The on-site monitoring of trace cadmium (Cd2+) and copper (Cu2+) ions in environmental waters is crucial for risk assessment but remains challenging due to the limitations of conventional methods, which often involve complex pretreatment and laboratory-bound instrumentation. Herein, we present an integrated centrifugal microfluidic chip that incorporates solid-phase extraction (SPE) for the efficient enrichment and subsequent detection of these heavy metal ions. The disc-shaped chip, fabricated with a multilayer polymer structure, automates the entire "load-adsorb-elute" sequence via centrifugal and Coriolis forces, using embedded capillary valves for precise fluidic control. Multi-walled carbon nanotubes were packed into the adsorption chamber, and alizarin complexone was added to the sample solution prior to adsorption to enhance selective complexation. The eluted analytes were quantified through two complementary modalities. Cd2+ was detected via a chemiluminescence inhibition assay, while Cu2+ was determined colorimetrically using bis-cyclohexanone oxalyl dihydrazone. Under optimized conditions, the chip achieved high enrichment factors of 100 for Cd2+ and 150 for Cu2+, with detection limits of 0.42 µg L-1 and 2.0 µg L-1, respectively. Linear ranges spanned 0.5-10 µg L-1 for Cd2+ and 5-500 µg L-1 for Cu2+. The method showed good reproducibility and was applied to the analysis of environmental water samples. This work demonstrates a portable and automated microfluidic platform that combines efficient SPE preconcentration with dual-mode detection, offering a practical solution for rapid on-site detection of trace heavy metal ions.

The present study explores the influence of surface wettability and viscosity ratio on capillary filling, wetting, and interface evolution of an immiscible binary system in a rotational microfluidic system. A thermodynamically consistent phase-field model is used to capture the spatiotemporal evolution of the interface, influenced by the complex interplay among the rotational force, surface tension, and viscous resistance. A comprehensive regime map, characterized by the local Weber number, is developed to classify the distinct interfacial transitions. Unlike classical pressure-driven systems that yield uniform centerline viscous fingering, we demonstrate that rotational forcing introduces velocity-dependent transverse Coriolis momentum. This Coriolis force acts as an active symmetry-breaking mechanism, laterally shifting the advancing fluid and driving a skewed morphological distortion. Under hydrophilic conditions, the interface transitions from a concave shape through weakly and strongly centrifugal force-dominated regimes as the rotational Reynolds number increases. Conversely, hydrophobic conditions maintain a convex meniscus, accelerating these regime transitions. Moreover, increasing the viscosity ratio significantly delays regime transitions because of increased viscous resistance from the displaced fluid. For hydrophobic substrates, overcoming this resistive capillary force requires a critical rotational Reynolds number to initiate flow, which scales with both the contact angle and the fluid properties. We believe that the findings of this study will advance the fundamental understanding of interfacial dynamics in rotational microfluidics and provide a foundation for the rational design of next-generation centrifugal lab-on-chip devices, typically used in diagnostics, sample preparation, and biochemical assays.

Precise, sheathless manipulation of blood microscale components remains a central challenge in microfluidics, particularly for Lab-on-a-Disc (LOD) platforms where inertial, rotational, and electrokinetic effects coexist. This simulation study proposes a two-phase particle-handling strategy that integrates rotation-assisted inertial focusing with high-frequency dielectrophoretic (DEP) sorting inside serpentine microchannels. In phase I, three channel geometries─an asymmetric sinusoidal, symmetric sinusoidal, and rectangular layout─were systematically evaluated to determine their ability to confine 3 μm particles using inertial lift, Dean vortices, and rotation-induced centrifugal and Coriolis forces. The asymmetric sinusoidal design produced the strongest hydrodynamic ordering, achieving focusing efficiencies above 96%, especially when combined with higher inlet velocity, narrow channel width, and increased serpentine turns. Rotational actuation further enhanced focusing, with the combined centrifugal-Coriolis contribution improving performance from ∼34% (no rotation) to ∼64% at 800 rad/s. In phase II, rotation was removed and the prefocused stream was directed into a DEP electrode array for label-free separation of red blood cells (RBCs) and platelets (PLTs). Here, the rectangular geometry─despite being the weakest inertial focuser─outperformed the sinusoidal channels by stabilizing particle trajectories before entering regions of steep ∇|E|2. Under |20| V and 10 GHz actuation, the device achieved ∼95% platelet isolation with concurrent ∼25% RBC diversion, while higher inlet velocities reduced separation due to shorter DEP residence times. The combined findings establish a unified inertial-DEP mechanism for high-precision, pump-free blood component handling on LOD systems and provide design rules for next-generation point-of-care hematology platforms.

