Tracer Particles Research Articles

Multiple-Exposure PTV With Variable Time Steps

Recording multiple exposures of the tracer particles onto a single digital image has the potential to simplify the hardware needed for 3D PTV measurements. A sequence with equal time intervals leads to the well-known directional ambiguity problem. Instead, a sequence with irregular time-intervals (two or more) allows resolving the ambiguity. Two fundamental criteria are introduced that determine whether a set of particle samples corresponds to a physical trace for a given neighborhood: the kinematic similarity criterion imposes similarity (i.e. proportionality) between the length travelled by the particle and time elapsed. Additionally, the trace regularity criterion favors sets with minimum fluctuations of the velocity vector. A numerical algorithm, based on combinatorial analysis is presented, whereby all possible sets are scrutinized and the set of particles yielding the minimum disparity from the above criteria corresponds to the physical trace. The algorithm is demonstrated using 3D experimental data and results are benchmarked against the state-of-the-art time-resolved analysis Shakethe-Box (single-frame, single-exposure).

Particle Shadow Velocimetry And Its Potential Applications And Advantages Vis-à-Vis Particle Image Velocimetry

Particle image velocimetry (PIV) is an established standard velocimetry technique in experimental fluid mechanics that involves determining a fluid flow velocity field from the motion of tracer particles illuminated by a laser sheet. The necessity of laser illumination poses challenges in certain applications, and is a potential entry barrier due to its complexity and high cost. A laser-free alternative to PIV is particle shadow velocimetry (PSV), which uses images of the shadows cast by the particles on the camera sensor under back-illumination, instead of the Mie scattering signal produced by laser illumination. This study aims to compare various aspects of PSV such as depth of field, seeding density, type of illumination required, particle size, image filtering, cost effectiveness, and limitations with those of PIV. PSV and PIV measurements are conducted in the wake of a flow past a cylinder and in a boundary layer developing over a flat plate. It is found that PSV is capable of achieving equivalent accuracy to PIV and is a viable alternative to PIV in certain applications where light sheet illumination creates experimental challenges.

Exploring Electrohydrodynamic Flows Inside Leaky Dielectric Drops: A Laser Velocimetry Approach

A novel experimental methodology based on laser velocimetry for the investigation of electrohydrodynamic (EHD) flows inside a neutrally buoyant leaky dielectric drop of 2.25 mm of radius is proposed. Utilizing fluorescent particles, 2D and 3D Lagrangian Particle Tracking (LPT) measurements of the EHD flows inside an initially spherical drop under a constant electric field are reported. Two leaky dielectric fluids, namely Silicone and Castor oils, were used as either the drop or the medium phases, depending on the case investigated, thus covering oblate and prolate drops both with small and larger deformations. 2D measurements of the trajectories and velocities of the tracer particles in a Lagrangian referential enabled a direct comparison with the leaky dielectric model (LDM), a well-stablished theory covering drops with smaller deformations, showing a good agreement with our measurements. The symmetry inside a drop with increased deformation is investigated from an analysis of the mean 3D velocity field, whose measurements converge to the two-dimensional analysis at the plane of symmetry of the drop, suggesting symmetrical flow structures inside the drop.

Single-Frame Lagrangian Tracking Of 3-D Acoustic Streaming Flows Using Digital Defocusing Micro Particle Streak Velocimetry

