Aluminum fluoride (AlF₃) is an essential industrial material widely used in aluminum electrolysis and ceramics, yet its performance depends critically on the powder properties of its precursor, aluminum fluoride trihydrate (AFT). However, conventional AFT crystals suffer from irregular morphologies, leading to poor flowability, low bulk density, and severe caking. In this study, we successfully prepared highly spherical AFT particles in an additive-free aqueous solution. Through integrated offline and in-situ analyses, we elucidated the AFT spherical agglomeration mechanism dominated by an "agglomeration-abrasion" process. Guided by this mechanism, key process parameters, including temperature, stirring rate, and residence time, were systematically optimized using response surface methodology. Under the optimized conditions, the resulting AFT particles achieved an average circularity of 90.74% and a high yield of 85.7%. Compared to commercial powders, the optimized spherical AFT exhibited maximum improvements of 30.1% in bulk density and 41.4% in flowability, along with significantly enhanced anti-caking properties. The combination of spherical morphology and high yield enhances batch capacity while offering potential for continuous production, providing a green and cost-effective route for the industrial manufacturing of high-quality AFT powders.

In this study, magnetite nanoparticles (Fe₃O₄) were surface-engineered with a biobased carboxymethyl inulin (CMI) coating to develop a recyclable inhibitor for controlling mineral scale formation through interfacial interactions. The Fe₃O₄@CMI nanocomposite was synthesized via co-precipitation, achieving a uniform ~59 wt% polymer layer without altering the cubic spinel structure of magnetite. Comprehensive surface and interface characterization by XRD, FTIR, TGA, VSM, and SEM confirmed the preservation of superparamagnetic properties and effective polymer anchoring via carboxylate-iron interactions. The coated nanoparticles exhibited strong affinity for scaling ions, disrupting crystal nucleation and growth at the solid-liquid interface, as evidenced by morphological transformations of gypsum, calcite, and barite deposits. Under both static and high-pressure-high-temperature dynamic conditions, Fe₃O₄@CMI achieved complete gypsum inhibition at concentrations as low as 1-5 ppm and maintained full efficiency over multiple magnetic recovery cycles. Enhanced calcium compatibility in saline brines further underscores the stability of the modified surface, preventing secondary precipitation and enabling reliable reuse. These results highlight the critical role of interface engineering in tailoring nanoparticle-scale crystal interactions for sustainable and low-discharge chemicals for oilfield scale management.

Hydrogen generation during thermal runaway significantly elevates the risk of explosive combustion in lithium-ion batteries. Although hydrogen generated from binders constitutes a minor fraction, its absolute quantity remains substantial in large-scale stationary energy storage systems. Moreover, binder decomposition occurs during the later stages of thermal runaway with rapid reaction rates, further raising the danger level. Herein, graphite anode with polyacrylonitrile binder is in situ cyclized to eliminate the active hydrogen, while maintaining superior cohesiveness. On one hand, cyclized polyacrylonitrile with largely reduced hydrogen atoms can prevent binder-induced hydrogen generation and realize a reduction of hydrogen fraction by over 23%. As the three-dimensional cross-linking binders increase the thermal stability of anodes, the peak decomposition temperature of solid electrolyte interphase is increased from 150 to 200 ℃ to above 200 ℃, while the peak reaction temperature between lithiated graphite and the electrolyte is delayed by at least 15 ℃. On the other hand, the transformation from linear to cyclic molecular structures of cyclized polyacrylonitrile enables uniform and tight encapsulation of graphite and enhanced cohesiveness. Capacity retentions of 97% after 200 cycles in half cells and 72% after 800 cycles in full cells are achieved.

This manuscript mainly proposed an effective method to well disperse the composite conductive agent which is composed of carbon nanotubes (CNTs) and graphene (Gr) in lithium-ion battery (LIB) slurry. Electrochemical Impedance Spectroscopy (EIS), Scanning Electron Microscopy (SEM) and gravitational sedimentation (GS) are employed to characterize the electrochemical, morphological and stability characterizations of LIB slurry, respectively. Specifically, electrochemical characterizations of LIB electrode slurries are performed by fitting Nyquist plots with a 10-parameter EEC, and quantitative morphological analysis of SEM images is conducted using a Mask R-CNN instance segmentation algorithm, both of which were proposed in our prior published research works. Consequently, the dispersion characterizations of LIB slurry are able to be summarized as follows: LiCoO₂ particles are well dispersed in LIB slurry at φ_com2 = 0.5%, by contrast, the composite conductive agent achieves superior coating and networking of LiCoO₂ particles under the conditions of both φ_com2 = 0.5% and m_CNTs:m_Gr = 4:1, due to the maximized CNTs-Gr synergistic effect. Meanwhile, the formed three-dimensional "long-range" conductive network maintains the stability of its internal skeleton structure during the sedimentation of LIB slurry. This finding holds significant potential to advance the application of CNTs/Gr composite conductive agents in LIB slurry.

