Pub Date : 2026-01-26DOI: 10.1016/j.powtec.2026.122172
Guoliang Zhao , Jian Liu , Ye Wang , Rong Huang , Jiamei Hao , Hulin Gao
Cassiterite was the core raw material of the tin industry, and its separation and purification were crucial, and the removal of impurities such as calcite becomes the key to cassiterite flotation. This study investigated the depressant effect of carboxymethyl chitosan (CMCS) on the flotation separation of cassiterite from calcite and explored its depressant mechanism in detail. The artificial mixed minerals yielded a cassiterite concentrate with a grade of 73.21% and a recovery rate of 83.11%. SEM-EDS results revealed weak CMCS adsorption on cassiterite surfaces but significant adsorption on calcite. FTIR and XPS analyses further confirmed that Ca sites on calcite surfaces had a higher affinity for CMCS than cassiterite. MD simulations provided microscopic evidence for CMCS adsorption on calcite surfaces by illustrating the spatial distribution of water molecules. Density functional theory (DFT) calculations demonstrated that CMCS formed CaO bonds with calcite. This study provides a theoretical basis and promising new strategies for the flotation separation of cassiterite and calcite.
{"title":"Selective adsorption mechanism of novel depressant CMCS in cassiterite/calcite flotation system: Experimental and computational simulation study","authors":"Guoliang Zhao , Jian Liu , Ye Wang , Rong Huang , Jiamei Hao , Hulin Gao","doi":"10.1016/j.powtec.2026.122172","DOIUrl":"10.1016/j.powtec.2026.122172","url":null,"abstract":"<div><div>Cassiterite was the core raw material of the tin industry, and its separation and purification were crucial, and the removal of impurities such as calcite becomes the key to cassiterite flotation. This study investigated the depressant effect of carboxymethyl chitosan (CMCS) on the flotation separation of cassiterite from calcite and explored its depressant mechanism in detail. The artificial mixed minerals yielded a cassiterite concentrate with a grade of 73.21% and a recovery rate of 83.11%. SEM-EDS results revealed weak CMCS adsorption on cassiterite surfaces but significant adsorption on calcite. FTIR and XPS analyses further confirmed that Ca sites on calcite surfaces had a higher affinity for CMCS than cassiterite. MD simulations provided microscopic evidence for CMCS adsorption on calcite surfaces by illustrating the spatial distribution of water molecules. Density functional theory (DFT) calculations demonstrated that CMCS formed Ca<img>O bonds with calcite. This study provides a theoretical basis and promising new strategies for the flotation separation of cassiterite and calcite.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"473 ","pages":"Article 122172"},"PeriodicalIF":4.6,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-25DOI: 10.1016/j.powtec.2026.122165
Shuai Wang , Xushu Zeng , Yuxin Ge , Zhanheng Zhu , Kun Luo , Jianren Fan
Industrial-scale screw conveyors are widely employed for the efficient conveying and heating of particulate materials; however, the particle dynamics and heat transfer characteristics within such systems remain insufficiently understood. In this study, a high-fidelity discrete element method (DEM) model was employed to systematically investigate the influence mechanisms of two key design parameters (i.e., screw blade configurations and screw pitch) on particle flow behavior, residence time, temperature distribution, and mixing uniformity. The results reveal that increasing the pitch from 200 mm to 400 mm significantly and almost linearly enhances both conveying and heating rates; however, an excessively large pitch compromises heat retention at the outlet, while a 300 mm pitch achieves the optimal balance between conveying efficiency and heat transfer performance. The baffle configuration extends particle residence time by approximately 10%, improves longitudinal lifting and tumbling, and slightly enhances mixing uniformity. The chain configuration increases residence time by about 50% and promotes more thorough mixing, yet tends to generate stagnant zones in the mid-section of the conveyor. A particle size segregation effect is observed, with fine particles accumulating in the lower layers and coarse particles in the upper layers. While this stratification enlarges the effective heat transfer contact area, excessive segregation can conversely hinder overall heat transfer. These findings provide a systematic theoretical foundation and practical engineering guidance for the structural optimization and parameter selection of industrial-scale screw conveyors.
