Local Particle Research Articles

An evaluation of two-way coupled Euler–Lagrange methodology through direct comparison with particle-resolved simulations

The two-way coupled Euler–Lagrange (EL) methodology is an efficient computational tool for investigating multiphase flows, enabling simulations with tens of millions of particles without Reynolds number limitations. This method resolves the fluid motion on scales larger than a filter length scale, which typically exceeds the particle size and the inter-particle spacing. However, EL simulations require closure models to account for unresolved scales. This work compares particle-resolved (PR) and EL simulations to assess the accuracy of EL solutions. We examine how well EL simulations capture the statistical distribution of particle and fluid quantities in multiphase flows by comparing them with PR solutions. The focus is on modeling the force on particles and understanding the influence of the filter scale on EL simulation accuracy. The results show that, due to variations in feedback forces at individual particle locations, the forces computed in the EL method do not consistently correlate with those obtained from the PR simulations.

Physics-Based and Data Driven Modeling of Electrophoretic Coatings: Hybrid and Multiphysics Strategy

Electrophoretic coatings are used in several applications where surface treatment is intended to provide corrosion protection. These coatings are widely used in the automotive, aerospace, or many other sectors. These kind of coatings are electrochemically applied and have good levelling, penetration, adhesion, and corrosion resistance properties. A wide variety of materials can be deposited by this technique and among these coatings, this presentation will focus on ceramic deposits. In this case, electrophoretic deposition is carried out using a suspension containing ceramic particles and the deposition takes place on a conductive substrate through the application of an electric field. The control of process parameters and post-processing parameters (heat treatment or sintering) necessary to consolidate the raw coatings obtained can be difficult to define. In order to improve process management and understanding of electrophoretic deposition, we will explore several strategies and modelling theories implemented in the field of electrophoretic coating through a comprehensive analysis in order to optimize the coating process, improve quality and increase efficiency on complex geometry parts. Several theoretical approaches and models have been used to better understand electrochemical interactions and forces involved in electrophoresis to identify parameters related to electrophoretic mobility. The multiple parameters involved in electrophoretic coatings make the modelling of this process complex and the models developed are neither universal nor applicable to all chemistries which requires a specific development for each electrolyte and suspension. In a second part, we discuss limits of theoretical models and describes a strategy to develop a new modelling approach. This approach combines a physics-based model of current distribution and a data-driven optimization applied to electrophoretic coating. This methodology allows to model the thickness distribution on a part with complex geometry on an industrial scale, with the ability to adapt to a variation in the chemistry of the suspension used. This hybrid methodology allow to reduce experimental and fundamental characterizations, and can be easily applied to a new chemistry to estimate and well describe the throwing power at a macroscale. Furthermore, in some cases, physics-based modeling with secondary distribution can exhibit accuracy defects when the local concentration of particles drops, due to their consumption and low mass transport phenomena. In order to better describe the process behavior in this specific case, we develop a multiphysics model of tertiary current distribution than can account for the local distribution of particles, particularly near the part. This modeling approach allows to better anticipate thickness distribution in areas with low fluid mixing and agitation. The local efficiency is linked to the local current and particle concentration, as describe by a two phase flow model. The models developed are intended to help accurately predict and control the distribution of coating thickness and also local particle concentration to predict critical depletion zones. In conclusion, this conference explore different modeling strategies of electrophoretic coatings, by focusing on the optimization of process parameters and the consideration of the different mechanisms governing deposition with the objective of improving coating distribution on complex part.

Brownian dynamics simulation of the structural evolution in monodisperse hard-sphere suspensions during drying and sedimentation processes.

