IF 2.3 4区材料科学

JOM Pub Date : 2025-09-05 DOI: 10.1007/s11837-025-07692-6

M. M. Sadawy, Saad. M. Fayed, Hani E. Sharafedin, A. I. Salem, Ahmed Hosny, Shengli Li

{"title":"Hydrated Nano-Blast Furnace Slag: A Green and Efficient Adsorbent for Industrial Wastewater Treatment","authors":"M. M. Sadawy, Saad. M. Fayed, Hani E. Sharafedin, A. I. Salem, Ahmed Hosny, Shengli Li","doi":"10.1007/s11837-025-07692-6","DOIUrl":"10.1007/s11837-025-07692-6","url":null,"abstract":"<div><p>This study investigated the efficiency of hydrated nanoscale blast furnace slag (NBFS) as a cost-effective and sustainable adsorbent for removing iron, copper, and zinc ions from wastewater. The NBFS was modified through a dual process involving nanoscale transformation and hydration with water (20 wt.%) for 7 days, enhancing its surface area and reactivity. The hydrated NBFS was characterized using XRF, SEM, EDS, FTIR, and XRD techniques, revealing its amorphous to crystalline transformation and the presence of OH<sup>−</sup> as a functional group. Batch adsorption experiments were conducted to optimize the parameters of adsorbent dosage, pH, contact time, initial ion concentration, and temperature. The results demonstrated remarkable removal efficiencies of 99.4% for Fe, 96.2% for Cu, and 93.7% for Zn at an optimal pH of 6, a contact time of 90 min, and a temperature of 70 °C. The adsorption process followed pseudo-second-order kinetics and the Langmuir isotherm model, indicating a chemisorption mechanism with monolayer coverage. Thermodynamic studies confirmed that the adsorption process was spontaneous. Additionally, the hydrated NBFS exhibited excellent reusability, maintaining a high removal efficiency over five consecutive adsorption-desorption cycles.</p></div>","PeriodicalId":605,"journal":{"name":"JOM","volume":"77 11","pages":"8534 - 8547"},"PeriodicalIF":2.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11837-025-07692-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145327635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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TMS Meeting Headlines TMS会议头条

IF 2.3 4区材料科学

JOM Pub Date : 2025-09-05 DOI: 10.1007/s11837-025-07773-6

引用次数: 0

Integrating Atomistic Simulations and Machine Learning to Predict Unstable Stacking Fault Energies of Refractory Non-dilute Random Alloys 集成原子模拟和机器学习预测难熔非稀随机合金不稳定层错能

IF 2.3 4区材料科学

JOM Pub Date : 2025-09-05 DOI: 10.1007/s11837-025-07728-x

Richard Brinlee, Amin Poozesh, Anvesh Nathani, Anshu Raj, Xiang-Guo Li, Iman Ghamarian, Shuozhi Xu

{"title":"Integrating Atomistic Simulations and Machine Learning to Predict Unstable Stacking Fault Energies of Refractory Non-dilute Random Alloys","authors":"Richard Brinlee, Amin Poozesh, Anvesh Nathani, Anshu Raj, Xiang-Guo Li, Iman Ghamarian, Shuozhi Xu","doi":"10.1007/s11837-025-07728-x","DOIUrl":"10.1007/s11837-025-07728-x","url":null,"abstract":"<div><p>This study utilizes three machine learning (ML) models—XGBoost, graph neural networks (GNN), and graph attention networks (GATs)—to predict unstable stacking fault energies (USFEs) in over 1000 refractory non-dilute random alloys, including mono, binary, ternary, quaternary, and quinary systems. Data for training are generated through atomistic simulations. In ML models, each chemical composition is encoded as a five-dimensional numerical vector to facilitate the representation of features, which are then normalized to balance the input scales during model training. Although explicit inter-composition connections are not included, the models learn compositional trends through node features and internal attention mechanisms. Because the lattice parameter is a byproduct in calculating the USFE in atomistic simulations, we also build three models for the lattice parameters. All models achieve reasonable accuracy in predicting lattice parameters but show variability in USFE predictions. Among the three models, GAT achieves the highest accuracy with average errors of 0.68% for USFE and 0.09% for the lattice parameter, outperforming GNN (1.24%, 0.11%) and XGBoost (0.46%, 0.54%). This study highlights the potential of graph-based ML models in predicting material properties from simulation-derived datasets, offering insights that could enhance traditional methods in materials science.</p></div>","PeriodicalId":605,"journal":{"name":"JOM","volume":"77 11","pages":"8127 - 8136"},"PeriodicalIF":2.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145327516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Optimization and Comparative Analysis of Neutralization Agents for Iron, Aluminum, and Chromium Removal in HPAL Pregnant Leach Solution HPAL妊娠浸出液中除铁、铝、铬中和剂的优化及对比分析