Maximizing drug loading in cavity microneedles through precision cavity engineering and centrifugal techniques.

Tensor flow based neural network modeling of microbial bioconvection over porous surfaces under Coriolis effects using Cattaneo-Christov heat and mass flux

This paper presents a comparative study of PID, Fuzzy Logic Control (FLC), and Sliding Mode Control (SMC) strategies for trajectory tracking of a nonlinear 3-DOF robotic manipulator. A complete dynamic model is derived using the Euler–Lagrange formulation, incorporating inertia coupling, Coriolis and centrifugal effects, gravitational forces, and joint friction. The developed model is validated against published results, demonstrating close agreement in amplitude and phase characteristics under sinusoidal joint trajectories. The three controllers are implemented under identical conditions and evaluated in both joint space and Cartesian space using step inputs, infinity trajectories, and circular paths. Performance is quantitatively assessed using RMSE, ITAE, and IAE metrics. The results indicate that SMC achieves the highest tracking accuracy, reducing average RMSE by approximately 80% compared to PID, while FLC achieves nearly 50% improvement. In Cartesian tracking, SMC maintains peak position errors below 0.005 m, significantly outperforming PID, which exhibits deviations up to 0.11 m under dynamic motion. Statistical analysis further confirms improved robustness under the considered simulation scenarios and the consistency of SMC across all joints. The findings demonstrate that robust nonlinear control significantly enhances convergence speed, tracking precision, and disturbance rejection capability in planar 3-DOF manipulators. The validated modeling framework and systematic benchmarking provide practical guidance for selecting appropriate control strategies in industrial robotic applications.

Direct numerical simulations are conducted in this study to investigate fully developed turbulent flows in spanwise rotating ducts with different aspect ratios. The global friction Reynolds number Reτ is fixed at 180, while the global friction rotation number Roτ varies from 0 to 10. The duct aspect ratios (AR) considered include 0.5, 1, and 2. The objective of this study is to explore in depth the kinematic and dynamic characteristics of secondary flows under different rotation numbers and aspect ratios, as well as their impact on the flow physics of wall-bounded turbulence. The results show that as the rotation rate increases, the secondary flow structures in both square (AR = 1) and AR = 2 ducts follow an evolution path from corner vortices, through additional vortices, to large-scale circulations dominated by the Coriolis force, although differences exist in the generation, development, and decay processes of each structure. In contrast, the AR = 0.5 duct directly evolves from corner vortices to Coriolis-dominated circulations. Analysis of the secondary flow intensity indicates that the expansion of the spanwise scale allows the secondary flow to fully develop, and the secondary flow intensity in the duct is significantly enhanced. The study further confirms that the secondary flow in rotating ducts is mainly driven by the Ekman layer, and the Ekman layers in ducts with different aspect ratios exhibit similarities. Turbulence statistics and transport analysis further reveal that the square duct with a smaller AR shows higher sensitivity of mean velocity and turbulence fluctuations to changes in rotation number, with more pronounced suppression effects by rotation, while the secondary flow significantly enhances the local turbulence intensity and transport capacity.

This study proposes a new analytical framework for identifying the optimal parameters of a tuned mass damper (TMD) aimed at mitigating torsional oscillations in steam turbine shafts. Improper TMD design may induce eccentric shaft rotation, which becomes particularly hazardous for high-speed shafts due to the substantial Coriolis and centrifugal forces generated during operation. These inertial forces can significantly degrade shaft performance and structural integrity. To address this issue, the present work formulates an analytical approach based on the exact solution of the equivalent frequency equation, enabling the determination of the optimal TMD parameters in closed form. Obtaining analytical expressions for these parameters is crucial, as it allows designers to configure an optimal TMD directly from the initial physical characteristics of the turbine shaft, without relying on computationally expensive numerical optimization. Numerical simulations are conducted to validate the proposed method, demonstrating that the analytically optimized TMD can effectively eliminate torsional oscillations in steam turbine shafts.