{"title":"Effect of blade configuration and screw pitch on granular flow and heat transfer in industrial-scale screw conveyors: A DEM study","authors":"Shuai Wang , Xushu Zeng , Yuxin Ge , Zhanheng Zhu , Kun Luo , Jianren Fan","doi":"10.1016/j.powtec.2026.122165","DOIUrl":"10.1016/j.powtec.2026.122165","url":null,"abstract":"<div><div>Industrial-scale screw conveyors are widely employed for the efficient conveying and heating of particulate materials; however, the particle dynamics and heat transfer characteristics within such systems remain insufficiently understood. In this study, a high-fidelity discrete element method (DEM) model was employed to systematically investigate the influence mechanisms of two key design parameters (i.e., screw blade configurations and screw pitch) on particle flow behavior, residence time, temperature distribution, and mixing uniformity. The results reveal that increasing the pitch from 200 mm to 400 mm significantly and almost linearly enhances both conveying and heating rates; however, an excessively large pitch compromises heat retention at the outlet, while a 300 mm pitch achieves the optimal balance between conveying efficiency and heat transfer performance. The baffle configuration extends particle residence time by approximately 10%, improves longitudinal lifting and tumbling, and slightly enhances mixing uniformity. The chain configuration increases residence time by about 50% and promotes more thorough mixing, yet tends to generate stagnant zones in the mid-section of the conveyor. A particle size segregation effect is observed, with fine particles accumulating in the lower layers and coarse particles in the upper layers. While this stratification enlarges the effective heat transfer contact area, excessive segregation can conversely hinder overall heat transfer. These findings provide a systematic theoretical foundation and practical engineering guidance for the structural optimization and parameter selection of industrial-scale screw conveyors.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"473 ","pages":"Article 122165"},"PeriodicalIF":4.6,"publicationDate":"2026-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-24DOI: 10.1016/j.powtec.2026.122170
Weiwen Lu , Shuang Lin , Shihua Shao , Kangkang Tan , Liangjun Chen , Hongming Long , Zhengwei Yu
The pellet size distribution, as a critical factor affecting blast furnace permeability, reduction reaction kinetics, and hot metal quality. Its high-precision online identification is essential for optimizing pelletizing parameters, improving pellet quality, and sustaining the stable and efficient operation of the blast furnace. In practical applications, machine vision-based pellet size identification is vulnerable to particle segregation, material stacking, and imaging distortions, which cause substantial discrepancies between the surface and true bulk size distributions and ultimately hinder its engineering applicability and large-scale industrial adoption. To address these issues, this study proposes a fused GAN_GVMD_ARNN integrated neural network model to correct the pellet size distribution data obtained from machine vision. After correction, 88% of the samples exhibit a deviation within ±2% between the image-based size composition and the results of sieve analysis. The experimental results demonstrate that the proposed model can effectively enhance the accuracy of pellet size distribution detection and significantly reduce measurement errors, providing a new technical pathway for image-based granulometric analysis.
{"title":"High-precision online correction of pellet size distribution under stacking conditions: An ARNN model enhanced by GAN-GVMD and attention mechanism","authors":"Weiwen Lu , Shuang Lin , Shihua Shao , Kangkang Tan , Liangjun Chen , Hongming Long , Zhengwei Yu","doi":"10.1016/j.powtec.2026.122170","DOIUrl":"10.1016/j.powtec.2026.122170","url":null,"abstract":"<div><div>The pellet size distribution, as a critical factor affecting blast furnace permeability, reduction reaction kinetics, and hot metal quality. Its high-precision online identification is essential for optimizing pelletizing parameters, improving pellet quality, and sustaining the stable and efficient operation of the blast furnace. In practical applications, machine vision-based pellet size identification is vulnerable to particle segregation, material stacking, and imaging distortions, which cause substantial discrepancies between the surface and true bulk size distributions and ultimately hinder its engineering applicability and large-scale industrial adoption. To address these issues, this study proposes a fused GAN_GVMD_ARNN integrated neural network model to correct the pellet size distribution data obtained from machine vision. After correction, 88% of the samples exhibit a deviation within ±2% between the image-based size composition and the results of sieve analysis. The experimental results demonstrate that the proposed model can effectively enhance the accuracy of pellet size distribution detection and significantly reduce measurement errors, providing a new technical pathway for image-based granulometric analysis.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"473 ","pages":"Article 122170"},"PeriodicalIF":4.6,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-24DOI: 10.1016/j.powtec.2026.122162
Xiangwei Liu , Changyu Wang , Yuqing Feng , Yandi Wang , Ruizhi Dong , Heiko Briesen , Yuan Tan
During the storage and handling of food grains, moisture variation causes particles to swell and agglomerate, which strongly influences their flow behavior. As the most suitable numerical modeling tools for such particulate systems, the discrete element method (DEM) still struggles to balance geometric accuracy, computational efficiency and experimental calibration effort at different moisture levels. This study develops a size-class–weighted DEM calibration framework that efficiently captures the combined influence of moisture-induced particle morphology on flowability, using soybeans as a representative food grain. The framework enables rapid construction of quasi-spherical particle models composed of six sub-spheres, reproducing shape changes across a broad moisture range (0.50–21.62 wt%) while reducing calibration workload by ∼75%. Calibration was performed using angle-of-tilting tests, from which a flowability index was derived. Validation through angle-of-repose tests achieved up to 99.6% agreement with experiments, confirming the framework's reliability. The calibrated and validated model revealed a non-monotonic relationship between moisture and flowability, with the lowest flowability observed at 17.12 wt% moisture before improving at higher levels. Overall, this work provides a physically grounded and computationally efficient approach for predicting moisture-dependent flowability in soybeans and other grains with similar morphology, enhancing the understanding and control of particulate behavior in food processing systems.
