搜索结果：Fluid Flow and Transfer Processes

This study aims to develop and examine the combined impacts on boundary-layer flow and heat transfer features of non-Newtonian Cross fluid rheology, Buongiorno's nanofluid model, bioconvection, and enthalpy transport under a heat source/sink regime. The flow is developed in a cylindrical coordinate system because Cross fluid is assumed to be moving on the stretching cylinder, with the Buongiorno nanofluid model that encompasses the Brownian motion and the thermophoretic diffusion as the most prominent mechanisms of transportation of nanoparticles in the flow. The microorganisms are assumed to be gyrotactic, and their motion is influenced by fluid velocity and concentration gradients. The Cross rheological model explains the shear-thinning and shear-thickening properties of the fluid, and the suspension is stabilized by bioconvection caused by motile microorganisms. To simulate realistic heat transfer behavior, the effects of internal heat sources/sinks and enthalpy change are incorporated. The thermal and solutal slip boundary conditions are assumed at the surface of the stretching cylinder. The current work is novel because it simultaneously integrates Cross fluid characteristics with microorganism-induced bioconvection and Buongiorno's nanofluid model, taking into account enthalpy changes and heat source/sink effects. The similarity variables are introduced, which convert the governing equations of momentum, energy, and concentration as well as microorganism density in the form of dimensionless equations, and then solved numerically via the fifth-order Runge-Kutta (RK) method with the shooting approach on Matlab software. The findings indicate that the velocity field decreases with the increase in Weissenberg number, but the bioconvection and buoyancy parameters improve the flow and heat transfer. Motile microorganisms increase bioconvection, which improves fluid mixing but lowers the density of microorganisms near the surface. The findings show that the augmentation in thermophoresis considerably enhances both temperature and concentration profiles, whereas an increase in the Brownian motion parameter improves the temperature distribution while decreasing nanoparticle concentration. In general, the paper emphasizes the synergistic interactions of non-Newtonian rheology, nanoparticle transport, bioconvection, and enthalpy over the stretching cylinder, which have applications in industrial and biomedical processes. The results of this work have important practical applications in advanced thermal management systems, such as cooling electronic devices, biomedical engineering procedures like medication administration and microbial movement, and energy systems like nuclear reactors and solar thermal collectors.