In this study, a single-frame particle streak velocimetry technique is applied to the classic DDPIV(Digital Defocusing Particle Image Velocimetry) concept to achieve a single-frame 3-D Lagrangian tracking of particles in microscopic flows. The shortcoming of images suffering low signal to noise ratio due to pinholes can be avoided. With the streak resolving algorithm, it allows extended exposure time when streak images are taken, and the single-frame approach also eliminates the need for high-cost and complicated synchronization hardware for double-pulse frame-straddling light sources. For each long-exposure, color-coded images received from each pinhole equipped with red, green or blue color filters, the streak-resolving algorithm is applied first to find each streak on the separate color channel, followed by an one-time triplet-matching process to group the red, green and blue streak projections. From the streak triplets, 3-D reconstruction can be done on all the resolved points on the streak, and trajectory fitting can then be applied to resolve the tracer particle trajectories in the field of view with temporal history. This procedure was applied for visualizing a microscale 3-D acoustic streaming flow pattern induced by a longitudinal spine-shaped fin oscillating at 12kHz. The height of the channel is 1mm with the spine of 0.3mm height and a 30 。 tip angle. Resolved flow fields show that the particle streak images can be resolved with the same level of accuracy to the particle tracking method, while the throughput of velocity vectors can be significantly higher due to multiple velocity vectors can be resolved from each streak triplet. The methodology has the potential to be applied to various applications that can capture long-exposure images and possible to resolve higher-order information such as acceleration and forces applied on the particles or the flow.

Unbalanced Optimal Transport For Stochastic Particle Tracking

Non-invasive flow measurement techniques, such as particle tracking velocimetry, resolve 3D velocity fields by pairing tracer particle positions in successive time steps. These trajectories are crucial for evaluating physical quantities like vorticity, shear stress, pressure, and coherent structures. Traditional approaches deterministically reconstruct particle positions and extract particle tracks using tracking algorithms. However, reliable track estimation is challenging due to measurement noise caused by high particle density, particle image overlap, and falsely reconstructed 3D particle positions. To overcome this challenge, probabilistic approaches quantify the epistemic uncertainty in particle positions, typically using a Gaussian probability distribution. However, the standard deterministic tracking algorithms relying on nearest-neighbor search do not directly extend to the probabilistic setting. Moreover, such algorithms do not necessarily find globally consistent solutions robust to reconstruction errors. This paper aims to develop a globally consistent nearest-neighborhood algorithm that robustly extracts stochastic particle tracks from the reconstructed Gaussian particle distributions in all frames. Our tracking algorithm relies on the unbalanced optimal transport theory in the metric space of Gaussian measures. Specifically, we optimize a binary transport plan for efficiently moving the Gaussian distributions of reconstructed particle positions between time frames. We achieve this by computing the partial Wasserstein distance in the metric space of Gaussian measures. Our tracking algorithm is robust to position reconstruction errors since it automatically detects the number of particles that should be matched through hyperparameter optimization. Notably, our tracking algorithm also readily applies to the standard deterministic PTV case. Finally, we validate our method using an in vitro flow experiment using a 3D-printed cerebral aneurysm.

In-line PIV Using a Schlieren System

"The article describes recent tests and developments of PIV recording and evaluation techniques that take advantage of strong forward scattering of tracer particles by in-line recording set ups. By collimating the light of a low-power light source between a pair of schlieren mirrors the observation area is increased to more than 350 mm. The same setup allows for schlieren recording of density gradients. The in-line imaging arrangements have a relatively high background intensity level on which brighter particle images can be detected. Ideally this background is constant in time such that it can be removed through subtraction. The use of forward scattering has a significant influence on the required pulse energy of the light source used. Typically, sufficient illumination is achieved with about 1% of the pulse energy that would normally be used for a conventional orthogonal PIV arrangement employing a laser light sheet. "