{"title":"A novel size-class-weighted DEM calibration framework for predicting the moisture-dependent flowability of soybean","authors":"Xiangwei Liu , Changyu Wang , Yuqing Feng , Yandi Wang , Ruizhi Dong , Heiko Briesen , Yuan Tan","doi":"10.1016/j.powtec.2026.122162","DOIUrl":"10.1016/j.powtec.2026.122162","url":null,"abstract":"<div><div>During the storage and handling of food grains, moisture variation causes particles to swell and agglomerate, which strongly influences their flow behavior. As the most suitable numerical modeling tools for such particulate systems, the discrete element method (DEM) still struggles to balance geometric accuracy, computational efficiency and experimental calibration effort at different moisture levels. This study develops a size-class–weighted DEM calibration framework that efficiently captures the combined influence of moisture-induced particle morphology on flowability, using soybeans as a representative food grain. The framework enables rapid construction of quasi-spherical particle models composed of six sub-spheres, reproducing shape changes across a broad moisture range (0.50–21.62 wt%) while reducing calibration workload by ∼75%. Calibration was performed using angle-of-tilting tests, from which a flowability index was derived. Validation through angle-of-repose tests achieved up to 99.6% agreement with experiments, confirming the framework's reliability. The calibrated and validated model revealed a non-monotonic relationship between moisture and flowability, with the lowest flowability observed at 17.12 wt% moisture before improving at higher levels. Overall, this work provides a physically grounded and computationally efficient approach for predicting moisture-dependent flowability in soybeans and other grains with similar morphology, enhancing the understanding and control of particulate behavior in food processing systems.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"473 ","pages":"Article 122162"},"PeriodicalIF":4.6,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-24DOI: 10.1016/j.powtec.2026.122171
Renjie Yang , Xun Wang , Xian Xie , Xiong Tong , Ruiqi Xie
Efficient flotation of fine-grained cassiterite is a universally recognized challenge in the tin mineral processing industry. Currently, the traditional flotation process faces issues in its recovery, including low tin recovery rate, high gangue entrainment, and excessive reagent consumption. For the first time, this study employed sodium monododecyl phosphate (SMP) as a hydrophobic modifier to pretreat fine-grained cassiterite, realizing the mineral's selective hydrophobic agglomeration and thereby enhancing its flotation recovery with the traditional collector salicylhydroxamic acid (SHA). Flotation experimental results showed that SHA performed poorly in floating the −23 μm cassiterite fraction, with a recovery of only 14.69% under optimal conditions. In contrast, pretreating fine-grained cassiterite with SMP (stirring speed: 700 rpm, pH: 9, SMP concentration: 130 mg/L, stirring time: 5 min) increased its recovery to 80.39% (an enhancement of 65.70%) under otherwise unchanged flotation conditions. Furthermore, artificial mixed ore flotation experiments confirmed that SMP exerted a favorable selective hydrophobic agglomeration effect on cassiterite, enabling the selective enhanced recovery of cassiterite in cassiterite-quartz mixed systems. Additionally, the mechanism underlying SMP-induced flotation enhancement was clarified using a series of surface analysis techniques. SMP forms chemical bonds with Sn atoms on the cassiterite surface using its phosphate groups as anchoring sites, ultimately generating stable Sn-O-P-O-Sn five-membered cyclic chelates adsorbed on the cassiterite surface. This enhances inter-particle hydrophobic interactions, promotes cassiterite agglomeration, increases the mineral's apparent particle size, and thus strengthens flotation recovery. This study provides a novel hydrophobic modifier and a feasible strategy for the efficient flotation of fine-grained cassiterite.