Are bioactive human-equivalent doses (HEDs) of perfluorooctane sulfonate (PFOS), derived from long-term low-level in vitro exposure of human granulosa cells comparable to HEDs inferred from follicular fluid PFOS concentrations in women undergoing ART and in occupationally exposed women? The bioactive HEDs overlapped with and, in some cases, were lower than the median HEDs inferred from follicular fluid PFOS concentrations. PFOS exposure is a growing public health concern, with evidence suggesting adverse female reproductive effects. However, the relevance of current human exposure levels to granulosa cell function remains unclear. Four independent vials of human granulosa cells (HGrC1 cells) were thawed and expanded into separate flasks (biological replicates). Cells were allocated to four experimental groups and exposed to PFOS (0.01, 0.1, or 1&#x2009;&#xb5;M) or vehicle control (0.05% DMSO) for up to 12&#x2009;weeks, with re-dosing at each passage. Different apical endpoints, along with transcriptomic changes, were evaluated at designated time points. Clinical relevance of PFOS risk to human granulosa cells was assessed by integrating experimental data with physiologically based toxicokinetic (PBTK) modeling. Viability of HGrC1 cells was assessed using the Alamar Blue assay. Estradiol and progesterone secretion were quantified by enzyme-linked immunosorbent assay. Flow cytometry was used to determine the proportions of live, apoptotic and necrotic cells, as well as cell cycle distribution. Global mRNA expression was assessed by DNA nanoball sequencing technology (DNBSEQ), whereas pathway-level molecular functions were derived using bioinformatic tools. Benchmark concentrations (BMCs) were calculated from key endpoints with concentration-dependent responses and used to estimate HEDs via PBTK modeling. These HEDs were compared with HEDs inferred from follicular fluid PFOS levels reported in the literature to derive bioactivity exposure ratios (BERs) and assess relevance to human exposure. In HGrC1 cells, long-term PFOS exposure altered steroidogenesis, apoptosis/necrosis, cell cycle distribution (P&#x2009;<&#x2009;0.05), and gene expression (at least 2-fold change, Q-value &#x2264; 0.05). Median transcriptomic HEDs were 18.1 (95% CI: 1.1-35.1) and 17.5&#x2009;ng/kg bw/day (95% CI: 8-27.1) for 6- and 12-week exposures, respectively, with corresponding 5th percentile HEDs of 3.7&#x2009;ng/kg bw/day (95% CI: 0.4-9.3) and 1.4&#x2009;ng/kg bw/day (95% CI: 0.5-3.5). Pathway-level HEDs ranged from 2.8 to 24.1&#x2009;ng/kg bw/day, with eicosanoid synthesis showing the greatest sensitivity. HEDs for apical endpoints ranged from 0.4 to 203&#x2009;ng/kg bw/day, with the sub-G1 cell cycle phase being most sensitive. HEDs derived from the 5th percentile transcriptomic data, eicosanoid metabolism, and the sub-G1 phase yielded BERs below 1, indicating that PFOS levels measured in follicular fluid of ART patients may be sufficient to induce these biological effects. For occupational exposure, BERs derived from all endpoints were below 1. A subset of nine granulosa-cell genes, including CYP1B1 and TIPARP (aryl hydrocarbon receptor signaling), showed HEDs that were below the follicular-fluid-inferred HED, highlighting potential high-priority targets and candidate biomarkers. Raw and processed RNA-sequencing data are deposited in NCBI Gene Expression Omnibus (GEO) under accession number GSE315651. The estimated exposure values were based on predictions from a PBTK model rather than empirical human exposure data. Also, differences in protein concentrations in vitro and in vivo may affect free PFOS levels and bioactivity estimates. We addressed this with additional adjustments for PFOS-albumin binding. Finally, follicular fluid PFOS concentrations in occupational settings were approximated from serum concentrations using blood-to-follicular fluid transfer efficiency (BFTE) values. Our findings suggest that PFOS concentrations in follicular fluid from women undergoing ART and those who have been occupationally exposed may be sufficient to perturb granulosa cell mRNA expression and key pathways, including eicosanoid, interleukin, and GPCR signaling. The identified genes may serve as candidate biomarkers linking PFOS exposure to clinical outcomes in ART settings. Overall, this study provides a framework for interpreting PFOS reproductive toxicity and refining health-protective exposure thresholds. This research was supported by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia (Faculty of Sciences, Novi Sad: Grants No. 451-03-137/2025-03/200125 & 451-03-136/2025-03/200125), the Institute of Physics, Belgrade, National Institute of the Republic of Serbia, and the Science Fund of the Republic of Serbia, Grant No. 7010, 'Integration of Biological Responses and PBTK Modeling in Chemical Toxicity Assessment: &#x410; Case Study of Perfluorooctanoic Acid (PFOA)-ToxIN'. The authors declare no conflicts of interest.

This work provides a thorough examination of the mixed convection flow of a non-Newtonian Carreau-Yasuda Buongiorno nanofluid model in the presence of a transverse magnetic field. The physical system incorporates the Cattaneo-Christov flux model to account for non-Fourier heat and mass transfer, magnetohydrodynamic (MHD) effects, and the influence of thermal and solutal buoyancy forces. In the Buongiorno model, Brownian motion and thermophoresis are introduced as processes for nanoparticle transport, whereas the Carreau-Yasuda formulation reflects the fluid's shear-dependent viscosity characteristic. Additionally, the model takes into account the impacts of heat absorption/generation, Joule heating and chemical reactions in the fluid medium. Similarity transformations are applied to convert the governing partial differential equations to a set of nonlinear ordinary differential equations, and these determined equations are cracked numerically by using the multistep Adam-Bashforth numerical scheme along with the predictor and corrector approach. The effects of important dimensionless factors are investigated in detail, including the power-law index, Weissenberg number, magnetic field strength, thermal and solutal relaxation times, Brownian and thermophoretic parameters, and chemical reaction rate. The findings show that the velocity field is reduced by increasing the magnetic field and Weissenberg number, while the non-Fourier heat/mass fluxes and nanoparticle dynamics have a major impact on the thermal and concentration boundary layers. The results provide valuable information for the optimization and design of chemically reactive transport processes and advanced heat management systems in non-Newtonian nanofluid applications.

