Particuology最新文献

{"title":"Boiler NOx emission prediction based on ensemble learning and extreme learning machine optimization","authors":"Ze Dong ,&nbsp;Jun Li ,&nbsp;Xinxin Zhao ,&nbsp;Wei Jiang ,&nbsp;Mingshuai Gao","doi":"10.1016/j.partic.2025.07.023","DOIUrl":"10.1016/j.partic.2025.07.023","url":null,"abstract":"<div><div>The nitrogen oxides (NOx) emission measurement of selective catalytic reduction (SCR) denitrification system has issues that insufficient live processing and irregular purge readings. Therefore, establishing an accurate NOx concentration prediction model can significantly advance the timeliness and precision of NOx measurement. The study proposes a prediction method based on ensemble learning and extreme learning machine (ELM) optimization to build a NOx concentration prediction model for SCR denitrification system outlet. Firstly, to enhance the modeling precision of ELM for complex feature objects under all working conditions, the ensemble learning framework was introduced and an ensemble learning model based on ELM was designed. Secondly, to alleviate the impact of random initialization of ELM network learning parameters on the stability of modeling performance, the multi strategy improved dingo optimization algorithm (MS-DOA) is given by introducing Tent chaotic mapping, Lévy flight and adaptive t-distribution strategy to ameliorate the initial solution and position update process of population. Finally, the SCR denitrification operating data from 660 MW coal-fired power plant was opted for experimental validation. The findings demonstrate that the established SCR denitrification system outlet NOx concentration prediction model has high modeling accuracy and prediction accuracy, and provides a reliable approach for achieving accurate prediction of boiler NOx emissions.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"105 ","pages":"Pages 123-139"},"PeriodicalIF":4.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of pellet geometry within the thermal degradation process of biomass: Computational model of a fluidized bed reactor","authors":"Camilo Andrés López ,&nbsp;Tatiana Camila Puentes-Escobar","doi":"10.1016/j.partic.2025.07.021","DOIUrl":"10.1016/j.partic.2025.07.021","url":null,"abstract":"<div><div>The influence of pellet geometry on the biomass pyrolysis process within a fluidized bed reactor is analyzed. Using a computational model based on the Core Shrinking Model (CSM), the effects of pellet size, density and geometry (spherical, cylindrical and ellipsoidal) on heat and mass transfer, as well as on the thermal degradation efficiency, were investigated. The results indicate that cylindrical and ellipsoidal geometries have better efficiency in heat and mass transfer compared to spherical geometry, due to their greater surface-to-volume ratio. Furthermore, it was observed that pellets with smaller equivalent particle diameters decompose more quickly due to their higher heat transfer efficiency. However, the study also reveals that the formation of pellets with specific geometries has a limited impact on the formation of a particular product. These findings have significant implications for the optimization of reactor design and selection of pellet geometries to improve the efficiency of biomass pyrolysis processes.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"105 ","pages":"Pages 95-103"},"PeriodicalIF":4.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144878596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of biomass-based carbon dioxide adsorbents research","authors":"Jia Fang ,&nbsp;Chengzhuang Zhang ,&nbsp;Zhiqiang Han ,&nbsp;Peng Chen ,&nbsp;Yize Dang ,&nbsp;Haifei Wang ,&nbsp;Xueshun Wu","doi":"10.1016/j.partic.2025.07.020","DOIUrl":"10.1016/j.partic.2025.07.020","url":null,"abstract":"<div><div>Excessive CO₂ emissions pose a severe environmental threat, driving interest in carbon capture technologies. Biomass-derived activated carbon (BAC) emerges as a promising adsorbent due to its renewable feedstocks, cost-effectiveness, and tunable properties. This review comprehensively analyzes recent advances in BAC for CO₂ capture. Key findings indicate that agricultural/forestry wastes are optimal feedstocks, while alkali/alkaline earth metals and N/S-containing functional groups enhance surface alkalinity and CO₂ affinity. Pyrolysis is identified as the preferred preparation method for optimizing pore structure. Physical activation (CO₂, steam) and chemical modification (KOH/NaOH, amine grafting, metal oxide impregnation) significantly improve porosity and adsorption capacity. Notably, N-doping increases CO₂ uptake by 31.6–55.2 %, and microporous volume (0.59–0.71 cm³/g) is critical for performance. However, challenges include high energy consumption during KOH activation, feedstock variability impacting consistency (&gt;22 % ash content differences), competitive adsorption from flue gas impurities (&gt;30 % capacity loss), and metal leaching risks. Future research should prioritize in-situ mechanistic studies, heteroatom co-doping, and scalable production techniques to advance industrial deployment.