids, respectively, at 0.05 vol% and 55 °C, while the corresponding LHTC enhancements reached 44%, 50%, and 53%. Under turbulent flow, CuO/DW exhibited the highest heat-transfer performance, attributed to a 25% increase in TC and corresponding improvement in connective heat transfer. Since the boundary-layer thickness exceeded the nanoparticle diameter (30 nm), nanoparticles penetrated the interfacial film, inducing localized micro-convection and catalytic micro-mixing, which intensified interfacial heat transport. The experimentally determined Nusselt numbers showed strong agreement with the Xuan–Qiang correlation at 55 °C, suggesting that the nanoparticle volume fraction governs the catalytic interfacial heat-transfer mechanism. Full article

Hydrogen-fueled gas turbines face challenges related to flashback risk, nitrogen oxide (NO_x) emissions, and operational flexibility. In this study, a Center-Graded Spiral Micromixing (CGSM) combustor was designed and experimentally investigated to enhance the robustness of fuel–air mixing under hydrogen-rich conditions. The proposed CGSM concept employs spiral microtubes to induce curvature-driven secondary flows, promoting mixing through airflow-controlled mechanisms rather than relying solely on fuel jet momentum. Numerical simulations were conducted to qualitatively analyze the internal flow and mixing characteristics of the spiral microtubes, followed by pressurized combustor experiments at an inlet pressure of 0.3 MPa and elevated air temperatures. The experimental results demonstrate stable combustion of pure hydrogen under lean conditions, with NO_x emissions being maintained below 25 ppm, corrected to 15% O₂, without observable flashback or combustion oscillations within the designated operating range (from ignition to full load). The combustor further exhibits stable operation with blended hydrogen–methane and hydrogen–ammonia fuels, enabling online fuel switching without hardware modification. Application tests on an 80 kW micro-gas turbine indicate that the CGSM combustor can support stable operation across the full range of load conditions, from ignition to full-load operation, under both simple- and reheat-cycle modes, with performance characteristics that are consistent with established operational standards for micro-gas turbines. These results suggest that the CGSM concept provides a feasible micromixing strategy for hydrogen and hydrogen-rich fuels at a moderate pressure and micro-gas turbine scale. Full article

RNA-based interventions are particularly promising for next-generation therapeutic strategies and hold significant potential when integrated with diagnostic modalities. Among noncoding RNAs, microRNAs (miRNAs) regulate gene expression post-transcriptionally and represent compelling targets for cancer therapy. However, their clinical translation remains hindered by instability, off-target effects, and limited delivery efficiency. Here, we report the microfluidic synthesis of hybrid lipid–polymer nanoparticles (LiPoNs) that co-deliver an AntimiR-21 and the magnetic resonance imaging contrast agent gadolinium diethylenetriamine penta-acetic acid (Gd-DTPA). The LiPoNs were obtained using coupled Hydrodynamic Flow Focusing (cHFF), enabling precise control over lipid–polymer self-assembly and surpassing the compositional limitations reported with conventional micromixers. The resulting AntimiR-21–Gd-DTPA–LiPoNs exhibited an average hydrodynamic diameter of 124 nm, narrow polydispersity (PDI < 0.2), and encapsulation efficiency up to 60%. In MDA-MB-231 breast cancer cells, treatment with AntimiR-21–LiPoNs induced suppression of miR-21 and a corresponding decrease in migratory capacity, demonstrating effective functional delivery and gene expression modulation. These findings establish a versatile microfluidic platform for engineering multifunctional lipid–polymer nanostructures whose hybrid architecture combines the biocompatibility and membrane fusion capability of lipids with the structural robustness and controlled release properties of polymers, thereby advancing RNA-based theranostic design for precision oncology and related applications. Full article

The current state and prospects of microreactor synthesis of functional materials in single- and two-phase flows with a liquid continuous phase are analyzed. Microreactors allow fine control over the size, composition, structure, and properties of synthesized particles in co-precipitation processes. The results obtained by various teams provide grounds to expect fairly extensive capabilities for controlling the processes of nucleation and particle growth in microreactors—by controlling the pH, reagent concentrations, micromixing quality, and residence time in each of the reactor zones—in the nucleation growth zones. The advantages of microreactor synthesis have been demonstrated with a high quality of micromixing in a volume of 0.2–0.5 mL, which ensures the production of nanoparticles without impurities, a stoichiometric ratio of atoms in the product, and limitation of agglomerate growth due to a short residence time (in the order of several milliseconds). The transition to an industrial scale is very easy due to the fairly high productivity of a single microreactor (up to 10 m³/day for suspension, up to 200–300 kg/day for solid phase). Intensive mixing in microreactors with a diameter of 2–4 mm or less, due to Taylor vortices, contributed to the use of two-phase microreactors for the synthesis of both organic and inorganic substances. Full article

Microreactors offer remarkable advantages in intensifying mixing/mass transfer and hold promising prospects for industrial applications. In this study, T-shaped microreactors (TMRs) integrated with baffle, orifice-plate, and venturi structures (featuring different contraction angles) were designed. Based on the Villermaux–Dushman reaction system, three-dimensional computational fluid dynamics (CFD) models were established to simulate the fluid flow and mixing-reaction processes in these microreactors. The results demonstrate that peaks in velocity, turbulent kinetic energy, and turbulent dissipation rate consistently emerge in the confluence region of the two fluid streams. In the operating range of this study, the baffle configuration exhibits the highest micromixing performance but also induces the largest pressure drop, followed by the orifice-plate structure. Notably, the venturi structure not only enhances micromixing efficiency but also results in a minimal increase in pressure drop and eliminates flow dead zones. Specifically, the venturi structure with a 45° contraction angle achieves a balance between energy consumption and micromixing efficiency. Using the agglomeration model, the micromixing times of the microreactors with various structures were determined to range from 0.025 to 0.234 ms. Full article