Li₄Ti₅O₁₂-TiO₂ nanocomposites represent highly promising materials for energy storage applications owing to their attractive electrochemical properties. However, precisely optimizing their morphology and compositions is essential. In this study, the effects of lithium content on the synthesis of the Li₄Ti₅O₁₂-TiO₂ nanocomposites prepared by the hydrothermal method were investigated. The samples were prepared using different molar ratios of LiOH·H₂O: tertbutyl titanate (TBT) (4:5, 6:5, 8:5, 10:5, and 12:5) using a hydrothermal process at 180 ℃ for 12 h, followed by a calcination step. The microstructure, phase analysis, and morphology of the samples were investigated using X-ray diffraction (XRD), Raman spectroscopy, and field-emission scanning electron microscopy (FESEM) analyses. XRD results showed a phase evolution from an anatase-rich TiO₂ (at a ratio of 4:5) to a Li₄Ti₅O₁₂-dominated nanocomposite (at a ratio of 12:5) with a minor TiO₂ rutile phase. Also, the crystallite size of the Li₄Ti₅O₁₂ phase first increased to a maximum value of 47.3 nm and then decreased to 20-21 nm at higher ratios. FESEM images revealed a growth in particle size of the samples from 138 to 196 nm, by increasing the ratio from 4:5 to 6:5, and then a reduction of particle size to about 55 nm by using higher ratios. The results showed that for achieving Li₄Ti₅O₁₂-TiO₂ rutile nanocomposites with nanoscale particles, higher LiOH·H₂O:TBT ratios are preferred.

To investigate the ignition and combustion mechanisms of boron agglomerates in oxygen-free steam for water ramjet applications, a laser ignition single-particle experimental system was established. The combustion process was found to comprise four sequential stages: preheating and structural loosening, molten collapse, micro-explosion combustion, and quasi-steady combustion. The results indicate that steam can act as an oxidizer to support vigorous boron combustion. Its unique chemical role (reacting with B₂O₃ to form volatile HBO₂) effectively accelerates the removal of the surface oxide layer, resulting in a relatively thin molten shell. Entrapped steam continuously reacts with internal boron, generating gaseous products (H₂, etc.) that trigger a distinct micro-explosion mode characterized by sustained ejection rather than the expansion-dominated behavior observed in air. Kinetic analysis reveals that the quasi-steady combustion stage is diffusion-controlled, with a burning rate constant comparable to that in air. A quantitative evaluation based on volume change yields a final combustion efficiency of approximately 39.1% in pure steam. These single-particle-level observations provide essential experimental evidence for understanding boron combustion mechanisms and for designing boron-based water-reactive fuel systems.

Supercritical water gasification (SCWG) is a highly promising technology. A fundamental aspect of SCWG involves the flow of supercritical water (SCW) around interactive particles, which is inherently complex due to the presence of the wake effect. This study numerically investigates particle wake characteristics and wake-particle interactions in high-viscosity supercritical water (SCW) via an adaptive lattice Boltzmann method (LBM, N/D = 30, coarse-fine ratio 0.025:0.060) to support supercritical water gasification (SCWG) reactor optimization. The adaptive LBM effectively balances accuracy and efficiency, resolving SCW's steep viscosity gradients and fine wake structures well. Interparticle distance (L/D) is the dominant factor for particle drag, affecting trailing particles far more significantly, with three interaction regimes (strong: L/D = 0-2, moderate: 2-4, weak: ≥4). SCW's high viscosity amplifies wake overlap at L/D ≤ 2, minimizing trailing particle pressure drag and suppressing vortex shedding; increasing L/D weakens shielding, elevates drag, and makes trailing particles behave like isolated ones. Interparticle angle raises drag ratios, inducing distinct vortex structures at 30°-60° and 60°-90°, with identical drag at 90°. SCW wake symmetry and vortex shedding show Re-dependent transitions, with critical Re = 92 corresponding to the minimum trailing particle drag ratio. A drag ratio correlation with L/D and Re is also established. This work provides a reliable numerical tool for SCW particle interactions and theoretical guidance for SCWG reactor optimization, with future work focusing on particle swarms and experimental validation.

