Kinetic modelling of tomatine extraction from tomato plant waste: influence of solvent, particle size, solvent concentration and solvent ratio

Optimizing compressive strength in eco-friendly cement composites using CO₂-sequestered precipitated calcium carbonate by particle size and replacement ratio

A predictive model based on key particle properties for segregation of free-flowing powder blends measured using Near-Infrared spectroscopy.

The variation law and mechanism of the permeability characteristics of coal gangue ceramsite lightweight aggregate concrete (CLAC) remain unclear. Therefore, in this study, the effect of the ceramsite size and replacement ratio on the pore structure characteristics of the CLAC was analyzed by mercury pressure test. Moreover, based on a fractal approach, the relationship between permeability characteristics and pore structure of the CLAC was established. The results indicate that incorporating coal gangue ceramsite effectively decreases the maximum pore size. The fractal dimension increases as the replacement ratio of 20–30 mm and 10–20 mm ceramsite rises, whereas an opposite trend is observed when the content of 5–10 mm ceramsite increases. At moderate replacement levels, the introduction of ceramsite aggregates can reduce the fraction of detrimental pores and promote the formation of harmless and slightly harmful pores; however, at high replacement levels, the fraction of harmful and macropores may increase. Moreover, the fractal dimension is negatively correlated with the permeability grade and residual strength, but positively correlated with the strength degradation rate.

ABSTRACT Zhundong coal has severe slagging and fouling from alkali metals, with sintering being the most critical step in slagging. Co – firing with kaolin is a relatively effective solution to these issues, but the sintering mechanism of kaolin on Zhundong coal ash remains unclear, which limits the optimization of its addition ratio and particle size parameters. In this study, the effects of kaolin particle size and addition ratio on the sintering characteristics of Zhundong coal ash were systematically investigated. The results indicated that as the temperature increased, the area shrinkage rate of ash blocks underwent stages of stabilization, decrease, increase, and rapid decrease. After kaolin was added, the temperature at which the shrinkage rate began to decrease was increased by approximately 100°C compared with that of the raw coal ash. At the sintering temperature, when kaolin with larger particle sizes was added, the ash blocks tended to form an abundant porous structure, thereby reducing the compactness of the ash blocks. The sintering strength of the ash blocks increased with an increase in addition ratio but decreased with an increase in particle size. When the addition ratio of 100–150 µm kaolin reached 3 wt.%, the sintering strength of the ash blocks decreased to 6.15 MPa, a 23.9% reduction compared to that without kaolin. Furthermore, after the addition of kaolin, NaAlSiO4 was detected in all ash samples, which is consistent with the conclusion that kaolin can capture alkali metals in coal ash. Finally, the influence mechanism of kaolin on the sintering process of Zhundong coal ash was proposed.

When considering effective interactions in a many-body or thermodynamic system, it is important to recognize that the inherent character of the effective forces between two bodies already incorporates many-body effects that appear unified in a nontrivial way. Working backward to disentangle these effects into the contributions of pairs, triplets, or larger groups is generally complicated and seldom accomplished. However, this could offer essential insights into the structural architecture and self-assembly of complex systems, such as soft materials. In this contribution, we tackle this problem by employing a simulation-based method, here termed contraction of the bare forces (CBF), which, on the one hand, permits a precise evaluation of the effective interactions between colloids [de los Santos-López et al.,J. Chem. Phys. 157, 074903 (2022)0021-960610.1063/5.0099919] and, on the other hand, makes it possible to quantify the many-body contributions to these effective interactions. The CBF approach is applied to calculate the depletion forces in asymmetric binary mixtures of hard spheres; the approach is sufficiently sensitive to quantify the effects of higher-order terms on the depletion forces between large particles. To assess the accuracy of our approach, we first explore and confirm the long-established prediction founded on purely geometric considerations, which states that for the particle size ratio, q, smaller than q<q_{3}=0.1547, the depletion interaction between large colloids does not depend on the concentration of large particles, provided that the chemical potential of the smaller particles is kept constant. In contrast, for mixtures with less size asymmetry, such effects become considerably influential. Specifically, we have conducted an in-depth examination of scenarios with size asymmetries values of q=0.45 and 0.60. We directly compare our results for the depletion forces with those obtained from the integral equationframework for effective interactions. Through the use of a naive approximation formulated at the level of the bridge functions, this comparison has further enabled us to identify higher-order contributions to the depletion forces between large colloids, thereby improving and sharpening the underlying theoretical approximations. More importantly, in this work, we explicitly disentangle the many-body components of the depletion forces and assess how significantly they affect the contact attraction strength as a function of both the size ratio and the concentration of the large colloids.

