Primary Particle Size Research Articles

Testing floc settling velocity models in rivers and freshwater wetlands

Abstract. Flocculation controls mud sedimentation and organic carbon burial rates by increasing mud settling velocity. However, calibration and validation of floc settling velocity models in freshwater are lacking. We used a camera, in situ laser diffraction particle sizing, and suspended sediment concentration–depth profiles to measure flocs in Wax Lake Delta, Louisiana. We developed a new workflow that combines our multiple floc data sources to distinguish between flocs and unflocculated sediment and measure floc attributes that were previously difficult to constrain. Sediment finer than ∼10 to 55 µm was flocculated with median floc diameter of 30 to 90 µm, bulk solid fraction of 0.05 to 0.3, fractal dimension of ∼2.1, and floc settling velocity of ∼0.1 to 1 mm s−1, with little variation along water depth. Results are consistent with a semi-empirical model indicating that sediment concentration and mineralogy, organics, water chemistry, and, above all, turbulence control floc settling velocity. Effective primary particle diameter is ∼2 µm, about 2 to 6 times smaller than the median primary particle diameter, and is better described using a fractal theory. Flow through the floc increases settling velocity by an average factor of 2 and up to a factor of 7 and can be described by a modified permeability model that accounts for the effect of many primary particle sizes on flow paths. These findings help explain discrepancies between observations and an explicit settling model based on Stokes' law that depends on floc diameter, permeability, and fractal properties.

Cavity formation in silica‐filled rubber compounds observed during deformation by ultra small‐angle x‐ray scattering

AbstractWhen silica‐filled rubber compounds are deformed, structural modifications in the material's bulk lead to irreversible damage, the most significant of which is cavitation appearing within the interfaces of interconnected polymer and filler networks. This work introduces a new method to analyze cavitation in industrial‐grade rubbers based on ultra small‐angle x‐ray scattering. This method employs a specially designed multi‐sample stretching device for high‐throughput measurements with statistical relevance. The proposed data reduction approach allows for early detection and quantification of cavitation while providing at the same time information on the hierarchical filler structures at length scales ranging from the primary particle size to large silica agglomerates over four orders of magnitude. To validate the method, the scattering of SSBR rubber compounds filled with highly dispersible silica at different ratios was measured under quasi‐static strain. The strain was applied in incremental steps up to a maximum achievable elongation or breakage of the sample. From the measurements performed in multiple repetitions, it was found that the minimum strain necessary for cavity formation and the size evolution of the cavities with increasing strain are comparable between these samples. The sample with the highest polymer content showed the lowest rate of cavity formation and higher durability of silica structures. The structural stability of the compounds was determined by the evolution of the filler hierarchical structures, obtained by fitting data across the available strain range.

Enhancement of Mechanical Properties and Microstructure of Aluminium alloy AA2024 By adding TiO2 Nanoparticles

Modern engineering applications, especially in the automotive and aerospace industries, require essential and appealing properties such as lightweight with high strength and resistance. The key objective of the present study is to investigate the effect of TiO2 nanoparticles on the microstructure, impact strength, hardness and wear resistance of the stir cast aluminum alloy AA2024, An aluminium alloy was reinforced with different mass fractions (0 %, 2.5 %, 5 %, 7.5 %) of titanium dioxide nanoparticles by stir casting followed by solution annealing at 500°C for 3 h, quenching in water and aging at 175°C for 3 h. Results showed that regular morphology and fine grain size of primary AA2024 particles are achieved after the addition of 2.5 wt.% TiO2 compared to the sample without the addition of nanoparticles composite. In addition, it was found that adding nanoparticles increased energy absorption, and this effect is improved by increasing impact strength by adding nanoparticles, the impact strength increased from 5 j/m2 to 7 j/m2 at 5%. At the same time, the increase of nanoparticles effect decreases the mass losses (increase in wear resistance). With a weight fraction of 5 wt.% TiO2, the alloy exhibits the highest value of hardness.

