Transport Dynamics Research Articles

Macrotransport of active particles in periodic channels and fields: Rectification and dispersion.

Transport and dispersion of active particles in structured environments, such as corrugated channels and porous media, are important for the understanding of both natural and engineered active systems. Owing to their continuous self-propulsion, active particles exhibit rectified transport under spatially asymmetric confinement. While progress has been made in experiments and particle-based simulations, a theoretical understanding of the effective long-time transport dynamics in spatially periodic geometries remains less developed. In this paper, we apply generalized Taylor dispersion theory to analyze the long-time effective transport dynamics of active Brownian particles (ABPs) in periodic channels and fields. We show that the long-time transport behavior is governed by an effective advection-diffusion equation. The derived macrotransport equations allow us to characterize the average drift and effective dispersion coefficient. For the case of ABPs subject to a no-flux boundary condition at the channel wall, we show that regardless of activity, the average drift is given by the net diffusive flux along the channel. For ABPs, their activity is the driving mechanism that sustains a density gradient, which ultimately leads to rectified motion along the channel. Our continuum theory is validated against direct Brownian dynamics simulations of the Langevin equations governing the motion of each ABP.

Capturing the attenuating influence of a Three Gorges Dam on downstream sediment loads using artificial neural networks

ABSTRACT River sediment dynamics have been significantly altered by dam constructions, with the Three Gorges Dam (TGD) on the Yangtze River being a prominent example. This study aims to quantitatively assess the attenuating impact of TGD operations on downstream sediment discharge using artificial neural network (ANN) models. Seven ANN models were developed for stations along the middle and lower Yangtze River, trained on measured water and sediment data. The models effectively captured the relationships between upstream inputs and downstream outputs. Results revealed that variations in sediment discharge at each station were predominantly influenced by changes in sediment input from its immediate upstream section, rather than by changes in water discharge. This suggests that the TGD's impact on downstream sediment transport was primarily due to its sediment trapping efficiency, rather than alterations in the hydrological regime. The influence diminished gradually farther downstream, attributed to tributary contributions and sediment transport dynamics. ANNs, adept at handling input uncertainties, underscore the importance of boundary conditions; the integration of data-driven and physics-based models illuminates sediment dynamics in regulated rivers. This approach provides insight into dam management implications and sediment transport processes.

The Construction and Mechanism Study of High-Speed Carrier Transport Channel in Gallium Arsenide Homojunction Toward High-Performance Photoelectrochemical Photodetector.

The energy band structure and surface/interface properties are prerequisite for not only preserving the intrinsic material quality but also manipulating carrier transport behavior for photoelectrochemical (PEC) photodetection. How to precisely design/regulate the band structure and surface/interface properties of semiconductor materials is the key to improving the performance of PEC photodetection. Herein, the quintuple heterotypic homojunction (QH) GaAs film is fabricated with a gradient energy band via plasma-assisted molecular beam epitaxy for constructing a high-speed carrier transport channel in PEC photodetection, which can efficiently drive the separation and transport of photogenerated electron-hole pairs. The designed QH-GaAs-based PEC photodetector exhibits excellent performances, compared with bare i-GaAs, delivering an ultrashort rise/decay times of only 1.1/1.1ms and a high responsivity of 20.4mAW-1 at 0V under 850nm illumination. Strikingly, an ultrahigh detectivity with 1.46×1012 Jones is achieved. More importantly, the QH-GaAs device can stably operate underwater seawater environment. This study provides a novel strategy for designing and fabricating multiple heterotypic homojunction with gradient energy band to boost charge transport dynamics for PEC fields.