The drying behavior of monodisperse colloidal films, with a focus on the influence of process variables on film microstructures, is explored via Brownian dynamics (BD) simulations. In our model, hard-sphere colloidal particles are dispersed in a Newtonian liquid with an initial particle volume fraction of 0.1. The effects of the drying rate and sedimentation on the evolving microstructures are systematically investigated using two dimensionless numbers: the Péclet number (Pe), which represents the competition between evaporation and diffusion, and the sedimentation number (Ns), which reflects the relative influence of sedimentation on evaporation. First, we analyze the local particle volume fraction and film structure at various Pe and Ns. As Pe increases, particle accumulation occurs near the liquid-gas interface, whereas a high Ns promotes dense packing near the substrate owing to sedimentation. The BD simulation results, viz. the local volume fraction profiles and drying regime maps, are in good agreement with those of the continuum model proposed by Wang and Brady. Structural analysis of the dried films reveals that at a low Pe (Pe = 0.1), a face-centered cubic (FCC) structure dominates, primarily independent of the sedimentation effects. In contrast, a high Pe leads to hexagonal close-packed or amorphous structure formation. Notably, at intermediate drying rates (Pe = 10), an increase in Ns promotes additional FCC ordering in the final film structure. Our study provides new insights into the hitherto underexplored role of sedimentation in the structural evolution of drying colloidal films, revealing the mechanisms of drying-induced assembly in colloidal systems.

Quantum wires with local particle loss: Transport manifestations of fluctuation-induced effects

We investigate the transport properties of a quantum wire of weakly interacting fermions in the presence of local particle loss. We calculate current and conductance in this system due to applied external chemical potential bias that can be measured in experimental realizations of ultracold fermions in quasi one-dimensional traps. Using a Keldysh field theory approach based on the Lindblad equation, we establish a perturbative scheme to study the effect of imbalanced reservoirs. Logarithmically divergent terms are resummed using a renormalization group method, and a novel powerlaw behavior for the conductance as a function of the potential bias across the wire is found. In contrast to the equilibrium case of a potential barrier in a Luttinger liquid, the conductance exhibits a scaling behavior, which depends on the interaction strength and on the loss probability. Repulsive interactions reduce the conductance of the wire while attractive interactions enhance it. However, perfect reflectivity and transparency are only reached in the absence of particle loss. Published by the American Physical Society 2024

Sensitivity of wavelet-based optical flow velocimetry (wOFV) to common experimental error sources

Abstract The influence of several potential error sources and non-ideal experimental effects on the accuracy of a wavelet-based optical flow velocimetry (wOFV) method when applied to tracer particle images is evaluated using data from a series of synthetic flows. Out-of-plane particle displacements, severe image noise, laser sheet thickness reduction, and image intensity non-uniformity are shown to decrease the accuracy of wOFV in a similar manner to correlation-based particle image velocimetry (PIV). For the error sources tested, wOFV displays a similar or slightly increased sensitivity compared to PIV, but the wOFV results are still more accurate than PIV when the magnitude of the non-ideal effects remain within expected experimental bounds. For the majority of test cases, the results are significantly improved by using image pre-processing filters and the magnitude of improvement is consistent between wOFV and PIV. Flow divergence does not appear to have an appreciable effect on the accuracy of wOFV velocity estimation, even though the underlying fluid transport equation on which wOFV is based implicitly assumes that the motion is divergence-free. This is a significant finding for the broader applicability of planar velocimetry measurements using wOFV. Finally, it is noted that the accuracy of wOFV is not reduced notably in regions of the image between tracer particles, as long as the overall seeding density is not too sparse i.e. below 0.02 particles per pixel. This explicitly demonstrates that wOFV (when applied to particle images) yields an accurate whole field measurement, and not only at or adjacent to the discrete particle locations.