Polycaprolactone (PCL) microspheres are emerging as versatile biomaterials for minimally invasive soft tissue augmentation due to their tunable biodegradability and favorable biocompatibility. Nevertheless, the extent to which monodispersity governs the functional performance of PCL microspheres, particularly in modulating host tissue responses and regenerative efficacy, remains poorly understood. Herein, we propose a method to controllably prepare monodisperse oil-in-water (O/W) droplet templates using coaxial flow-focusing microfluidics, and then obtaining monodisperse PCL microspheres with programmable sizes via solvent evaporation. The droplet dimensions are inversely regulated by the outer-to-inner phase flow rate ratio, while PCL concentration in the organic phase exerts minimal influence on initial droplet size but markedly reduces the volume shrinkage during solidification, yielding microspheres that better retain their geometries. Notably, the resultant PCL microspheres can maintain structural integrity and size uniformity over two-month period under physiologically mimetic conditions. Comprehensive biocompatibility assessments reveal that PCL microspheres exhibit negligible hemolytic activity and cytotoxicity, demonstrating excellent hemocompatibility and cytocompatibility. Notably, in a rabbit soft tissue implantation model, monodisperse PCL microspheres with an average diameter of 42 μm elicit attenuated foreign body reactions and potentiate endogenous collagen deposition relative to the polydisperse microsphere control group. These results provide useful guidance for the application of PCL microspheres in soft tissue augmentation.

This study compares the performance of a new three-channel coaxial nozzle with a conventional Schlick nozzle in fluidized bed particle coating. The new nozzle produces droplets with a Sauter mean diameter of around 10 μm, offering a middle ground between aerosol and conventional nozzles. Yields of processes, coating coverages of particles, coating thickness and surface roughness were compared for the same experimental conditions of these nozzles. Non-porous glass particles (mean diameter 653 μm) and porous γ-Al₂O₃ particles (mean diameter 610 μm) were used as cores, with an aqueous sodium benzoate (NaB) solution as the coating liquid. A scanning electron microscope (SEM) was utilized to capture images of the particles after each experiment. To analyze the coverage on the particle surfaces, MATLAB image processing was applied to SEM images of coated particles. Moreover, these images were used to determine the surface roughness of the coating. In addition to manual measurements of coating thickness on particles by image processing, some coated γ-Al₂O₃ particles were sectioned to measure the coating thickness by ImageJ. The manual thickness measurements were supplemented by results obtained by laser scattering. The coating process by means of the new nozzle was also compared with an aerosol coating process which has droplet size with a mean diameter of around 1 μm, in terms of process yield, product coating coverage and thickness. The new nozzle acts as an intermediate between the aerosol generator and the conventional Schlick nozzle in terms of droplet size. These findings suggest that the new nozzle has significant potential for use in fluidized particle coating, as an alternative to conventional nozzle, offering smaller droplet size.

Shear-induced particle migration in the internal die flows of concentrated particulate suspensions during slot coating processes was investigated using a diffusive flux model implemented within three-dimensional computational fluid dynamics simulations. Comparative simulations demonstrated that particle migration markedly altered the internal flow characteristics and particle distributions inside the slot dies. Inhomogeneous particle distributions at the feed inlet were found to modify the flow behavior in the chamber region and profoundly affect the velocity and particle concentration fields in the slit region. These changes critically influenced the die exit velocity and concentration profiles, which governed the uniformity of the wet coating thickness. The insights obtained from this study offer practical guidance for die design and process control to achieve a uniform coating thickness and stable slot coating operation.

High-capacity silicon anodes hold great promise for safe and energy-dense all-solid-state lithium batteries (ASSLBs), yet their practical application is hindered by interfacial degradation and mechanical fracture, which severely limit their cycle life. Herein, we unravel the particle-size-dependent electro-chemo-mechanical failure mechanisms of Si anodes in sulfide-based ASSLBs. The micro-sized Si (μm-Si) anode exhibits favorable initial Coulombic efficiency (ICE, 79.15%) and reversible capacity (2260.5 mAh g⁻¹) but succumbs to progressive particle fracture under prolonged cycling due to cumulative mechanical stress from large volume swings. By contrast, the nano-sized Si (nm-Si) anode suffers from severe interfacial side reactions and irreversible volume expansion due to its larger specific area and dense electrode structure, resulting in lower initial performance (ICE of 72.21%, 1372.7 mAh g⁻¹). In subsequent cycles, the nm-Si anode experiences continuous interfacial side reactions, leading to substantial accumulation of interfacial decomposition byproducts and sustained capacity decay. These contrasting failure pathways establish electro-chemo-mechanical coupling as the governing principle and provide a particle-size-dependent design framework for high-performance Si-based ASSLBs.