Ground-Based MAX-DOAS Observations for Spatiotemporal Distribution and Transport of Atmospheric Water Vapor in Beijing

Understanding the spatiotemporal distribution and transport of atmospheric water vapor in urban areas is crucial for improving mesoscale models and weather and climate predictions. This study employs Multi-Axis Differential Optical Absorption Spectroscopy to monitor the dynamic distribution and transport flux of water vapor in Beijing within the tropospheric layer (0–4 km) from June 2021 to May 2022. The seasonal peaks in precipitable water occur in August, reaching 39.13 mm, with noticeable declines in winter. Water vapor was primarily distributed below 2.0 km and generally decreases with increasing altitude. The largest water vapor transport flux occurs in the southeast–northwest direction, whereas the smallest occurs in the southwest–northeast direction. The maximum flux, observed at about 1.2 km in the southeast–northwest direction during summer, reaches 31.77 g/m2/s (transported towards the southeast). Before continuous rainfall events, water vapor transport, originating primarily from the southeast, concentrates below 1 km. Backward trajectory analysis indicates that during the rainy months, there was a higher proportion of southeasterly winds, especially at lower altitudes, with air masses from the southeast at 500 m accounting for 69.11%. This study shows the capabilities of MAX-DOAS for remote sensing water vapor and offers data support for enhancing weather forecasting and understanding urban climatic dynamics.

Satellite derived air pollution climatology over India and its neighboring regions: Spatio-temporal trends and insights

This study examines the spatial and temporal variations of key air pollutants, including Nitrogen Dioxide (NO₂), Carbon Monoxide (CO), Tropospheric Ozone (O₃), Sulfur Dioxide (SO₂), Aerosol Optical Depth (AOD), and Formaldehyde (HCHO) over India and neighboring regions, using satellite data from 2005 to 2022. Peak NO₂ (∼11–13 × 101⁵molecules/cm2) occurs in pre-monsoon and winter, mainly over urban centers, thermal plants, and crop-burning areas, emphasizing anthropogenic emissions. High CO levels (2.0–2.3 × 101⁸molecules/cm2) during summer dominate in Indo-Gangetic Plains (IGP), Eastern India, and Northeastern region, linked to the incomplete combustion of organic matter (e.g., natural forest fires and biofuel-based household cooking). Stable CO trends reflect effective government policies promoting cleaner fuels. Tropospheric O₃ shows a spatial gradient, with higher values in northern and coastal regions influenced by sunlight, humidity, and precursor emissions. Seasonal peaks in summer are governed by solar intensity, while the December peak over the northern region is likely due to dynamical transport from O₃-rich areas. SO₂ hotspots in IGP, central and eastern India, especially during winter (∼1.3–1.9 × 101⁵molecules/cm2), are attributed to local anthropogenic emissions and fossil fuel combustion such as coal. Long-term trends reveal rising SO₂ levels. AOD hotspots occur over IGP, Central and Southern India, with particularly high values during the pre-monsoon (0.5–0.6) and winter seasons. HCHO shows hotspots in the IGP, west coast, eastern, and northeastern regions, peaking in summer (7.5–8.5 × 101⁵molecules/cm2) due to biogenic VOC emissions. This study underscores the need for integrated policies to mitigate emissions, improve air quality, and protect public health.

Confined mass transport in two-dimensional capillary

Abstract Over the past decade, nanofluidics has undergone significant expansion, propelled by advances in crafting artificial channels at nanometric and sub-nanometric scales with diverse geometries. Central to this domain, two-dimensional capillaries have risen as a pivotal research platform, marked by their angstrom-level precision, unparalleled wall surface smoothness, and clearly defined surface charge states. Their advent has profoundly deepened our understanding of mass transport dynamics, spanning gases, water molecules, and ions, shedding light on the complex interactions among various influencing factors and revealing a range of previously undiscovered physical phenomena. This review delves into the development of 2D capillaries, the principal fluid transport phenomena observed within, and the critical elements that affect these processes. We also touch on a fascinating discovery - the quantum liquid friction seen in water moving over carbon surfaces. In anticipation of future explorations in nanofluidics, we envision a trajectory aimed at emulating the efficiency levels of biological protein channels, setting the stage for a new era of scientific inquiry and technological innovation.

