Evolution Of Size Distribution Research Articles

Evolution of the Floe Size Distribution in Arctic Summer Based on High-Resolution Satellite Imagery

Evolution of the Floe Size Distribution in Arctic Summer Based on High-Resolution Satellite Imagery

The plant‐level view of Korea's growth miracle and slowdown

AbstractWe analyze the evolution of the plant size distribution, static allocative efficiency and business dynamism of the Korean manufacturing sector during its growth miracle (1967–2000) and the subsequent slowdown since 2000. The average plant size has an inverse‐U pattern over time, with a peak in the late 1970s. The measure of static misallocation decreases modestly until 1983 but increases substantially afterwards. These results are at odds with what one may extrapolate from the existing cross‐country evidence on the positive relationship between plant size and economic development or the negative one between static misallocation and development. We also find that the growth rate of manufacturing productivity is not systematically correlated with either the level or the rate of change of the average plant size or static misallocation. On the other hand, business dynamism, measured by either churning or responsiveness to shocks, diminished significantly since 2000, coinciding with the decline in the growth rate of manufacturing productivity. Our findings call for more systematic research on how economic performance correlates with establishment/firm size distribution and with static and dynamic allocative efficiency.

Is a more physical representation of aerosol chemistry needed for fog forecasting?

AbstractWith the changing climate, the study of fog formation is essential due to the impact of the complexity of natural and anthropogenic aerosols. The evolution of the droplet size distribution in the presence of different aerosol species remains poorly understood. To make progress towards reducing the uncertainty of fog forecasts, the Eulerian–Lagrangian particle‐based small‐scale model for the diffusional growth of droplets is used to better understand the droplet activation and growth. The small‐scale model simulations are performed using observed data from the Winter Fog Experiment study over Indira Gandhi International Airport, New Delhi. The microphysical properties, such as droplet number concentrations (Nd) and liquid water content (LWC), important for fog simulation, are evaluated to gain more insights. The small‐scale simulations have shown the droplet microphysical properties at different evolutionary stages. The Nd and effective radius change with variations in LWC for different aerosol chemistries (i.e., organics, mix, and inorganic). The calculated visibility at small scale is also shown with the variation of Nd and LWC. This study compared visibility from an existing parametrization with parcel–direct numerical simulation calculation. The hygroscopicity , which is highly related to the activation of aerosols to condensation nuclei, is taken into account to demonstrate the contribution of aerosol chemistry to fog droplet formation. The results highlight that hygroscopicity is essential in the numerical model for fog and visibility prediction as the microphysical properties of fog are regulated by aerosol species.

Evolution of grain size distribution in the circumgalactic medium

Abstract In order to theoretically understand dust properties in the circumgalactic medium (CGM), we construct a dust evolution model that incorporates the evolution of grain size distribution. We treat the galaxy and the CGM as separate one-zone objects, and consider the mass exchange between them. We take into account dust production and interstellar dust processing for the galaxy based on our previous models, and newly incorporate sputtering in the hot phase and shattering in the cool phase for the CGM. We find that shattering increases the dust destruction (sputtering) efficiency in the CGM. The functional shape of the grain size distribution in the CGM evolves following that in the galaxy, but it is sensitive to the balance between sputtering and shattering in the CGM. For an observational test, we discuss the wavelength dependence of the reddening in the CGM traced by background quasar colors, arguing that, in order to explain the observed reddening level, a rapid inflow from the CGM to the galaxy is favored because of quick dust/metal enrichment. Small grain production by shattering in the CGM also helps to explain the rise of dust extinction toward short wavelengths.

A constrained machine learning surrogate model to predict the distribution of water-in-oil emulsions in electrostatic fields

Accurately describing the evolution of water droplet size distribution in crude oil is fundamental for evaluating the water separation efficiency in dehydration systems. Enhancing the separation of an aqueous phase dispersed in a dielectric oil phase, which has a significantly lower dielectric constant than the dispersed phase, can be achieved by increasing the water droplet size through the application of an electrostatic field in the pipeline. Mathematical models, while being accurate, are computationally expensive. Herein, we introduced a constrained machine learning (ML) surrogate model developed based on a population balance model. This model serves as a practical alternative, facilitating fast and accurate predictions. The constrained ML model, utilizing an extreme gradient boosting (XGBoost) algorithm tuned with a genetic algorithm (GA), incorporates the key parameters of the electrostatic dehydration process, including droplet diameter, voltage, crude oil properties, temperature, and residence time as input variables, with the output being the number of water droplets per unit volume. Furthermore, we modified the objective function of the XGBoost algorithm by incorporating two penalty terms to ensure the model’s predictions adhere to physical principles. The constrained model demonstrated accuracy on the test set, with a mean squared error of 0.005 and a coefficient of determination of 0.998. The efficiency of the model was validated through comparison with the experimental data and the results of the population balance mathematical model. The analysis shows that the initial droplet diameter and voltage have the highest influence on the model, which aligns with the observed behaviour in the real-world process.