Flow Measurements Above A DBD Plasma Actuator Array By Means Of Defocusing PTV

Lagrangian defocusing particle tracking velocimetry (DPTV) measurements are conducted in a thin, wall-parallel volume above a plasma actuator array that is applied to mimic the effect of wall oscillations by inducing alternating, wall-parallel forcing in opposite directions into the air above the actuator surface. The aim of the experiments is to capture the plasma-induced flow structures in otherwise quiescent air in order to increase the understanding of different actuation parameters. For this purpose, high-speed particle image velocimetry equipment with one camera is used in a DPTV setup, where the out-of-plane particle coordinate is obtained through the diameter of a defocused particle image. On this basis, an approach for continuous particle tracking in several consecutive frames is presented, allowing to derive three component, three dimensional velocity and acceleration data. Light reflections that occur on the adjacent actuator surface give raise to particular challenges concerning the measurement uncertainty estimation as well as the calibration procedure for the evaluation of the wall-normal coordinate of tracer particles. To overcome the latter, a calibration approach is presented for which solid particles are applied to the actuator surface and their particle image diameter is captured at different camera positions in a separate measurement. The estimation of in-plane and out-of-plane displacement measurement uncertainties is conducted following a newly-developed procedure where the deviation of particle displacements from a straight track is evaluated for measurements in quasi-quiescent air. The obtained results show the suitability of DPTV measurement technique for the practical application of the characterization of flow structures above a plasma actuator array. The measurement accuracy is found to be limited due to the available illumination, which depends on the used components. The measured flow fields together with optical and electrical measurement data allow for a further analysis of the present forcing strategy. Particularly, by recording phase-resolved, three-dimensional flow velocity and acceleration fields in the vicinity of the wall, the spatio-temporal occurrence and homogeneity of the near-wall forcing effects can be analyzed in future investigations.

Spatiotemporal Filter Velocimetry With Arbitrary-Shaped Measurement Region For Accurate Measurement In The Vicinity Of A Boundary

Viscous stress at a boundary or an interface is a source of drag acting on a body or a fluid particle and therefore its measurement is of great importance for understanding the motion of the body or the fluid particle. In this study, spatiotemporal filter velocimetry (SFV: Hosokawa & Tomiyama, 2012) is extended to arbitrary quadrilateral measurement areas fitted to an interface shape for accurate measurement of flow about a deformed drop, and it is applied to flows about single drops of glycerol-water solution falling in stagnant silicon oil under clean and contaminated conditions. Figure 1 shows the trajectories of tracer particles and the measured velocity distributions. No separation is observed for the spherical and ellipsoidal drops. On the other hand, the stagnant region is observed in the dimple region of the tail of the cap drop. These results clearly indicate that the flow about the deformed drop is successfully measured by SFV with arbitrary quadrilateral measurement areas. Figure 2 shows the trajectories of tracer particles and the measured velocity distributions of single ellipsoidal drops in clean and contaminated systems. Triton X-100 was used as the surfactant and its concentration C in the drop ranges from 0.0 to 0.1 mol/m3 . The drop tail becomes flat and then slightly dimpled shape, and the internal circulation becomes weak as C increases. The internal circulation remains even at the high surfactant concentration condition under which the internal circulation in single spherical drop is fully damped (Hosokawa et al., 2017). We also evaluate interfacial velocity, interfacial shear stresses, the Marangoni stress and surfactant concentration at the interface from measured velocity distributions in the vicinity of the interface. As a result, we confirmed that SFV enables us to measure velocity distribution about a single deformed drop and enables us to evaluate interfacial velocity, interfacial shear stresses, the Marangoni stress and surfactant concentration at the interface.

Wall Shear Stress Characteristics Of A Turbulent Boundary Layer Obtained With Multi-Aperture Defocusing Micro-PTV And High-Speed Stereo Profile-PIV