An In Vitro Platform for Pharmacokinetic Quantification and Optimization of Cerebrospinal Fluid Filtration and Drug Circulation

Abstract Background: Modification of cerebrospinal fluid (CSF) transport dynamics is an expanding method for treating central nervous system injury and diseases. One application of this route is to modify the distribution of solutes in the CSF, however few tools currently exist for this purpose. The present study describes the use of a subject-specific in-vitro CSF phantom to perform a parametric evaluation of the Neurapheresis? CSF Management System (NP) for both CSF filtration and intrathecal drug circulation. Methods: An in-vitro CSF phantom was constructed which included realistic anatomy for the complete subarachnoid space. This platform was configured to test multiple parametric modifications of a dual-lumen catheter and filtration system. Calibrated mapping of tracer distribution and area under the curve (AUC) measurements were used to compare filtration and intrathecal-circulation schemes using the NP device versus the clinical standards of care. Results: The NP device showed potential advantages over lumbar drain (LD) for clearance of simulated subarachnoid hemorrhage, especially in the spinal canal. Use of the NP device in combination with simulated intracerebroventricular drug infusion (ICV) resulted in an increased extent and uniformity of tracer spread compared to ICV alone. Conclusion: NP improved clearance of simulated subarachnoid hemorrhage compared to LD and increased uniformity of tracer concentration via simulated ICV, providing support for NP use in these scenarios. The in-vitro CSF phantom system presented here quantitatively described the effects of parametric boundary modification on solute distribution in the intrathecal space.

The role of kinesin superfamily proteins in hepatocellular carcinoma.

The most prevalent form of primary liver cancer, hepatocellular carcinoma (HCC) poses a significant global health challenge due to its limited therapeutic options. Researchers are currently focused on the complex molecular landscape that governs the initiation and progression of HCC in order to identify new avenues for diagnosis, prognosis, and treatment. In the context of HCC, the Kinesin Superfamily Proteins (KIFs) have become critical regulators of cellular processes, prompting a growing interest in their function among the diverse array of molecular actors implicated in cancer. The KIFs, a family of microtubule-based molecular motors, are renowned for their essential roles in the dynamics of mitotic spindles and intracellular transport. Beyond their well-established functions in normal cellular physiology, emerging evidence indicates that dysregulation of KIFs significantly contributes to the pathogenesis of HCC. Novel therapeutic targets and diagnostic markers are revealed through the unique opportunity to comprehend the complex interplay between KIFs and the molecular events that drive HCC.

Digital Twin Reveals the Impact of Carbon Binder Domain Distribution on Performance of Lithium‐Ion Battery Cathodes

The rising demand for high‐performance lithium‐ion batteries (LIBs) emphasizes the need for precise electrode design. The carbon binder domain (CBD) within electrodes, crucial for electron transport and structural integrity, can impede lithium‐ion transport and reduce electrochemically active sites. This study leverages digital twin technology to investigate the impact of CBD distribution along the electrode thickness on LIB cathode performance. Virtual LIB cathodes with varying CBD configurations are generated, and their performance using 3D heterogeneous electrochemical modeling is evaluated. The results reveal that a steep CBD gradient significantly diminishes charge capacity compared to a mild gradient, particularly at higher current rates. This reduction is attributed to an increased tortuosity factor and an uneven distribution of electrochemical activity, which adversely affect mass transport and electrochemical reaction dynamics. These effects are more pronounced at lower porosities and higher loading levels. These findings highlight that optimizing CBD distribution is critical for advancing electrode design and enhancing LIB cathode performance.

Effect of Plow Pan on the Redistribution Dynamics of Water and Nutrient Transport in Soils