Investigation of iron oxide nanoparticle formation in a spray-flame synthesis process using laser-induced incandescence

In this work, iron-oxide nanoparticle formation in the spray-flame synthesis (SFS) process of the standardized SpraySyn 2.0 burner was investigated in situ using laser-induced incandescence (LII). For the evaluation of these measurements, prior LII-experiments within iron-oxide aerosols (Fe3O4 and α-Fe2O3) with known primary particle size distribution and morphological properties were performed to determine the thermal accommodation coefficient (TAC) α, which led to approx. α = 0.08. The applicability of the TAC results within the flame was validated using spectrally and temporally resolved measurements in the flame at 65 mm HAB employing a spectrograph. Data for a bimodal particle size distribution, obtained from Transmission Electron Microscopy (TEM), were used in the LII-evaluation. The validated TAC was then used to evaluate the primary particle size evolution from in situ Time-Resolved (TiRe) LII-measurements using PMTs along the centre axis of the burner, ranging from 10 mm to 50 mm HAB. These measurements reveal a relatively constant effective particle diameter along HAB with dp,eff ≈ 300 nm. To further investigate particle formation in SFS, 2-dimensional time-resolved LII-measurements in the SFS flame were performed, showing a clear particle formation region up to approx. 30 mm HAB, from where on a constant particle mass is observed.

Particle size analysis of iron hydroxide adipate tartrate (IHAT) in a food supplement: Interlaboratory testing of a dynamic light scattering method

Iron hydroxide adipate tartrate (IHAT) is a nano-scale material with a diameter of less than 5 nm intended for use as iron source in food supplements. It is the first engineered nanomaterial that was authorised as novel food in the European Union in 2022 (Commission Implementing Regulation (EU) 2022/1373) and subsequently added to the European Union list of novel foods. Official control laboratories of EU Member States are required to conduct compliance testing of novel foods, including IHAT, against approved specifications. In the case of IHAT, the authorised specifications include the constituent particle size, referred to in the implementing regulation as ‘primary particle size’. In this study, a method to determine the constituent particle size distribution of IHAT using the volume-based hydrodynamic diameter with dynamic light scattering is proposed and tested in an interlaboratory comparison study involving five experienced European food control and food research laboratories. Three test materials were examined, including an early batch of IHAT without the flow agent, a damaged material unintentionally exposed to water, and the final commercial product that included the flow agent. The results demonstrate that dynamic light scattering can reliably measure the particle size of particles in the low nanometre range if samples are prepared and measured following a robust, easy-to-reproduce, and standardised protocol. The results obtained for the commercial product met the compliance requirements specified in the annex of the Commission Implementing Regulation in all laboratories for the primary particle size distribution (Dv(10/50/90)). The method proposed in this study could represent an initial step towards the full validation of the method.

Cracking Mechanism and Inhibition Strategies of Polycrystalline NCM Electrode Particles.

Developing a high-energy-density cathode material (LiNi1-x-yCoxMnyO2, NCM) for lithium-ion batteries is crucial to the electric vehicle and energy storage industries. However, the continuous insertion/extraction of Li+ generates diffusion-induced stress, causing NCM particles to crack or even pulverize, leading to battery capacity loss and limiting its wider commercial application. Current experimental studies are primarily postmortem examinations, and it is difficult to capture the particle cracking evolution. Simulation studies frequently ignore or simplify anisotropic volume contraction, demonstrating an insufficient understanding of the cracking mechanism of NCM polycrystalline particles, and cracking prevention strategies still need improvement. Therefore, we develop an anisotropic polycrystalline fracture phase-field model (AP-FPFM) that focuses on the anisotropic volume contraction of primary particles and precisely generates grain boundary distribution, coupling with Li+ diffusion, mechanical stress, and particle cracking. We employ AP-FPFM to demonstrate the behavior and mechanism of NCM polycrystalline particle cracking and illustrate the necessity and importance of anisotropic volume contraction to understand particle cracking. Furthermore, we explore the effects of average primary particle size, secondary particle size, and core-shell structure modulation on crack initiation and propagation and propose strategies to inhibit or migrate NCM polycrystalline particle cracking. This work provides theoretical support for revealing the cracking mechanism of anisotropic polycrystalline NCM particles and supplying optimization strategies to suppress particle cracking and improve the mechanical stability.