A multi-aperture 3d 3c micro PTV system is presented which relies on single window optical access for both high-speed tracer illumination and image recording. Similar to the “defocusing” concept described by C. Willert & Gharib (1992), the wall distance of individual particles is obtained from the size of projected particle image triplets formed by a triplet of apertures on the entrance pupil of the microscope lens. The present article extends upon previously published material Klinner & Willert (2022) by applying multi-aperture micro particle tracking velocimetry (MA-micro PTV) on a canonical turbulent boundary layer (TBL) to track the near-wall motion of tracer particles with the aim of estimating the unsteady wall-shear stress from particle tracks. The technique is validated with measurements of a TBL inside the closed test section of the 1 m wind tunnel of DLR in Göttingen (1mWK) at free- stream velocities of 5.2 to 20 m/s with corresponding shear Reynolds numbers between 560 and 1630. In the viscous sublayer, the probability density distributions of stream- and span-wise wall shear stress (WSS) components could be reliably captured down to probability densities of 10E−3. As far as we know, this has not been achieved in the past, particularly not for the span-wise component. For the stream-wise component the measured Reynolds-number dependency of the root mean squared fluctuations agrees to correlations by Örlü & Schlatter (2011). Furthermore, the skewness of the stream-wise WSS agrees well to values from DNS. On the other hand, the span-wise WSS fluctuations consistently underestimate the predicted DNS values, for which it is assumed that the deviation can be explained by the rapid decrease of the span-wise velocity fluctuations with increasing wall distance. Wall-normal profiles of 3c velocity statistics were obtained by bin averaging of particle velocities. Up into the buffer layer, these profiles agree well with profiles from stereo PIV as well as from DNS and LES, indicating an accurate determination of both near-wall velocities and inner scaling.

FlowFit3: Efficient Data Assimilation Of LPT Measurements

Lagrangian particle tracking (LPT) techniques such as Shake-The-Box provide accurate flow measurements by following the movement of tracer particles within a flow. The technique gives measured values of position, velocity and acceleration at the locations of the scattered particles as opposed to a Eulerian grid like with window based techniques such as PIV. This is advantageous for e.g spatially highly resolved flow statistics. Often it is also desirable to have access to a grid-structured representation of the data, especially for the calculation of spatial gradients of flow field measures. While a simple interpolation onto a grid is possible, data assimilation techniques using physics based regularization such as FlowFit2 or VIC+ and VIC#are frequently used nowadays. Through knowledge of the Navier-Stokes equations a higher spatial resolution can be obtained than from interpolation alone. We present the new and highly efficient FlowFit3 approach and its evaluation on synthetic data.

Object Registration Techniques For 3D Particle Tracking

Image based 3D particle tracking is currently the most widely used technique for volumetric velocity measurements. Inspecting the flow-field around an object is however, hampered by the latter, obstructing the view across it. In this study, the problem of measurement limitations due to the above is addressed. The present work builds upon the recent proposal from Wieneke and Rockstroh (2024), whereby the information of the occluded lines of sight can be incorporated into the particle tracking algorithm. The approach, however, necessitates of methods that accurately evaluate the shape and position of the object within the measurement domain. Methods of object marking and the following 3D registration of a digital object model (CAD) are discussed. For the latter, the Iterative Closest Point (ICP) registration algorithm is adopted. The accuracy of object registration is evaluated by means of experiments, where marking approaches that include physical and optically projected markers are discussed and compared. Three objects with growing level of geometrical complexity are considered: a cube, a truncated wing and a scaled model of a sport cyclist. The registered CAD representations of the physical objects are included in aerodynamic experiments, and the flow field is measured by means of large-scale particle tracking using helium filled soap bubbles. Three operating regimes are studied and compared: monolithic, partitioned and object-aware (OA) monolithic. The results indicate that object registration enables a correct reconstruction of particle tracers and strongly reduces the domain clipping typical of the monolithic approach. Furthermore, the dynamical use of all views in the OA monolithic method offers clear benefits compared to the partitioned approach, namely a lower occurrence of ghost particles. Finally, the combined visualization of the object and the surrounding flow pattern offers means of insightful data inspection and interpretation, along with posing a basis for PIV data assimilation at the fluid-solid interface.