Plow pans are an essential part of the agricultural soil structure. By adjusting the soil bulk density and plow pan height, the water and nutrient transport are dynamically redistributed. Plow pans play a crucial role in promoting crop growth, increasing yields, and supporting sustainable land management. In this study, a column experiment was conducted to investigate the effects of plow pan height (10 cm and 15 cm) and bulk density (1.2, 1.4, and 1.6 g cm⁻3) on soil nutrient and water leaching under high-volume (HV) and low-volume (LV) fertilizer applications. The results reveal that the leachate volume decreased by 61.9% at a plow pan height of 10 cm and by 96.2% at a plow pan height of 15 cm when the bulk density was increased from 1.2 to 1.4 g cm⁻3 under HV conditions. There was no leachate when the plow pan bulk density was 1.6 g cm−3. The reserved concentration of alkali-hydrolyzable N in the plow pan soils was the highest when the plow pan had a bulk density of 1.4 g cm−3 and a height of 15 cm. However, when the plow pan height was 15 cm, the available P content in the plow pan soils decreased by 27.0% and 21.0% at bulk densities of 1.4 g cm⁻3 and 1.6 g cm⁻3, respectively, when compared with 1.2 g cm⁻3. Furthermore, the available P concentrations in the plow pan and subsoil layers decreased with an increase in the plow pan height. The available K concentrations in the topsoil decreased by 26.8% and 24.0% when the plow pan bulk density was increased from 1.2 to 1.4 g cm−3 at heights of 10 and 15 cm, respectively. Thus, the optimal plow pan height and bulk density are closely related to the types of soil nutrients. However, it is clear that excessively high bulk densities (e.g., 1.6 g cm−3) negatively impact soil properties. For different nutrient requirements, a bulk density of 1.2 or 1.4 g cm−3 can be chosen, with each providing suitable options based on the specific nutrient needs. This research offers practical insights into changes in nutrient adsorption and fixation in agricultural production associated with alterations in plow pan bulk density.

Computational analysis of heat transport dynamics in viscous dissipative blood flow within a cylindrical shape artery through influence of autocatalysis and magnetic field orentation

Nanofluids consisting of tetra nanoparticles are crucial in bio medical sciences due to their improved thermal transport characteristics. The advanced tailored properties of tera nanoparticles make them useful in several medical interventions, such as hyperthermia treatment, where the targeted tissue can be heated more efficiently, leading to better treatment outcomes. The current study investigates the heat transfer enhancement in a hemodynamic system using tetra nanoparticles. The physical configuration of the blood flow is assumed with in a permeable cylindrical shape stenosed artery. The model incorporates the Carreau model with inclusion of diverse factors such as, exponential space-based heat source, viscous dissipation, infinite shear rate and permeability of surface. Additionally, impact of chemical reaction (autocatalysis) and magnetohydrodynamic (MHD) consequences is also integrated into the system. The framed partial differential equations (PDEs) generated by physical problem are converted into new dimensionless form of an ordinary differential system (ODEs). Bvp4c MATLAB procedure is fetched for numerical investigation. It is observed that, velocity profile of the fluid is reduced due to intensification in inclined magnetic effect, whereas autocatalysis effect promotes the concentration of nanoparticles in blood flow mixture, which increases the temperature field of fluid. Furthermore, augmentation in the values of Wassenberg number increased the elasticity in blood which enables it to deform and stretch more readily in reaction to alterations in flow conditions and hence reduction is seen in overall blood flow rate. The results revealed the significance of these integrated factors for accurate modelling of blood flow passing through a stenosed artery, which is crucial in medical interventions.

EEG microstate transition cost correlates with task demands.

The ability to solve complex tasks relies on the adaptive changes occurring in the spatio-temporal organization of brain activity under different conditions. Altered flexibility in these dynamics can lead to impaired cognitive performance, manifesting for instance as difficulties in attention regulation, distraction inhibition, and behavioral adaptation. Such impairments result in decreased efficiency and increased effort in accomplishing goal-directed tasks. Therefore, developing quantitative measures that can directly assess the effort involved in these transitions using neural data is of paramount importance. In this study, we propose a framework to associate cognitive effort during the performance of tasks with electroencephalography (EEG) activation patterns. The methodology relies on the identification of discrete dynamical states (EEG microstates) and optimal transport theory. To validate the effectiveness of this framework, we apply it to a dataset collected during a spatial version of the Stroop task, a cognitive test in which participants respond to one aspect of a stimulus while ignoring another, often conflicting, aspect. The Stroop task is a cognitive test where participants must respond to one aspect of a stimulus while ignoring another, often conflicting, aspect. Our findings reveal an increased cost linked to cognitive effort, thus confirming the framework's effectiveness in capturing and quantifying cognitive transitions. By utilizing a fully data-driven method, this research opens up fresh perspectives for physiologically describing cognitive effort within the brain.

