Computational Materials Science最新文献_第7页

First-principle study of hydrogen solubility in bcc iron

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-02-05 DOI: 10.1016/j.commatsci.2024.113649

Y. Ngiam, Y. Chen, M.X. Huang

引用次数: 0

Confidence-Aware Mean Teacher for semi-supervised metallographic image semantic segmentation

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-02-05 DOI: 10.1016/j.commatsci.2024.113645

Yuying Cao , Bing Luo , Yonghua Chen , Li Xu , Changchun Ding

{"title":"Confidence-Aware Mean Teacher for semi-supervised metallographic image semantic segmentation","authors":"Yuying Cao , Bing Luo , Yonghua Chen , Li Xu , Changchun Ding","doi":"10.1016/j.commatsci.2024.113645","DOIUrl":"10.1016/j.commatsci.2024.113645","url":null,"abstract":"<div><div>Semantic segmentation of metallographic images using deep learning has become an emerging topic in materials science. However, existing methods generally rely on plenty of labeled images for supervised learning but pay insufficient attention to the problems of class imbalance and limited samples in datasets, which usually result in degraded model performance. Therefore, to accurately segment microstructures in metallographic images, we propose a new semi-supervised semantic segmentation model called Confidence-Aware Mean Teacher Network (CA-MT). By generating pseudo-labels, unlabeled images can also participate in training. According to the learning state of the model at different stages, the training process is divided into three phases: exploration, growth, and stabilization, and different strategies are applied to generate adaptive pseudo-labels, respectively. This can improve the quality of the training set and enable the model to learn more adequate semantic information for each class. Meanwhile, data augmentation is an effective way to improve the generalization ability of the model in a sample-limited situation. Based on this, we propose an adaptive threshold adjustment strategy (CCAT) depending on the class confidence to deal with the class imbalance problem and an adaptive CutMix augmentation method (CDAC) that utilizes the global confidence of unlabeled images as a guide to mitigate the disturbance caused by insufficient samples. Experiments show that CA-MT outperforms five state-of-the-art semi-supervised segmentation models under different partitioning protocols for two metallographic image datasets, MetalDAM and UHCS. The source code of the present work is available in <span><span>https://github.com/Cccoral/CA-MT</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"249 ","pages":"Article 113645"},"PeriodicalIF":3.1,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accelerated design of age-hardened Mg-Ca-Zn alloys with enhanced mechanical properties via machine learning

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-02-05 DOI: 10.1016/j.commatsci.2025.113665

Chenhui Zhang , Yuhui Zhang , Benpeng Ren , Yurong Wu , Yanling Hu , Yanfu Chai , Longshan Xu , Qinghang Wang

{"title":"Accelerated design of age-hardened Mg-Ca-Zn alloys with enhanced mechanical properties via machine learning","authors":"Chenhui Zhang , Yuhui Zhang , Benpeng Ren , Yurong Wu , Yanling Hu , Yanfu Chai , Longshan Xu , Qinghang Wang","doi":"10.1016/j.commatsci.2025.113665","DOIUrl":"10.1016/j.commatsci.2025.113665","url":null,"abstract":"<div><div>Precipitation-hardenable magnesium alloys have significant applications due to their lightweight and high specific strength properties. However, the wide compositions and aging treatment conditions pose challenges in efficiently identifying optimal combinations for rapid peak aging. In this study, 294 sets of data were collected for the age-hardening Mg-Ca-Zn alloys from the literature. By studying the suitability of various Machine Learning (ML) models, including linear models, support vector regression (SVR), random forest (RF), XGBoost, and AdaBoost, the alloys hardness was optimized using active learning based on the most suitable model. The results illustrate that the random forest model was the most effective model in predicting both the hardness and hardness variation of experimental data. The prediction of alloy hardness presents better performance compared to hardness variation. The alloy composition and aging process with the fast-aging response resulted in peak hardness of 71.10 Hv after aging at 175 °C for 8 h. This research demonstrates the potential of data-driven approaches in alloy design and optimization of age-hardening alloys.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"249 ","pages":"Article 113665"},"PeriodicalIF":3.1,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143151779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Revealing the tensile anisotropic mechanisms of additive manufactured IN718 alloy based on crystal plasticity modeling

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-02-04 DOI: 10.1016/j.commatsci.2025.113735