Collision frequencies across collision regimes in two-component systems

Agglomeration is the most important growth process in particle systems but modelling efforts typically assume mono-disperse primary particle distributions for the closure of the collision frequency that determines the growth rates. Real systems such as sooting flames, however, involve poly-disperse primary particle distributions. Also, systems with multiple components, where primary particles are of distinct but different sizes, cannot be treated as mono-disperse. Here, we introduce bi-disperse primary particle distributions and use Langevin dynamics simulations to develop closures for the collision kernels that are applicable over a wide range of agglomerate characteristics. The simulations cover fractal dimensions from 1.4 to 2.2, primary particle diameters from 5 nm to 50 nm, primary particle size ratios from 2 to 10 and agglomerates of up to a size of 200 primary particles with varying particle compositions. The Langevin dynamics simulations cover all collision regimes from ballistic to diffusive and allow to deduce expressions for the respective collision diameters, the hydrodynamic radii and the projected area as functions of particle characteristics. It is shown that existing expressions for the transition regime that were developed for the modelling of the collision kernel of spherical particles continue to hold for collision kernels of agglomerates in two-component systems under the condition that the collision diameters and drag coefficients are modelled accurately. An example ‘a posteriori’ simulation for a particle size ratio of 6 uses the population balance equation and demonstrates that bi-variate kernels are needed for the accurate prediction of the growth rates. Errors in predicted number density at the end of the simulations are less than 12 % while mono-variate kernels developed for mono-disperse primary particle systems overpredict the growth rate by 46%.

Powder wetting behavior and granule formation mechanism expansion in single-drop granulation

Single-drop granulation is performed under a variety of conditions to characterize the behavior that results from a liquid droplet impacting a powder bed. Drop impact velocity, liquid binder properties, powder bed consolidation status, and primary particle size are all demonstrated to have significant effects on the resulting granule formation mechanism. The process is broken down into a drop impact/drop deformation stage, a drop rebound stage, and a drop imbibition stage. These stages are often in competition with each other to determine the overall drop penetration behavior. Twelve granule formation mechanisms are identified and characterized in this study, in addition to two established granule formation mechanisms that were not observed in this work.

Revisiting Contrail Ice Formation: Impact of Primary Soot Particle Sizes and Contribution of Volatile Particles.

Aircraft contrails, formed largely on soot particles in current flights, are important for aviation's non-CO2 climate impact. Here we show that the activation of nonvolatile soot particles during contrail formation is likely determined by the sizes of primary soot particles rather than the effective sizes of soot aggregates as assumed in previous studies, which can explain less-than-unity fractions of soot particles forming contrail ice particles as recently observed during ECLIF (Emission and CLimate Impact of alternative Fuels) campaigns. The smaller soot primary sizes compared to aggregate sizes delay the onset of contrail ice formation, increase the maximum plume supersaturation reached in the contrail plume, and thus increase the probability of small volatile particles contributing to the total contrail ice particle number. This study suggests that the range of conditions for volatile plume particles to contribute significantly to the contrail ice number budget is wider than previously thought. As the aviation industry is moving toward sustainable aviation fuel and/or lean-burning engine technology, which is expected to reduce not only the emission index of nonvolatile soot particles but also the sizes of primary soot particles, this study highlights the need to better understand how the combined changes may affect contrail formation, contribution of volatile particles, and climate impacts.

Earth-abundant Li-ion cathode materials with nanoengineered microstructures

AbstractManganese-based materials have tremendous potential to become the next-generation lithium-ion cathode as they are Earth abundant, low cost and stable. Here we show how the mobility of manganese cations can be used to obtain a unique nanosized microstructure in large-particle-sized cathode materials with enhanced electrochemical properties. By combining atomic-resolution scanning transmission electron microscopy, four-dimensional scanning electron nanodiffraction and in situ X-ray diffraction, we show that when a partially delithiated, high-manganese-content, disordered rocksalt cathode is slightly heated, it forms a nanomosaic of partially ordered spinel domains of 3–7 nm in size, which impinge on each other at antiphase boundaries. The short coherence length of these domains removes the detrimental two-phase lithiation reaction present near 3 V in a regular spinel and turns it into a solid solution. This nanodomain structure enables good rate performance and delivers 200 mAh g−1 discharge capacity in a (partially) disordered material with an average primary particle size of ∼5 µm. The work not only expands the synthesis strategies available for developing high-performance Earth-abundant manganese-based cathodes but also offers structural insights into the ability to nanoengineer spinel-like phases.

Mass Transfer Resistance and Reaction Rate Kinetics for Carbohydrate Digestion with Cell Wall Degradation by Cellulase.

