DEM simulation of aggregation of suspended nanoparticles

Ozonation/UV irradiation of dispersed Ag/AgI nanoparticles in water resources: stability and aggregation

Proliferation of nanoparticles (NPs) as aqueous pollutants is a matter of growing concern today. The aggregation kinetics of colloidal bare silver (Ag, 20.5 nm) and silver iodide (AgI, 15.3 nm) NPs were investigated during ozone/ultraviolet (O₃/UV) oxidation. Dynamic light scattering was applied to monitor the aggregation of NPs, and the z-average of treated samples was considered aggregate diameter. The effect of temperature, pH, and initial concentration of NPs was investigated on the aggregation rate constant and stability ratio. At a short oxidation period of approximately 1 min, the lower stability ratio was achieved for Ag NPs (< 50) than AgI NPs (> 100). Under acidic conditions, the negative surface charge of both NPs was neutralized that resulted in faster aggregation. In contrast, the impact of temperature and initial concentration of NPs on the aggregation rate was different for both NPs, which was due to the type of O₃/UV interaction with the surface of NPs and the thickness of the electrical double layer surrounding the NPs. The aggregation behavior of Ag NPs obeyed diffusion-limited regime, while an intermediate regime between diffusion- and reaction-limited was observed for AgI NP aggregation. The resulting aggregate morphologies showed that the clusters were ramified for Ag and compressed for AgI NPs. Applying the O₃/UV oxidation process for water treatment purposes leads to a significant reduction in aggregation time for inherently unstable Ag and stable AgI toxic NPs from several hours or days to several minutes.

Dielectrophoresis-Based Universal Membrane Antifouling Strategy toward Colloidal Foulants

Membrane fouling compromises the benefits of membrane technology, leading to its performance deterioration and incremental cost. Coupling with an electric field has been attractive but is limited by the electrical dependence of the electrophoresis (EP) mechanism and undesired faradic reactions. This study reports a universal dielectrophoresis-based (DEP) membrane antifouling strategy for electronegative, electropositive, and neutral colloidal foulants, which depends on the particle polarizability rather than its charge. The porous Ni@PVDF model electroconductive membrane was fabricated to construct a nonuniform electric field inducing DEP, while applying a low voltage avoided side electrochemical reactions. For electronegative SiO₂(-) and electropositive Al₂O₃(+) particles with a lower relative permittivity than the medium water (78), the membrane permeability all remarkably increased by 90.1% under AC/DC (±1.0 V) fields. By contrast, serious membrane fouling occurred for the BaTiO₃ colloids with a higher relative permittivity (∼2000). Notably, the permittivity of nearly all colloids in wastewater treatment is much less than that of water, which makes the dielectrophoresis-based antifouling strategy universal. The theoretical simulation systematically analyzed the forces on particles including DEP, EP, and others, indicating that the formed protected area on the membrane pore wall by DEP forces prevented the irreversible membrane blockage of colloids and facilitated loose cake layer formation for alleviating membrane fouling. In brief, this work reported a hopeful concept for dielectrophoresis-based membrane antifouling and verified its antifouling mechanism.

A comprehensive estimate of the aggregation and transport of nSiO2 in static and dynamic aqueous systems