Grain Size in Landscapes

Earth's terrestrial topography evolves in response to the interaction of tectonics, climate, and lithology. Recent discoveries suggest that the grain size of sediments produced on hillslopes and transported through river networks is key to understanding these interactions. Hillslope grain size varies systematically with erosion rate and residence time, the degree of chemical and physical weathering, and the fracture density and susceptibility to weathering of rock. Variations in initial grain size strongly influence the spatial evolution of grain size distributions as particles mix and wear during downstream transport through channel networks. In rivers, the size and flux of the coarse fraction of the sediment load control the rate of incision into bedrock and thus govern channel slope and ultimately the relief of actively eroding landscapes. These relationships suggest that a primary way that tectonics, climate, and lithology influence landscape evolution is through their controls on sediment grain size. ▪ Recent research reveals the central role of sediment grain size in controlling bedrock river morphodynamics, linking grain size to channel slope and topographic relief. ▪ Tectonics, climate, and lithology govern the size of sediments produced on hillslopes; hence, grain size mediates their influence on landscape evolution. ▪ Feedbacks linking sediment grain size, topography, weathering, erosion, and sediment transport provide new opportunities for advances in Earth surface science.

On Nucleation Pathways and Particle Size Distribution Evolutions in Stratospheric Aircraft Exhaust Plumes with H2SO4 Enhancement.

Stratospheric aerosol injection (SAI) is proposed as a means of reducing global warming and climate change impacts. Similar to aerosol enhancements produced by volcanic eruptions, introducing particles into the stratosphere would reflect sunlight and reduce the level of warming. However, uncertainties remain about the roles of nucleation mechanisms, ionized molecules, impurities (unevaporated residuals of injected precursors), and ambient conditions in the generation of SAI particles optimally sized to reflect sunlight. Here, we use a kinetic ion-mediated and homogeneous nucleation model to study the formation of H2SO4 particles in aircraft exhaust plumes with direct injection of H2SO4 vapor. We find that under the conditions that produce particles of desired sizes (diameter ∼200-300 nm), nucleation occurs in the nascent (t < 0.01 s), hot (T = 360-445 K), and dry (RH = 0.01-0.1%) plume and is predominantly unary. Nucleation on chemiions occurs first, followed by neutral new particle formation, which converts most of the injected H2SO4 vapor to particles. Coagulation in the aging and diluting plumes governs the subsequent evolution to a narrow (σg = 1.3) particle size distribution. Scavenging by exhaust soot is negligible, but scavenging by acid impurities or incomplete H2SO4 evaporation in the hot exhaust plume and enhanced background aerosols can matter. This research highlights the need to obtain laboratory and/or real-world experiment data to verify the model prediction.

Unraveling grain growth of metallic tungsten: Investigating the nanoscale realm of hydrogen reduction of tungsten oxides

This paper focuses on the experimental observation of tungsten grain evolution during the process of hydrogen reduction of tungsten trioxide. The objective is to gain insights into the grain size distribution (GSD) evolution and morphology changes of metallic tungsten. The study employs an amalgamation of conventional characterization techniques – such as TGA, SEM-EDS, TEM and XRD – alongside cutting-edge techniques like phase contrast nano-tomography from synchrotron sources. Conducted as a quasi in-situ study, this research offers the opportunity to observe the transient evolution of the formed metallic tungsten phase within its precursor WO2 particles. The paper presents and discusses quantitative results concerning the evolution of GSD and morphological changes, encompassing growth rates of both crystallites and grains of the synthesized metallic phase. Additionally, the quasi in-situ study highlights the dependence of grain size on water concentration during the reduction process. The qualitative and quantitative findings contribute to a more nuanced understanding of the kinetics of grain growth of metallic tungsten and offer insights into the intricate interplay between reduction parameters, GSD evolution and morphological changes. Gaining a deeper understanding of the underlying mechanisms driving the changes in GSD establishes a foundation for predictive theory with immediate academic and industrial impact.

