Microfluidics and Nanofluidics最新文献

Fluid transport in nanochannels driven by an electric field is a promising approach for shale oil and gas extraction and membrane separation. However, the fundamental mechanism of this process under the combined conditions of nanoconfinement and geological formations is not fully understood. This study constructs an alumina nanochannel system with pore diameters ranging from 26.1 to 206.2 nm. Pressure-driven experiments (0.01–0.1 MPa) were conducted to compare the transport characteristics of deionized water and simulated formation water (2% KCl). During these experiments, electric fields were applied either parallel or perpendicular to the flow direction. The objective was to decouple the interconnected influences of nanoconfinement, ion effects, and the electric field. The results demonstrate that measured flow rates were lower than the values predicted by the classical Hagen-Poiseuille theory in all experimental scenarios. The effect of the electric field on flow was ion-dependent. For deionized water, the electric field did not alter the flow rate. In contrast, for the simulated formation water, a parallel electric field increased the flow rate by an average of 14.3%, and a perpendicular electric field increased it by an average of 5.5%. Through systematic experiments, this study reveals the combined effects of nanoscale confinement, electric field, and ionic environment on fluid transport. The multi-parameter control design allows for the differentiation of influences from various mechanisms that affect flow rate changes, providing a theoretical basis for understanding transport phenomena in nanochannels under complex conditions.

The present research provides a detailed theoretical and analytical exploration of electrothermal interactions and Joule heating phenomena in metachronal cilia-induced peristaltic electroosmotic transport of ionic liquids through microchannels. The main focus lies in examining how the combined influence of an external magnetic field, dynamic ciliary movement, electroosmotic flow, and internal heat generation governs microscale fluid dynamics in biomimetic microfluidic environments. The complex nonlinear equations governing momentum, energy, and electric potential are reformulated into nondimensional form under the assumptions of long wavelength and negligible inertia. Closed-form analytical expressions are derived using boundary conditions that incorporate ciliary wave motion, electric double-layer structure, and validated electroosmotic slip relationships grounded in the Poisson–Boltzmann and Nernst–Planck formulations. The multiphysical coupling demonstrates that stronger magnetic fields markedly decelerate the fluid owing to Lorentz-force-induced resistance, whereas Hall current contributions enhance motion by counteracting magnetic drag. Intensified electroosmotic strength magnifies double-layer interactions adjacent to the walls, thus improving fluid conveyance. Flow modulation through porous channel layers is dictated by the Darcy parameter - larger values diminish hydrodynamic opposition and promote throughput. Ciliary dimensions and eccentricity significantly determine propulsion efficiency and drag response. Thermal contributions from Joule heating and radiative transfer enlarge thermal boundary regions and alter viscosity distribution, thereby influencing the overall stability and flow rate. Comparison with benchmark numerical findings validates the analytical framework and confirms its computational reliability. This integrative multiphysics model deepens the understanding of cilia-driven electroosmotic mechanisms and offers valuable design guidelines for microchannel systems utilizing ionic liquids, relevant to biomedical, energy, and microchemical technologies requiring controlled electrothermal pumping at the microscale.

Ensuring a safe and clean water supply is essential for public health and environmental sustainability. The presence of contaminants, such as residual chlorine and copper ions, can pose significant health risks. Thus, developing rapid and reliable water quality monitoring techniques is essential. Conventional laboratory-based methods are highly accurate but depend on expensive instrumentation and trained personnel, making them unsuitable for on-site applications. To address this problem, this study presents a finger-actuated microfluidic chip integrated with a smartphone-based colorimetric analysis system for the rapid on-site detection of residual chlorine and copper ions in water. The PDMS/glass hybrid device is fully power-independent and utilizes only manual finger pressure to propel the samples and reagents through the microchannel network. The device incorporates a square-wave microchannel design to enhance passive fluid mixing within the confined microscale environment. The simulation and experimental results demonstrate an excellent agreement, with mixing efficiencies of 98.5% and 95.5%, respectively. For quantitative detection, a 3D-printed cassette is combined with a custom-developed smartphone application to capture and process RGB color data in real-time. The calibration curves constructed using residual chlorine (0.6–6 ppm) and copper ion (0.25–2 ppm) control samples exhibit excellent linearity, with coefficients of determination (R²) of 0.9902 and 0.9867, respectively. Moreover, verification trials performed using real environmental water samples reveal relative errors lower than 10.0% for residual chlorine and 9.6% for copper ions, confirming both the reliability and practical applicability of the proposed system. Overall, the portable, power-free microfluidic platform provides a cost-efficient and user-friendly tool for decentralized water quality monitoring, offering a practical solution for enhancing public health protection in regions lacking access to conventional laboratory infrastructure.