细粒锡石的高效浮选是锡矿加工行业公认的难题。目前，传统浮选工艺在回收上存在锡回收率低、带矸量大、药剂用量大等问题。本研究首次采用单十二烷基磷酸钠（SMP）作为疏水改性剂对细粒锡石进行预处理，实现矿物的选择性疏水团聚，从而提高其与传统捕收剂水杨基羟肟酸（SHA）的浮选回收率。浮选实验结果表明，在最佳条件下，SHA对−23 μm锡石的浮选效果较差，回收率仅为14.69%。在不改变浮选条件的情况下，采用SMP（搅拌转速700 rpm、pH = 9、SMP浓度130 mg/L、搅拌时间5 min）预处理细粒锡石，回收率可达80.39%（提高65.70%）。此外，人工混矿浮选实验证实，SMP对锡石具有良好的选择性疏水团聚作用，可在锡石-石英混合体系中选择性提高锡石的回收率。此外，通过一系列表面分析技术，阐明了smp诱导浮选增强的机理。SMP以其磷酸基作为锚定位点与锡石表面的Sn原子形成化学键，最终生成稳定的Sn- o - p - o -Sn五元环螯合物吸附在锡石表面。这加强了颗粒间疏水相互作用，促进锡石团聚，增加矿物的表观粒度，从而加强浮选回收率。本研究为细粒锡石的高效浮选提供了一种新的疏水改性剂和可行的策略。
{"title":"Study on enhanced flotation of fine-grained cassiterite using sodium monododecyl phosphate as a novel hydrophobic modifier and its mechanism","authors":"Renjie Yang , Xun Wang , Xian Xie , Xiong Tong , Ruiqi Xie","doi":"10.1016/j.powtec.2026.122171","DOIUrl":"10.1016/j.powtec.2026.122171","url":null,"abstract":"<div><div>Efficient flotation of fine-grained cassiterite is a universally recognized challenge in the tin mineral processing industry. Currently, the traditional flotation process faces issues in its recovery, including low tin recovery rate, high gangue entrainment, and excessive reagent consumption. For the first time, this study employed sodium monododecyl phosphate (SMP) as a hydrophobic modifier to pretreat fine-grained cassiterite, realizing the mineral's selective hydrophobic agglomeration and thereby enhancing its flotation recovery with the traditional collector salicylhydroxamic acid (SHA). Flotation experimental results showed that SHA performed poorly in floating the −23 μm cassiterite fraction, with a recovery of only 14.69% under optimal conditions. In contrast, pretreating fine-grained cassiterite with SMP (stirring speed: 700 rpm, pH: 9, SMP concentration: 130 mg/L, stirring time: 5 min) increased its recovery to 80.39% (an enhancement of 65.70%) under otherwise unchanged flotation conditions. Furthermore, artificial mixed ore flotation experiments confirmed that SMP exerted a favorable selective hydrophobic agglomeration effect on cassiterite, enabling the selective enhanced recovery of cassiterite in cassiterite-quartz mixed systems. Additionally, the mechanism underlying SMP-induced flotation enhancement was clarified using a series of surface analysis techniques. SMP forms chemical bonds with Sn atoms on the cassiterite surface using its phosphate groups as anchoring sites, ultimately generating stable Sn-O-P-O-Sn five-membered cyclic chelates adsorbed on the cassiterite surface. This enhances inter-particle hydrophobic interactions, promotes cassiterite agglomeration, increases the mineral's apparent particle size, and thus strengthens flotation recovery. This study provides a novel hydrophobic modifier and a feasible strategy for the efficient flotation of fine-grained cassiterite.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"473 ","pages":"Article 122171"},"PeriodicalIF":4.6,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-23DOI: 10.1016/j.powtec.2026.122166
Ge Yu , Yifu Long , Deyu Yue , Meng Li , Yafeng Yang , Shaofu Li , Xizhong An
Laser powder bed fusion (L-PBF) additive manufacturing (AM) of titanium alloys involves complex interactions between thermal and fluid phenomena that strongly influence molten pool geometry, surface morphology, and defect formation. However, conventional experimental and numerical optimization of process parameters is computationally expensive and unsuitable for rapid quality prediction. This study establishes a machine learning (ML) – Shapley additive explanation (SHAP) framework for fast and interpretable prediction of key quality indicators, including molten pool depth, surface roughness, and pore type of L-PBF titanium alloys, using datasets generated from a validated discrete element method (DEM) - computational fluid dynamics (CFD) numerical simulations. Seven ML algorithms (Regression, KNN, BPNN, DT, RF, SVR, and XGBoost) are systematically evaluated with min-max normalized inputs and 5-fold cross-validation. Among them, XGBoost demonstrates the best balance of prediction accuracy, generalization, and efficiency across both regression and classification tasks. To enhance interpretability and reduce the impact of experimental design, SHAP is applied to quantify feature contributions, nonlinear dependence trends, and parameter interaction effects. The SHAP results reveal that molten pool depth is primarily governed by laser power, whereas surface roughness and pore type are dominated by laser scanning velocity. Dependence and partial dependence analysis further uncover monotonic relationships and class switches, such as the strong positive sensitivity of depth to energy input, the suppression of shrinkage pores driven by velocity, and the linear promotion of lack-of-fusion pores by hatch spacing. SHAP interaction matrices confirm that coupled effects between laser power and scanning velocity control both molten pool morphology and pore transition mechanisms, while combinations involving hatch spacing exhibit only weak interactions. Overall, this interpretable ML-SHAP framework not only achieves rapid and accurate prediction of material quality indicators but also provides mechanistic insights consistent with underlying L-PBF physics. The developed approach offers a practical and physically informed tool for intelligent parameter optimization and quality control in additive manufacturing of titanium alloys.