Modeling titanium dioxide (TiO2) nanoclusters using a 2D sectional method with molecular dynamics (MD) determined coagulation rates

Accurate prediction of the particle size distribution (PSD) evolution of growing nanometer scale particles is important in designing gas-phase synthesis reactors for the production of nanomaterials. Towards improved predictions of growth, we model the evolution of the PSD of 1-4 nm TiO2 particles from the decomposition of titanium tetraisoproxide (TTIP) using a two-dimensional (2D) sectional method, uniquely with coagulation rates derived from molecular dynamics (MD) trajectory calculations which account for detailed particle–particle interactions. The PSDs predicted by the 2D sectional method are compared to recent experimental measurements of PSDs in the 1-3 nm range in a flow tube reactor. The nucleation of particles is modeled based on prior mobility measurements of ions attributed to TTIP and their decomposition, with the specific nucleation rate here fitted as a fraction of base nucleation rate (k) derived from these prior measurements. In the 2D sectional model, we examine the influence of the initial (nucleated) particle charge distribution on the PSD, with different coagulation rate coefficients for neutral-charged and charged-charged particle collisions. With the MD-derived coagulation rate coefficients, we find that using nucleation rate coefficients between 0.005k and 0.03k leads to strong agreement between modeled PSD and measured PSD for a wide variety of experimental residence times, initial TTIP concentrations and temperatures. Increasing the charge fraction from 0% (uncharged) to 80% (bipolar) does not result in a significant change in the PSD, because the particles rapidly self-neutralize through coagulation based on the simulation results. The results with MD-derived coagulation rate coefficients are compared to those of the sectional method with classical kinetic theory of gases (KTG) rates with a constant enhancement factor to account for potential interactions. Through comparison, we find that the predictions from the classical KTG model consistently exhibit weaker coagulation rates than the MD-derived model during the PSD evolution.

Modelling W/O/W double emulsions preparation in static mixers: Accounting for the shear-thinning behaviour of the dispersed phase

The dispersion of a shear-thinning non-Newtonian fluid using in-line mixers to prepare double emulsions is investigated experimentally and numerically in this study. A two-step method is adopted for the preparation of double emulsions, comprising in a first step the preparation of a reverse water-in-oil (W/O) emulsion using a high-shear rotor-stator device. This inner emulsion is dispersed in a second step into an outer aqueous phase by continuous parallel pumping of both phases through a set of static mixers. The second preparation step is modelled using a population balance equation (PBE) accounting for droplet breakage inside the mixers. Since the inner emulsion behaves as a shear-thinning fluid, the breakage efficiency depends on the local shear rate. Using classical turbulent breakage kernels is therefore inappropriate, hence there is a need for a kernel accounting for the shear-thinning character of the dispersed phase. To tackle this issue, single-phase CFD simulations of the fluid flow through the mixers are carried out showing a high shear rate magnitude near the walls of the pipe and the mixer crossbars. To avoid CFD-PBE direct coupling, the probability density function (PDF) of the shear rate is extracted from the CFD simulations. This PDF is then used to develop a volume-averaged PBE, where a classical Ostwald-de Waele model is employed to relate the apparent viscosity of the inner emulsion to the shear rate. Different experimental parameters influencing the quality of the dispersion are investigated, including the fraction of the inner emulsion phase, the oil viscosity and the inner and outer aqueous phase viscosities. In the different cases, the model captures the transient evolution of the droplet size distribution of the W/O/W double emulsions at the outlet of the mixers while the computational time remains very low.

Simulation on liquid phase sintering of CeO2-CoO ceramic by diffusional Monte Carlo Potts model

Difficulty in control of in-situ crystal growth of CeO2-CoO ceramics limits its catalyst application of solid oxide fuel cells. It is necessary to explore a method to simulate the microstructure growth process of this ceramics under high temperature. In this work, the diffusional Monte Carlo Potts model for the simulation on liquid phase sintering of CeO2-CoO ceramics is established. With geometric and concentration-dependent probability calculated, the phenomena of solidification and melting in liquid phase sintering process are simulated. Moreover, effects of diffusion and grain consolidation are also taken into consideration. The simulation on both isothermal sintering and cooling process is run. The properties of grain growth, grain size distribution and sintering neck evolution are studied. It is found that the grain growth exponent, temporal revolution of grain number and sintering neck obtained from simulation basically agree with relevant theories. In addition, grain size distribution basically remains constant and follows lognormal distribution during the sintering process. This work provides a method to study the in-situ crystal growth process of liquid phase sintered ceramics.