Asymmetric deformation and failure behavior of roadway subjected to different principal stress based on biaxial tests

The magnitude and direction of stress will affect the failure of roadway. The impact of stress magnitude and direction on roadway failure was investigated using a rock failure system equipped with true triaxial loading, acoustic emission (AE), and digital image correlation (DIC) technologies. The system allowed for the simulation of rock sample failures under various three-dimensional stress conditions, while real-time monitoring was conducted using a high-precision microseismic system. By prefabricating rectangular holes at different angles in sandstone specimens, roadways under different stress effects in engineering can be simulated. Biaxial loading tests were then performed on these prefabricated sandstone cube specimens to observe external fracture characteristics and internal fracture information using acoustic emission equipment. The peak strength of samples with holes is approximately 38–56% of that of intact samples. In the early and middle loading stages, the strain on the surface is on the order of 10-3. In the later loading stage, the strain on the surface is on the order of 10-2. The findings indicate that roadway failure primarily involves local particle ejection, fragment spalling, large-scale particle ejection, plate crack buckling, and eventual failure. The ultimate failure mode varies based on stress deflection angles: with no included angle, the roadway exhibits a ’V’ shaped failure zone on both sides, predominantly experiencing tensile failure. At included angles of 30°, 45°, and 60° between stress and roadway axis, the roadway displays a “—” failure pattern along the diagonal, characterized by a combination of tension and shear failure. The extension angle of the“—” failure zone varies depending on the stress deflection angle. At a 90° included angle, the roadway shows a ’V’ shaped failure in the roof and floor, primarily undergoing tensile failure. Real-time monitoring of the strain field evolution around the roadway during failure using DIC method revealed valuable insights. AE events at different deflection angles reflect the progression of micro cracks in the specimen, showing a strong correlation with macro failure. The research outcomes elucidate the mechanisms behind various forms of roadway failure induced by stress deflection and shed light on the failure mechanism at different stress deflection angles.

A high-performance ray tracing particle tracking model for the simulation of microplastics in inland and coastal aquatic environments

In this study, we present a high-performance Particle Tracking Model (PTM) designed for simulating any type of particles, with a focus on microplastics. The PTM is efficient compared to existing models, parallelized, and utilizes a ray tracing algorithm incorporating both ray reflection and ray refraction in order to traverse particles as well as find the location of each particle over three-dimensional unstructured grids. Various numerical corrections are implemented in the model to address computational round-off errors and discontinuities in the water surface level of the input hydrodynamic models. To increase the accuracy of the model, partially reflective boundary conditions are imposed as well as the capability to simulate microplastics beaching and washout in very shallow areas or dry computational cells. Several tests are conducted to study the performance, scalability, and accuracy of the model. The proposed model is tested with over 3.88 billion double-precision particles on three-dimensional computational grids with up to approximately one million cells. The tests show that the ray tracing approach is efficient, achieves over 17× faster runtime, and offers greater accuracy compared to using an auxiliary grid for particle location finding. For larger timesteps, the ray tracing PTM with refraction shows improved accuracy compared to the ray tracing PTM without refraction. The model's capabilities are tested in a real-world case study over the Saguenay Fjord, Quebec, Canada. The model is utilized to reproduce the paths of five surface drifters. A second numerical test is conducted in the Fjord and high particle concentration areas are identified.

Effects of fluid properties on coarse particles transport in vertical pipe

The mineral resources in deep-seabed are attracting extensive attention. A numerical simulation of particle transport in a vertical pipe for a deep-sea mining system is conducted using the CFD-DEM method. The effects of fluid density, fluid viscosity and rheological parameters of non-Newtonian fluids on the liquid-solid flow behavior in a vertical pipe are investigated. For Newtonian fluids, increasing the density or viscosity enhances the particles' performance in following the fluid and reduces the slip velocity, but also increases the pressure drop. The efficient lifting of particles can be facilitated by adjusting fluid density and viscosity, while considering factors such as energy consumption. For non-Newtonian fluids, an increase in either the flow behavior index n or the consistency coefficient k results in an increase in the fluid's apparent viscosity. This leads to an increase in the particle suspension capacity and local particle velocity, along with a decrease in local particle concentration.