{"title":"Machine learning rapid prediction for quality indicators in advanced manufacturing processes of titanium alloys","authors":"Ge Yu , Yifu Long , Deyu Yue , Meng Li , Yafeng Yang , Shaofu Li , Xizhong An","doi":"10.1016/j.powtec.2026.122166","DOIUrl":"10.1016/j.powtec.2026.122166","url":null,"abstract":"<div><div>Laser powder bed fusion (L-PBF) additive manufacturing (AM) of titanium alloys involves complex interactions between thermal and fluid phenomena that strongly influence molten pool geometry, surface morphology, and defect formation. However, conventional experimental and numerical optimization of process parameters is computationally expensive and unsuitable for rapid quality prediction. This study establishes a machine learning (ML) – Shapley additive explanation (SHAP) framework for fast and interpretable prediction of key quality indicators, including molten pool depth, surface roughness, and pore type of L-PBF titanium alloys, using datasets generated from a validated discrete element method (DEM) - computational fluid dynamics (CFD) numerical simulations. Seven ML algorithms (Regression, KNN, BPNN, DT, RF, SVR, and XGBoost) are systematically evaluated with min-max normalized inputs and 5-fold cross-validation. Among them, XGBoost demonstrates the best balance of prediction accuracy, generalization, and efficiency across both regression and classification tasks. To enhance interpretability and reduce the impact of experimental design, SHAP is applied to quantify feature contributions, nonlinear dependence trends, and parameter interaction effects. The SHAP results reveal that molten pool depth is primarily governed by laser power, whereas surface roughness and pore type are dominated by laser scanning velocity. Dependence and partial dependence analysis further uncover monotonic relationships and class switches, such as the strong positive sensitivity of depth to energy input, the suppression of shrinkage pores driven by velocity, and the linear promotion of lack-of-fusion pores by hatch spacing. SHAP interaction matrices confirm that coupled effects between laser power and scanning velocity control both molten pool morphology and pore transition mechanisms, while combinations involving hatch spacing exhibit only weak interactions. Overall, this interpretable ML-SHAP framework not only achieves rapid and accurate prediction of material quality indicators but also provides mechanistic insights consistent with underlying L-PBF physics. The developed approach offers a practical and physically informed tool for intelligent parameter optimization and quality control in additive manufacturing of titanium alloys.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"473 ","pages":"Article 122166"},"PeriodicalIF":4.6,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-23DOI: 10.1016/j.powtec.2026.122164
Tokio Morimoto
We assess Pore Network Modeling (PNM) and coarse-grid CFD (CG-CFD) methods for predicting fluid–particle interaction forces that control initiation of internal erosion (suffusion/suffosion) in gap-graded, cohesionless soils — a practical problem for dams, levees and embankments. Two DEM-generated benchmark packings with size ratio 10, a 45% fine-content overfilled (suffosion-prone) sample and a 10% fine-content underfilled (suffusion-prone) sample, were simulated with fully-resolved CFD (FR-CFD) using a fluid mesh 30 times finer than the smallest particle to produce reference force fields. FR-CFD revealed strong pressure and velocity heterogeneity and large variability in forces on fines. The PNM reproduced spatial heterogeneity, force magnitudes and directions for both coarse and fine particles with excellent agreement to FR-CFD, demonstrating suitability for engineering analyses of internal instability at much lower cost. Standard empirical models used in CG-CFD predicted total forces on coarse particles reasonably well but failed to capture force variability on fines because they depend only on particle diameter and global velocity. A local-solid-fraction drag correction improved coarse–fine differentiation but still poorly matched forces on fines, indicating that local porosity alone is insufficient. Findings show that pore geometry and connectivity—captured by PNM—are essential to predict fluid-particle interaction forces on fines in gap-graded packs. The FR-CFD benchmarks and PNM validation presented here enable more reliable, computationally efficient CFD–DEM assessments of susceptibility to suffusion and suffosion in geotechnical practice.