Antibiotic resistance (AMR) is a global health crisis responsible for over five million deaths annually. Rapid antimicrobial susceptibility testing (RAST) is critical for timely clinical decision-making. This study develops a hydrogel-based 3D culture microfluidic platform enclosed within a PMMA box, enabling safe and rapid testing of highly pathogenic bacteria. The microfluidic chip employs a Christmas tree concentration gradient generator, capable of simultaneously delivering four distinct drug concentrations. Theoretical, finite-element method, and experimental analyses demonstrated precise gradient control by tuning inlet flow-rate ratios (Q1/Q0), concentration ratios (C0/C1), and absolute concentrations (C0). Optimizing hydrogel porosity (90%) and chamber height (200 &#x3bc;m) enhanced mass transfer, improving bacterial growth and drug delivery. Using Escherichia coli ATCC 25922 as a model, the system determined the minimum inhibitory concentration (MIC, 2 &#x3bc;g/mL) of gentamicin within 2 h&#x2500;8 to 10-fold faster than standard methods, while matching conventional AST accuracy. From a fluid dynamics perspective, this work optimized the flow and mass transfer processes in AST, thereby enhancing the contact between nutrients, drugs, and bacteria. This hydrogel-based 3D microfluidic system provides a safe, efficient, and scalable RAST platform with strong potential for clinical applications against highly pathogenic and drug-resistant bacteria.

In this paper, Casson-Williamson and Maxwell fluid flow over a stretching porous sheet is investigated numerically, taking into account the effects of thermal radiation, thermophoresis, magnetohydrodynamics (MHD), and chemical processes. The flow, heat transfer, and mass diffusion controlling partial differential equations (PDEs) are converted into ordinary differential equations (ODEs) by use of a similarity transformation. Utilizing the fourth-order Runge-Kutta (RK) method, the resulting equations are solved. The study examines key thermal and flow characteristics, including the influence of thermal radiation, the Prandtl number, Brownian motion, thermophoresis, Schmidt number, chemical reaction, magnetic field strength, Casson parameter, and Deborah number on velocity, temperature, and concentration profiles. Findings reveal that an increase in thermal radiation, Prandtl number, and Brownian motion parameter leads to a decline in temperature, whereas thermophoresis enhances fluid temperature. Higher Schmidt numbers reduce concentration due to lower mass diffusivity, while strong chemical reactions increase concentration. The application of a magnetic field results in velocity suppression due to Lorentz forces, whereas the elastic and rheological properties of Casson and Maxwell fluids further hinder fluid motion. The study presents thorough numerical results that demonstrate differences in the skin friction coefficient, Sherwood number, and Nusselt number, presented in graphical form. The research extends the theoretical framework of porous-sheet MHD flows by demonstrating how the standard boundary-layer similarity equations are modified by plastic yield (Casson), shear-rate-dependent viscosity (Williamson), and fluid elasticity (Maxwell).

Momentum and thermal transport characteristics of a two-phase dusty Eyring-Powell hybrid nanofluid induced by a rotating disk in a Darcy-Forchheimer porous medium are numerically analysed under electromagnetohydrodynamic conditions. The working fluid comprises blood filled with Ag-Cu hybrid nanoparticles, while shear-dependent viscosity is modelled through the Eyring-Powell constitutive relation. To account for dust-fluid interactions, a two-phase model incorporates interphase momentum and heat transfer processes. The governing partial differential equations are transformed into a system of nonlinear ordinary differential equations using appropriate similarity transformations. The resulting boundary value problem is solved numerically using the MATLAB built-in solver bvp4c. The effects of porous resistance, inertial drag, electromagnetic field intensity, dust-interaction parameters, thermal Biot number, internal heat generation, and nanoparticle concentration on velocity distributions, temperature fields, skin friction coefficients, and heat-transfer rates are systematically examined. The numerical results show that while surface convection and more nanoparticles improve heat-transfer efficiency, porous drag, electromagnetic forces, and non-Newtonian effects significantly reduce momentum transport. Effective interphase interaction is essential for the momentum and heat transfer&#xa0;between the fluid and dust phases. These results provide a physical understanding of EMHD-controlled transport phenomena in rotating porous configurations pertinent to magnetically regulated blood transport in rotating biomedical devices.