Resolving Flow Structures Inside Three Dimensional Packed Beds With Gas Flow By Ray Tracing Particle Image Velocimetry

Two different configurations are investigated in this study by ray tracing Particle Image Velocimetry to access the interior of different spherical packing structures. Configuration 1 consists of a regular bidisperse packed bed of 10mm and 40mm spheres based on a body-centered cubic arrangement. Ray tracing Particle Image Velocimetry was performed behind two spheres in the 40mm layer for particle Reynolds numbers from 200 to 700. The averaged velocity flow fields show the jet structures according to the pores between the underlying smaller spheres and the influence of the large spheres. Since ray-tracing Particle Image Velocimetry suffers from experimental and numerical limitations, planar 2D Particle Image Velocimetry measurements are performed to obtain spatially highly resolved validation data in the optically accessible void pores. These measurements were performed at different height positions in the bed showcasing that similar flow fields appear in the different pores. Configuration 2 deals with the jet flow (Re=5900) around an individual sphere, part of a body-centred cubic arrangement of d=40mm spheres. The emphasis lays on the temporally resolved snapshot data of the turbulent jet flow obtained by ray tracing Particle Image velocimetry. Data obtained from both configurations is used for a comprehensive discussion of the chances and challenges of ray tracing Particle Image Velocimetry. Limitations appear on the experimental side, like generation of depth of field, illumination and reflections, sufficient measurement signal, and accuracy of the geometry, but also on the numerical side, like the reproduction of the geometry, material properties, and real-world conditions. Since all these phenomena are interlinked, performing the ray tracing method in more complex systems is questionable.

Anomalous diffusion of scaled Brownian tracers.

A model for anomalous transport of tracer particles diffusing in complex media in two dimensions is proposed. The model takes into account the characteristics of persistent motion that an active bath transfers to the tracer; thus, the model proposed here extends active Brownian motion, for which the stochastic dynamics of the orientation of the propelling force is described by scaled Brownian motion (sBm), identified by time-dependent diffusivity of the form D_{β}∝t^{β-1},β>0. If β≠1, sBm is highly nonstationary and suitable to describe such nonequilibrium dynamics induced by complex media. In this paper, we provide analytical calculations and computer simulations to show that genuine anomalous diffusion emerges in the long-time regime, with a time scaling of the mean-squared displacement t^{2-β}, while ballistic transport t^{2}, characteristic of persistent motion, is found in the short-time regime. We also analyze the time dependence of the kurtosis, and the intermediate scattering function of the position distribution, as well as the propulsion autocorrelation function, which defines the effective persistence time.

Comparison of a conventional image processing approach with an artificial neural network approach to three‐dimensionally trace multiple particles in dynamic x‐ray microtomography experiments under laboratory conditions

AbstractThis paper compares a classic digital image processing approach to trace particles in laboratory x‐ray micro‐computed tomography (µCT), which is based on a combination of random sample consensus (RANSAC) algorithm and least squares ellipse fitting (LSF), with an approach based on artificial neural networks (ANNs). In order to be able to perform the comparison, dynamic experiments were carried out in a laboratory microtomography facility. During active scans with a duration of 30–75 s several sedimentation experiments have been carried out with an exposure time of 0.13 s/projection. Through the movement of the particles during the scan curved motion artefacts in the reconstructed data occur, where the vertex marks the coordinate of the particle. It could be shown that both approaches enable the tracing of particles in laboratory x‐ray µCT with deviations from a manually evaluated result of exemplarily 1.25% for the conventional digital image processing (CDIP) and 0.48% for the ANN. It was found that ANNs are able to identify particle positions in non‐symmetrical motion artefacts, appearing around the first and last position of the particles in the scan, allowing an extension of the motion range of the particles that can be evaluated. Both methods have their advantages and disadvantages. Due to the high complexity and size as well as partly black box structures of neural networks, they are not 100% comprehensible whereas conventional image processing is 100% transparent and understandable. But because of the complexity of the tracing of particles, the CDIP code offers many parameters that can be set, which is why the application is therefore slightly more complex.