{"title":"Critical appraisal of pore network and coarse-grid CFD models for predicting fluid–particle interaction forces in gap-graded soils","authors":"Tokio Morimoto","doi":"10.1016/j.powtec.2026.122164","DOIUrl":"10.1016/j.powtec.2026.122164","url":null,"abstract":"<div><div>We assess Pore Network Modeling (PNM) and coarse-grid CFD (CG-CFD) methods for predicting fluid–particle interaction forces that control initiation of internal erosion (suffusion/suffosion) in gap-graded, cohesionless soils — a practical problem for dams, levees and embankments. Two DEM-generated benchmark packings with size ratio 10, a 45% fine-content overfilled (suffosion-prone) sample and a 10% fine-content underfilled (suffusion-prone) sample, were simulated with fully-resolved CFD (FR-CFD) using a fluid mesh 30 times finer than the smallest particle to produce reference force fields. FR-CFD revealed strong pressure and velocity heterogeneity and large variability in forces on fines. The PNM reproduced spatial heterogeneity, force magnitudes and directions for both coarse and fine particles with excellent agreement to FR-CFD, demonstrating suitability for engineering analyses of internal instability at much lower cost. Standard empirical models used in CG-CFD predicted total forces on coarse particles reasonably well but failed to capture force variability on fines because they depend only on particle diameter and global velocity. A local-solid-fraction drag correction improved coarse–fine differentiation but still poorly matched forces on fines, indicating that local porosity alone is insufficient. Findings show that pore geometry and connectivity—captured by PNM—are essential to predict fluid-particle interaction forces on fines in gap-graded packs. The FR-CFD benchmarks and PNM validation presented here enable more reliable, computationally efficient CFD–DEM assessments of susceptibility to suffusion and suffosion in geotechnical practice.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"473 ","pages":"Article 122164"},"PeriodicalIF":4.6,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146045219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The presence of endogenous Cl− in sea sand and seawater will deteriorate the mechanical properties and durability of marine structures, and are the main reason restricting its large-scale application. The hydration heat, Cl− content, compressive and flexural strength of seawater and sea sand mortar are measured in this paper. The macroscopic analysis indicates that during initial phase of cement hydration, the presence of endogenous Cl− and nanoparticles collectively accelerate hydration process and boost the early compressive strength. Adding nano-CaCO3 can promote the participation of endogenous Cl− in hydration, while nano-SiO2 reduces the participation of endogenous Cl− in hydration. In later stage of hydration, endogenous Cl− reduces the strength, while nanoparticles can enhance the Cl− bonding capacity and strength and reduce the deterioration of strength caused by endogenous Cl−. Microscopic results show that nano-CaCO₃ facilitates the reaction between a greater amount of endogenous Cl− and Ca(OH)₂, generating more Friedel's salt. However, nano-SiO₂ preferentially reacts with Ca(OH)₂ to produce C-S-H gels, suppressing the generation of Friedel's salt. Adding nano-CaCO3 can enhance the chemical bonding Cl− capacity, while adding nano-SiO2, although it reduces the chemical bonding capacity of mortar, improves its physical adsorption Cl− capacity. Furthermore, nanoparticles limit the size and aggregation of Friedel's salt, reducing the influence of endogenous Cl− on strength deterioration.