Defiltering turbulent flow fields for Lagrangian particle tracking using machine learning techniques

We propose a defiltering method of turbulent flow fields for Lagrangian particle tracking using machine learning techniques. Numerical simulation of Lagrangian particle tracking is commonly used in various fields. In general, practical applications require an affordable grid size due to the limitation of computational resources; for instance, a large-eddy simulation reduces the number of grid points with a filtering operator. However, low resolution flow fields usually underestimate the fluctuations of particle velocity. We thus present a novel approach to defilter the fluid velocity to improve the particle motion in coarse-grid (i.e., filtered) fields. The proposed method, which is based on the machine learning techniques, intends to reconstruct the fluid velocity at a particle location. We assess this method in a priori manner using a turbulent channel flow at the friction Reynolds number Reτ=180. The investigation is conducted for the filter size, nfilter, of 4, 8, and 16. In the case of nfilter=4, the proposed method can perfectly reconstruct the fluid velocity fluctuations. The results of nfilter=8 and 16 also exhibit substantial improvements in the fluctuation statistics although with some underestimations. Subsequently, the particle motion computed using the present method is analyzed. The trajectories, the velocity fluctuations, and the deposition velocity of particles are reconstructed accurately. Moreover, the generalizability of the present method is also demonstrated using the fields whose computational domain is larger than that used for the training. The present findings suggest that machine learning-based velocity reconstruction will enable us precise particle tracking in coarse-grid flow fields.

Dynamic behavior of metal droplets impacting on porous surfaces

During the operation of solid rocket motors, the behavior of condensed particles impacting the wall will have a remarkable influence on the structure and performance of the engine. Especially when the aircraft is under overload flight conditions, the condensed particles will form a local high concentration particle flow under the action of inertia force, continuously scouring the surface of the insulation layer, seriously affecting the thermal protection structure and the work safety of the engine. Therefore, it is an essential issue to master the behavior mode of the condensate particle impinging the wall and clarify its dynamic characteristics and evolutionary mechanism. In this paper, the dynamic behavior of aluminum droplets impacting on the porous surface is experimentally investigated by preparing the porous wall, the influence mechanism of the porous structure on the spreading process of aluminum droplets is clarified, and the effects of the droplet's initial parameters as well as surface environment are analyzed. Combined with the fluid of volume method, the flow process of droplets on the porous surface is simulated. With the variation of the dimensionless parameters M and N, the main behavior patterns of the droplets obtained so far are rebound, adhesion, partial rebound, partial adhesion, and porous seepage. The presence of pore structure enhances the hydrophobicity of the wall and makes the droplets more easily broken during spreading. When the droplet initial energy is certain and the wall structure conditions change, there is a strong competitive relationship between its spreading and penetration. When the droplet initial energy is increased, its spreading and penetration strengths are significantly increased. The research results can provide a reference for the erosion process of condensed-phase droplets impinging on the char layer and provide theoretical basis and data support for the design and optimization of SRMs.

Numerical assessment of ICRF-specific plasma-wall interaction in the new ITER baseline using the SSWICH-SW code

In 2023, switching the material on the first wall of ITER to tungsten (W) was recommended. In magnetic Fusion devices, waves in the Ion Cyclotron Range of Frequencies (ICRF) interact with the Scrape-Off Layer (SOL) via RF-sheath rectification. This contribution re-assesses this phenomenon close to the ITER ICRF antenna, focusing on the ICRF-specific gross erosion of W from the antenna port sides. Our quantitative estimates rely on predictive multi-2D numerical simulations of the ICRF antenna environment using the SSWICH-SW code. They combine Slow Wave propagation from the antenna mouth to the SOL, the excitation of RF oscillations in the sheath voltages at the antenna port sides and a subsequent DC biasing of the SOL. Maps of the parallel RF electric field at the antenna mouth, from the antenna code TOPICA, excite the system. Our simulations cover more than four decades in the local densities near the antenna. Since both the sputtering and the local heat loads are proportional to the local particle fluxes, the most intense Plasma-Wall Interaction is found for high local density, with or without ICRF waves. In these conditions, larger margins also exist for coupling the ICRF power. We tested several operational trade-offs between these two constraints. The simulated target plasma contains 2% of neon ions. These are efficient at sputtering W, already at low accelerating voltages. Consequently, although the RF-sheath rectification sufficiently amplifies the local sputtering at the antenna port for a detection using visible spectroscopy, the ICRF-induced increment of the gross W production represents at worse 22% of the W source expected from thermal sheaths over the eighteen out-board mid-plane ports. An upper bound, independent of our main assumptions, is proposed for this enhancement factor. This moderate expected global increase questions the ability to detect ICRF-specific W contamination of the plasma core, even at the planned maximal ICRF power.