Deep learning assisted particle size ranking and estimation from SEM images without explicit segmentation.

ABSTRACT Internal stability is an important attribute for granular soils in assessing the sensitivity to suffusion. The particle composition of soil matrix can be used to establish the internal stability criterion. Overviews of current researches on the soil skeleton, the critical particle size for the skeletal fraction is unclear and inadequate, especially for soil matrix with significant fine contents. The content of erodible particles cannot be accurately determined to assert the internal unstable. In this article, a new formula for identifying the critical particle size of soil matrix with a particular particle size distribution is derived analytically. The soil particles are separated into filling and skeletal fractions based on their influence on the matrix volume. A modified experimental method is designed to investigate the separation point of particle fractions using the discrete element numerical simulation. The results indicate that the critical particle size of fractal‐graded soil can be expressed as a function concerning particle size ratio and fractal dimension. Particles larger than the critical particle size belong to the skeletal fractions, the remaining particles are the filling fractions that implicate the potential erodible particles in suffusion. A new geometrical criterion is proposed to evaluate whether soil matrix is overfilled by filling fractions based on the critical mass ratio rather than conventional fine content thresholds, which demonstrates broader applicability across widely graded soils. This study will facilitate further research on the internal stability of graded soils, the design of filter layers, and establishing a unified criterion for assessing the sensitivity to suffusion.

Synergetic preparation of flaky α-Al2O3 with large particle size and high aspect ratio via seed-induced epitaxial growth and calcination strategy

Imparting anisotropic interactions to isotropic particles is a critical challenge in colloidal science. While DNA functionalization enables programmable assembly, creating distinct patches often requires intricate, heterogeneous surface chemistries. We address this limitation by introducing a robust, ligation-assisted strategy to engineer DNA patchy colloids from uniform spheres. By coupling sequential DNA hybridization with enzymatic ligation, we achieve the covalent immobilization of distinct DNA functionalities without requiring complex surface prepatterning. Characterization using confocal fluorescence microscopy confirms the structural integrity and spatial resolution of the resulting patches. We further show that patch geometry in assembled clusters is tunable via the core-to-shell particle size ratio (α). This streamlined, covalent functionalization method provides a versatile platform for designing biointerfaces and advancing the self-assembly of programmable matter.

Sinking marine snow particles, composed primarily of organic matter, control the global export of photosynthetically fixed carbon from the ocean surface to depth. The fate of sedimenting particles is partly regulated by their encounters with suspended objects, which leads to mass accretion and potentially alters their buoyancy, and with bacteria that can colonise the particles and degrade them. Their collision rates are typically calculated using two types of models focusing either on direct (ballistic) interception with a finite interaction range, or advective-diffusive capture with zero interaction range. Yet, since many relevant marine encounter scenarios span across both regimes, quantifying such encounters remains challenging because the two models yield asymptotically different predictions at high Péclet numbers. We reconcile the two approaches by quantifying encounters in the general case using theoretical analysis and simulations. By solving the advection-diffusion equation in Stokes flow around a sphere to model mass transfer to a sinking particle by finite-sized objects, we determine a new formula for the Sherwood number as a function of the Péclet number and the ratio of particle sizes. Contrary to the common assumption, we find that diffusion still plays a significant role in generating encounters even at high Péclet numbers. We predict that at Péclet numbers as high as 10 6 the direct interception model underestimates the encounter rate by up to two orders of magnitude. This overlooked contribution of diffusion to encounters suggests that processes affecting the fate of marine snow may proceed at a rate much higher than previously thought.

In complex-composition fluid environments, fine solid particles exacerbate cavitation on equipment surfaces, accelerating surface erosion and damage. This study employs high-speed photography and Kelvin impulse theory to investigate bubble collapse dynamics near triple unequally sized particles, mainly focused on the particle size ratio effect and associated symmetry-breaking behavior. Key findings include: (1) The size ratio of the particles has a significant influence on the bubble collapse morphology, and an increase in the size ratio exacerbates the asymmetric deformation of bubbles. (2) The size ratio of the particles has a pronounced effect on the velocity field of the ambient flow field surrounding the bubble, and an increase in the size ratio aggravates the inhomogeneity of the liquid velocity distribution. (3) The increase in the size ratio of the particles leads to a decrease in the number of zero-Kelvin impulse points and changes in their positions.