Micromixers are crucial for rapid and homogeneous mixing in lab-on-a-chip systems. This study presents a novel passive micromixer that synergistically combines a Zigzag channel with D-shaped obstacles to enhance mixing across a broad Reynolds number (Re) range of 0.1–50. The design leverages flow splitting, recombination, and the generation of localized high-velocity streams to effectively disrupt laminar flow. A comprehensive parametric study optimized key geometric parameters, including obstacle dimensions (b₂, a₂) and the number of mixing units (n). Results show that optimizing b₂ to 500 μm and increasing a₂ to 250 μm significantly enhances mixing efficiency. Mechanistic analysis reveals that centrifugal forces in the Zigzag channel work synergistically with obstacle-induced perturbations to stretch and fold the fluid interface, promoting transverse transport. The optimized mixer, fabricated and experimentally validated, achieves a high mixing index (>0.85) under all Re conditions. This work provides valuable design insights for developing efficient, compact micromixers for micro-total analysis systems. Full article

Passive micromixers can be used in a wide range of chemical applications for reagent preparation as well as chemical analysis. To investigate a micromixer with high performance under various Re conditions, based on the research of previous scientists, we hereby parameterize three influential factors on the structural design of the micromixer. In this study, we chose five distinct level values from a set of three influential factors of the micromixer, based on the results of a one-way impact analysis to ascertain their degree of influence. For five different Re cases, the Taguchi orthogonal test was performed using the selected five-level values, the fluid mixing efficiency was examined numerically, and we used the orthogonal table L₂₅5⁶. Finally, a set of optimization parameters was selected. An optimized micromixer structural model with high mixing efficiency under different Re conditions has been achieved. The degree of stirring of the optimized micromixer and the comparison curves before and after the optimization were also analyzed. We have also manufactured and tested the micromixer of this design. The simulation results show that the mixing efficiency of “the After Optimized Y-shaped channel Koch fractal Cesàro construction” micromixer (AOYKC) designs in this paper is increased by 15.99%, 21.19%, 19.34%, 11.41%, and 0.04% at Re = 0.1, 1, 10, 20, and 100. Full article

Electrokinetics has established itself as a central pillar in microfluidic research, offering a powerful, non-mechanical means to manipulate fluids and analytes. Mechanisms such as electroosmotic flow (EOF), electrophoresis (EP), and dielectrophoresis (DEP) re-main central to the field, once more layers of complexity emerge heterogeneous interfaces, viscoelastic liquids, or anisotropic droplets are introduced. Five research directions have become prominent. Field-driven manipulation of droplets and emulsions—most strikingly Janus droplets—demonstrates how asymmetric interfacial structures generate unconventional transport modes. Electrokinetic injection techniques follow as a second focus, because sharply defined sample plugs are essential for high-resolution separations and for maintaining analytical accuracy. Control of EOF is then framed as an integrated design challenge that involves tuning surface chemistry, engineering zeta potential, implementing nanoscale patterning, and navigating non-Newtonian flow behavior. Next, electrokinetic instabilities and electrically driven micromixing are examined through the lens of vortex-mediated perturbations that break diffusion limits in low-Reynolds-number flows. Finally, electrokinetic enrichment strategies—ranging from ion concentration polarization focusing to stacking-based preconcentration—demonstrate how trace analytes can be selectively accumulated to achieve detection sensitivity. Ultimately, electrokinetics is converging towards sophisticated integrated platforms and hybrid powering schemes, promising to expand microfluidic capabilities into previously inaccessible domains for analytical chemistry and diagnostics. Full article

The present paper investigates the steady laminar flow and thermal mixing performance of non-Newtonian Al₂O₃ nanofluids within a two-layer cross-channel micromixer, employing three-dimensional numerical simulations to solve the governing equations across a low Reynolds number range (0.1 to 50). It also addresses secondary flows and thermal mixing performance with two distinct inlet temperatures for thin nanofluids. Additionally, it explores how fluid properties and varying concentrations of Al₂O₃ nanoparticles impact thermal mixing efficiency and entropy generation. Simulations were conducted to optimize performance by adjusting the power law index (n) across different nanoparticle concentrations (1–5%). The findings show that magnetohydrodynamics can enhance mixing efficiency by generating vortices and altering flow behavior, providing important guidance for improving microfluidic system designs in practical applications. Full article

Natural convection in enclosures heated from both sides is a topic of interest in various space and safety applications in nuclear power reactors. The transient dynamics during natural convection in enclosures is critically dependent on micro-scaled boundary layers and also the timescales of micromixing. In the present work, a square enclosure operating at two high Rayleigh numbers (Ra = 3.27 × 10¹⁰ and Ra = 6.55 × 10¹⁰, with water as the working fluid) have been chosen for study. First, the velocity and timescales were found using Computational Fluid Dynamic (CFD) simulations for the square enclosure with Ra 3.27 × 10¹⁰ and compared with scaling laws that presently define them. An empirical correlation for heat transfer is then developed for the Ra range (1.3 × 10¹⁰ < Ra < 6.55 × 10¹⁰). Then, an existing DL framework (Proper Orthogonal Decomposition and Long Short-Term Memory (POD-LSTM)) network) is compared qualitatively and quantitatively with the CFD data. The transient data Ra = 6.55 × 10¹⁰ was chosen for this purpose. The scaling laws show a 30% deviation for the predictions of the transient length and time scales as compared to CFD and DL model predictions. Further, accurate results up to 99.6% have been obtained by the DL model when compared with the CFD model. The DL model is also found to require an order of magnitude less time than the one required for a CFD simulation. Full article