REliable PIcking by Consensus (REPIC): a consensus methodology for harnessing multiple cryo-EM particle pickers

Cryo-EM particle identification from micrographs (“picking”) is challenging due to the low signal-to-noise ratio and lack of ground truth for particle locations. State-of-the-art computational algorithms (“pickers”) identify different particle sets, complicating the selection of the best-suited picker for a protein of interest. Here, we present REliable PIcking by Consensus (REPIC), a computational approach to identifying particles common to the output of multiple pickers. We frame consensus particle picking as a graph problem, which REPIC solves using integer linear programming. REPIC picks high-quality particles even when the best picker is not known a priori or a protein is difficult-to-pick (e.g., NOMPC ion channel). Reconstructions using consensus particles without particle filtering achieve resolutions comparable to those from particles picked by experts. Our results show that REPIC requires minimal (often no) manual intervention, and considerably reduces the burden on cryo-EM users for picker selection and particle picking. Availability: https://github.com/ccameron/REPIC.

Nonthermal eigenstates and slow relaxation in quantum Fredkin spin chains

We study the dynamics and thermalization of the Fredkin spin chain, a system with local three-body interactions, particle conservation, and explicit kinetic constraints. We consider deformations away from its stochastic point in order to tune between regimes where kinetic energy dominates and those where potential energy does. By means of exact diagonalization, perturbation theory, and variational matrix product states, we show there is a sudden change of behavior in the dynamics that occurs, from one of fast thermalization to one of slow metastable (prethermal) dynamics near the stochastic point. This change in relaxation is connected to the emergence of additional kinetic constraints, which lead to the fragmentation of Hilbert space in the limit of a large potential energy. We also show that this change can lead to thermalization being evaded for special initial conditions because of nonthermal eigenstates (akin to quantum many-body scars). We provide clear evidence for the existence of these nonthermal states for large system sizes even when far from the large-potential-energy limit, and explain their connection to the emergent kinetic constraints. Published by the American Physical Society 2024

Vesicle Picker: A tool for efficient identification of membrane protein complexes in vesicles

Electron cryomicroscopy (cryo-EM) has recently allowed determination of near-atomic resolution structures of membrane proteins and protein complexes embedded in lipid vesicles. However, particle selection from electron micrographs of these vesicles can be challenging due to the strong signal contributed from the lipid bilayer. This challenge often requires iterative and laborious particle selection workflows to generate a dataset of high-quality particle images for subsequent analysis. Here we present Vesicle Picker, an open-source program built on the Segment Anything model. Vesicle Picker enables automatic identification of vesicles in cryo-EM micrographs with high recall and precision. It then exhaustively selects all potential particle locations, either at the perimeter or uniformly over the surface of the projection of the vesicle. The program is designed to interface with cryoSPARC, which performs both upstream micrograph processing and downstream single particle image analysis. We demonstrate Vesicle Picker’s utility by determining a high-resolution map of the vacuolar-type ATPase from micrographs of native synaptic vesicles (SVs) and identifying an additional protein or protein complex in the SV membrane.

Is ‘global’ warming concept consistent with thermodynamics according to ChatGPT?