Fire and smoke transport dynamics in a dead-end tunnel under heavy rainfall

Fire is one of the most common major accidents during tunnel construction and operation. This work conducted scale-model experiments to investigate the pool burning progress and flame characteristics in a dead-end tunnel with one end closed and the other open under heavy rainfall. The results show that, compared to opening both ends, the global burning time of fires is significantly decreased, and the quasi-stable burning phase is advanced under the combined effects of the closed end and heavy rainfall. The reason is that the increase in ceiling temperature, resulting from the accumulation of hot smoke, leads to an increase in radiative feedback of the fuel from the environment and an acceleration in the pool's burning rate. A coefficient (denoted by γ) is defined to evaluate the increase in the burning rate resulting from the dead-end. The enhancement ratio is found to be related to rainfall intensity, raindrop size, and pool size, and a correlation has been established based on the experimental results. The fire has an increased flame height and a reduced tilt angle under the impact of the dead-end. The changes in flame geometry parameters are mainly influenced by thermal buoyancy and the restriction of the dead-end. Prediction formulas for flame height and tilt angle under the combined effects of the dead-end and heavy rainfall have been proposed based on theoretical analysis. Under these combined effects, the tunnel space becomes eroded by dirty air.

Structural insights into human zinc transporter ZnT1 mediated Zn2+ efflux.

Zinc transporter 1 (ZnT1), the principal carrier of cytosolic zinc to the extracellular milieu, is important for cellular zinc homeostasis and resistance to zinc toxicity. Despite recent advancements in the structural characterization of various zinc transporters, the mechanism by which ZnTs-mediated Zn2+ translocation is coupled with H+ or Ca2+ remains unclear. To visualize the transport dynamics, we determined the cryo-electron microscopy (cryo-EM) structures of human ZnT1 at different functional states. ZnT1 dimerizes via extensive interactions between the cytosolic (CTD), the transmembrane (TMD), and the unique cysteine-rich extracellular (ECD) domains. At pH 7.5, both protomers adopt an outward-facing (OF) conformation, with Zn2+ ions coordinated at the TMD binding site by distinct compositions. At pH 6.0, ZnT1 complexed with Zn2+ exhibits various conformations [OF/OF, OF/IF (inward-facing), and IF/IF]. These conformational snapshots, together with biochemical investigation and molecular dynamic simulations, shed light on the mechanism underlying the proton-dependence of ZnT1 transport.

Quantum tunneling high-speed nano-excitonic modulator

High-speed electrical control of nano-optoelectronic properties in two-dimensional semiconductors is a building block for the development of excitonic devices, allowing the seamless integration of nano-electronics and -photonics. Here, we demonstrate a high-speed electrical modulation of nanoscale exciton behaviors in a MoS2 monolayer at room temperature through a quantum tunneling nanoplasmonic cavity. Electrical control of tunneling electrons between Au tip and MoS2 monolayer facilitates the dynamic switching of neutral exciton- and trion-dominant states at the nanoscale. Through tip-induced spectroscopic analysis, we locally characterize the modified recombination dynamics, resulting in a significant change in the photoluminescence quantum yield. Furthermore, by obtaining a time-resolved second-order correlation function, we demonstrate that this electrically-driven nanoscale exciton-trion interconversion achieves a modulation frequency of up to 8 MHz. Our approach provides a versatile platform for dynamically manipulating nano-optoelectronic properties in the form of transformable excitonic quasiparticles, including valley polarization, recombination, and transport dynamics.