{"title":"Combined effects of nanoparticles and endogenous Cl− on cement hydration, mortar strength and microstructure in marine structures","authors":"Maohua Zhang , Jiyin Cui , Fating Xie , Daocheng Zhou","doi":"10.1016/j.powtec.2026.122158","DOIUrl":"10.1016/j.powtec.2026.122158","url":null,"abstract":"<div><div>The presence of endogenous Cl<sup>−</sup> in sea sand and seawater will deteriorate the mechanical properties and durability of marine structures, and are the main reason restricting its large-scale application. The hydration heat, Cl<sup>−</sup> content, compressive and flexural strength of seawater and sea sand mortar are measured in this paper. The macroscopic analysis indicates that during initial phase of cement hydration, the presence of endogenous Cl<sup>−</sup> and nanoparticles collectively accelerate hydration process and boost the early compressive strength. Adding nano-CaCO<sub>3</sub> can promote the participation of endogenous Cl<sup>−</sup> in hydration, while nano-SiO<sub>2</sub> reduces the participation of endogenous Cl<sup>−</sup> in hydration. In later stage of hydration, endogenous Cl<sup>−</sup> reduces the strength, while nanoparticles can enhance the Cl<sup>−</sup> bonding capacity and strength and reduce the deterioration of strength caused by endogenous Cl<sup>−</sup>. Microscopic results show that nano-CaCO₃ facilitates the reaction between a greater amount of endogenous Cl<sup>−</sup> and Ca(OH)₂, generating more Friedel's salt. However, nano-SiO₂ preferentially reacts with Ca(OH)₂ to produce C-S-H gels, suppressing the generation of Friedel's salt. Adding nano-CaCO<sub>3</sub> can enhance the chemical bonding Cl<sup>−</sup> capacity, while adding nano-SiO<sub>2</sub>, although it reduces the chemical bonding capacity of mortar, improves its physical adsorption Cl<sup>−</sup> capacity. Furthermore, nanoparticles limit the size and aggregation of Friedel's salt, reducing the influence of endogenous Cl<sup>−</sup> on strength deterioration.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"473 ","pages":"Article 122158"},"PeriodicalIF":4.6,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-22DOI: 10.1016/j.powtec.2026.122167
Xiting Li , Zhuo Chen , Haiming Cheng , Qihang Wang , Min Gu , Weitong Du , Jiayong Qiu
The declining quality of global crude oil has led to a steady rise in the output of medium- and high‑sulfur petroleum coke (HSPC), driving research into its utilization in higher-value applications such as fuel or as a reducing agent in industrial processes. In this study, a one-step method was developed for simultaneous desulfurization and preparation of metallized pellets through carbothermal reduction of Zinc-bearing dust using HSPC. The effects of alkaline additives (KOH and NaOH) were systematically examined alongside key parameters including temperature and additive dosage. Thermodynamic analysis and mineralogical characterization elucidated the core mechanism: alkaline additives chemically fix gaseous sulfur species into stable solid sulfates, while concurrently modifying the slag phase structure to encapsulate residual sulfur, thereby achieving efficient sulfur immobilization and separation from the metallic phase. Results showed that sulfur content progressively decreased with rising temperature. Notably, at the optimum condition of 1400 °C with an 8% additive dosage, the desulfurization efficiency reached maximum of 69.88% for NaOH and 72.76% for KOH, demonstrating their superior performance. The majority of residual sulfur was retained within the slag phase as sulfides, enabling clear phase segregation from metallic iron without hindering its formation.