This study analyzes the impact of local thermal non-equilibrium on the bioconvection flow of hybrid nanofluid across a slender extending sheet containing gyrotactic bacteria using artificial neural networks trained using a Bayesian regularization backpropagation approach (ANN-BRS). The effects of magnetic fields, thermal radiation, and Hall current are all things related to fluid flow. The suggested model has particular applicability in microscale drug delivery systems, where gyrotactic microorganisms and hybrid nanofluid can be employed to control nutrition and medication dispersion under non-equilibrium temperature circumstances. It can be used in lab-on-chip and organ-on-chip technologies to improve bio-mixing and accurate heat control. The model also applies to micro-solar collectors and porous micro-heat exchangers, which use hybrid nanoparticles to boost thermal efficiency. It can also be used in bioreactors and biomedical cooling systems, where local thermal non-equilibrium effects and ANN-based prediction allow for precise control of heat, mass, and microbe transfer, resulting in optimal performance. Similarity transformations are used to convert the original nonlinear PDEs into non-dimensional ODEs and the bvp4c program is applied to numerically resolve the resulting boundary-value problem. The training, testing, and validation processes yield the expected outcomes for every scenario based on the chosen data points. Regression analysis, histograms of error, and mean square error (MSE) metrics are employed to assess the ANN-BRS model's outcome. The liquid phase heat thermal profile increases as the interphase heat transfer parameter values rise, while the solid phase thermal profile decreases.

Flow dynamics play a fundamental role in modulating thrombus evolution, serving as a primary driver for mass transport, cell-protein interactions, and structural stability. While it is well-established that local flow patterns significantly influence thrombus growth and morphological changes, the precise biomechanical mechanisms linking varying flow conditions to the dynamic processes of accumulation and detachment remain to be fully elucidated. This study focuses on the intricate correlation between flow-mediated forces and thrombus stability, aiming to uncover how fluidic environments regulate the multiscale transition from cellular adhesion to macroscopic thrombus formation. Based on dissipative particle dynamics and a coarse-grained cell model, this study establishes a mesoscopic-scale model for simulating platelet activation, adhesion, and fibrin formation. The proposed method enables high-resolution numerical simulation of thrombus growth, achieving multi-scale computations spanning protein-cell-thrombus levels. Ultimately, it allows for analysis and prediction of thrombus growth status, compositional changes, and detachment processes during thrombus development. By combining microfluidic experiments and multiscale computational method, we systematically elucidated the dynamics of thrombus formation and detachment under non-physiological shear flow conditions. Our results indicate that flow intensity significantly modulates the cellular-to-fibrin ratio within thrombus. Through combined experimental and computational analyses, we identified two distinct thrombus detachment mechanisms: shear-driven boundary fragmentation detachment and pressure gradient-induced internal layer separation via thrombus fissuring. Diverging from traditional views that predominantly implicate fluid shear stress in thrombus detachment, our quantitative assessments reveal that momentum transfer from blood cell collisions is a pivotal factor in the detachment process. This insight highlights the interplay and competition between hydrodynamic and cellular kinetics in thrombus growth evolution.