Tracer dynamics in the active random average process

We investigate the dynamics of tracer particles in the random average process (RAP), a single-file system in one dimension. In addition to the position, every particle possesses an internal spin variable σ(t) that can alternate between two values, ±1, at a constant rate γ. Physically, the value of σ(t) dictates the direction of motion of the corresponding particle and, for finite γ, every particle performs non-Markovian active dynamics. Herein, we study the effect of this non-Markovian behavior in the fluctuations and correlations of the positions of tracer particles. We analytically show that the variance of the position of a tagged particle grows sub-diffusively as ∼ζqt at large times for the quenched uniform initial conditions. While this sub-diffusive growth is identical to that of the Markovian/non-persistent RAP, the coefficient ζq is rather different and bears the signature of the persistent motion of active particles through higher-point correlations (unlike in the Markovian case). Similarly, for the annealed (steady-state) initial conditions, we find that the variance scales as ∼ζat at large times, with the coefficient ζa once again different from the non-persistent case. Although both ζ q and ζa individually depart from their Markovian counterparts, their ratio ζa/ζq is still equal to 2 , a condition observed for other diffusive single-file systems. This condition turns out to be true even in the strongly active regimes, as corroborated by extensive simulations and calculations. Finally, we study the correlation between the positions of two tagged particles in both quenched uniform and annealed initial conditions. We verify all our analytical results using extensive numerical simulations.

Collapsing molecular clouds with tracer particles – II. Collapse histories

ABSTRACT In order to develop a complete theory of star formation, one essentially needs to know two things: what collapses and how long it takes. This is the second paper in a series, where we query how long a parcel of gas takes to collapse and the process it undergoes. We embed pseudo-Lagrangian tracer particles in simulations of collapsing molecular clouds, identify the particles that end in dense knots, and then examine the collapse history of the gas. We find a nearly universal behaviour of cruise-then-collapse, wherein a core stays at intermediate densities for a significant fraction of its life before finally collapsing. We identify time immediately before each core collapses, $t_{\rm {sing}}$, and examine how it transitions to high density. We find that the time to collapse is uniformly distributed between $0.25 t_{\rm {ff}}$ and the end of the simulation at $\sim\!\! 1 t_{\rm {ff}}$, and that the duration of collapse is universally short, $\Delta t \sim 0.1 t_{\rm {ff}}$, where $t_{\rm {ff}}$ is the free-fall time at the mean density. We describe the collapse in three stages: collection, hardening, and singularity. Collection sweeps low-density gas into moderate density. Hardening brings kinetic and gravitational energies into quasi-equipartition. Singularity is the free-fall collapse, forming an envelope in rough energy balance and central overdensity in $\sim\!\! 0.1 t_{\rm {ff}}$.

Cytoplasmic fluidization contributes to breaking spore dormancy in fission yeast

The cytoplasm is a complex, crowded environment that influences myriad cellular processes including protein folding and metabolic reactions. Recent studies have suggested that changes in the biophysical properties of the cytoplasm play a key role in cellular homeostasis and adaptation. However, it still remains unclear how cells control their cytoplasmic properties in response to environmental cues. Here, we used fission yeast spores as a model system of dormant cells to elucidate the mechanisms underlying regulation of the cytoplasmic properties. By tracking fluorescent tracer particles, we found that particle mobility decreased in spores compared to vegetative cells and rapidly increased at the onset of dormancy breaking upon glucose addition. This cytoplasmic fluidization depended on glucose-sensing via the cyclic adenosine monophosphate-protein kinase A pathway. PKA activation led to trehalose degradation through trehalase Ntp1, thereby increasing particle mobility as the amount of trehalose decreased. In contrast, the rapid cytoplasmic fluidization did not require de novo protein synthesis, cytoskeletal dynamics, or cell volume increase. Furthermore, the measurement of diffusion coefficients with tracer particles of different sizes suggests that the spore cytoplasm impedes the movement of larger protein complexes (40 to 150 nm) such as ribosomes, while allowing free diffusion of smaller molecules (~3 nm) such as second messengers and signaling proteins. Our experiments have thus uncovered a series of signaling events that enable cells to quickly fluidize the cytoplasm at the onset of dormancy breaking.