IF 2.3 4区材料科学

JOM Pub Date : 2025-09-05 DOI: 10.1007/s11837-025-07699-z

Apriansyah Dwi, Weizhi Zeng, Pengyun Xu

{"title":"Optimization and Comparative Analysis of Neutralization Agents for Iron, Aluminum, and Chromium Removal in HPAL Pregnant Leach Solution","authors":"Apriansyah Dwi, Weizhi Zeng, Pengyun Xu","doi":"10.1007/s11837-025-07699-z","DOIUrl":"10.1007/s11837-025-07699-z","url":null,"abstract":"<div><p>High-pressure acid leaching (HPAL) pregnant leach solution (PLS) derived from laterite ore contains valuable metals, such as nickel and cobalt, alongside impurities, including iron, aluminum, and chromium. Efficient impurity removal with minimal losses of valuable metals is essential for effective PLS purification. This study investigates the effect of CaCO<sub>3</sub> particle size (− 400 mesh) on precipitation performance, revealing an 11% improvement in aluminum removal efficiency compared to coarser particles. A two-stage precipitation process was found to be optimal. In the first stage (80°C, pH 3.0, 2 h), 96% Fe, 92% Al, and 97% Cr were removed, with minimal co-precipitation of Ni (1.04%) and Co (2.05%). The second stage (70°C, pH 4.5, 1.5 h) achieved 99.9% removal of Fe, Al, and Cr, though with slightly higher Ni loss (3.95%). Morphological analysis revealed that CaCO<sub>3</sub> produced crystalline residues, facilitating improved solid-liquid separation compared to the amorphous residues formed using NaOH and MgO. The thermogravimetric analysis confirmed superior moisture control in CaCO<sub>3</sub>-derived residues, showing only 2.88% mass loss at 115°C, significantly lower than residues from MgO and NaOH. These results provide practical guidance for impurity removal in HPAL operations and highlight the effectiveness of CaCO<sub>3</sub> as a neutralizing agent.</p></div>","PeriodicalId":605,"journal":{"name":"JOM","volume":"77 10","pages":"7461 - 7475"},"PeriodicalIF":2.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145079002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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TMS Member News TMS会员新闻

IF 2.3 4区材料科学

JOM Pub Date : 2025-09-04 DOI: 10.1007/s11837-025-07766-5

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Applying to Graduate School: Tips & Tricks 申请研究生院：技巧和技巧

IF 2.3 4区材料科学

JOM Pub Date : 2025-09-04 DOI: 10.1007/s11837-025-07769-2

Janelle P. Wharry, Youxing Chen, Ericmoore E. Jossou

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JOM Technical Topics JOM技术主题

IF 2.3 4区材料科学

JOM Pub Date : 2025-09-04 DOI: 10.1007/s11837-025-07765-6

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The 2024 TMS Annual Financial Report TMS 2024年度财务报告

IF 2.3 4区材料科学

JOM Pub Date : 2025-09-04 DOI: 10.1007/s11837-025-07770-9

Srini Chada, James J. Robinson

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Influence of Melting Amount of TZM on the Microstructure and Properties of TZM/CoCrFeNiMo0.2/Q235 Electron Beam Welded Joints TZM熔量对TZM/CoCrFeNiMo0.2/Q235电子束焊接接头组织和性能的影响