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"105 ","pages":"Pages 104-122"},"PeriodicalIF":4.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144878597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical analysis of particle agglomeration in a continuous pan granulator using DEM","authors":"Gisele M. de Souza,&nbsp;Rondinelli M. Lima,&nbsp;Claudio R. Duarte,&nbsp;Marcos A.S. Barrozo","doi":"10.1016/j.partic.2025.07.022","DOIUrl":"10.1016/j.partic.2025.07.022","url":null,"abstract":"<div><div>Pan granulators are widely used in granulation processes; however, the relationship between particle dynamics within the equipment and the underlying agglomeration mechanisms remains not fully understood. To address this, the present study conducted numerical simulations using the Discrete Element Method (DEM) with cohesive contact force models. Various models were evaluated and compared with experimental data to determine the one that best represented the behavior of the granular bed. The selected model, which incorporates the Easo capillarity model for particle-particle interactions and the SJKR adhesion model for particle-wall interactions, yielded satisfactory results. The numerical findings highlighted significant changes in granular flow dynamics when cohesive forces were taken into account. Additionally, the influence of cohesive forces and rotational speeds on residence time distributions (RTD) was analyzed, revealing the presence of a short-circuit effect in all cohesive granular beds. Finally, a new methodology was developed to quantify particle agglomeration. Larger and more numerous agglomerates were observed when the pan granulator operated in rolling or cascading regimes, conditions that were associated with longer residence times and an increased number of particle contacts.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"105 ","pages":"Pages 140-154"},"PeriodicalIF":4.3,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144878598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of water-powder interaction on the mechanical and metallurgical behavior of integrated steel plant byproducts agglomerates","authors":"Sara Scolari,&nbsp;Davide Mombelli,&nbsp;Gianluca Dall’Osto,&nbsp;Carlo Mapelli","doi":"10.1016/j.partic.2025.07.019","DOIUrl":"10.1016/j.partic.2025.07.019","url":null,"abstract":"<div><div>In 2023, 1888 Mt of steel were produced worldwide, with 70 % via integrated cycle steel plant, generating 34 Mt of dust and 25 Mt of sludge. These wastes are rich in Fe and C but are too fine for direct recycling. Agglomeration is therefore essential to recycle them as suitable feedstock. This work studies how water–powder interactions affect the mechanical (impact resistance, cold compressive strength) and metallurgical (degree of reduction, swelling) properties of self-reducing briquettes made by combining two iron-bearing dusts (BOF dust and a secondary dust) with two reducing agents (BF sludge and another secondary dust) to form hydrophilic–hydrophilic, hydrophobic–hydrophilic, and hydrophobic–hydrophobic mixtures. Water expelled from hydrophobic dust acts as a lubricant during compaction, reducing surface cracks and enhancing eight times the impact resistance. Hydrophilic particles, however, lower impact resistance (failing 10-drop tests) due to hydration repulsion that weakens the briquette. While water absorbed by hydrophilic powders forms gasification channels on drying, enabling a reduction degree up to 94 %, it also causes severe swelling below 1200 °C. The best overall performance was achieved by a hydrophobic–hydrophilic combination with double water content, yielding compressive strength of 18 MPa, degree of reduction of 91 % and swelling of −1.86 %.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"105 ","pages":"Pages 74-87"},"PeriodicalIF":4.3,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144866781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of particle motion in a rotatory flow field exposed to a forced vortex condition","authors":"Sina Gouran ,&nbsp;Saad Alshahrani ,&nbsp;Hijaz Ahmad","doi":"10.1016/j.partic.2025.07.018","DOIUrl":"10.1016/j.partic.2025.07.018","url":null,"abstract":"<div><div>To enhance the performance and service life of the operating instrument in the food production process, the purpose of this paper is to study particle motion in a forced vortex flow condition as a way of performance improvement. To solve the nonlinear equations of motion for the fine particle, a meshless Galerkin technique is applied. After declaring the proper accuracy of the results by comparison with existing research papers, the influences of some critical parameters on the particle movement have been examined. The radial part of the sphere velocity increases when the sphere size increases. However, this radial velocity is reduced by enhancing the sphere's initial velocity. For all situations, the sphere's velocity reduction is observed over time.