This study employs a benchmarked Discrete Element Method model to investigate the influence of particle shape on the compressibility behavior of granular assemblies within a controlled comparative framework. Twenty idealized particle geometries with different shape characteristics were analyzed under constrained compression at vertical stress levels ranging from 0.1 to 3.2 MPa. Macro- and micro-scale responses were evaluated using constrained modulus and average coordination number, together with additional contact-scale analyses to improve the interpretation of particle-scale behavior. The results indicate that both macro- and micro-scale responses remain strongly stress-dependent, suggesting that conventional indicators alone cannot fully isolate particle-shape effects. A stress-normalized scaling approach was therefore applied to reduce the dominant influence of stress and clarify geometry-related trends. The analyses demonstrate that increasing particle irregularity promotes denser contact networks, redistributes contact forces across more contacts, and alters local deformation mechanisms. The findings provide a comparative DEM-based assessment of shape-dependent compressibility and contact-scale force-deformation behavior in idealized granular assemblies.

Hydrogen stands as a pivotal energy carrier with significant potential to facilitate the global transition towards a low-carbon energy future. The main challenge in current stage is the production of hydrogen with less emission and high efficiency. To resolve this problem, chemical looping hydrogen production (CLHP) is proposed and investigated. The key factors influencing the efficiency of CLHP are the gas-solid flow, heat transfer and mass transfer processes. A dual-reactor system is established in this work and numerical model based on CPFD is utilised for investigating the reaction characteristics. Hydrogen production decreases with increasing gas velocity in the hydrogen production reactor. Variations in the solid circulation rate alter the mass and heat distribution within the system, consequently affecting the hydrogen production rate. A riser gas velocity of 7 m/s and a circulation rate of 0.15 kg/s are the recommended values for the current constructor. Overall, reactor temperature remains the predominant influencing factor. This study provides insights for reactor optimization and scale-up design.

This study investigates particles erosion characteristics of shaftless rim-driven thrusters (RDTs) adopting CFD-DEM method. A three-dimensional RDTs model was developed to evaluate the effect of particles size, shape, and flow rate on erosion pattern and hydrodynamic performance. The results indicate that larger particles could induce severe localized erosion at blade leading edge owing to the higher inertia, whereas smaller particles generate more uniform but milder wear. Mixed particles distribution can produce combined effect, resembling actual sediment-laden environments. Moreover, blade number and hub-to-tip ratio also markedly influence erosion. The fewer blades and smaller r/R values lead to concentrated erosion, and increasing blade number and r/R enhances flow uniformity and reduces wear. The comparison between spherical and irregular (barley-shaped) particles reveal that irregular morphology causes stronger localized erosion and greater efficiency losses. In addition, higher particle mass flow rate intensifies erosion, expanding the affected regions from localized hotspots to entire blade surfaces.

Developing sustainable dielectric ceramics with high energy storage performance under a moderate electric field is still a great challenge for the next generation pulse power capacitors. Herein, recycled photovoltaic waste glass (PVWG) was added into Bi₀.₅Na₀.₅TiO₃ (BNT)-based lead-free ceramics via a conventional solid-state route and sintered at 1120 ℃ for 2 h. The PVWG additive facilitated liquid-phase sintering, reduced porosity, promoted grain-boundary homogeneity and improved the dielectric breakdown strength. Therefore, the optimized BNT-08 ceramic exhibits a high relative density of 97.04 ± 0.15 %, a reduced remanent polarization (P_r) of 9.4 ± 0.3 μC cm⁻², an increased breakdown strength (E_b ~220 ± 5 kV cm⁻¹) and a significantly slimmer P-E hysteresis loop. Hence, a recoverable energy density (W_rec) of 1.76 ± 0.07 J cm⁻³ and an energy storage efficiency of 78 ± 2 % were obtained under a moderate electric field at 220 kV cm⁻¹. The enhanced energy storage performance was ascribed to the synergistic effects of structural stabilization, defect-regulated charge transport, and PVWG-induced microstructural refinement. This simple, low cost and environmentally friendly method demonstrates PVWG as a promising multifunctional additive for electroceramic applications in line with the circular strategy.

Thermal energy storage (TES) is a key enabler for the large-scale utilization of intermittent renewable energy sources like solar and wind power, and it also offers an efficient pathway for industrial electrification and decarbonization. However, the widespread adoption of TES is hindered by the high cost of conventional TES materials, such as alumina, magnesium oxide, and other ceramics. This study investigates the feasibility of converting coal gangue, an abundant industrial waste with considerable environmental impact, into a low-cost, mechanically stable, and thermally efficient material for medium-to high-temperature sensible heat storage applications. Three representative coal gangue samples from the Ordos region in Inner Mongolia, China, were calcined at temperatures ranging from 1000 to 1300 ℃ to optimize their phase compositions, mechanical strengths, and thermophysical properties. Among the samples, Sample A from Jungar exhibited the best overall performance, achieving a volumetric heat storage density of approximately 555 kWh m⁻³ at 1200 ℃, which is comparable to typical sensible heat storage materials, while maintaining good mechanical integrity and satisfactory cyclic stability. With near-zero raw-material cost, a simple single-step preparation process, and potential policy incentives for solid-waste utilization, the coal-gangue-based composites developed here offer clear economic and environmental advantages and introduce a promising, low-cost material system for sustainable TES applications at medium-to high-temperature levels.