Aim. Taking care of the environment on Planet Earth is still important and has be- come popular exceeding boundaries of science. Therefore description of climate changes has evolved into the concept of Global Warming since the 20th century. On the other hand, principles of thermodynamics where temperature is defined locally (not globally) are still valid. In my research I have applied tools like ChatGPT to detect possible contra- dictions and propose bridging gaps between statistical physics and the concept of global warming. Methods. The concept of temperature based on calculations of local particles’ kinetic energy in a microcanonical ensemble has been confronted with the concept of so called ‘average’ temperature in ‘global’ warming. The principles of Kinetic Theory and Statisti- cal Ensembles provided by statistical physics have been applied to ChatGPT based on natural language Results. Contradictions between the concept of average temperature in global warming and the concept of temperature based on local particle kinetic energy arise due to the different scales, heterogeneity, presence of feedback mechanisms, and boundary conditions. According to the chatGPT’s verdict, the concept of temperature based on calculations of local particles kinetic energy in the microcanonical ensemble is statistically more accurate. Conclusion. The concept of so called ‘global’ warming (confronted with the physics- based concept of temperature, providing a more accurate and nuanced understanding of temperature changes in different scales and contexts) should be replaced by the idea of local warming which is consistent with the concept of temperature based on calcula- tions of local particles kinetic energy in the microcanonical ensemble and experimental measurements provided by NASA. Therefore, talking about local (not global) warming is more reasonable when our goal is to prevent our coexistence with environment on Planet Earth from disasters.

Model test study on the dynamic failure process of tunnel surrounding rocks in jointed rock mass under explosive load

The presence of joints can significantly reduce the integrity and stability of an engineering rock mass. Under dynamic loads, such as from blasting excavation, the key blocks divided by joints may be destabilized and prone to sliding, potentially leading to engineering geological disasters like rockbursts. To study the dynamic instability process, similar materials for the rock mass and joints were developed based on the similarity theory, and a tunnel model in the jointed rock mass was constructed. Subsequently, a detonating fuse was used to generate a dynamic load, and the dynamic instability process of the tunnel surrounding rock in the jointed rock mass under explosive load was studied using the geotechnical multifunctional testing device. The deformation characteristics and dynamic instability process of the tunnel surrounding rock were analyzed using acceleration sensors, resistance strain gages, linear variable displacement transducers and motion camera. The study shows that the acceleration at the tunnel vault is significantly greater than at the straight wall and floor under blast loads, with differences reaching an order of magnitude. Acceleration waveforms were classified into three categories based on peak characteristics, explained through the propagation of explosive stress waves. Additionally, strain and displacement at the tunnel arch were also significantly greater than in other areas, indicating more severe stress concentration and dynamic damage at the arch, necessitating reinforced support in tunnel excavation. The entire dynamic instability process of the tunnel surrounding rock was successfully recorded using a motion camera. The dynamic failure process was divided into several phases, the appearance of cracks on the joint surface, particle ejection accompanied by the dropping of jointed blocks, a significant drop of the jointed blocks, and return to calm. The dynamic failure modes include the dropping and rotation of jointed blocks, local particle ejection, and shear cracks on jointed block.

On the potential of the Cluster Ion Counter (CIC) to observe local new particle formation, condensation sink and growth rate of newly formed particles

Abstract. The Cluster Ion Counter (CIC) is a simple three-channel instrument designed to observe ions in the electrical mobility equivalent diameter range from 1.0 to 5 nm. With the three channels, we can observe concentrations of both ion clusters (sub-2 nm ions) and intermediate ions. Furthermore, as derived here, we can estimate condensation sink (CS), intensity of local new particle formation, growth rate of newly formed particles from 2 to 3 nm and formation rate of 2 nm ions. We compared CIC measurements with those of a multichannel ion spectrometer, the Neutral cluster and Air Ion Spectrometer (NAIS), and found that the concentrations agreed well between the two instruments, with correlation coefficients of 0.89 and 0.86 for sub-2 nm and 2.0–2.3 nm ions, respectively. According to the observations made in Hyytiälä, Finland, and Beijing, China, the ion source rate was estimated to be about two to four ion pairs cm−3 s−1. The new CIC is a simple and cheap instrument that can be used in different environments to obtain information about small ion dynamics, local intermediate ion formation and CS in a robust way when combined with the theoretical framework presented here.