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"105 ","pages":"Pages 88-94"},"PeriodicalIF":4.3,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144866782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-enhanced support vector machine framework for nanoparticle size and surface nanotopography analysis","authors":"Mehrdad Khakbiz ,&nbsp;Mohammad R. Shahmoradi ,&nbsp;Farshad Akhlaghi ,&nbsp;Kimia Soroush","doi":"10.1016/j.partic.2025.07.017","DOIUrl":"10.1016/j.partic.2025.07.017","url":null,"abstract":"<div><div>This study presents a machine learning-based approach using Support Vector Machines (SVM) to model the particle size distribution (PSD) and predict surface characteristics of Al-B₄C nanocomposite powders synthesized through high-energy ball milling. Two SVM kernels, Polynomial and Radial Basis Function (RBF), were applied to simulate PSD curves and surface morphology, with experimental validation conducted via laser particle size analysis and scanning electron microscopy (SEM). The models demonstrated strong predictive capabilities, achieving R² values between 0.91 and 0.99 and cross-validation coefficients (q²) from 0.93 to 0.99. Normal distribution models yielded lower RMSE values (0.11–2.13) compared to cumulative distribution models (4.34–6.55), indicating higher precision in modeling. SEM analysis revealed morphological transitions during milling, with particles evolving from spherical to fragmented shapes after 4 h. Surface metrics including roughness, waviness, and isotropy were quantified, showing that isotropy decreased from 82.48 % at 0 h to 57.69 % at 4 h due to directional deformation, then partially recovered to 62.50 % at 10 h. Gaussian Process Regression (GPR) showed strong alignment with experimental surface trends and accurately predicted nanoscale topographic parameters. Response Surface Methodology (RSM) was employed to visualize size reduction behavior for B₄C particles with initial sizes of 90, 700, and 1200 nm. For 700 nm particles, size reduction stabilized beyond 10 h, while 90 nm particles exhibited rapid refinement within the first 5–10 h. In contrast, 1200 nm particles showed slower, continuous reduction requiring &gt;15 h of milling. SVM models successfully captured these nonlinear trends, with minor underestimations at intermediate time points. RSM plots for aluminum particle sizes (21 and 71 μm) revealed that Al-21 led to stable and uniform distributions, whereas Al-71 exhibited nonlinear behavior with volume percentage drops under specific conditions. These findings confirm that SVM and GPR are robust tools for modeling PSD and surface evolution in ball-milled nanoparticles.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"106 ","pages":"Pages 156-173"},"PeriodicalIF":4.3,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of fine-grinding products in horizontal stirred mill: Particle size distribution prediction, parameter optimization, industrial comparison, and fluid motion simulation","authors":"Hongquan Wei ,&nbsp;Xiaolong Zhang ,&nbsp;Ruizhe Liu ,&nbsp;Ruichen Wang ,&nbsp;Yuexin Han","doi":"10.1016/j.partic.2025.07.015","DOIUrl":"10.1016/j.partic.2025.07.015","url":null,"abstract":"<div><div>Fine grinding was an essential process in the development and utilization of mineral resources, and a horizontal stirred mill, as a representative equipment for fine grinding, was widely used in the fields of mining and metallurgy. In this study, the prediction and optimization of the particle size distribution for the grinding product in a horizontal stirred mill was carried out. A prediction equation of particle size distribution for grinding products in a horizontal stirred mill was established based on grinding kinetics principles, with a relative error of 5 %. The effect of grinding process parameters on the grinding efficiency was investigated. The results indicated that the grinding parameters had a significant effect on the particle size distribution of the grinding product. Under the optimum conditions (mill speed 1700 rpm, grinding concentration 36 %, pulp handling capacity 20 L/h, and media filling ratio 54 %), the content of −45 + 15 μm was 40.01 %, and the uniformity index <em>n</em> was 0.99, with a uniform particle size distribution. The fluid motion simulation results indicated that the high-velocity gradient and high turbulence intensity occurred near the stirring disk with a better grinding effect, relatively, the grinding effect near the barrel wall was poor.