{"title":"One-step desulfurization of metallized pellets roasted by high-sulfur petroleum coke and zinc-bearing dust: Migration and removal mechanisms of sulfur","authors":"Xiting Li , Zhuo Chen , Haiming Cheng , Qihang Wang , Min Gu , Weitong Du , Jiayong Qiu","doi":"10.1016/j.powtec.2026.122167","DOIUrl":"10.1016/j.powtec.2026.122167","url":null,"abstract":"<div><div>The declining quality of global crude oil has led to a steady rise in the output of medium- and high‑sulfur petroleum coke (HSPC), driving research into its utilization in higher-value applications such as fuel or as a reducing agent in industrial processes. In this study, a one-step method was developed for simultaneous desulfurization and preparation of metallized pellets through carbothermal reduction of Zinc-bearing dust using HSPC. The effects of alkaline additives (KOH and NaOH) were systematically examined alongside key parameters including temperature and additive dosage. Thermodynamic analysis and mineralogical characterization elucidated the core mechanism: alkaline additives chemically fix gaseous sulfur species into stable solid sulfates, while concurrently modifying the slag phase structure to encapsulate residual sulfur, thereby achieving efficient sulfur immobilization and separation from the metallic phase. Results showed that sulfur content progressively decreased with rising temperature. Notably, at the optimum condition of 1400 °C with an 8% additive dosage, the desulfurization efficiency reached maximum of 69.88% for NaOH and 72.76% for KOH, demonstrating their superior performance. The majority of residual sulfur was retained within the slag phase as sulfides, enabling clear phase segregation from metallic iron without hindering its formation.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"473 ","pages":"Article 122167"},"PeriodicalIF":4.6,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-22DOI: 10.1016/j.powtec.2026.122163
Yuanfei Lan , Houan Zhang , Jiqiong Lian , Haoyu Cai
Porous anatase TiO2 is a promising candidate for environmental remediation due to its high photocatalytic activity. However, achieving precise control over its pore structure and crystallinity remains challenging. Here, we regulated the architecture of TiO2 microspheres by adjusting the size of silica templates (53–200 nm) and the precursor concentration. The template size dictates macropore replication through spatial confinement, with an intermediate template size (∼108 nm) yielding the best balance between specific surface area (14.91 m2 g−1) and pore volume (0.13 cm3 g−1). The precursor concentration influences crystal growth kinetics, where the optimized condition results in the formation of an interconnected mesoporous network composed of nanosheet assemblies. Structural optimization enhances light scattering and inhibits electron–hole recombination, as confirmed by ultraviolet–visible spectroscopy and photoluminescence analyses. Among all samples, the TiO2 microsphere prepared with a 108 nm SiO2 template and precursor concentration of 0.1 mol L−1 (S108M06) exhibits the highest photocatalytic performance for methylene blue degradation, achieving 88.8% degradation efficiency within 60 min, with an apparent first order rate constant of k = 0.035 min−1. This study elucidates the existence of a synergistic mechanism based on geometric confinement and kinetic regulation, wherein the template imposes geometric confinement to form periodic pores, while the precursor concentration governs nucleation kinetics and crystal orientation. These findings provide systematic insight into how geometric confinement and growth kinetics cooperatively regulate the structure–property–performance relationships of porous TiO2 microspheres, offering guidance for the rational design of advanced photocatalysts.
{"title":"Controllable synthesis of porous anatase TiO2 microspheres: Regulating pore structure via template size and precursor concentration","authors":"Yuanfei Lan , Houan Zhang , Jiqiong Lian , Haoyu Cai","doi":"10.1016/j.powtec.2026.122163","DOIUrl":"10.1016/j.powtec.2026.122163","url":null,"abstract":"<div><div>Porous anatase TiO<sub>2</sub> is a promising candidate for environmental remediation due to its high photocatalytic activity. However, achieving precise control over its pore structure and crystallinity remains challenging. Here, we regulated the architecture of TiO<sub>2</sub> microspheres by adjusting the size of silica templates (53–200 nm) and the precursor concentration. The template size dictates macropore replication through spatial confinement, with an intermediate template size (∼108 nm) yielding the best balance between specific surface area (14.91 m<sup>2</sup> g<sup>−1</sup>) and pore volume (0.13 cm<sup>3</sup> g<sup>−1</sup>). The precursor concentration influences crystal growth kinetics, where the optimized condition results in the formation of an interconnected mesoporous network composed of nanosheet assemblies. Structural optimization enhances light scattering and inhibits electron–hole recombination, as confirmed by ultraviolet–visible spectroscopy and photoluminescence analyses. Among all samples, the TiO<sub>2</sub> microsphere prepared with a 108 nm SiO<sub>2</sub> template and precursor concentration of 0.1 mol L<sup>−1</sup> (S108M06) exhibits the highest photocatalytic performance for methylene blue degradation, achieving 88.8% degradation efficiency within 60 min, with an apparent first order rate constant of <em>k</em> = 0.035 min<sup>−1</sup>. This study elucidates the existence of a synergistic mechanism based on geometric confinement and kinetic regulation, wherein the template imposes geometric confinement to form periodic pores, while the precursor concentration governs nucleation kinetics and crystal orientation. These findings provide systematic insight into how geometric confinement and growth kinetics cooperatively regulate the structure–property–performance relationships of porous TiO<sub>2</sub> microspheres, offering guidance for the rational design of advanced photocatalysts.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"473 ","pages":"Article 122163"},"PeriodicalIF":4.6,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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