This paper introduces an enzymatic approach to estimate internal mass-transfer resistances during food digestion studies. Cellulase has been used to degrade starch cell walls (where cellulose is a significant component) and reduce the internal mass-transfer resistance, so that the starch granules are released and hydrolysed by amylase, increasing the starch hydrolysis rates, as a technique for measuring the internal mass-transfer resistance of cell walls. The estimated internal mass-transfer resistances for granular starch hydrolysis in a beaker and stirrer system for simulating the food digestion range from 2.2 × 107 m-1 s at a stirrer speed of 100 rpm to 6.6 × 107 m-1 s at 200 rpm. The reaction rate constants for cellulase-treated starch are about three to eight times as great as those for starch powder. The beaker and stirrer system provides an in vitro model to quantitatively understand external mass-transfer resistance and compare mass-transfer and reaction rate kinetics in starch hydrolysis during food digestion. Particle size analysis indicates that starch cell wall degradation reduces starch granule adhesion (compared with soaked starch samples), though the primary particle sizes are similar, and increases the interfacial surface area, reducing internal mass-transfer resistance and overall mass-transfer resistance. Dimensional analysis (such as the Damköhler numbers, Da, 0.3-0.5) from this in vitro system shows that mass-transfer rates are greater than reaction rates. At the same time, SEM (scanning electron microscopy) images of starch particles indicate significant morphology changes due to the cell wall degradation.

Fabrication of an In‐situ Synthesized Porous Silica‐Ruthenium‐Nickel Composite Catalyst for Hydrolysis of Ammonia Borane

AbstractThis work investigated in‐situ synthesis of porous silica‐nickel‐ruthenium composite catalysts for hydrolysis of ammonia borane. The precursors were prepared with an anionic surfactant, sodium dodecyl sulfate (SDS), to form porous structure in the precursor particles, and the precursors was treated in aqueous solution including sodium borohydride and ammonia borane for in‐situ process to parallelly activate and use the catalysts for hydrolysis of ammonia borane. The result of TEM and nitrogen sorption measurements suggested that the primary particle size of the in‐situ synthesized catalysts decrease with increasing the amount of SDS and sodium chloride as the additive for controlling the primary particle size probably because of the effect of sodium ions to inhibit nuclei growth of the primary particles. From the EDS analyses, the composition of active nickel and ruthenium contents increased with increasing the amount of SDS and sodium chloride except for the highest amount of SDS probably because of adsorption of the metal cations with the excess amount of the surfactant anion to decrease the amount of the metal cations including the catalyst. The in‐situ synthesized catalyst including small size primary particles and high nickel and ruthenium content tended to exhibit high activity for hydrolysis of ammonia borane.

Improving the predictions of black carbon (BC) optical properties at various aging stages using a machine-learning-based approach

Abstract. It is necessary to accurately determine the optical properties of highly absorbing black carbon (BC) aerosols to estimate their climate impact. In the past, there has been hesitation about using realistic fractal morphologies when simulating BC optical properties due to the complexity involved in the simulations and the cost of the computations. In this work, we demonstrate that, by using a benchmark machine learning (ML) algorithm, it is possible to make fast and highly accurate predictions of the optical properties for BC fractal aggregates. The mean absolute errors (MAEs) for the optical efficiencies ranged between 0.002 and 0.004, whereas they ranged between 0.003 and 0.004 for the asymmetry parameter. Unlike the computationally intensive simulations of complex scattering models, the ML-based approach accurately predicts optical properties in a fraction of a second. Physiochemical properties of BC, such as total particle size (number of primary particles (Npp), outer volume equivalent radius (ro), mobility diameter (Dm), outer primary particle size (ao), fractal dimension (Df), wavelength (λ), and fraction of coating (fcoating), were used as input parameters for the developed ML algorithm. An extensive evaluation procedure was carried out in this study while training the ML algorithms. The ML-based algorithm compared well with observations from laboratory-generated soot, demonstrating how realistic morphologies of BC can improve their optical properties. Predictions of optical properties like single-scattering albedo (ω) and mass absorption cross-section (MAC) were improved compared to the conventional Mie-based predictions. The results indicate that it is possible to generate optical properties in the visible spectrum using BC fractal aggregates with any desired physicochemical properties within the range of the training dataset, such as size, morphology, or organic coating. Based on these findings, climate models can improve their radiative forcing estimates using such comprehensive parameterizations for the optical properties of BC based on their aging stages.