Application of PAT Probes in Aluminum Phosphate Adjuvant Manufacturing.

This study is focused on monitoring process parameters and quality attributes of aluminum phosphate (AlPO4) using multiple in-line probes incorporated into an industrial-scale adjuvant suspension manufacturing unit. The manufacturing of aluminum adjuvant suspension was monitored at manufacturing scale using conductivity, turbidity, infrared, and particle sizing and count probes to follow the continuous evolution of particle formation and size distribution, and the reaction kinetics during the synthesis of AlPO4. The data showed that AlPO4 forms large particles at the early stages of mixing, followed by a decrease in size and then stabilization towards the later stages of mixing and pH adjustment. The results provided a complementary view of process events and assisted in optimizing several parameters, e.g., flow rate of reactants AlCl3 and Na3PO4 solutions, mixing rate, pH, and conductivity of AlPO4, as well as adjuvant quality attribute such as particle size, thus streamlining and shortening the process development stage. The results of this study showed the usefulness of the in-line probes to automate continuous assessment of AlPO4 batch-to-batch consistency during in-house adjuvant production at the industrial scale.

A journey through space and time in the Godbert-Greenwald furnace: The evolution of a dust cloud particle size distribution

Minimum Ignition Temperature (MIT) characterizes the ignition sensibility of a dust cloud. This work assesses the role of a standard Godbert-Greenwald furnace in the agglomeration/deagglomeration and fragmentation phenomena. Several organic powders and different dispersion pressures were tested. The average residence time varied from 120 to 330 ms according to the amount of powder injected and the pulse pressure. Entanglement was observed for coarser cellulose particles, while surface cohesion forces characterised the agglomerates of finer cellulose, glucose and ascorbic acid. The latter was characterised by fragmentation, especially at 0.5 and 1 bar(g). Biot, Pyrolysis and Damköhler numbers were used to analyse the effects of cellulose agglomeration and deagglomeration. At 600 K, the pyrolysis is the rate-limiting step, but from 700 K, the external heat transfer becomes the rate-limiting step, which would not happen without agglomeration. Due to the particle size distribution evolution, but also to turbulence and residence time variation, MIT can vary by 50 °C.

Large eddy simulation-bivariate sectional model for non-spherical TiO2 nanoparticle synthesis in flame

Numerical simulation of nanoparticle synthesis in flame necessitates a high level of fidelity for turbulent flame, as well as delivers more detail insight into the evolution of structure and size distribution of particles undergoing various dynamic events. In the present work, a new simulation approach coupling large-eddy simulation (LES) and bivariate sectional model is proposed to explore the synthesis of nanoparticles in turbulent flame. More specifically, the nonlinear LES-partially stirred reactor model (NLES-PaSR) is utilized to simulate the turbulent flame, wherein the gradient-type structural subgrid-scale (SGS) model for turbulent flow and partially stirred reactor (PaSR) model for turbulent combustion are considered. In addition, the volume-based bivariate sectional model is thoroughly coupled with the LES model for the first time to describe the spatiotemporally resolved formation and growth of nanoparticles using particle number concentration and surface area concentration as two sets of variables. Compared directly with the LES-monodisperse (LES-Mono) and LES-univariate sectional (LES-UniSe) models, the LES-bivariate sectional (LES-BiSe) model has significant advantages in its ability to analyze and predict the size, morphology, as well as polydispersed particle size distribution (PSD) evolution of nanoparticles at a moderate computational cost simultaneously. In the LES framework, the proposed model successfully simulates the spatiotemporally resolved formation and growth of non-spherical TiO2 nanoparticle in turbulent diffusion burner. The predicted results derived from the LES-BiSe model are in good agreement with the experimental measurements. Also, the aggregate and primary particle size distribution shows highly temporal fluctuation, which mainly results from the continuous variations of particle path induced by the unsteady turbulent combustion. Furthermore, the present work demonstrates the profound dependence of particle morphological on both spatiotemporal evolution and their intrinsic size distribution. In particular, the large aggregates in the higher sections are commonly found as irregular structure with fractal-like dimensions.