To investigate the release of dust, coarse (x_50.3 = 980 μm) and fine (x_50.3 = 3.6 μm) limestone was discharged into a wind tunnel using a model conveyor belt. Different test setups were used to measure the dust release in different phases of the discharge. The discharge mass flow, belt speed and wind tunnel air velocity were varied. Systematic differences were found between the two size fractions. The dust release of the fine material mainly takes place during the fall, while the dust release of the coarse material is dominated by the impact on the bulk pile. For the coarse material, a model for the individual release of dust-laden coarse material particles from the literature can be used as an explanatory approach. A different explanatory approach is required to describe the release of dust from the fine material.

Numerical simulations were conducted to study the pyrolysis of polypropylene (PP) in a fluidized bed reactor (FBR). For that purpose, a Eulerian-Lagrangian solver was developed, incorporating the gas-solid hydrodynamics in FBR, particle-level heat transfer, and a five-lump pyrolysis reaction kinetic model. This framework captures the mutual interplay among these physicochemical processes and enables predicting the yields of permanent gas (G), light fraction (LF), and heavy fraction (HF). Analysis of the characteristic timescales confirms that the pyrolysis reaction is significantly slower than convective heat transfer. At 505 ℃, LF was the dominant product (67.4 wt%), followed by G (29.6 wt%) and HF (3 wt%), and the product distribution significantly shifted toward G formation with increasing reactor temperature. In contrast, variations in particle size (1.5-2.5 mm) and operation mode (batch-wise vs. continuous) affected the transient thermal behavior but had minor effects on product yields, as heat transfer is not rate-determining under the investigated conditions.

Inertial migration of a neutrally buoyant rigid sphere in circular Poiseuille flow is strongly affected by particle rotation, yet its role remains poorly understood. This study employs three-dimensional fully-resolved CFD-DEM simulations to investigate inertial migration with and without particle rotation. The model is validated against experimental equilibrium radial positions. Simulation results reveal that suppressing rotation consistently shifts the equilibrium radial position toward the pipe centerline, but rotation's effect on the migration dynamics depends on the sphere's initial radial position. When rotation is suppressed, radial migration accelerates for the sphere released near the pipe wall, whereas radial migration slows for the sphere released closer to the centerline. While the freely rotating spheres experience a transition between different migration regimes as the sphere-to-pipe diameter ratio or the fluid Reynolds number increases, non-rotating spheres remain in the monotonic regime since they stabilize closer to the pipe centerline where both shear-gradient and wall-induced lift forces vanish. Moreover, suppressing rotation increases the entry length required for the sphere to achieve full migration. This study elucidates how particle rotation affects inertial migration and offers new insights into rotation-modulated lateral migration in microfluidics.

The road performance of recycled asphalt pavement (RAP) is crucial for low-carbon road construction. However, existing studies lack refined simulation of the mesostructure involving RAP, new aggregates, aged asphalt, and new asphalt, leaving the effects of different RAP contents on stress distribution and damage mechanisms unclear. This study develops discrete element models to analyze the influence of RAP content on mesoscopic stress evolution, crack propagation, and aggregate breakage. The results show that when RAP content exceeds 45%, aged asphalt and RAP exhibit notably non-uniform distributions. The maximum normal stress occurs at the loading center, while the maximum shear stress is located at the bottom sides of the loading center. As RAP content rises from 15 % to 60 %, the number of effective microcracks increases by 2.04 times. The length and area of slip-bands grows rapidly, and the crack damage index D follows an exponential upward trend. Considering rutting resistance, crack resistance, and resource utilization efficiency comprehensively, the recommended suitable RAP content range is 30 % - 45 %, with the following threshold values: number of slip-bands≤8, average length of slip-bands≤48 mm, and D ≤ 7.5 %. The findings provide a theoretical basis for understanding the meso-mechanical behavior of recycled asphalt mixtures.