Influence of crystal dimension on performance of spherical crystal self-emission imager

Abstract The spherical crystal imaging system, noted for its high energy spectral resolution (monochromaticity) and spatial resolution, is extensively applied in high energy density physics and inertial confinement fusion research. This system supports studies on fast electron transport, hydrodynamic instabilities, and implosion dynamics. The X-ray source, produced through laser-plasma interaction, emits a limited number of photons within short time scales, resulting in predominantly photon-starved images. Through ray-tracing simulations, we investigated the impact of varying crystal dimensions on the performance of a spherical crystal self-emission imager. We observed that increasing the crystal dimension leads to higher imaging efficiency but at the expense of monochromaticity, causing broader spectral acceptance and reduced spatial resolution. Furthermore, we presented a theoretical model to estimate the spatial resolution of the imaging system within a specific energy spectrum range, detailing the expressions for the effective size of the crystal. The spatial resolution derived from the model closely matches the numerical simulations.

Hierarchical Equations of Motion for Quantum Chemical Dynamics: Recent Methodology Developments and Applications.

ConspectusQuantum effects are critical to understanding many chemical dynamical processes in condensed phases, where interactions between molecules and their environment are usually strong and non-Markovian. In this Account, we review recent progress from our group in development and application of the hierarchical equations of motion (HEOM) method, highlighting its ability to address some challenging problems in quantum chemical dynamics.In the HEOM method, the bath degrees of freedom are represented using effective modes from exponential decomposition of the bath correlation function. Complex spectral densities and low temperature simulations often require a larger number of modes, making the simulations very expensive. Recent advances, such as the barycentric spectral decomposition (BSD) technique, can significantly reduce the number of effective modes, allowing to handle complex spectral densities and enabling simulations at very low temperatures, including near-zero temperature dynamics.Another key improvement in the computational efficiency is the use of tensor network methods like matrix product states and hierarchical tensor networks. These techniques allow for efficient HEOM propagation with thousands of effective modes, crucial for simulating large molecular systems interacting with multiple baths. This combination enables simulations of excitation energy transfer (EET) in systems like the Fenna-Matthews-Olson (FMO) complex and even larger systems with experimentally determined spectral densities.The versatility of the HEOM method is demonstrated through applications to a wide range of chemical dynamics problems. Simulations of EET and related ultrafast spectroscopy are first briefly covered. Applications of the HEOM to quantum tunneling effects in proton transfer reactions are then presented. Early works have studied the non-Kramers dependence of the rate constant as a function of bath friction due to deep tunneling and revealed vibrationally nonadiabatic dynamics within the so-called nontraditional view of proton transfer reactions. A recent work on the large kinetic isotope effects in soybean lipoxygenase also indicated that many quantum correction approximations to classical transition-state theory may fall short in describing deep tunneling effects.Charge transport and separation dynamics in organic semiconductors are another area where the HEOM method has been instrumental. We first demonstrate that the HEOM provides a unified description of both band-like and thermally assisted charge carrier transport in organic materials. The effect of non-nearest neighbor transitions is then investigated by combining generalized master equations with exact memory kernels. The HEOM method also enables simulation of charge separation in organic photovoltaics (OPVs) and reveals how factors such as external electric fields, entropy, and charge delocalization influence the charge separation barrier and dynamics.Moreover, HEOM has been applied to investigate hydrogen atom scattering on the Au(111) surface and vibrational energy relaxation at molecule-metal interfaces. These studies provide deeper insights into how electron-hole pair excitations and temporary charge transfer states influence the nuclear motion, offering a new framework for simulating nonadiabatic dynamics on metal surfaces.In summary, the HEOM method has developed into a robust tool for simulating quantum effects in condensed phases. Future developments in algorithm efficiency and computational power will likely expand its applicability to even more complex systems.

Phase Distribution Dictates Charge Transfer and Transport Dynamics in Layered Quasi-2D Perovskite.