Abstract The thermosphere is influenced by both solar and geomagnetic forcing from above and atmospheric waves from below, resulting in complex and variable dynamics. Neutral winds are key parameters describing these dynamics and their coupling with the ionosphere. In this study, nighttime thermospheric neutral winds over the low‐latitude Asian sector are investigated using ground‐based observations from Sanya (18.34°N, 109.62°E) and Lijiang (26.85°N, 100.22°E). Despite being less than 10° apart in latitude, the results reveal distinct latitude‐dependent meridional wind structures, with a pronounced double‐trough pattern at Sanya and a single‐trough structure at Lijiang. The nighttime zonal wind remains predominantly eastward throughout the year at Lijiang. Compared with observations, the empirical Horizontal Wind Model captures the general seasonal and local‐time variations but with systematic amplitude errors of 20–40 m/s. In contrast, the physics‐based Thermosphere–Ionosphere–Electrodynamics General Circulation Model fails to capture key nighttime structures, with the wind‐speed biases reaching over 50 m/s at Lijiang. Additionally, both equatorward and westward wind enhancements of ∼100 m/s were observed during the March 2024 storm. The disturbed equatorward wind is primarily driven by pressure gradient force, while the westward deflection is dominated by both Coriolis and pressure gradient forces. These results emphasize the importance of regional measurements for improving thermospheric wind modeling at low latitudes.

Abstract The dispersal of meltwater discharged from the Laurentian Channel (LC) is investigated from numerical experiments with an eddy-resolving model representing the western North Atlantic during the last ice age. Meltwater dispersal is simulated over a full summer, when glacial ablation rates were presumably the highest. In our experiments, meltwater forms a buoyant plume, which flows to the southwest along the continental slope owing to the Coriolis force. Four mechanisms of offshore export are identified. 1) Meltwater is carried seaward by Ekman currents driven by upwelling-favorable winds along the slope. 2) Part of it is entrained away from the slope by meander crests and warm-core rings of the Gulf Stream (GS) between the LC and Cape Hatteras. 3) The other part is generally diverted offshore by the GS near Cape Hatteras, where the GS leaves the slope. 4) Meltwater can be trapped in a GS meander trough that pinches off and produces a cold-core ring, leading to its penetration into the subtropical gyre. In turn, the buoyant plume has relatively small but noticeable effects on the GS. In the western, weakly meandering segment of the GS, the vertical shear in horizontal velocity is generally reduced due to the presence of melt (light) water along the inshore flank of the GS. Our results are discussed in light of (i) a two-layer theory of a surface density front subjected to background flow and wind stress and (ii) sediment records from the Laurentian Fan and the Sargasso Sea.

Purpose This study aims to investigate magnetohydrodynamic bioconvection induced by gyrotactic microorganisms in nanofluid flow over a rotating frame. Adding gyrotactic microorganisms to nanoparticles improves heat transfer in systems like microbial fuel cells, bacteria-powered micromixers, microfluidic devices, enzyme biosensors and chip-based microsystems. Design/methodology/approach The Buongiorno nanofluid model is used to incorporate Brownian motion and thermophoresis. The classical Fourier and Fick laws are generalized using the Cattaneo–Christov heat and mass flux theory to incorporate thermal and solutal relaxation phenomena. The governing partial differential equations are reduced to ordinary differential equations by using similarity transformations. The Keller–Box method has been used to solve these equations. The system is first converted into first-order form, then discretized with central differences and linearized using Newton’s method. A block tridiagonal matrix algorithm is used to obtain the numerical solution. This implicit scheme is stable, accurate and efficient. The numerical solutions are used to train an artificial neural network model with the Levenberg–Marquardt algorithm. Findings The results show that Coriolis and Lorentz forces reduce the velocity field, while thermal relaxation suppresses energy transport. Skin friction coefficient decays as the rotation and magnetic parameter values are increased. The model achieves high accuracy, with absolute errors between 10−4 and 10−5. Originality/value The proposed hybrid numerical–machine learning framework provides an accurate and computationally efficient approach for analyzing complex bioconvective nanofluid systems.