Persistent Luminescence Nanoplatform for Autofluorescence-Free Tracking of Submicrometer Plastic Particles in Plant.

The uptake of plastic particles by plants and their transport through the food chain make great risks to biota and human health. Therefore, it is important to trace plastic particles in the plant. Traditional fluorescence imaging in plants usually suffers significant autofluorescence background. Here, we report a persistent luminescence nanoplatform for autofluorescence-free imaging and quantitation of submicrometer plastic particles in plant. The nanoplatform was fabricated by doping persistent luminescence nanoparticles (PLNPs) onto polystyrene (PS) nanoparticles. Cr3+-doped zinc gallate PLNP was employed as the dopant for autofluorescence-free imaging due to its persistent luminescence nature. In addition, the Ga element in PLNP was used as a proxy to quantify the PS in the plant by inductively coupled plasma mass spectrometry (ICP-MS). Thus, the developed nanoplatform allows not only dual-mode autofluorescence-free imaging (persistent luminescence and laser-ablation ICP-MS) but also ICP-MS quantitation for tracking PS in plant. Application of this nanoplatform in a typical plant model Arabidopsis thaliana revealed that PS mainly distributed in the root (>99.45%) and translocated very limited (<0.55%) to the shoot. The developed nanoplatform has great potential for quantitative tracing of submicrometer plastic particles to investigate the environmental process and impact of plastic particles.

Numerical simulation study of nanoparticle diffusion in gray matter

PurposeNanomedicine-based approaches have shown great potential in the treatment of central nervous system diseases. However, the fate of nanoparticles (NPs) within the brain parenchyma has not received much attention. The complexity of the microstructure of the brain and the invisibility of NPs make it difficult to study NP transport within the grey matter. Moreover, regulation of NP delivery is not fully understood. Methods2D interstitial system (ISS) models reflecting actual extracellular space (ECS) were constructed. A particle tracing model was used to simulate the diffusion of the NPs. The effect of NP size on NP diffusion was studied using numerical simulations. The diffusion of charged NPs was explored by comparing experimental and numerical simulation data, and the effect of cell membrane potential on the diffusion of charged NPs was further studied. ResultsThe model was verified using previously published experimental data. Small NPs could diffuse efficiently into the ISS. The diffusion of charged NPs was hindered in the ISS. Changes in cell membrane potential had little effect on NP diffusion. ConclusionThis study constructed 2D brain ISS models that reflected the actual ECS and simulated the diffusion of NPs within it. The study found that uncharged small NPs could effectively diffuse within the ISS and that the cell membrane potential had a limited effect on the diffusion of charged NPs. The model and findings of this study can aid the design of nanomedicines and nanocarriers for the diagnosis and treatment of brain diseases.

Mixing performance in an asymmetrical non-twin kneading element channel

Abstract The kneading elements play a crucial role in the distributive and dispersive mixing in the conventional co-rotating twin screw extruders. A novel kind of asymmetrical dual-speed co-rotating non-twin kneading elements (NTKE) with a zero staggered angle was designed to introduce symmetry break to improve mixing. Finite element method was applied to solve the time-dependent flow field where mesh superposition technique was used to impose the boundary conditions of moving parts and further to avoid the remeshing at every time steps. The flow and mixing of several fluids obeying the Carreau constitutive model with the different power law exponents were investigated numerically and compared with the conventional co-rotating twin kneading elements (TKE). Distributive mixing was evaluated through evolution of tracer droplets and decaying of variance index with time. Moreover, the dispersive mixing was examined in terms of the statistical distributions of mixing index. An integral function with regard to the mixing index was proposed to evaluate the proportion of tracer particles subjected to the elongation.