Silicon dioxide nanoparticles (nSiO₂) are extensively used in diverse fields and are inevitably released into the natural environment. Their overall aggregation behaviour in the environmental matrix can determine their fate and ecotoxicological effect on terrestrial and aquatic life. The current study systematically evaluates multiple parameters that can influence the stability of colloidal nSiO₂ (47 nm) in the natural aquatic environment. At first, the influence of several hydrochemical parameters such as pH (5, 7, and 9), ionic strength (IS) (10, 50, and 100 mM), and humic acid (HA) (0.1, 1, and 10 mg L^-1) was examined to understand the overall aggregation process of nSiO₂. Furthermore, the synergistic and antagonistic effects of ionic strength and humic acid on the transport of nSiO₂ in the aqueous environment were examined. Our experimental findings indicate that pH, ionic strength, and humic acid all had a profound influence on the sedimentation process of nSiO₂. The experimental observations were corroborated by calculating the DLVO interaction energy profile, which was shown to be congruent with the transport patterns. The present study also highlights the influence of high and low shear forces on the sedimentation process of nSiO₂ in the aqueous medium. The presence of shear force altered the collision efficiency and other interactive forces between the nanoparticles in the colloidal suspension. Under the experimental stirring conditions, a higher abundance of dispersed nSiO₂ in the upper layer of the aqueous medium was noted. Additionally, the transport behaviour of nSiO₂ was studied in a variety of natural water systems, including rivers, lakes, ground, and tap water. The study significantly contributes to our understanding of the different physical, chemical, and environmental aspects that can critically impact the sedimentation and spatial distribution of nSiO₂ in static and dynamic aquatic ecosystems.

An efficient multiscale bi-directional PBM-DEM coupling framework to simulate one-dimensional aggregation mechanisms

The mesoscale population balance modelling (PBM) technique is widely used in predicting aggregation processes. The accuracy and efficiency of PBM depend on the formulation of its kernels. A model of the volume- and time-dependent one-dimensional aggregation kernel is developed for predicting the temporal evolution of the considered particulate system. To make the developed model physically relevant, the PBM model needs three unknown parameters as input: volume-dependency in collisions, collision frequency per particle and aggregation probability. For this, the microscale discrete element model (DEM) is used. The system’s collision frequency is extracted periodically using a novel collision detection algorithm that detects and ignores duplicate collisions.

Finally, a multiscale bi-directional PBM–DEM coupling framework is presented to simulate the aggregation mechanism. PBM and DEM simulations take place periodically to update the particle size distribution (PSD) and extract the collision-frequency, respectively. The coupling framework successfully explains the dependence between the PSD and the collision frequency. Additionally, computational cost of the algorithm is optimized while maintaining the accuracy of the results. Lastly, the accuracy and efficiency of the developed framework are verified using two different test cases. In one of the examples, a simple aggregation is simulated directly inside the DEM for the first time.

Light Extinction by Agglomerates of Gold Nanoparticles: A Plasmon Ruler for Sub-10 nm Interparticle Distances

Plasmon rulers relate the shift of resonance wavelength, λ_l, of gold agglomerates to the average distance, s, between their constituent nanoparticles. These rulers are essential for monitoring the dynamics of biomolecules (e.g., proteins and DNA) by determining their small (<10 nm) coating thickness. However, existing rulers for dimers and chains estimate coating thicknesses smaller than 10 nm with rather large errors (more than 200%). Here, the light extinction of dimers, 7- and 15-mers of gold nanoparticles with diameter d_p = 20-80 nm and s = 1-50 nm is simulated. Such agglomerates shift λ_l up to 680 nm due to plasmonic coupling, in excellent agreement with experimental data by microscopy, dynamic light scattering, analytical centrifugation, and UV-visible spectroscopy. Subsequently, a new plasmon ruler is derived for gold nanoagglomerates that enables the accurate determination of sub-10 nm coating thicknesses, in excellent agreement also with tedious microscopy measurements.

CFD Modeling of Flame Jump across Air Gap between Evasé and Capture Duct for Ventilation Air Methane Abatement

The ventilation air–methane (VAM) released from underground mines is often transported into regenerative thermal oxidizer (RTO) devices and burnt into heat energy. This study numerically investigates the scenarios where explosion occurs inside the RTO and the flame and pressure waves propagate back quickly towards the VAM discharge duct. Possibilities of secondary explosion in the discharge duct, hence in the downstream underground mines, are examined. The results critically showed that when the methane concentration accumulated in the RTO reached 7.5% or above, the flame generated from the explosion jumped to the evasé of the discharge section (over a distance of 29.4 m) and could induce explosions in underground mines.