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"105 ","pages":"Pages 64-73"},"PeriodicalIF":4.3,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CFD-DEM investigation of fluidization of the non-monodisperse particle system in a spouted bed","authors":"Dianyu E ,&nbsp;Yiliu Wu ,&nbsp;Yingming Wen ,&nbsp;Weifu Sun ,&nbsp;Kaiwei Chu ,&nbsp;Jin Xu ,&nbsp;Huaqing Ma ,&nbsp;Jiaxin Cui","doi":"10.1016/j.partic.2025.07.014","DOIUrl":"10.1016/j.partic.2025.07.014","url":null,"abstract":"<div><div>Spouted bed is a type of fluidized bed that has been widely used in various industrial processes because of its excellent mass and heat transfer efficiency. In practical applications, the fluidization of the multicomponent particle system containing non-spherical particles is frequently encountered in spouted beds. To better understand the spouting behaviors of the multicomponent particle system, therefore, this study employs a CFD-DEM (Computational Fluid Dynamics-Discrete Element Method) coupling approach to investigate the spouting behaviors. Spherical particles along with two types of ellipsoidal particles (i.e., oblate ellipsoid, and prolate ellipsoid) are included in this paper. Through the combination of these three particle types, seven distinct systems (three monodisperse systems, three binary mixtures, and one ternary mixture) are simulated to analyze the effects of particle shape and composition of particle systems on spouting behaviors. The simulation results reveal that introducing non-spherical particles into systems containing either spherical or oblate ellipsoidal particles tends to enhance spouting behaviors, whereas adding spherical particles to prolate ellipsoidal particle systems inclines to suppress it. The addition of non-spherical particles into the spherical particle system can enhance the particle interlocks, and using the oblate particles should have more important influence than prolate particles. Moreover, the influence of particle shape on the spout deflection behaviors is quite complicated, and the use of prolate ellipsoidal particles versus oblate ellipsoidal particles may produce opposite effects. These findings should provide valuable insights for optimizing spouted bed operations involving complex particle mixtures.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"105 ","pages":"Pages 51-63"},"PeriodicalIF":4.3,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing rice bran ball milling via a friction-coupled population balance model: Integrating comminution theory and energy efficiency","authors":"Rogério Andrade,&nbsp;Amanda Barros,&nbsp;Leonardo Batista,&nbsp;Janaina Lima,&nbsp;Ana Sarinho,&nbsp;Renata Almeida,&nbsp;Hugo M. Lisboa","doi":"10.1016/j.partic.2025.07.013","DOIUrl":"10.1016/j.partic.2025.07.013","url":null,"abstract":"<div><div>Despite rice bran's considerable nutritional and functional potential, its fibrous structure and high oil content complicate efforts to produce uniform, finely milled powders for food and nutraceutical applications. This study addresses that challenge by examining how milling time (30–90 min) and rotational speed (30–120 rpm) influence both the extent of particle size reduction and the associated energy demand. A laboratory ball mill was used to generate a broad range of operating conditions, while mechanical energy usage and particle-size parameters (<em>d</em>₁₀, <em>d</em>₅₀, <em>d</em>₉₀) were recorded. Population Balance Modeling (PBM) served as the primary analytical framework, calibrated through experimental size distributions to yield breakage kinetics. Frictional effects were incorporated to determine net breakage energy, and classical comminution laws (Bond, Rittinger, Kick) were also evaluated for benchmarking. Results revealed two key milling regimes: an early stage with rapid fragmentation of larger particles, followed by a fine-dominated phase marked by diminished breakage rates and agglomeration. Friction-coupled PBM simulations achieved near-unity parity with experimental data, significantly improving upon simplistic energy models. Short, high-speed milling (e.g., 30 min at 120 rpm) delivered moderate fineness (<em>d</em>₅₀ ≈ 70–90 μm) at relatively low energy (≈0.002–0.005 kWh/ton), whereas prolonged milling (≥90 min) could push median sizes below 5 μm but escalated energy consumption (∼5 kWh/ton). These findings highlight the trade-off between achieving ultra-fine bran and managing rising power costs. By integrating friction-coupled PBM insights with empirical measurements, the study provides a rigorous basis for multi-objective process optimization, guiding industrial-scale rice bran milling toward both enhanced product quality and improved energy efficiency.</div></div>","PeriodicalId":401,"journal":{"name":"Particuology","volume":"105 ","pages":"Pages 36-50"},"PeriodicalIF":4.3,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144723184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}