Several studies have investigated counterflow and concurrent flow in channels separated by a membrane to simulate mass transfer through membranes; however, few of them have used computational fluid dynamics (CFD). The current study aimed to numerically simulate and physically describe the distribution of pressure and velocity in counter-current flow by solving Navier-Stokes (N-S) equations in the channel and membrane pores (vertical channels). This is in contrast to most previous studies, in which the channel flow was simulated using N-S equations while ultra-filtration membrane flow was simulated using Darcy's law. Consequently, the current study was executed using a CFD simulation to achieve several significant features: avoiding the execution of experimental tests, reducing the effort of model design and the expense and time consumption of fabrication, and facilitating the easy observation of variations in the pressure and the horizontal and vertical velocity for each point in the model. Two-dimensional CFD methods directly simulated the flow in channels and membrane pores to solve the N-S equations for each point in the whole domain, for which the velocity (horizontal and vertical) and pressure were calculated. In the current study, it was found that the pressure decreased from the inlet to the outlet of the channel, the horizontal velocity decreased from the inlet to the middle of the channel length and then increased to the outlet of the channel, and the vertical velocity decreased from the inlet to the middle of the channel length (L/2) with an upward direction (positive) and from L/2 to the outlet of the channel with a downward direction (negative). The analytical solution (1D model) was used to validate a numerical simulation (CFD) for the current study, but there were slight differences in the results between them. The results were perfectly explored and displayed the flow distribution patterns inside the channels and the membrane pores (vertical channels). The current study model represents the hemodialysis process.

This research examines the magnetohydrodynamic (MHD) radiative peristaltic flow of a couple-stress fluid containing a three-component hybrid nanofluid of Tio2 Al2O3 and Cu nanoparticles dispersed in blood, flowing through a symmetric channel. Driven by biomedical applications, including targeted drug delivery, thermal ablation, and hyperthermia therapy, as well as industrial cooling processes, the model incorporates realistic effects including compliant channel walls, velocity slip, viscous dissipation, Joule heating, and thermal radiation. The governing nonlinear equations are formulated, non-dimensionalized, and solved numerically under the lubrication approximation. The results demonstrate that temperature increases with Hartmann number, Brownian motion, and viscous dissipation, but decreases with radiation and thermophoretic effects. Magnetic fields are found to suppress axial velocity, whereas fluid properties and buoyancy forces enhance it. Furthermore, the size and shape of trapped boluses are shown to vary significantly with magnetic strength and nanoparticle parameters. These findings highlight the potential of ternary hybrid nanofluids for improving drug delivery efficiency, advancing microfluidic devices, and enhancing heat management in biomedical and industrial systems.

Although women often need to take medication during pregnancy, reliable human-based models mimicking the maternal-fetal interface and allowing predictions on drug transport across the human placenta are scarce. In this study, we developed a novel microfluidic Transwell-based co-culture model consisting exclusively of primary cells (trophoblasts/endothelial cells) for assessing maternal-fetal drug transfer. We aimed to (1) investigate the effects of fluidic flow on drug transfer patterns, (2) evaluate barrier integrity and different transfer processes (diffusion, active transport) across the combined trophoblast/endothelial monolayers and (3) determine the expression and functional activity of main placental drug efflux transporters (ABCB1 and ABCG2). After applying different flow rates (50/150&#xa0;&#xb5;l/min), our system maintained cellular integrity and barrier function while enhancing syncytialization markers such as hCG. Our model effectively mimics key features of the placental microenvironment, including polarized expression and functional activity of both efflux transporters. Using fluorescent substrates and specific inhibitors (ABCB1: Rhodamine 123/Cyclosporin A; ABCG2: Bodipy-FL-Prazosin/Ko123), we confirmed that both transporters are not only expressed in the primary co-cultures, but also actively restrict the passage of compounds in the mother-to-fetus direction. Importantly, our system also captured passive diffusion dynamics of reference compounds (antipyrine/caffeine), with transport rates increasing under higher flow, mirroring in vivo behaviour. While our model does not yet replicate the full complexity of the placenta, our findings provide strong evidence that dynamic flow systems can recapitulate key placental transport phenomena and offer a valuable in vitro model to study human-based transplacental transport processes. KEY POINTS: Medication use during pregnancy is an essential aspect of obstetrical care, it remains a major concern due to potential risks to fetal and placental development. Current in vitro models for assessing maternal-fetal drug transfer mostly consist of immortalized cell lines and/or lack critical components of the placental microenvironment, such as stromal cells or dynamic fluid flow. We developed a dynamic Transwell-based co-culture model , composed exclusively of primary trophoblast and endothelial cells. The model effectively mimics key features of the placental barrier properties, including polarized expression and functional activity of major placental drug efflux transporters. The dynamic primary cell based flow systems offer a physiologically relevant human in vitro model to investigate and predict transplacental drug transfer.