Pore-Scale Simulations of Particles Migration and Deposition in Porous Media Using LBM-DEM Coupling Method

This paper studies the migration and deposition of suspended particles in porous media. This problem results from the fact that during the operation of a groundwater source heat pump, the recharging process will contribute to the impairment of soil permeability. A coupling lattice Boltzmann method, discrete element method and immersed moving boundary method were used to investigate the migration of particles in porous media. The DKT (Drifting, Kissing, Tumbling) phenomena were employed to validate our program. The coupled effects of concentration, flow rate and pH on the clogging mechanism of the porous media were analyzed. Results show that, due to the repulsive barrier between the particles and porous media, there is a critical velocity. At a low flow rate, the deposition ratio increases with the increase in velocity. Beyond the critical velocity, the deposition ratio decreases when the velocity increases due to higher shear force. Permeability impairment increases with the increase in concentration, especially in the low flow rate condition. Changes in pH mainly affect the repulsive barrier. For a low flow rate, the decrease in repulsive barrier greatly promotes the deposition of particles. Under the condition of favorable deposition, the increase in flow rate reduces the deposition phenomenon. Under the condition of unfavorable deposition, the lower flow rate condition has a lower deposition ratio. The process of particle deposition and the dynamic motion after deposition were observed such as particles gliding over the surface. Accumulated particles in the downstream form bridges and hinder fluid flow. At a high flow rate, strong shear force is more capable of destroying bridges and recovering permeability. Adsorbed particles glide on the surface of the grain and deposit in the downstream. This paper aims to help understanding of the micro-events of particle deposition and the clogging process.

Effect of nanoparticle concentration on coagulation rate of colloidal suspensions

Theoretically and with the help of numerical simulation the coagulation rate of nanoparticle suspensions is analyzed. Analytical expressions are proposed that describes the rate of stationary coagulation of the nanoparticles suspended in a solvent ( d n a / d t , wheren a is the particle concentration) and the characteristic coagulation time θ = - n a / ( d n a / d t ) . In the contrast to traditionally used equations, the proposed expressions allow one to describe with high accuracy the rate of stationary coagulation of not only low concentrated suspensions, where the volume content of nanoparticles is ρ ≪ 1 %, but also rather highly concentrated ones, at ρ ∼ 1 % and more ( ρ = n a v a wherev a is a particle volume), which are relevant for most of the industrial applications. Analytical expressions are written for both three-dimensional geometry, which is relevant for real colloids, and two-dimensional geometry, which is useful to compare results of the analytical solution and numerical simulation. Computer experiments are performed in the framework of the two-dimensional method of stochastic dynamics. Satisfactory agreement of the obtained analytical expressions with the results of numerical calculations is demonstrated. The dependences of the coagulation time on the height of the interparticle energy barrier and on the suspension concentration are analyzed. It is shown that, in contrast to the obtained theoretical expressions, the traditionally used formulas overestimate the characteristic coagulation time for highly concentrated suspensions by more than an order of magnitude.

Effect of volume fraction on chains of superparamagnetic colloids at equilibrium

For a few decades, the influence of a magnetic field on the aggregation process of superparamagnetic colloids has been well known on short time scale. However, the accurate study of the equilibrium state is still challenging on some aspects. On the numerical aspect, current simulations have only access to a restricted set of experimental conditions due to the computational cost of long-range interactions in many-body systems. In the present paper, we numerically explore a new range of parameters thanks to sped up numerical simulations validated by a recent experimental and numerical study. We first show that our simulations reproduce results from previous study in well-established conditions. Then we show that unexpectedly long chains are observed for higher volume fractions and intermediate fields. We also present theoretical developments taking into account the interaction between the chains which are able to reproduce the data that we obtained with our simulations. We finally confirm this model thanks to experimental data.