Predictive control of Wind–Hydrogen coupled systems integrating secondary decomposition and PSO-AWOA

This study applies classical fluid-structure interaction (FSI) principles to analyze the lateral deflection and natural frequency of slurry discharge pipelines in slurry shield machines. By idealizing the pipeline as an infinitely long cylinder supported by equally spaced rigid rings and adopting the Euler-Bernoulli beam theory and classical fluid-structure interaction principles, the control differential equation considering the interaction between the pipeline and the flowing slurry was adapted for the tunneling environment. This model incorporates the dynamic coupling between symmetrical and asymmetrical vibration modes driven by slurry flow velocity and Coriolis force. Through analytical solutions and numerical methods, the natural frequencies and mode shapes were determined. The results show that the slurry flow will reduce the natural frequencies and may lead to system instability at high flow rates. The accuracy of the model was verified by using the measured data from the site of the South-to-North Water Diversion Project in Beijing, China, spanning four different geological strata. The relative error ranged from 1.58 to 6.29%. The results highlight the dominance of low-order modes and demonstrate that the true engineering value lies in predicting how geological conditions and slurry impurities significantly influence the pipeline's dynamic behavior, providing guiding suggestions for the engineering design and vibration control of similar systems.

Abstract Accurate prediction of heavy precipitation over the Sichuan Basin (SCB) remains challenging due to the complexity of the surrounding mountains and their interactions with environmental airflow. Identifying key error sources in numerical weather prediction is therefore critical. This study investigates an orographic heavy rainfall event over the SCB that was largely missed by operational forecasting systems. Using multisource observations and reanalysis, we show that underestimation of precipitation is closely associated with insufficient low‐level convergence resulting from underestimated low‐level winds. A series of nudging‐based sensitivity experiments were conducted to assess the impacts of winds, temperature, and humidity on precipitation forecasts. Results indicate that the wind field exerts the dominant influence: wind nudging improves both wind and rainfall simulations, increasing SCB rainfall by nearly fourfold. Momentum analysis reveals that local variations in easterly winds are mainly governed by the Coriolis force acting on the ageostrophic winds, while northerly wind variations are determined by both the Coriolis force acting on the ageostrophic winds and frictional effects. Further regional wind nudging experiments demonstrate that the precipitation peak simulated by northeasterly wind nudging is delayed by nearly five hours, whereas easterly wind nudging captures the diurnal cycle of precipitation more accurately. These findings suggest that accurate prediction of the fine‐scale wind‐field structure is essential for improving forecasts of nocturnal heavy rainfall in the SCB.

In this paper, our aim is to investigate the effect of gravity modulation on thermal convection in a rotating horizontal porous medium with vertical heterogeneity. A machine learning technique is employed to numerically compute and predict the heat transfer rate under constant, linear, quadratic, and exponential heterogeneity models. Both linear and weakly nonlinear stability analyses are conducted to determine the onset of convection under the combined influence of vertical heterogeneity, Coriolis force, and gravity modulation. The critical Darcy–Rayleigh number is obtained using the Galerkin method, revealing that rotation and vertical heterogeneity significantly affect the stability thresholds. Furthermore, a feedforward artificial neural network (ANN) approach is developed to predict the Nusselt number, enabling a data-driven assessment of nonlinear heat transport across varying physical parameters. The ANN is trained and validated using numerical data derived from the weakly nonlinear analysis, demonstrating high prediction accuracy and strong generalizability. The key novel findings are as follows: (1) the Taylor number exhibits a stabilizing effect on the system, promoting stationary convection and (2) gravity modulation suppresses convection at higher modulation frequencies while enhancing heat transfer at lower frequencies. This hybrid analytical and ANN approach provides a robust framework for analyzing complex convective phenomena in a porous medium.

Abstract In this study, an analytical model for tropical cyclone (TC) outer-size expansion on the sphere is derived. The model builds upon a recently published model on the f plane by adding the fundamental dynamical component associated with latitudinal variations in the Coriolis parameter β that is known to limit TC expansion. The limiting process is identified to be the Coriolis acceleration due to the radial (ventilation) flow of β gyres, whose effects are captured semiempirically in the theory. Equilibrium size is predicted to be very weakly dependent on latitude and sea surface temperature, in stark contrast to the f -plane model. The theory with β successfully predicts both the characteristic size of TCs ( r 8 ∼ 500 km) and the very weak dependence of observed size with latitude found in the real tropics. The theory provides clear physical insight: In the tropics, a TC would expand toward the much larger size f -plane equilibrium scale ( f −1 ), but the Rossby wave effects of β strongly limit expansion thereby shrinking the equilibrium size on the sphere. Model predictions of the full size evolution compare reasonably well with two three-dimensional idealized β -plane TC simulations. Overall, results suggest that the theory captures key dynamics governing TC size in idealized and simplified settings and provides a theoretical foundation for understanding and potentially modeling aspects of TC size evolution and its variability across climate states. Significance Statement The purpose of this study is to build a physics-based predictive analytical model for tropical cyclone (TC) size expansion applicable on the sphere. This is important because a success of such a model would demonstrate the correctness of the present physical understanding of TC size dynamics, which directly affects TC hazards. Our results suggest that the condensational-heating-induced axisymmetric secondary circulation, surface friction, and the dynamical effect induced by the spherical geometry of Earth are three main elements governing TC size evolution.