Strategic manipulation of spatiotemporal evolution of charge carriers is critical for optimizing performance of quasi-two-dimensional (2D) perovskite-based optoelectronic devices. Nonetheless, the inhomogeneous phase distribution and band alignment engender intricate energy landscapes, complicating internal charge and energy funneling processes. Herein, we integrate high spatiotemporal resolution transient absorption microscopy with multiple time-resolved spectroscopy and find that asynchronous electron and hole transfers rather than direct energy transfer govern the funneling mechanisms. Notably, the charge funneling pathways and transport behaviors can be modifiable by phase manipulation. The accumulation of small-n phases suppresses the electron funneling toward large-n phases and doubles the carrier diffusion rate from 0.085 to 0.20 cm2/s, yielding a 1.5-fold enhancement in diffusion length. Phase order engineering is further corroborated for facilitating charge separation. Our investigation underscores the prospects of manipulating the phase distribution to control internal charge funneling and transport, thereby substantiating the theoretical foundations for optimizing optoelectronic devices.

Significance of magnetic field and Darcy–Forchheimer law on dynamics of non-Newtonian hybrid nanofluid flow over a spinning disc with Arrhenius activation energy and shape factor

Purpose The purpose of the study is to explore the three-dimensional heat and mass transport dynamics of the magneto-hydrodynamic non-Newtonian (Casson fluid) hybrid nanofluid flow comprised of − as nanoparticles suspended in base liquid water as it passes through a flexible spinning disc. The influence of a magnetic field, rotation parameter, porosity, Darcy−Forchheimer, Arrhenius’s activation energy, chemical reaction, Schmidt number and nanoparticle shape effects are substantial physical features of the investigation. Furthermore, the influence of hybrid nanofluid on Brownian motion and thermophoresis features has been represented using the Buongiorno model. The novelty of the work is intended to contribute to a better understanding of Casson non-Newtonian fluid boundary layer flow. Design/methodology/approach The governing mathematical equations that explain the flow and heat and mass transport phenomena for fluid domains include the Navier−Stokes equation, the thermal energy equation and the solutal concentration equations. The governing equations are expressed as partial differential equations, which are then converted into a suitable set of non-linear ordinary differential equations by using the necessary similarity variables. The ordinary differential equations are computed by combining the shooting operation with the three-stage Lobatto BVP4c technique. Findings Graphs and tables are used in the process of analysing the characteristics of velocity distributions, temperature profiles and solutal curves at varying values of the parameters, along with friction drag, heat transfer rate and Sherwood number. It has been revealed that the radial and axial velocities decrease when the Casson parameter value increases and that the rate of heat transmission is higher in hybrid nanofluids with nanoparticles in the shape of a blade. The increase in Brownian motion and thermophoresis parameters causes a rise in the temperature profile. Also, an increase in the activation energy parameter improves the solutal curve. The use of nanoparticles was shown to improve extrusion properties, the rotary heat process and biofuel generation. Originality/value All results are presented graphically and all physical quantities are computed and tabulated. The current results are compared to previous investigations and found to agree significantly with them.

Rotational Taylor dispersion in linear flows

The coupling between advection and diffusion in position space can often lead to enhanced mass transport compared with diffusion without flow. An important framework used to characterize the long-time diffusive transport in position space is the generalized Taylor dispersion theory. In contrast, the dynamics and transport in orientation space remains less developed. In this work we develop a rotational Taylor dispersion theory that characterizes the long-time orientational transport of a spheroidal particle in linear flows that is constrained to rotate in the velocity-gradient plane. Similar to Taylor dispersion in position space, the orientational distribution of axisymmetric particles in linear flows at long times satisfies an effective advection–diffusion equation in orientation space. Using this framework, we then calculate the long-time average angular velocity and dispersion coefficient for both simple shear and extensional flows. Analytic expressions for the transport coefficients are derived in several asymptotic limits including nearly spherical particles, weak flow and strong flow. Our analysis shows that at long times the effective rotational dispersion is enhanced in simple shear and suppressed in extensional flow. The asymptotic solutions agree with full numerical solutions of the derived macrotransport equations and results from Brownian dynamics simulations. Our results show that the interplay between flow-induced rotations and Brownian diffusion can fundamentally change the long-time transport dynamics.