Shear-induced migration of rigid spheres in a Couette flow

Concentration inhomogeneities occur in many flows of non-Brownian suspensions. Their modeling necessitates the description of the relative motion of the particle phase and of the fluid phase, as well as the accounting for their interaction, which is the object of the suspension balance model (SBM). We systematically investigate the dynamics and the steady state of shear-induced migration in a wide-gap Couette flow for a wide range of particle volume fraction, and we test the ability of the SBM to account for the observations. We use a model suspension for which macroscopic particle stresses are known. Surprisingly, the observed magnitude of migration is much lower than that predicted by the SBM when the particle stress in the SBM is equated to the macroscopic particle stress. Another noteworthy observation is the quasi-absence of migration for semidilute suspensions. From the steady-state volume fraction profiles, we derive the local particle normal stress responsible for shear-induced migration according to the SBM. However, the observed dynamics of migration is much faster than that predicted by the SBM when using this stress in the model. More generally, we show that it is not possible to build a local friction law consistent with both the magnitude and the dynamics of migration within the standard SBM framework. This suggests that there is a missing term in the usual macroscopic constitutive law for the particle normal stress driving migration. The SBM is indeed capable of accurately predicting both the magnitude and the dynamics of migration when a tentative phenomenological term involving a concentration gradient is added to the particle normal stresses determined in macroscopic experiments.

The impact of particle size and concentration on the characteristics of solid–fluid two-phase flow in vertical pipe under pulsating flow

Vertical pipe hydraulic conveying is currently considered the most promising method for deep-sea mining. The conveying velocity at the inlet of the vertical pipe is often close to a pulsating form due to the influence of the flexible pipe and the marine environment. This study employs a combined Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) approach to investigate the impact of various particle sizes and concentrations on the flow behavior of solid–fluid two-phase flow in a vertical pipe under pulsating flow. The study reveals that fluid velocities exhibit periodic fluctuations within the vertical pipe under pulsating inlet flow. Moreover, the periodic phenomenon of local increases in particle velocity and concentration becomes more pronounced as particle size and concentration increase. Larger particle sizes increase particle inertia, reducing the ability to follow the fluid and leading to more localized particle aggregation. Therefore, the flow pattern within the vertical pipe transitions from homogeneous flow to plug flow as particle size increases. Variations in fluid–solid interaction forces and particle collision forces are explored to explain this phenomenon. When the particle size exceeds a critical threshold, the collision force surpasses the fluid–solid interaction force, leading to the transition.

Solar evaporation of liquid marbles with composite nanowire arrays

Solar interfacial evaporation is a sustainable technology to produce fresh water. The synergistic realization of broadband light absorption and good thermal insulation is crucial to improving the thermal efficiency. Here, we propose a new structure over the surface of liquid marbles, which via nanowire arrays assembled with composite nanomaterials (Fe3O4/CNT nanoparticles) to enhance the evaporation efficiency. The composite materials can effectively absorb light across the entire solar spectrum. Multiple reflections of light over nanowire array further improve light absorption. The narrow spaces and local particle aggregation of the nanowire array enhance thermal insulation to improve the evaporation efficiency. A series of experiments were conducted to verify the concept. The results showed that liquid marbles with upward Fe3O4/CNT nanowire arrays (Fe3O4/CNT-ULM) enhance the light harvesting ability and thermal insulation. Fe3O4/CNT-ULM at a volume ratio 1:2 provides the highest evaporation rate of 12.25 μg/s, which is about 1.16 and 1.53 times higher than that of Fe3O4 and CNT, respectively. Numerical analysis further illustrates that the combination of composite materials and nanowire arrays enhances concentration of electromagnetic field and heat at the air/water interfaces. This promotes rapid evaporation at the thermal boundary region, which has important implications for the structure design of solar interfacial evaporator.