This study presents a portable and accurate nitrite detection system that integrates a differential gradient analysis with smartphone-assisted microfluidic colorimetry to improve detection efficiency and precision. A bidirectional concentration gradient was established via diffusion within a PDMS-based microfluidic chip, significantly reducing the dependency on standard calibration and shortening the total detection time to within 15 minutes. Sample images were captured using a smartphone camera, and nitrite concentrations were quantified through RGB color analysis using a custom-developed mobile application. The implementation of the differential colorimetric method significantly improved detection accuracy, particularly at low concentrations, reducing the measurement error from 9.12% (conventional methods) to 1.93%. The platform demonstrates compatibility with various smartphone models, thereby eliminating the need for bulky instrumentation or specialized training. These features collectively enhance its potential for rapid point-of-care testing. Overall, the proposed method offers a cost-effective and efficient solution for quantifying colorimetric-responsive analytes in resource-limited settings. The successful integration of microfluidic technology with smartphone-based analysis not only advances nitrite detection performance but also opens new avenues for detecting other analytes, underscoring its broad applicability in field applications.

The integration of electrothermal (ET) flow with dielectrophoresis (DEP) presents a promising solution to overcome throughput limitations and extend the effective working range in microfluidic particle trapping, particularly when using nanofibers or similar sub micrometer electrode structures. This study examines the role of ET flow in enhancing DEP-based particle capture across various fiber diameters, Clausius-Mossotti factors, and medium conductivities through numerical investigations. A two-fiber model was used to analyze the electric, thermal, and flow fields, while particle trajectories were evaluated to quantify trapping efficiency. The results show that while smaller fibers produce higher electric field gradients, larger fibers yield greater trapping efficiency due to their increased capture area and longer particle residence time. Importantly, ET flow significantly improves trapping performance for submicron fibers by expanding the effective trapping region and directing particles into high electric field zones where they can be captured by DEP. This enhancement is most pronounced at moderate voltages (7.5–15 V), as the ET flow varies with the fourth power of the voltage and plays a dominant role in particle motion under weak DEP conditions. Furthermore, high-conductivity environments benefit greatly from ET-induced recirculation, enabling efficient trapping in scenarios where traditional DEP methods are less effective. These findings provide crucial insights for the design of scalable, high-throughput DEP systems that incorporate nanostructured electrodes and electrohydrodynamic enhancement.

Organophosphorus nerve agents (OPNAs) can react with the tyrosine-411 residue of human serum albumin (HSA) in blood, producing phosphylated tyrosine adducts that can be used as long-lived biomarkers of nerve agent exposure. These adducts can be analyzed by liquid chromatography coupled to tandem mass-spectrometry (LC-MS/MS) after an enzymatic digestion step. The objective of this study was to develop an immobilized enzyme reactors (IMER) platform, in order to obtain a faster digestion of HSA than the conventional in-solution digestion (6–24 h). This study developed a packed-bed IMER platform based on γ‑Fe₂O₃ magnetic microbeads. The platform was first evaluated using α‑chymotrypsin (ChT) as a model enzyme. The resulting ChT@γ‑Fe₂O₃‑IMER showed enhanced catalytic activity and substrate affinity (Km = 0.25 mM) compared to the free enzyme (Km = 1.49 mM), along with good operational stability and repeatability. To demonstrate its specific practical utility in detection of nerve agent exposure, a pronase‑based IMER (Pronase@γ‑Fe₂O₃‑IMER) was fabricated for hydrolyzing phosphorylated albumin in exposed plasma. Multiple nerve agent adducts were successfully released from phosphorylated albumin within 1 h, which is six times faster than conventional solution digestion time. All the results show that the developed IMER platform offers a feasible method for rapid diagnostic analysis of protein biomarkers.

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The fabrication process described herein offers a straightforward and cost-effective alternative to traditional methods, thereby eliminating the need for complex instrumentation. This approach addresses the increasing demand for environmentally sustainable laboratory solutions by employing biodegradable materials to fabricate paper-based analytical devices. This study presents a straightforward, instrument-free screen-printing technique for fabricating biodegradable paper-based microtiter plates. The devices are constructed from a patterned cellulose substrate coated with a hydrophobic polycaprolactone (PCL) polymer. This coating is precisely configured to define discrete hydrophilic wells, establish lateral hydrophobic barriers, and form a continuous hydrophobic backing layer, thereby achieving effective spatial isolation of the hydrophilic regions. Clear and well-defined interfaces were observed between hydrophilic and hydrophobic zones. The method demonstrated a minimum channel width of 513 ± 16 μm for delivering aqueous samples. The process has high reliability in fabrication, with a strong linear correlation (R² = 0.99) observed between the set and actual widths. The fabricated paper microtiter plates were evaluated through colorimetric assays for Bovine Serum Albumin, glucose, and phosphate, utilizing a standard microplate reader and a flatbed scanner. The results exhibited a strong correlation (R² = 0.98) between the two measurement platforms and demonstrated good agreement with absorbance values obtained using commercial well plates. These findings underscore the effectiveness of the proposed method for fabricating paper microtiter plates, which offer a cost-effective and disposable alternative to conventional well plates, offering comparable analytical performances.