In industries like chemical processing, energy systems, metallurgy, filtration, and electronics cooling, activation energy in magneto-nanofluid flow with variant viscosity is essential for regulating reaction rates, maximizing heat and mass transfer, enhancing energy efficiency, and guaranteeing safe operation. This work is important because it advances our knowledge of heat and mass transmission in magnetized nanofluid flows, where the fluid viscosity varies nonlinearly with temperature or other physical parameters. The study's primary goal is to create a numerical model capable of precisely analyzing the intricate relationship between magnetic forces, nonlinear viscosity, porous media, and nanoparticle transport. To get the perfect predictions, the governing model employed the efficacy of artificial neural networks with Levenberg Marquardt structure back propagation (ANN-LMSB), which is designed to investigate energy activation with exponential viscosity variant with temperature on magneto-hydrodynamic nanofluid flow past porous plate (MHD-NFPP). To articulate mathematical modeling, the Reynolds exponential model is used. By employing the model of Darcy-Brinkman-Forchheimer, the momentum equation is additionally formulated. Thermophoresis force and Brownian diffusion have been inspected by implementing Buongiorno model. Along with magnetic body force, mass conservation, nanoparticle concentration, momentum, and energy equations are expressed. Initially, the flow of fluid is denoted by the scheme of PDEs, which are transformed into the structure of ODEs. By employing Adams numerical method, a data set for suggested ANN-LMSB is produced for diverse scenarios by alteration of stretching parameter, the Hartmann number, the thermal and concentration Grashof numbers, the thermophoresis, the Brownian motion, Prandtl number, the chemical reaction constant, Schmidt number, and relative temperature parametric number. By training, testing, and validation procedures of ANN-LMSB, estimated solution of distinct cases is verified, and for the perfection of the suggested model, the comparison for verification is carried out. Afterwards, execution of suggested ANN-LMSB was validated by regression evaluation, mean square error, and histogram studies. Correctness level in range from 10-9 to 10-11 approves distinction of suggested methodology established on the closeness of the recommended and reference results.

Due to the different thermal physical properties of solids and fluids in porous media, there exists a serious local thermal nonequilibrium phenomenon in the flow and heat transfer process in porous media, especially under conditions of higher thermal conductivity ratios and heat capacity ratios. Therefore, accurately and delicately capturing the flow and temperature changes in porous media has become a hot and difficult issue. The traditional BGK model relies on a single relaxation parameter, which results in poor computational stability of the model, while the MRT model, due to the introduction of multiple relaxation factors, causes large computational workload and implementation complexity. To address the issues of accuracy, stability, and complexity in numerical simulation of flow and heat transfer processes in porous media, a TRT-LB model is innovatively developed based on the REV scale under local thermal nonequilibrium conditions. In this model, two TRT-LB equations are introduced to calculate, respectively, the temperature distribution in the fluid and solid regions. The external term and source term are introduced into the model to predict the internal heat source and convective heat transfer process in the porous media more accurately. Then, the correctness of the model is verified by deducing the macroscopic control equation from the proposed model using the Chapman-Enskog method. Subsequently, the model is verified by using three classic benchmark cases: mixed convection in a porous channel, steady-state natural convection in a porous medium containing a heat-generating solid matrix, and transient natural convection in foam metals. The results show that the TRT-LB model can accurately and stably capture the flow and heat exchange processes in porous media, more accurately display the subtle differences in temperature in porous media under local thermal nonequilibrium conditions, and significantly reduce the implementation complexity and computational cost.