Application of the Discrete Element Method for Manufacturing Process Simulation in the Pharmaceutical Industry

Process simulation using mathematical modeling tools is becoming more common in the pharmaceutical industry. A mechanistic model is a mathematical modeling tool that can enhance process understanding, reduce experimentation cost and improve product quality. A commonly used mechanistic modeling approach for powder is the discrete element method (DEM). Most pharmaceutical materials have powder or granular material. Therefore, DEM might be widely applied in the pharmaceutical industry. This review focused on the basic elements of DEM and its implementations in pharmaceutical manufacturing simulation. Contact models and input parameters are essential elements in DEM simulation. Contact models computed contact forces acting on the particle-particle and particle-geometry interactions. Input parameters were divided into two types-material properties and interaction parameters. Various calibration methods were presented to define the interaction parameters of pharmaceutical materials. Several applications of DEM simulation in pharmaceutical manufacturing processes, such as milling, blending, granulation and coating, were categorized and summarized. Based on this review, DEM simulation might provide a systematic process understanding and process control to ensure the quality of a drug product.

Numerical Study of Soft Colloidal Nanoparticles Interaction in Shear Flow

The mechanical behavior of nanoparticle assemblies depends on complex particle interactions that are difficult to study experimentally. Depending on the nanoparticle morphology, these interactions could lead to adhesive and elastic-plastic behavior during contact deformation. The aim of this research is to study the effect of contact interactions between polymer nanoparticles and their impact on the macroscopic properties of formed aggregates. For this purpose, the discrete element method (DEM) was used to develop an interaction model combining elastic-plastic deformation and adhesion to study the behavior of spherical polymeric nanoparticles. Initially, a pair of particles interacting in the normal direction was simulated to evaluate the effect of adhesion and plastic deformation in the pull-off force of the contact. Based on these results, the simulations were extended to a dispersed system of nanoparticles, in which multibody interactions become dominant. Considering the aggregation between the nanoparticles induced by a shear flow, we performed an analysis of the number of aggregates and aggregates size in time to characterize the strength of clusters formed during the process. The simulation results showed that the interaction strength upon breakage of the clusters, correlating with the aggregates size, depends on the nanoparticle's softness. In this way, we verified that the type of contact interaction directly influences the macroscopic mechanical response of nanoparticle assemblies. Therefore, our model represents a new way of predicting the mechanical behavior of polymer nanoparticle systems and of optimizing it by adjusting primary particle properties.

Coupling colloidal forces with yield stress of charged inorganic particle suspension: A review

This paper aims to summarize the series of investigations on coupling suspension yield stress and DLVO (Derjaguin-Landau-Verwey-Overbeek) forces, i.e. van der Waals and electrical double layer forces. This summary provides a better understanding of the basic phenomena associated, historical development and current status of this useful coupling, and also discusses the applicability and limitations/variations of such coupling applied to different types of concentrated aqueous particle suspensions. Aqueous suspensions discussed are composed of charged inorganic fine particles, including metal oxide colloidal particles, mineral fine particles, and clays. The research gaps are identified and specific future perspectives are discussed to further enhance the use of this unique and useful coupling, and to aim for the transition from the modelling of similar particle suspension systems to its dissimilar/mix particle suspension systems that fit more with the current and future industry needs in particle processing.

Superparamagnetic colloids in viscous fluids

The influence of a magnetic field on the aggregation process of superparamagnetic colloids has been well known on short time for a few decades. However, the influence of important parameters, such as viscosity of the liquid, has received only little attention. Moreover, the equilibrium state reached after a long time is still challenging on some aspects. Indeed, recent experimental measurements show deviations from pure analytical models in extreme conditions. Furthermore, current simulations would require several years of computing time to reach equilibrium state under those conditions. In the present paper, we show how viscosity influences the characteristic time of the aggregation process, with experimental measurements in agreement with previous theories on transient behaviour. Afterwards, we performed numerical simulations on equivalent systems with lower viscosities. Below a critical value of viscosity, a transition to a new aggregation regime is observed and analysed. We noticed this result can be used to reduce the numerical simulation time from several orders of magnitude, without modifying the intrinsic physical behaviour of the particles. However, it also implies that, for high magnetic fields, granular gases could have a very different behaviour from colloidal liquids.