Bridging the Gap: Scaling up Processes for the Development of Li-Rich Mn-Rich Layered Oxides

As the global demand for more powerful and long-lasting energy storage solutions continues to grow, Li-rich Mn-rich layered oxides (LMR) emerges as a promising class of next-generation cathode materials for lithium-ion batteries. The LMR material stands out due to its impressive electrochemical specific capacity, surpassing 280 mAh g–1, along with a high discharge voltage exceeding 3.5 V. It also boasts a remarkable specific energy density close to 1000 Wh kg–1, all while maintaining a relatively lower cost.Current synthesis methods often rely on batch coprecipitation reactions followed by the calcination of precipitated Mn-rich precursors. However, the inherent challenges of batch reactions, particularly in terms of reproducibility and quality, prompt the exploration of more sophisticated approaches. Moreover, the transition from benchtop experiments to large-scale production introduces a distinct set of challenges. Parameters that work seamlessly on a smaller scale may not translate as effectively when producing the material at the kilogram scale. This scaling-up process involves navigating complexities such as chemical handling risks, and challenges related to reaction heat transfer and mixing efficiency. These factors collectively underscore the difficulties in achieving precise control over critical precursor characteristics, including primary and secondary particle size, morphology, tap density, and stoichiometry.In response to these challenges, this presentation will discuss an innovative approach. High-quality Li-rich Mn-rich materials are synthesized using continuous coprecipitation, facilitated by a pre-pilot scale Taylor Vortex Reactor (TVR) at the Materials Engineering Research Facility (MERF) in Argonne National Lab (ANL). This emerging synthesis technology offers a scalable solution for the production of high-quality cathode materials. This presentation will delve into the intricacies of the synthesis process, providing valuable insights into the relationship between the characteristics of the synthesized LMR precursors and their subsequent impact on cathode performance.

Nb Doping Reduces the Primary Particle Size of the Li-Rich Cathode

Lithium-rich materials exhibit promising potential as commercial lithium-ion battery cathodes, offering a specific energy of 900 Wh.kg−1, surpassing other commercial cathode materials by more than 20%. However, challenges such as low initial efficiency, poor conductivity, and subpar cycling performance, along with rapid voltage decay, have impeded their commercialization. In this study, we propose a niobium-doping technique for lithium-rich materials. By controlling particle size during high-temperature sintering, niobium facilitates the production of highly crystalline, small-grain lithium-rich materials. This approach achieves both high capacity and long cycle life. Specifically, at 0.5 C, the pouch cell demonstrates a maximum specific capacity of 230.2 mAh.g−1, retaining 85.2% after 500 cycles, with a voltage drop of less than 0.3 mV/cycle. Additionally, we investigated the mechanism of niobium in suppressing particle growth through doping with elements of varying M-O bond strengths, obtaining systematic data.

Assessing the Effect of Fe2O3 Nanoparticles on Catalase Activity in Patients with Chronic Periodontitis: In Vitro study and Molecular Docking

Periodontal disease, also known as gum disease, is a chronic inflammatory condition that affects the supporting structures of the teeth, including the gums and underlying bone. It is primarily caused by a bacterial infection resulting from poor oral hygiene practices. The main objectives of the current study were to synthesize iron oxide nanoparticles (Fe2O3-NPs) and their characteristics were analyzed through UV, SEM, and X-ray analysis. Additionally, the dispersion of the synthesized NPs was investigated using UV and TEM techniques. The study also aimed to assess the kinetic behavior and the impact of Fe2O3-NPs on catalase activity in the saliva of the patient and control groups. The findings revealed a significant increase in catalase activity (p>0.05) in both serum and saliva of all patient groups compared to the control group. The UV-visible spectrum shows that the absorption peaks for synthesized α- and γ-iron oxide nanoparticles was at 225 nm. According to the SEM image analysis, the primary particle size of the nano-particles is approximately 26.8 nm. The X-ray diffraction results indicate that the Fe2O3-NPs range in size from 14 nm to 26 nm. UV and TEM study conclude that water a suitable solvent for Fe2O3-NPs dispersion on kinetic study of catalase (CAT) activity. The kinetic data cleared that the α-Fe2O3-NPs have an inhibitory effect for the total activity of salivary CAT in the samples of both healthy and patients with chronic periodontitis. Lineweaver–Burk graph showed that (α-Fe2O3) inhibit catalase by un comp. inhibition. γ-Fe2O3-NPs inhibited total salivary CAT activity in healthy and patients with chronic periodontitis samples. Lineweaver –Burk graph showed that (γ-Fe2O3) inhibit catalase by uncompetitive inhibition.