The biomedical engineering and polymer processing industries experience rising needs for thermal management systems because of continuous technology improvements. The study investigates how a Casson fluid magnetohydrodynamic (MHD) stagnation-point flow behaves when used with an expanding surface while including viscous dissipation, chemical reaction, Joule heating, and thermal radiation through the Rosseland approximation. The model uses velocity slip and convective boundary conditions to create more realistic physical behavior. The governing nonlinear partial differential equations(PDEs) are transformed into a system of coupled ordinary differential equations(ODEs) using similarity transformations and solved numerically via the shooting method with a fourth-order Runge-Kutta scheme implemented in MATLAB. The results show that increasing the Casson parameter leads to a 15 to 25 percent improvement in the velocity profile because it decreases the resistance from yield stress. The temperature profile rises significantly (about 20-30%) with an increasing magnetic parameter as a result of intensified Joule heating effects. Higher Schmidt number values result in a significant reduction in concentration profiles which decreases by almost 10 to 20 percent because of decreased mass diffusivity. The Peclet number shows an inverse relationship with the motile microorganism density which causes a decrease of about 12 to 18 percent when it rises. The findings provide valuable insights which help industries and biomedical fields to improve their thermal systems that use non-Newtonian fluids.

A new method of connecting capillary electrophoresis (CE) to mass spectrometry (MS) is introduced in which a vibrating sharp edge spray ionization (VSSI) probe is adapted to deliver a secondary fluid directly at the capillary electrophoresis surface. In VSSI, acoustic streaming at a sharp edge converts solutions into an aerosol. Consequently, a superimposed electric field is not required to nebulize fluid as is the case for electrospray ionization. In this report, a directed VSSI auxiliary flow assists in analyte transfer to the MS, making it amenable to electrophoretic separations that have a low electroosmotic bulk flow. Unlike a coaxial sheath, a directed auxiliary flow can be used with nonconductive liquids because the superimposed fluid is not integral to the process of electrophoresis grounding. An order of magnitude improvement in analyte signal is realized when deionized water is used for the supplementary liquid. In addition to the multifunctional role of VSSI for delivery of fluid, mixing with analyte, and nebulization, a self-aligning grounding cap is described for use with standard fused silica separation capillaries that have a blunt cut at the end. These features enable coupling to a commercial CE instrument. The direct CE-VSSI-MS interface is compatible with background electrolytes maintained at acidic or neutral pH and even composed of 200 mM ammonium acetate. Separations are demonstrated with cationic beta-blockers, amino acids, peptide standards, a peptide mixture from a chymotrypsin digestion of transferrin, and a 17-residue peptide monomer and homodimer derived from Huntington's protein that is implicated in protein aggregation.

Wedge geometries are widely used in aerodynamics, heat exchangers, solar collectors, and chemical processing equipment. This study focuses on the combined impacts of thermal radiation, latent heat of fusion, Hiemenz flow, Joule heating, and electro-magnetohydrodynamic (EMHD) flows on the natural convection flow over a vertical wedge, which has not been examined previously. Due to the wide range of engineering applications involving wedge geometries, it is important to consider and discuss the effects of different thermophysical properties on the flow and heat transfer behavior. We examined upper-convected Maxwell (UCM) viscoelastic liquid flow in a permeable medium with phase change (melting effects). A one-argument scaling method has been introduced for transforming the developed equations of the liquid flow model into non-linear ordinary differential equations (ODEs). The numerical solution of the ODEs with boundary conditions is explored using the BVP4C technique, and the results are shown in graphs and analyzed. The velocity of the fluid increases with the magnetic field, porosity, electric field, Deborah number, suction, melting heat, and Hiemenz flow, while it decreases with higher Prandtl number. Similarly, the temperature distribution is enhanced by porosity, Prandtl number, melting heat, Hiemenz flow, as well as magnetic and electric field effects. The sensitivity analysis reveals that the melting heat parameter significantly enhances the Nusselt number (&#x2248;&#x2009;18.98%), establishing it as the most dominant factor in thermal energy transmission, while suction contributes moderately with a stable variation of &#x2248;&#x2009;19.57%. In contrast, the Hiemenz parameter exhibits a negligible negative influence (nearly 200 times smaller), confirming its minimal role in affecting heat transfer performance.