Extensive research and empirical evidence demonstrate that nanofluids enhance heat transfer efficiency in microchannels, but this improvement is often accompanied by increased pressure drop and particle clogging. This study aims to determine the optimal parameters for preparing stable nanofluids and to discuss the effects of different parameters on thermal and hydraulic performance. By analyzing the impact of varying ultrasonication time, particle concentration, particle size, surfactant type, and mixing ratios on stability, the most stable nanofluid was selected for evaluation of flow heat transfer and cost-effectiveness. Results indicate that a 1:1 mixed nanofluid of TiO2 (20 nm)-SiO2 (50 nm) exhibits optimal stability under conditions of 90 min ultrasonication, 0.20 vol% total particle concentration, and 0.15 wt% xanthan gum. At a Reynolds number of 550, this mixed nanofluid exhibits superior thermal performance. Compared with deionized water, its convective heat transfer coefficient and Nusselt number increase by 40.25% and 37.94%, respectively, while the pressure drop rises by only 17.18%. The performance evaluation criterion reaches 1.43, accompanied by a high cost-performance factor. These findings demonstrate that mixing large and small particles of TiO2 and SiO2 not only significantly enhances thermal performance but also positively impacts stability and hydraulic properties. A 90 min ultrasonic treatment time markedly improves stability and optimizes dynamic light scattering results.

Particle size segregation is a common occurrence in sheared granular flows under gravity. Segregation of size-bidisperse grain mixtures at size ratios of three or less has been extensively studied, but comparatively little is known about segregation of grains with more widely varying sizes, despite their relevance to natural and industrial flows. At larger size ratios the segregation behaviour of bidisperse mixtures may change drastically, including reversal of the direction of segregation, which no existing continuum model accounts for. This paper investigates the segregation behaviour of bidisperse granular mixtures up to a size ratio of seven and formulates a new continuum model for size segregation that captures the observed suppression and reversal of segregation. Discrete element method (DEM) simulations of flows on an inclined plane show a reversal of behaviour as the volume fraction of small particles increases, from states where the large particles rise to the free surface to states where they sink. At intermediate small-particle volume fractions, segregation is significantly reduced or even entirely absent, leading to well-mixed flows. In addition, a striking layering effect is observed at large size ratios, where large particles organise into distinct layers one particle thick, separated by thin bands of small particles. This layering is demonstrated both in simulations and, for the first time, in laboratory experiments. The continuum segregation model introduces a new bidirectional segregation flux that accounts for the reversal in segregation. The model is in good quantitative agreement with DEM simulations across a range of small-particle volume fractions.

Despite the common occurrence of hydrate particle agglomerationsin engineering applications and naturally occurring environments,there is still a gap in exploring the agglomeration mechanism of gashydrate particles in aqueous solutions due to the experimental challengesand limitations. Herein, particle agglomerations of methane hydratesare investigated by using dissipative particle dynamics. Our resultsshow that the agglomeration behaviors of methane hydrate particlesare related to particle sizes, the particle size ratios, and the shapesof hydrate particles. Before hydrate particle agglomerations, thedistance between any two hydrate particles in these hydrate particlesystems exhibits an oscillation manner, and their fluctuation amplitudestrongly depends on the particle sizes. Furthermore, the hydrate particlemotions in those agglomeration processes are consistent with previousstudies at the microscopic scale. This work not only extends the researchscale of hydrate particle agglomerations but also provides a new computationalmethod framework for gas hydrate communities in the world.

The conversion of agricultural residues into biomass briquettes presents a sustainable alternative for energy generation, addressing waste management challenges, reducing fossil fuel dependence, and mitigating carbon emissions. This study analyzes the influence of material mesh granularity and corn cob-to-coconut shell residue blend composition on the energy content and quality metrics of extruded briquettes. The primary objective is to investigate the effects of formulation parameters on energy yield (calorific value), structural durability (shatter index), and ash content. Employing an experimental approach combined with statistical analysis (Analysis of Variance (ANOVA) and Friedman test), the impacts of varying mesh sizes and compositional mass ratios were systematically evaluated. The results showed that calorific values ranged between 4,739–5,143 cal/g, ash content varied from 14.95–23.62%, and the shatter index from 0.04–1.33%. The optimal performance was obtained at 50 mesh with 70% corn cob charcoal and 30% coconut shell residue, yielding the highest calorific value (5,143 cal/g), the lowest ash content (16.66%), and excellent durability (shatter index 0.04%). Statistical analysis (ANOVA and Friedman test) confirmed that both particle size and blending ratio significantly affected all quality metrics (p 0.05). These findings provide actionable insights for enhancing energy content and overall quality of extrusion-derived briquettes from agricultural residues. The research underscores the essential role of precise material selection and parameter control in developing efficient and sustainable solid biomass fuels.