Ruiping Lai , Jianfeng Zhao , Liming Lei , Lei Shi , Shengchuan Wu , Xu Zhang

{"title":"Revealing the tensile anisotropic mechanisms of additive manufactured IN718 alloy based on crystal plasticity modeling","authors":"Ruiping Lai , Jianfeng Zhao , Liming Lei , Lei Shi , Shengchuan Wu , Xu Zhang","doi":"10.1016/j.commatsci.2025.113735","DOIUrl":"10.1016/j.commatsci.2025.113735","url":null,"abstract":"<div><div>The mechanical behavior of IN718 alloy produced by additive manufacturing (AM) displays significant anisotropy due to its unique microstructure, which differs markedly from conventionally manufactured materials. This study focuses on understanding the tensile anisotropy of AM IN718 alloy by employing a crystal plasticity approach. Grain boundary strengthening is modeled through the Hall-Petch relationship, and a modified dislocation mean free path model is incorporated to account for the grain size effect. These models are applied to simulate the influence of grain morphology (columnar and equiaxed grains) and crystallographic texture on the tensile response of AM IN718 alloy. The results reveal that columnar grains and texture affect both yield strength and strain-hardening behavior. Columnar grains, aligned along the build direction, induce significant variations in yield strength and strain-hardening due to differences in effective grain size in different loading directions. Texture can also affect the strain-hardening behavior by influencing the dislocation multiplication. The study offers a qualitative assessment of how grain morphology and crystallographic orientation govern the anisotropic behavior of AM IN718 alloy, providing insights that can guide the optimization of mechanical properties in AM-produced components.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"251 ","pages":"Article 113735"},"PeriodicalIF":3.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143290496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synergistic insights into the tungsten–tantalum-vacancy system: A DFT-cluster expansion study

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-02-04 DOI: 10.1016/j.commatsci.2025.113718

Dhanshree Pandey , Kalle Heinola , Christian Hill , Nicola Seriani

{"title":"Synergistic insights into the tungsten–tantalum-vacancy system: A DFT-cluster expansion study","authors":"Dhanshree Pandey , Kalle Heinola , Christian Hill , Nicola Seriani","doi":"10.1016/j.commatsci.2025.113718","DOIUrl":"10.1016/j.commatsci.2025.113718","url":null,"abstract":"<div><div>Vacancies play a fundamental role in determining the mechanical properties of alloys of tungsten and tantalum, which are of interest as plasma-facing materials in nuclear-fusion applications. To understand their behaviour, they have been investigated by means of density functional theory, cluster expansion calculations, as well as Monte Carlo simulations. It is found that vacancy formation energies increase with tungsten concentration, and it is easier to remove a tantalum atom than tungsten. Vacancies tend to cluster and form voids with faceted surfaces. A strong tendency towards tantalum segregation around vacancies and voids is observed at all temperatures considered, up to 3000 K. We show how this cloud of tantalum atoms surrounding the vacancies should slow down vacancy migration, thereby influencing their dynamics. This mechanism could in turn delay void formation, which is responsible for mechanical degradation of the alloy upon neutron irradiation. In conclusion, these findings suggest that vacancies induce partial segregation in alloys, which in turn slows down vacancy diffusion, thereby potentially affecting void formation and materials degradation.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"251 ","pages":"Article 113718"},"PeriodicalIF":3.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143290239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of strain and external electric field on the optoelectronic properties of HfS2/ZrSe2 heterostructures

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-02-03 DOI: 10.1016/j.commatsci.2025.113695

Shihang Sun, Lu Yang, Yanshen Zhao, Huaidong Liu, Xingbin Wei

{"title":"Effect of strain and external electric field on the optoelectronic properties of HfS2/ZrSe2 heterostructures","authors":"Shihang Sun, Lu Yang, Yanshen Zhao, Huaidong Liu, Xingbin Wei","doi":"10.1016/j.commatsci.2025.113695","DOIUrl":"10.1016/j.commatsci.2025.113695","url":null,"abstract":"<div><div>The strain’s electrical structure and optical characteristics as well as the electric field acting HfS<sub>2</sub>/ZrSe<sub>2</sub> heterojunction structure have been calculated by a first-principles approach based on density functional theory. A strain of −6%-6% is applied to the HfS<sub>2</sub>/ZrSe<sub>2</sub> heterojunction to analyze the changes in energy bands, density of states, dielectric function, and absorption coefficient. An electric field was also applied to the HfS<sub>2</sub>/ZrSe<sub>2</sub> heterojunction structure in the range of ± 0.08 V/Å with the increment set to 0.02 V/Å to analyze the electronic structure and optical properties. It is found that the heterojunction structure has an increasing gap when subjected to tension and a decreasing band gap under compressive strain. When the compressive strain exceeds −4%, the heterojunction structure is transformed from semiconductor to metal, and the electrical conductivity is greatly improved; the highest absorption coefficient and the most obvious changes are observed when compressed to −6%; the direct band gap is always maintained under the action of the electric field which is beneficial to the material’s use of light. A decrease in the band gap under the action of a positive electric field makes it easier for electrons to jump and promotes charge transfer.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"251 ","pages":"Article 113695"},"PeriodicalIF":3.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143290237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Fe-N system: crystal structure prediction, phase stability, and mechanical properties

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-02-03 DOI: 10.1016/j.commatsci.2025.113739

Ergen Bao , Jinbin Zhao , Qiang Gao , Ijaz Shahid , Hui Ma , Yixiu Luo , Peitao Liu , Yan Sun , Xing-Qiu Chen