The increasing global demand for lithium, driven by the rapid expansion of electric vehicles and renewable energy storage technologies, necessitates the development of sustainable and efficient extraction methods beyond conventional mining and brine evaporation. Produced water (PW), a high-salinity byproduct of oil and gas operations, has emerged as a promising yet underutilized secondary source of lithium. In this study, we present a novel microfluidic extraction platform based on a 3D-printed Y-shaped slug flow reactor for selective lithium recovery from synthetic and real PW samples. The device was fabricated using stereolithography (SLA) 3D printing and polydimethylsiloxane (PDMS) casting, enabling precise control over channel geometry and fluid behavior. Bis(2,4,4-trimethylpentyl) phosphinic acid dissolved in decane with 2% hexanol was employed as the organic extractant phase. Optimization studies revealed that lithium extraction efficiency peaked at pH 6.0, with a maximum recovery of 89% from synthetic solutions. The platform also demonstrated effective performance across varying lithium concentrations, with measurable recovery observed even at 20 mg/L. When applied to real PW samples containing 136 mg/L lithium and high concentrations of competing ions, the system achieved 36% recovery, which increased to 75.7% following selective removal of divalent cations. The microfluidic system outperformed traditional methods in terms of selectivity, reagent economy, and operational speed, while offering a scalable and environmentally friendly alternative for lithium recovery. This work establishes a foundation for the integration of microfluidic extraction with pre-treatment strategies, highlighting its potential for deployment in critical mineral recovery from industrial waste streams.

Fluorescence microscopy combined with microfluidic platforms allows for the analysis of single cells and the whole biomedical process to be done at high speed, however, it is often a very delicate method that can be heavily affected by motion-induced distortions during the high-speed flow. These artifacts, such as motion blur, misalignment, and shape deformation significantly lower automatical accuracy of the cell classification. The suggested research suggests that on-chip fluorescence microscopy employs an AI-based framework of distortion correction using Vision Transformers (ViT) and Generative Adversarial Networks (GAN) to remove motion artifacts in real-time. The combination of the GAN-ViT architecture does not only manage to reconstruct image quality but also to preserve fine cellular features when flowing system rates increase to 200 4 L/min, which provide PSNR = 38.6 dB and SSIM = 0.98. When the system was used in both synthetic and experimental microfluidic data, it was able to reach a classification accuracy of 99.9, thereby indicating consistency in the system despite varying flow rates. The speed of the framework is 950 frames per second (fps), almost equal to the 1000-fps smartphone camera acquisition rate, thereby, demonstrating its suitability to the real-time, high-throughput imaging. As opposed to the past CNN or transformer techniques, a hybrid GAN-ViT architecture offered by the authors of this study directly implements in the imaging pipeline, thus enabling the simultaneous motion correction and diagnostic classification to occur immediately. The study results highlight the fact that AI-based distortion correction not only increases the accuracy of the diagnosis, but also personnel and laboratory response in microfluidic fluorescence microscopy.

The growth of microfluidics has greatly increased the demand for microfluidic products. CO₂ lasers are being extensively employed to manufacture microfluidic devices using PMMA because of the flexibility, versatility, and cost-effectiveness involved. However, defining the relationships among the input parameters and responses, and getting the optimum results are challenging. Techniques of design of experiments like the Taguchi method, response surface methodology (RSM), and 2-level factorial design help to achieve optimum results. In this work, RSM based on the central composite design was employed to investigate the effect of the laser power (1.5, 3.0, and 4.5 W), scanning speed (10, 15, and 20 mm/s), and pulse rate (800, 900 and 1000 pulses per inch) on the microchannel depth, width, aspect ratio, and heat-affected zone (HAZ), during CO₂ laser fabrication of microchannels on PMMA substrates coated with a 500 nm layer of 99.95% pure aluminium. A total of 54 experiments were conducted, full quadratic models were developed, and multi-objective optimization was done. The optimization results were validated experimentally, and a repeatability test was performed using the optimum conditions. Using analysis of variance (ANOVA), the models were tested at a 95% confidence interval, and the significance of the parameters was determined. The laser power is the most significant factor followed by the scanning speed and pulse rate. The models are adequate with small absolute prediction errors of 2.21%, 1.54%, 2.53%, and 2.87% for the microchannel width, depth, aspect ratio, and HAZ respectively. For every response, the repeatability result is high with a small standard deviation of 1.809, 1.358, 0.022, and 1.949 of the microchannel width, depth, aspect ratio, and HAZ respectively. The models can be used by manufacturing engineers to efficiently predict the microchannel characteristics.