IF 2.3 4区材料科学

JOM Pub Date : 2025-09-03 DOI: 10.1007/s11837-025-07658-8

Debin Song, Ting Wang, Ruofan Wang, Siyuan Jiang

{"title":"Influence of Melting Amount of TZM on the Microstructure and Properties of TZM/CoCrFeNiMo0.2/Q235 Electron Beam Welded Joints","authors":"Debin Song, Ting Wang, Ruofan Wang, Siyuan Jiang","doi":"10.1007/s11837-025-07658-8","DOIUrl":"10.1007/s11837-025-07658-8","url":null,"abstract":"<div><p>The influence of TZM melting amount on microstructure and mechanical properties of TZM/CoCrFeNiMo<sub>0.2</sub>/Q235 electron beam welded joints was studied by using different interlayer thicknesses and beam offset distances. TZM molybdenum alloy and Q235 steel were joined using a CoCrFeNiMo<sub>0.2</sub> high-entropy alloy as an interlayer. The study demonstrated that optimal welding parameters, including an interlayer thickness of 0.4 mm and a beam offset distance of 0.2 mm, resulted in joints with superior tensile strength and defect-free weld morphology. Adjustments to interlayer thickness and beam positioning effectively controlled the melting extent of the TZM base material, thereby regulating the Mo content within the weld and suppressing the formation of brittle intermetallic compounds. Detailed microstructural analysis revealed that fine eutectic structures within the reaction layer played a crucial role in improving the performance of the joints, while excessive interlayer thickness or improper beam offset compromised mechanical integrity. These findings provided valuable insights into the development of high-performance composite structures and innovative welding strategies for dissimilar material joints.</p></div>","PeriodicalId":605,"journal":{"name":"JOM","volume":"77 11","pages":"8403 - 8415"},"PeriodicalIF":2.3,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145327589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Prediction of Corrosion in the Stainless Steel 316L in the Near-Surface Zone by Numerical Simulation 316L不锈钢近表面腐蚀的数值模拟预测

IF 2.3 4区材料科学

JOM Pub Date : 2025-09-03 DOI: 10.1007/s11837-025-07661-z

Sandra Friedrich, Thomas Mehner, Axel Dittes, Carolin Binotsch, Till Clausmeyer, Thomas Lampke, Birgit Awiszus

{"title":"Prediction of Corrosion in the Stainless Steel 316L in the Near-Surface Zone by Numerical Simulation","authors":"Sandra Friedrich, Thomas Mehner, Axel Dittes, Carolin Binotsch, Till Clausmeyer, Thomas Lampke, Birgit Awiszus","doi":"10.1007/s11837-025-07661-z","DOIUrl":"10.1007/s11837-025-07661-z","url":null,"abstract":"<div><p>Austenitic stainless steels such as 316L (1.4404) are widely used in chemical plant engineering applications because of their exceptional corrosion resistance. However, forming processes significantly affect the material's microstructure, which in turn influences its corrosion behavior. Depending on the chemical composition and forming history, 316L tends to martensite formation during forming, which strongly impacts the corrosion behavior in narrow zones close to the surface. In forming processes with tool contact, local martensite formation occurs at least on the surface up to a few micrometers into the bulk of the material. The residual stress state, phase fractions, crystallite sizes and microstrain are experimentally determined by x-ray diffraction and numerically predicted. This paper introduces a numerical approach to predict corrosion rates of 316L after cold rolling. The method extends conventional forming simulations with empirically calibrated models that factor in the component surface and the near-surface microstructure. This approach facilitates the optimization of workpiece designs and forming processes and is also adaptable to other materials and forming operations.</p></div>","PeriodicalId":605,"journal":{"name":"JOM","volume":"77 10","pages":"7529 - 7539"},"PeriodicalIF":2.3,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11837-025-07661-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145078866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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