Sorption-enhanced steam gasification (SESG) represents a promising route for hydrogen-rich syngas production. However, the rapid deactivation of conventional CaO-based sorbents, and the efficiency loss associated with the high temperature sorbent regeneration step, remain as critical challenges. In this study, a redox-activated SrMnO₃ sorbent was used for isothermal SESG of biomass in a fluidized-bed to investigate fuel flexibility, torrefaction effects, and long-term stability. Four biomass feedstocks as well as their torrefied counterparts were evaluated. All untreated feedstocks produced hydrogen-rich syngas with H₂ concentration >60% and H₂/CO ratios >4 under isothermal operation at 850 ℃. Torrefaction decreased H₂ purity and syngas yield due to reduced volatile matter content. Long-term experiments in both a fluidized-bed reactor and TGA demonstrated excellent cyclic stability of SrMnO₃ and strong ash resistance. The structural and compositional properties of the sorbents were characterized in detail, confirming the chemical and structural stability of the SrMnO₃ sorbent during prolonged cyclic operation. Process simulation further showed that SESG of biomass significantly enhanced cold gas efficiency while maintaining a comparable heat demand compared to state-of-the-art indirect biomass gasification. Overall, SrMnO₃ exhibits strong potential as a robust sorbent for efficient and flexible biomass-to-hydrogen conversion.

Hydrogel desorption shows promise for thermal management and passive cooling engineering applications, but challenges persist in understanding particle desorption and shrinkage. A Lattice Boltzmann-based phase-field model was developed by combining experiments and mesoscopic simulations to simulate conjugate heat transfer, desorption kinetics, and shrinkage of single hydrogel particles, achieving <5% deviation from experiments. Results show that raising temperature from 343 to 353 K increases 1-h desorption mass by ~12% of initial mass (vs. 1.3% for 313-323 K), driven by rising saturation vapor pressure and falling evaporation enthalpy. Shrinkage is more sensitive at high temperature and low humidity, with surface area reductions of ~17% (343-353 K) and~13% (20-30% RH), compared to ~5% under mild conditions. Reducing particle initial mass from 5.75 g to 0.16 g shortens the time to release 50% of the initial water from 516 min to 117 min, indicating greater efficiency for smaller particles. This work bridges the macro-pore scale gap and offers a numerical tool with design insights for passive cooling.

To improve understanding of proppant transport mechanisms in complex fracture networks, a field-scale model based on the Multiphase Particle-in-Cell (MP-PIC) method was developed using fracture geometries derived from real shale outcrops and validated against experimental data. Results indicate that: (1) intense vortex formation during early-to-mid injection stages or at high flow rates exacerbates the longitudinal heterogeneity of proppant distribution. (2) In the near-wellbore zone, the synergistic effects of fracture width variations, high flow velocities, and natural weak planes drive proppants to migrate preferentially along paths aligned with the maximum and minimum principal stress directions, forming a dual-channel transport pattern. (3) The volume of proppant entering secondary fractures decreases with distance from the injection point, and the proppant dune height within dominant channels exhibits stepwise attenuation. Larger intersection angles between secondary and main fractures hinder proppant migration. (4) Smaller proppant size and lower density improve the planar sweep and distribution uniformity coefficients, while increased fracturing fluid viscosity extends the proppant sweep range and further improves uniformity; high injection rates promote long-distance proppant transport and broader coverage but may reduce uniformity, leading to sparse proppant distribution and necking at fracture mouths. These findings provide quantitative guidance for optimizing hydraulic fracturing designs.

Hard-sphere/pseudo-particle modeling (HS-PPM) provides a parallel and more versatile implementation of molecular dynamics simulation based on hard-sphere model at large scales with remarkable performance. For more practical applications, however, more sophisticated and realistic boundary conditions have to be incorporated. In this work, the artifact of inlet-outlet coupling due to periodic boundary is basically eliminated by adding collisions at both ends and proportional-integral-differential (PID) control of density at the outlet based on implicit boundary conditions, maintaining reasonable flow field there for both high (up to 13.0) and low (down to 0.0) Mach numbers. Moreover, geometrically complex boundaries are approximated by a large number of polygonal (in particular, triangular) elements, instead of exact analytical descriptions, to balance the accuracy and efficiency. Given the challenges of nanoscale experimentation, the drag coefficients from simulation conducted at matching dimensionless numbers were compared with macroscopic results. With these improvements, the flow around a conical particle and the Inflatable Re-entry Vehicle Experiment (IRVE) was successfully simulated and demonstrated consistent to experiment and numerical results from direct simulation Monte Carlo (DSMC) towards the continuum flow limit (with the Knudsen number ranging from 0.1 to 1.7). Furthermore, the drag coefficient of nano-particles in fluid flow, which is challenging for experimental measurement, was obtained from simulation results, and the potential of HS-PPM in simulating particles and systems with complex structures is exemplified by the gas flow and diffusion in porous micro/nano-particles.