Modelling of droplet multiple breakage accounting for entire energy spectrum bottleneck effect and eddy-droplet discrepancy

This work focused on the contribution of the two aspects of entire energy spectrum bottleneck effect and eddy-droplet discrepancy to droplet multiple breakage simulation. The droplet breakage mechanism model was closured by more accurate turbulent parameters determined by accounting for the bottleneck effect and a formula was proposed to consider the effect of the eddy-droplet discrepancy. The influences of the two aspects on collision/interaction frequency density, breakage probability, breakage frequency and daughter size distribution (DSD) were analyzed. The proposed model agreed well with the measured breakage frequency, relative proportion of multiple breakage modes and DSDs from single droplet experiments and drop swarm experiments. The predicted size distribution evolution also exhibited a better agreement with experimental data by comparing with other models. An obvious quantitative prediction difference on whether to consider the two aspects proved the necessity and advantage of model development.The bottleneck effect represents a physical phenomenon fully validated by experimental data and direct numerical simulation results. Ignoring bottleneck effect hinders the acceptable reproduction of longitudinal velocity gradient skewness, while considering it obviously increases the quantitative prediction accuracy of turbulence parameters. Considering the physical fact that turbulent eddies will disappear, the eddy-droplet discrepancy neglected by existing mechanism model is used to characterize the impact of eddy lifetime on eddy-droplet collision/interaction. To summarize, the improvements of this work are beneficial for consolidating the breakage model physical foundation.

Modeling the distribution characteristics of vapor bubbles in cavitating flows

Dispersed vapor bubbles are the dominant rheology in cloud cavitation, and their size distribution is directly associated with cavitation noise and erosion. However, the numerical resolution of large numbers of dispersed bubbles remains a challenge. In this work, we establish a new cavitation model based on the population balance equation (PBE) that can predict the size distribution and spatiotemporal evolution of bubbles within cloud cavitation under different cavitation numbers. An expression for the phase transition source term without empirical parameters is derived based on the bubble size distribution (BSD) function, enabling the coupling of mass transfer in the governing equations with the PBE cavitation model. The cavitation model is solved alongside the Eulerian homogeneous mixture flow. The mass transfer between water and vapor, and the bubble coalescence and breakup under turbulent flows, are modeled to determine the BSD. The numerical model is carefully validated through comparisons with experimental results for cavitation flows on a wedge-shaped flat plate, and good agreement is achieved with respect to the pressure distribution, void fraction, and BSD. This confirms that our proposed cavitation model can accurately predict the void fraction and BSD within the cloud cavitation region.

Experimental and numerical investigation on soot formation and evolution of particle size distribution in laminar counterflow ethylene flames

A detailed investigation of the process of soot formation in ethylene-fueled laminar counterflow diffusion flames is conducted using dedicated experiments and numerical simulations. Two different strategies based on the Discrete Sectional Method (DSM) and the Split-based Quadrature Method of Moments (S-EQMOM) are considered to model the evolution of soot particle size distributions, and their comparative assessment is carried out for soot formation prediction and particle growth. A consistent chemical reaction mechanism describing the oxidation of hydrocarbon fuels and the prediction of soot precursors with the growth of polycyclic aromatic hydrocarbons (PAHs) up to pyrene ( ▪ ) is examined. Experiments for various strain rates and fuel compositions are performed to assess the sensitivity of soot production to these two parameters. The results show that both modeling strategies captured well the qualitative trends of soot volume fraction under variations in strain rate and mixture composition, with slight over-prediction of the peak values. For both soot models, a higher sensitivity of soot formation is noticed by changes in mixture composition compared to those of strain rate variation. Additionally, the soot models demonstrated promising performance in capturing the experimentally observed evolution of the soot particle size distribution (PSD).

Turning fly ash and waste gypsum into a resource for backfilling applications

Flue Gas Desulfurization Gypsum (FGDG), an industrial by-product generated by power plants, was thermally treated and incorporated in cement-free fly ash bricks. This study aimed to determine the effects of using a thermally treated FGDG as an additive to improve the mechanical and structural properties of cement-free fly ash bricks. FGDG was thermally treated for 2 h at different temperatures. The influence of varying amounts (10–50%) of thermally treated FGDG on the performance of cement-free bricks was analyzed through mechanical properties, micrography, durability, the evolution of particle size distribution and environmental characteristics experiments. The effect of curing temperatures and curing age on the strength development and microstructural properties was also investigated. A Toxicity Characteristic Leaching Procedure (TCLP) was carried out to determine the leachability of metals from the synthesized FA cement-free brick. The results showed that the FGDG had a high calcium oxide content. In contrast, FA is mainly composed of silica, and both materials carry cementitious properties making both good raw materials for this study. The FA cement-free bricks containing 30% of thermally treated FGDG, oven-cured at 60 ℃, yielded the highest unconfined compressive strength (UCS) of 7.14 MPa. However, curing at ambient temperature for 28 days yielded a better UCS of 7.37 MPa. The particle size distribution showed that particles transformed from fine particles at 7 days to larger particles at 28 days due to particle growth. Durability tests showed that the developed bricks could withstand 7 wet/dry cycles. The TCLP showed that the leachability concentrations of all metals are within the limit and, therefore, can be potentially used as a building material in backfilling. The synthesis of FA/FGDG composite will aid in reducing the generated waste gypsum in landfills consequently eradicating human health challenges and loss of biodiversity. This paper showed that developing FA/FGDG composites will reduce their environmental impact and make them a resource for other valuable products such as backfilling applications and green building bricks.