Modelling the Release, Transport and Fate of Engineered Nanoparticles in the Aquatic Environment - A Review

Engineered nanoparticles, that is, particles of up to 100 nm in at least one dimension, are used in many consumer products. Their release into the environment as a consequence of their production and use has raised concern about the possible consequences. While they are made of ordinary substances, their size gives them properties that are not manifest in larger particles. It is precisely these properties that make them useful. For instance titanium dioxide nanoparticles are used in transparent sunscreens, because they are large enough to scatter ultraviolet light but too small to scatter visible light.To investigate the occurrence of nanoparticles in the environment we require practical methods to detect their presence and to measure the concentrations as well as adequate modelling techniques. Modelling provides both a complement to the available detection and measurement methods and the means to understand and predict the release, transport and fate of nanoparticles. Many different modelling approaches have been developed, but it is not always clear for what questions regarding nanoparticles in the environment these approaches can be applied. No modelling technique can be used for every possible aspect of the release of nanoparticles into the environment. Hence it is important to understand which technique to apply in what situation. This article provides an overview of the techniques involved with their strengths and weaknesses. Two points need to be stressed here: the modelling of processes like dissolution and the surface activity of nanoparticles, possibly under influence of ultraviolet light, or chemical transformation has so far received relatively little attention. But also the uncertainties surrounding nanoparticles in general-the amount of nanoparticles used in consumer products, what constitutes the appropriate measure of concentration (mass or numbers) and what processes are relevant-should be explicitly considered as part of the modelling.

Analysis of nanoparticle agglomeration in aqueous suspensions via constant-number Monte Carlo simulation

A constant-number direct simulation Monte Carlo (DSMC) model was developed for the analysis of nanoparticle (NP) agglomeration in aqueous suspensions. The modeling approach, based on the "particles in a box" simulation method, considered both particle agglomeration and gravitational settling. Particle-particle agglomeration probability was determined based on the classical Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and considerations of the collision frequency as impacted by Brownian motion. Model predictions were in reasonable agreement with respect to the particle size distribution and average agglomerate size when compared with dynamic light scattering (DLS) measurements for aqueous TiO(2), CeO(2), and C(60) nanoparticle suspensions over a wide range of pH (3-10) and ionic strength (0.01-156 mM). Simulations also demonstrated, in quantitative agreement with DLS measurements, that nanoparticle agglomerate size increased both with ionic strength and as the solution pH approached the isoelectric point (IEP). The present work suggests that the DSMC modeling approach, along with future use of an extended DLVO theory, has the potential for becoming a practical environmental analysis tool for predicting the agglomeration behavior of aqueous nanoparticle suspensions.

Biotinylated thermoresponsive core cross-linked nanoparticles via RAFT polymerization and "click" chemistry

A straightforward approach to the synthesis of "clickable" thermoresponsive core cross-linked (CCL) nanoparticles was developed. This approach was based on reversible addition-fragmentation chain transfer (RAFT) radical cross-linking polymerization of styrene and divinylbenzene with azide-functionalized poly(N-isopropylacrylamide) (PNIPAM-N(3)) as macro chain transfer agent in a selective solvent. Spherical nanoparticles with a diameter of 12nm were obtained after 24h polymerization. When the lyophilized CCL nanoparticles were dispersed in THF, spherical nanoparticles were observed, confirming the stability of CCL nanoparticles. The transmission electron microscopy (TEM) studies demonstrated that spherical nanoparticles and wormlike structure coexisted in the aqueous solution. The CCL nanoparticles have a lower critical solution temperature (LCST) at about 29.6°C, a little lower than that of PNIPAM homopolymer. Biotin molecules were conjugated to the surface of CCL nanoparticles via "click" chemistry in aqueous media. After bioconjugation, the LCST shifted to 28.3°C. The bioavailability of biotin to protein avidin was evaluated by a 4'-hydroxyazobenzene-2-carboxylic acid/avidin (HABA/avidin) binding assay and TEM.