Synthesis of silver (Ag) nano/micro-particles via green process using Andrographis paniculata leaf extract as a bio-reducing agent

In this work silver nano/micro-particles have been synthesized using sambiloto (Andrographis paniculata) plant extract as a bio-reducing agent. The effects of different plant extract concentrations, AgNO3 precursor concentrations, and reaction time on the synthesized silver nano/micro-particles were investigated. The silver nano/micro-particles samples were then analyzed using UV-Vis spectrophotometer (UV-Vis), X-Ray Diffractometer (XRD), Field Emission Scanning Electron Microscopy (FESEM), Particle Size Analyzer (PSA), and Fourier Transform Infra-Red (FTIR) spectroscopy. The UV-Vis absorbance spectrum of the colloid silver nano/micro-particles exhibited that all samples had absorbance peaks at a wavelength around 450 nm, confirming the formation of silver nano/micro-particles. It was also found that the UV-Vis absorbance peak of the silver nano/micro-particles inversely increased with decreasing AgNO3 solution concentration. Whereas, the higher the sambiloto extract concentration the higher the UV-Vis absorbance peaks. The UV-Vis absorbance peak increased with increasing synthesis time, suggesting that silver nano/micro-particles became more prominent. The UV-Vis absorbance peaks of the silver nano/micro-particles were about 0.0462, 0.0637, 0.0729, and 0.0936 at reaction time of 5, 10, 20, and 40 min, respectively. The XRD analysis result confirmed that the synthesized silver nano/micro-particles were in the form of nanocrystals with a face-centered cubic centered without any impurities. Additionally, the FESEM images showed that the silver nano/micro-particles had the primary particle size of 150-300 nm. There was the formation of some secondary particles with the size of about 0.7-1.5?m due to the agglomeration of primary particles. The particle size distribution analysis further confirmed the presence of primary and secondary particles. Meanwhile, the FTIR analysis confirmed the presence of four main peaks, linked to functional groups in the sambiloto extract and involved in the creation of silver nano/micro-particles.

It takes three to tangle

The clustering of debris floating on liquid interfaces such as water surfaces is a complex phenomenon that finds its applications in numerous examples from industrial processing and environmental systems. The recent paper by Shin & Coletti (J. Fluid Mech., vol. 984, 2024, R7) presents an experimental campaign investigating the three effects of turbulence, particle interactions and interfacial effects, to elucidate how the three force scales drag, capillary forces and lubrication give rise to three distinct regimes of clustering in dense suspensions. The study, hence, provides a useful systematic to categorize the clustering mechanisms. As an important finding, it is shown that, depending on volume fraction and non-dimensional turbulent shear, particles either tend to cluster into aggregate sizes larger than the Kolmogorov scale or can break into pieces that are as small as the primary particle size.

New Insights into the Formation of Aggregates of Bidisperse Nano- and Microplastics in Water Based on the Analysis of In Situ Microscopy and Molecular Simulation.

Microplastics (MPs) and nanoplastics (NPs) in water pose a global threat to human health and the environment. To develop efficient removal strategies, it is crucial to understand how these particles behave as they aggregate. However, our knowledge of the process of aggregate formation from primary particles of different sizes is limited. In this study, we analyzed the growth kinetics and structures of aggregates formed by polystyrene MPs in mono- and bidisperse systems using in situ microscopy and image analysis. Our findings show that the scaling behavior of aggregate growth remains unaffected by the primary particle size distribution, but it does delay the onset of rapid aggregation. We also performed a structural analysis that reveals the power law dependence of aggregate fractal dimension (df) in both mono- and bidisperse systems, with mean df consistent with diffusion-limited cluster aggregation (DLCA) aggregates. Our results also suggest that the df of aggregates is insensitive to the shape anisotropy. We simulated molecular forces driving aggregation of polystyrene NPs of different sizes under high ionic strength conditions. These conditions represent salt concentration in ocean water and wastewater, where the DLVO theory does not apply. Our simulation results show that the aggregation tendency of the NPs increases with the ionic strength. The increase in the aggregation is caused by the depletion of clusters of ions from the NPs surface.

Tailoring Primary Particle Size Distribution to Suppress Microcracks in Ni-Rich Cathodes via Controlled Grain Coarsening

Tailoring Primary Particle Size Distribution to Suppress Microcracks in Ni-Rich Cathodes via Controlled Grain Coarsening