Microfluidic electrokinetic flows play a central role in applications such as lab-on-a-chip diagnostics, microelectronics cooling, and biomedical sample manipulation. These systems involve intricate heat transfer processes, including Joule heating from ionic currents, temperature-driven flow instabilities, and coupled thermal-fluid interactions, that crucially affect device performance, reliability, and scalability. Current challenges include non-equilibrium charge dynamics, incomplete thermophysical property data for complex fluids, and thermal crosstalk in integrated platforms. This review summarizes the literature published over the past 20 years, with occasional reference to earlier work, covering the fundamental mechanisms of heat generation and dissipation in electrokinetic microflows; analytical, numerical, and experimental approaches for characterizing thermal effects; and discussion on the limitations and application-driven opportunities. It also highlights open questions and future research directions and offers a comprehensive view of design principles and guidelines for developing robust, thermally optimized electrokinetic microfluidic technologies.

High-temperature heat transfer mechanisms seen in many systems are significantly influenced by thermal radiation. When there are significant temperature fluctuations within the thermal boundary layer, radiative heat transport is often inadequately captured by conventional linear radiation models. To overcome this constraint and provide a more accurate depiction of radiative heat transport, the quadratic thermal radiation model is used. Given these appealing features, the present study investigates the aqueous-based hybrid nanofluid over an extending surface with variable thickness influenced by quadratic thermal radiation. The hybrid nanofluid comprises carbide nanoparticles (SiC, TiC) suspended in water. The novelty of the proposed model lies in considering both homogeneous and heterogeneous reactions under convective boundary conditions at the surface. Analytical solutions are derived for the anticipated model using the optimal homotopy asymptotic method (OHAM). The trends of velocity and temperature distributions are analyzed via graphs against distinct parameters. The outcomes show that fluid velocity declines by approximately 52% as the volume fraction of carbide nanoparticles increases from 0.01 to 0.07. Also, the temperature increases by approximately 57% as quadratic thermal radiation increases from 0.1 to 3.1. Tabular results indicate that the carbide nanoparticle volume fraction ranges from 0.01 to 0.05, enhancing the heat transfer rate by approximately 37.5%. These results demonstrate that nonlinear radiation modeling and carbide-based hybrid nanofluids can greatly enhance heat transport. As a result, this study&#x2019;s findings could offer valuable theoretical guidance for the development and improvement of advanced thermal systems across fields such as fluid mechanics, thermal management, and chemical processing technologies. The model&#x2019;s trustworthiness is confirmed by comparing it with existing published work.

The main aim of this chapter is to provide an (at least semiquantitative) explanation of biomolecular crystallization (nucleation and growth) experimental results in solution flow, in order to further assist with optimization of the process. An overview will be provided of biomolecular crystal nucleation and growth in forced solution flows, but also in the presence and absence of natural (buoyancy-driven) convective flows. The chapter focuses first on the theoretical analysis of the different mass transfer modalities, diffusion versus convection dominated (both of crystal building blocks and of impurities), leading to biomolecule-depleted and to self-purifying (i.e., impurity-depleted) zones. The same topics will then be addressed, describing the experimentally investigated influence of forced flows, artificially created through air pressure, peristaltic pumping, oscillatory mixing, stirring, shearing, and other methods, both in small-scale laboratory and in large-scale industrial settings. In addition to forced flows, work on the influence of gravity-induced naturally occurring solution convection and crystal sedimentation will be reviewed, as well as the effects of its absence when crystallization trials are carried out under microgravity environments. By developing the principle of the separation of the nucleation and growth stages of crystallization ("double-pulse technique") not only in time but also in space, the reported results have shown that at solution flow velocities larger than those of buoyancy-driven convection, most crystals nucleated heterogeneously, while bulk-nucleated crystals predominated at lower flow velocities. Lastly, fluid flow also allowed the investigation of the important role of impurities of biological origin on the kind of crystal nucleation, homogeneous or heterogeneous. In view of the diverse needs for protein crystals (structure determination by conventional X-ray crystallography or by XFEL, industrial production of pharmaceuticals), flow-utilizing strategies may be adjusted to each specific crystallization need. Experiments could also be undertaken that would optimize the flow parameters separately and successively for each stage of the crystallization process (nucleation, growth, cessation of growth). Finally, it would be extremely informative to widen the range of proteins used in crystallization experiments involving flow, besides the usual lysozyme and a handful of others that have already been studied.