A one-dimensional model for Pt degradation and precipitation in proton exchange membrane fuel cell considering Pt nucleation, particle size growth, and band formation

Reducing Pt catalysts amount without sacrificing the performance and durability is critical for the commercialization of proton exchange membrane fuel cells (PEMFCs). Pt degradation in the cathode catalyst layer (CCL) decreases the electrochemically active surface area (ECSA), and Pt precipitation, especially Pt band formation, has a significant effect on proton exchange membrane (PEM) stability, resulting in severe PEMFC degradation during long-term operation. In this study, a one-dimensional model is developed focusing on Pt catalyst degradation and precipitation, including Ostwald-ripening, mass loss, precipitation in the PEM from nucleation, particle size growth, to Pt band formation. The model accuracy is comprehensively validated against the corresponding experimental data, including ECSA loss and particle size distribution (PSD) evolution in the CCL under different operating conditions (temperature, relative humidity, and loading mode), as well as the precipitated Pt size distribution characteristics and local potential in the PEM. Using this model, the Pt band formation process is comprehensively analyzed, and the effects of operating conditions on Pt degradation and Pt band formation are investigated in detail. It is found that the nucleation stage is brief, and then the significant inhomogeneity at the size growth stage causes Pt band formation. In addition, the high activation enthalpy of dissolution under low humidity can effectively inhibit Pt degradation, and Ostwald-ripening is the mean cause of Pt degradation, which is likely to occur during the rapid voltage change period.

Dynamic coassembly of nanodiamonds and block copolymers in organic solvents

Nonaqueous suspensions of nanoparticles have potential value in a wide range of applications, from coatings to environmental remediation. However, organic solvents often lead to nanoparticle agglomeration, and few methods developed to counteract this phenomenon. We present a novel approach to achieve stable nanoparticle suspensions in both nonpolar and polar aprotic solvents. Our method utilizes nanodiamonds (NDs) as a model system, due to the rich nature of their surface chemistry. This technique involves three key steps: (1) ultrasonication of air-oxidized NDs (OXNDs) in dimethylacetamide (DMAc), (2) the introduction of amphiphilic dispersants primarily composed of PVA-b-PMMA block copolymers (BCPs), and (3) exchanging DMAc with organic solvents to promote composite micelle formation, where BCP forms the micelle corona encapsulating OXND as the micelle core. Our method yields stable suspensions with particle sizes strongly influenced by thermokinetic interactions between OXND, BCP, and the solvent. Dynamic light scattering measurements of OXND–PVA-b-PMMA suspensions demonstrate that stabilization in toluene is governed by steric hindrance, while in THF or CHCl3 both electrostatic repulsion and steric hindrance contribute to particle stabilization. Characterization through electron microscopy and AFM reveals the efficacy of our coassembly method for producing uniformly-sized composite micelles. We identify a critical BCP:OXND weight ratio, analogous to the critical micelle concentration in surfactant-stabilized suspensions, crucial for effective particle stabilization. By analyzing the evolution of particle size distribution with varying solvent composition, we propose a dynamic coassembly mechanism between OXND and BCP, wherein OXND particles and encapsulating BCP chains dynamically rearrange to reach an equilibrium structure as the thermodynamic quantities of the surrounding medium change. Furthermore, BCP micellization is shown to play a vital role in preventing OXND aggregation during solvent exchange, resulting in uniformly sized particles. This enhanced understanding of the OXND–BCP coassembly mechanism in organic solvents holds promise for the development of novel functional materials. Our study provides insights into fabricating stable nanoparticle suspensions with diverse applications to coatings, lubricants, drug delivery, nanocomposite materials, biosensing, medical imaging, and environmental remediation.