To enhance the calibration efficiency and accuracy of Discrete Element Method (DEM) parameters for cohesive bulk materials, a collaborative method integrating Particle Swarm Optimization (PSO) and Backpropagation (BP) neural networks is proposed. Key macroscopic indicators (steady-state shear stress, angle of repose) are obtained via Jenike shear and funnel tests across a 0-50% moisture range. Orthogonal experiments determine micro-parameters (e.g., static/rolling friction, surface energy) to build a macro-micro mapping database. The core of the PSO-BP dual-model lies in its collaborative mechanism: the forward BP model predicts macroscopic responses to replace time-consuming DEM simulations, while the PSO algorithm optimizes the inverse BP model to accurately infer optimal micro-parameters from experimental macro-indicators (steady-state shear stress, angle of repose). Validation shows low errors (1.14% for angle of repose, 1.63% for steady-state shear stress) and good chute flow velocity agreement. This method overcomes traditional limitations of arbitrariness and ignored parameter coupling, providing reliable support for DEM simulation and equipment design for cohesive bulk materials.

Sinkholes, a common geotechnical failure, have been reported more frequently in recent years due to complex climate change and urbanisation. This study investigates mechanisms of sinkhole development, considering the influence of triggering depth and compaction degree through experiments integrated with Particle Image Velocimetry (PIV) technique and Discrete Element Method (DEM). Laboratory tests simulating the formation of sinkhole in subgrade soil are carried out under varying triggering depths and void ratios, where the soil displacement is recorded over time. DEM simulations are performed and validated against the experimental results analysed by PIV technique. The results show good agreement between DEM and experimental investigations, especially in capturing time-dependent stages and displacement fields of sinkhole development. Furthermore, the numerical investigation indicates that increasing the triggering depth results in later development of sinkhole with greater vertical displacement around the triggering point to promote its propagation towards the ground surface. Interestingly, dense soil exhibits highly localised mobilisation confined within well-defined displacement boundaries, whereas loose soil displays a wider displacement zone characterised by a funnel-shaped pattern. The interparticle contact behaviour further releases the insightful mechanism of sinkhole progression, giving considerable value to our understanding and prediction of this catastrophic failure.

This study performs a comparative assessment of three Machine Learning (ML) models to determine their robustness in data-sparse industrial environments for predicting and optimising the performance and energy consumption of an immersion mill. By employing active learning strategies that target high-variance regions in process space, a limited experimental dataset (15 batches) was found sufficient to accurately predict mill performance, provided the correct model architecture is chosen. Three models were used: Random Forest Regression (RFR), Gradient Boosted Trees (GBT) and Symbolic Regression (SR). Based on performance when used on completely unseen data, as well as interpretability and usability, the SR models were found to be the most effective for this application. The simple algebraic form of the SR models allowed for direct use in exploring 'what-if' scenarios, and equally allowed either model to serve as a constraint for the other to minimise energy use to achieve a target particle size. An unexpected finding during this work was that the relationship between final particle size and impeller speed and grinding media content is weaker than for classic vertical stirred mill designs owing to transport and/or mixing mechanisms novel to this particular mill design. The result of this study is a set of predictive models that can be used in optimising the immersion milling process, and effectively responding to changes in feed Particle Size Distribution (PSD) whilst minimising energy use.

Char particles from coal pyrolysis exhibit unique settling dynamics, such as terminal velocity and drag coefficient. Accurate quantification of drag characteristics is essential for pneumatic conveying. Current simulations adopting spherical drag models suffer large deviations for irregular char particles. To fill this gap, we built a visual platform to investigate free settling of coal and char particles (<200 μm). Terminal velocities were measured for individual particles and aggregates. Based on statistical analysis, we revised Stokes and Schiller drag formulations. In the Stokes form, the fitted coefficients for individual coal particles and coal aggregates are 26.04 ± 3.5 and 52.15 ± 4.8, respectively; for individual char particles and char aggregates, they are 41.05 ± 3.2 and 112.4 ± 4.3, respectively. In the Schiller form, the fitted coefficients for individual coal particles and coal aggregates are 26.19 ± 3.4 and 53.88 ± 4.2, respectively; for individual char particles and char aggregates, they are 40.94 ± 3.2 and 111.1 ± 4.2, respectively. These correlations can be directly employed in drag model for numerical simulation of char pneumatic conveying. Validation shows significantly improved accuracy. This work presents the first experimentally derived drag coefficient correlations for char particles, addressing the lack of quantitative data and offering a more precise tool for char transport design.