This study presents a sustainable approach utilizing activated carbon derived from hazelnut shells as an adsorbent for the simultaneous quantitative analysis of 48 different volatile organic compounds (VOCs) via GC-MS. The surface area of the produced activated carbon was successfully enhanced through the concurrent application of heat and steam. The effect of critical parameters, such as particle size and steam ratio, on the surface area and product yield was investigated. A high steam ratio was observed to increase the total surface area while decreasing the micropore surface area, which is attributed to the conversion of micropores into larger mesopores. Consequently, a 0.240-0.125mm particle size and a 1.0 steam/AC ratio were selected, as they provided an optimal balance between back pressure and surface area. The method achieved exceptionally low limits of detection (LOD), with the lowest value of 3.72 µgm⁻3 obtained for chlorobenzene. The reliability of the method was confirmed by comparing its LOD values with those of the GC-MS instrument, revealing that LODMet/LODGC-MS ratios were mostly between 1.0 and 2.0. The obtained LOD values were found to meet and often exceed the legal VOC limits of many countries, confirming the method's broad practical applicability.

ABSTRACT Monodisperse crosslinked polymer microspheres with phenylsulfonate were successfully synthesized via precipitation polymerization of divinylbenzene, styrene, and a styrene dimer with two phenyl sulfonate groups ( M ). The use of M in polymerization allowed us to obtain monodisperse microspheres even though the molar ratio of total crosslinker was less than 20 mol%. The effects of various polymerization conditions, including the molar ratio of total crosslinker, monomer concentration, initiator concentration, solvent composition, and comonomers, on yield, particle size, and sulfonic acid content were systematically investigated. The number‐averaged diameters of the polymer microspheres ( D n ) were in the range of 0.59 to 2.30 μm. Small particles were obtained at a high molar ratio of total crosslinker, whereas larger particles were obtained at higher monomer or initiator concentrations. In addition, the yield of microspheres increased with increasing the molar ratio of total crosslinker and monomer concentration. The solvent ratio and comonomer type also markedly influenced the size of the resulting microspheres. After the deprotection of the phenyl sulfonate moieties of the polymer microspheres, followed by acid treatment, monodisperse low‐crosslinked polymer microspheres with sulfonic acid were successfully obtained. The synthetic approach is a reliable method for preparing monodisperse low‐crosslinked polymer microspheres with sulfonic acid.

The accurate prediction of compressive strength (CS) is a fundamental requirement for structural safety, yet conventional empirical models remain limited in their ability to capture the complex nonlinear response of cementitious materials. Hybrid machine learning (ML) and deep learning (DL) models are investigated for predicting the CS of recycled powder mortar (RPM) using 10-fold cross-validation. Material type (classified as kind), particle size, water/binder (W/B), and mass replacement ratio (MRR) are used as input variables, with CS as the target response. Model performance was quantified using RMSE, R², MAE, and MAPE, and analysis of variance (ANOVA) was conducted to examine the statistical significance of the input variables. Based on 10-fold cross-validation, the SVR–PSO model exhibited the highest average predictive performance, attaining R² = 0.950 and RMSE = 2.042 MPa, thereby demonstrating superior accuracy and reliability relative to the other evaluated models. The interpretable hybrid ML–DL framework achieved high accuracy and robust generalization across folds, with error and stability analyses confirming unbiased predictions. MRR is the dominant factor controlling CS, with suggested optimal ranges; this influence is consistently supported by ALE, PDP, SHAP, and ICE analyses. Feature importance and PDP demonstrate Kind has a secondary yet meaningful effect on CS, reflecting differences in composition, morphology, and reactivity, with its subtler role in ALE and ICE analyses arising from its categorical and indirect mechanistic influence on hydration and pozzolanic activity. The framework offers a robust, interpretable tool for predicting CS, supporting data-driven mix design and sustainable mortar optimization.

Thermal and reactive flow characterisation in a modified conical solar thermochemical reactor for hydrogen production by steam methane reforming with varying porosity, particle size, and CH4-H2O molar ratio