Well–posedness and wave breaking of solutions for the Degasperis–Procesi equation including Coriolis effects

This paper investigates the intelligent companion flight control problem for mobile platforms (UGVs) and unmanned aerial vehicles (UAVs) under highly dynamic conditions. To address the Coriolis, Euler, and centrifugal fictitious forces introduced by a non-inertial reference frame and rapidly varying disturbances, an integrated approach of "non-inertial relative dynamics modeling + parameter preview estimation based on the Unscented Kalman Filter (UKF) + Continuous Gain Scheduling (CGS) MPC" is proposed. First, a complete and reproducible set of relative kinematics and dynamics under platform-fixed connections is presented, unifying gravity and thrust modeling. Subsequently, a unified UKF for platform angular velocity/angular acceleration and apparent acceleration is constructed, with its output fed into the MPC as time-varying parameters and tightening radii. Finally, a continuously varying weight scheduling law dependent on non-inertia intensity and uncertainty is proposed, balancing tracking accuracy and robustness. Simulation results indicate that, compared to fixed-weight MPC and simplified models that ignore fictitious forces, the proposed method significantly reduces peak errors and constraint violations under high-maneuvering and strong-noise conditions while maintaining control smoothness and real-time performance.

An analysis of a dataset originally constructed to provide a boundary condition for oceanographic modeling reveals widening of the tropics. On the poleward side of the edges of the atmospheric Hadley cells, the surface air wind veers eastward while on the equatorial side it veers westward because of the Coriolis force, thereby making the latitude where the zonal mean zonal wind in the surface air is zero a robust indicator of the Hadley cell edges. We have detected a trend in the latitudes of those wind nulls over the world's oceans in the Cross-Calibrated Multi-Platform (CCMP) surface air wind dataset and found that the tropics have widened by [Formula: see text] from 1995 through 2024, mostly in the northern hemisphere and mostly in autumn and winter. The CCMP dataset is particularly well suited to detecting widening of the tropics because of the simple physics of the proxy and its dense, global, and continuous sampling. Climate models reproduce the widening well in the southern hemisphere but not as significantly in the north, with repercussions for future desertification, especially in North America.

This study investigates the linear stability of the Rayleigh–Taylor instability in viscous fluids, elastic solids, and viscoelastic media (Maxwell fluids and Kelvin–Voigt solids) subject to rotation with the axis perpendicular to gravity. By establishing a unified dispersion relation, we theoretically demonstrate that rotation serves as a universal stabilizing mechanism across all considered rheological models, fundamentally altering the instability from a purely growing mode to an oscillatory traveling-wave mode. In viscous fluids, the Coriolis force monotonically suppresses the peak growth rate and shifts the dominant instability toward shorter wavelengths, although the dynamics remain governed by viscous mechanisms. In elastic solids, rotation compresses the unstable wavenumber bandwidth and reduces the cutoff wavenumber; notably, a critical rotation rate is identified beyond which the instability is completely suppressed. In viscoelastic media, the coupling between rotation and material relaxation yields complex behaviors. For Maxwell fluids, stress relaxation exhibits a regime-dependent dual role at fixed wavenumbers but consistently destabilizes the most unstable mode. Conversely, in Kelvin–Voigt solids, viscosity acts as a stabilizing factor under weak rotation but becomes destabilizing under strong rotation by damping the Coriolis-induced oscillations. Furthermore, the comparative analysis reveals that the characteristic modal transitions in both viscoelastic models originate from the competition between elastic restoring forces and viscous dissipation.