This paper develops a computational framework coupling a moisture-induced cohesive force model with the Coarse-Grained Discrete Element Method (CG-DEM) to efficiently and accurately simulate the mixed discharge process of wet coal in a laboratory-scale three-dimensional silo. The moisture-induced cohesive force model quantifies the effect of moisture on coal flowability by correlating moisture content with macroscopic mechanical parameters of the particles (cohesion, internal friction angle). Simulation results indicate that particle flow exhibits a significant central-channeling "funnel flow" characteristic, and the flow structure is dominated by the flowability of the lower coal layer. The moisture-induced cohesive force is a key factor controlling particle motion. The study further reveals the decisive influence of stacking sequence on the evolution of outlet coal quality: when the lower layer consists of high-moisture, poor-flowability Indonesian coal, the outlet calorific value shows a slow rising trend; conversely, when the lower layer consists of good-flowability Longwanggou coal, the outlet calorific value decreases rapidly. This research provides a reliable, low-cost numerical tool for understanding and predicting the discharge and mixing behavior of wet coal in industrial silos, offering guidance for optimizing coal blending and stabilizing the quality of feed coal.

Chemical recycling of polymethyl methacrylate (PMMA) to its monomer, methyl methacrylate (MMA), requires balancing primary depolymerization with the suppression of secondary gas-phase reactions. This study investigates non-oxidative MMA decomposition in a fluidized bed reactor across a temperature range of 623 to 1073 K using online FTIR spectroscopy. Experimental results reveal a significant shift in product selectivity: low temperatures favor a low-energy decarboxylation pathway (yielding CO₂ and methanol), while high temperatures promote radical cracking (yielding CO and light hydrocarbons). To describe this, a two-competing-reactions model (CRM) is used, outperforming the traditional single first-order approaches. The CRM identifies two distinct activation energies: E_a,1 = 76.5 kJ mol⁻¹ for decarboxylation and E_a,2 = 269.9 kJ mol⁻¹ for cracking. The research further demonstrates that the classical sequential decomposition model (PMMA → MMA→ light gases) overpredicts monomer yields at low temperatures. By integrating a direct solid-to-gas pathway to account for side-chain break-off and incorporating multi-volume reactor hydrodynamics, the model's predictive accuracy significantly improved. This integrated framework identifies an optimal recovery window near 723 K, achieving MMA yields over 95 %.

Carrier-phase direct numerical simulations (CP-DNS) of a three-dimensional turbulent shear- and mixing-layer are presented. DNS enables detailed investigation of complex multiphase turbulent reacting systems that are difficult to study experimentally; however, the reliability and reproducibility of such simulations remain uncertain and are potentially sensitive to the underlying numerical treatment. Given this, the simulations are cross-validated against DNS data by Luu et al. (Flow Turbul. Combust. 2024), first in a statistical sense and then, for the first time, by direct comparison of the instantaneous realizations of the two DNS. A further DNS is then presented for a higher Reynolds number at twice the grid resolution. This represents the most resolved carrier-phase DNS of such systems to date and enables higher turbulence conditions that better represent realistic burner operating conditions. The new simulations confirm the previously observed overall system behavior and further demonstrate the influence of Reynolds number on the combustion process. Higher turbulence intensity leads to a broader ignition zone, enhanced oxygen entrainment, and increased ignition and conversion rates, while the particle-scale oxidation behavior remains largely unchanged, indicating weak coupling between gas-phase turbulence and individual particle combustion.

Although negative pressure crystallization of ammonium sulfate can mitigate low yield and long processing time in atmospheric pressure crystallization, it still faces challenges in enhancing crystallization efficiency and achieving a uniform crystal size distribution. To address these issues, this study proposed an ultrasound-assisted negative pressure crystallization technique. Under optimized conditions (pH = 7, 300 rpm, 80 ℃, 45 min, 180 W, 0.03 MPa), the yield increased by 27.64 g and the direct yield improved by 36.80% compared with negative pressure crystallization. XRD and FTIR confirmed that this process maintained the crystal structure of ammonium sulfate while enhancing crystallinity. Mechanistic studies revealed that, compared with negative pressure crystallization, the synergistic effect of ultrasound narrowed the metastable zone width (MSZW) by approximately 33%, lowering the nucleation energy barrier. Ultrasound cavitation generated numerous bubbles, providing heterogeneous nucleation sites and localized supersaturation driving forces, which jointly accelerated nucleation and reduced the solid-liquid transition time by 35.7%. Furthermore, compared with the negative pressure crystallization system, the ultrasonic negative pressure crystallization reduced the solution viscosity by 5.7%, enhancing mass transfer and crystal growth. Ultimately, ultrasound-assisted negative pressure crystallization produced crystals with more uniform size and more regular morphology, offering important theoretical insights for improving ammonium sulfate crystallization processes.