{"title":"The Fe-N system: crystal structure prediction, phase stability, and mechanical properties","authors":"Ergen Bao , Jinbin Zhao , Qiang Gao , Ijaz Shahid , Hui Ma , Yixiu Luo , Peitao Liu , Yan Sun , Xing-Qiu Chen","doi":"10.1016/j.commatsci.2025.113739","DOIUrl":"10.1016/j.commatsci.2025.113739","url":null,"abstract":"<div><div>Nitriding introduces nitrides into the surface of steels, significantly enhancing the surface mechanical properties. By combining the variable composition evolutionary algorithm and first-principles calculations based on density functional theory, 50 thermodynamically stable or metastable Fe-N compounds with various stoichiometric ratios were identified, exhibiting also dynamic and mechanical stability. The mechanical properties of these structures were systematically studied, including the bulk modulus, shear modulus, Young’s modulus, Poisson’s ratio, Pugh’s ratio, Cauchy pressure, Klemen parameters, universal elastic anisotropy, Debye temperature, and Vickers hardness. All identified stable and metastable Fe-N compounds were found in the ductile region, with most exhibiting homogeneous elastic properties and isotropic metallic bonding overall. As the nitrogen concentration increases, their bulk moduli generally increase as well. The Vickers hardness values of Fe-N compounds range from 3.5 to 10.5 GPa, which are significantly higher than that of pure Fe (2.0 GPa), due to the stronger Fe-N bonds strength. This study provides insights into optimizing and designing Fe-N alloys with tailored mechanical properties.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"251 ","pages":"Article 113739"},"PeriodicalIF":3.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143290236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatic deblurring and rating classification for metal corrosion images

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-02-03 DOI: 10.1016/j.commatsci.2025.113725

Jiaxiang Wang , Pufen Zhang , Sijie Chang , Zhengyi Li , Peng Shi , Hongying Yu , Dongbai Sun

{"title":"Automatic deblurring and rating classification for metal corrosion images","authors":"Jiaxiang Wang , Pufen Zhang , Sijie Chang , Zhengyi Li , Peng Shi , Hongying Yu , Dongbai Sun","doi":"10.1016/j.commatsci.2025.113725","DOIUrl":"10.1016/j.commatsci.2025.113725","url":null,"abstract":"<div><div>Corrosion significantly impacts materials science and poses serious risks to engineering structures, highlighting the urgent need for automated and accurate methods for assessing corrosion ratings. However, images of metal corrosion surfaces captured in real-world environments often suffer from blurriness, complicating precise evaluation. To address this challenge, we propose a novel deep learning framework that integrates adaptive deblurring with corrosion ratings classification. First, we introduce a nonlinear activation free network (NAFNet) as an adaptive deblurring algorithm specifically designed for real-world blurry images. We retrain and fine-tune NAFNet on a corrosion dataset of blurry images, enabling the model to effectively understand and correct the inherent blurriness of corrosion features. Second, we develop a corrosion classification network (CCNet) based on residual networks, incorporating efficient channel attention (ECA) to enhance the capture of critical corrosion features. Additionally, we design a joint loss function that combines traditional cross-entropy loss with center loss, thereby improving both the accuracy and robustness of corrosion ratings classification. Experimental results demonstrate that our framework effectively eliminates blur and achieves high accuracy in corrosion ratings classification. The deblurring network achieves a peak signal-to-noise ratio (PSNR) of 32.11 dB and a structural similarity index (SSIM) of 0.9763 for metal corrosion images. Furthermore, our CCNet attains a mean average precision (mAP) of 91.57% in the classification of metal corrosion images, demonstrating its high accuracy and effectiveness.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"251 ","pages":"Article 113725"},"PeriodicalIF":3.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143290495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exceptional potential of laser-induced graphene for self-healing applications

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-02-03 DOI: 10.1016/j.commatsci.2025.113742

Farzane Hasheminia, Maryam Rasoulzadeh, Ali Ghavipanjeh, Sadegh Sadeghzadeh

{"title":"Exceptional potential of laser-induced graphene for self-healing applications","authors":"Farzane Hasheminia, Maryam Rasoulzadeh, Ali Ghavipanjeh, Sadegh Sadeghzadeh","doi":"10.1016/j.commatsci.2025.113742","DOIUrl":"10.1016/j.commatsci.2025.113742","url":null,"abstract":"<div><div>Laser-induced graphene (LIG), synthesised from polyimide, exhibits exceptional potential for self-healing applications owing to its unique thermal and mechanical properties. This study employed molecular dynamics simulations using the ReaxFF reactive force field to investigate LIG’s self-healing mechanisms of LIG under varying temperatures, pressure, and defect conditions. The results demonstrate that LIG can autonomously repair structural damage, restoring approximately 23 % of its original carbon-carbon bonds after tensile-induced fractures at 300 K and 0 atm pressure. For pristine graphene, high temperatures enable defect healing by overcoming energy barriers, allowing lattice reconstruction with carbon atom sources. In contrast, this study shows that such a mechanism is incorrect for LIG, highlighting a distinct self-healing behavior and marking a key conclusion of this research. Conversely, increased pressures (e.g., 0.1 atm) hinder the healing efficiency by restricting atomic movement, resulting in lower bond restoration rates. Simulations also reveal that the stress distribution in damaged LIG becomes more uniform post-healing at optimal conditions, enhancing material durability. These findings underline LIG’s capability to recover structural integrity autonomously, providing a foundation for its use in high-performance, durable materials for applications in electronics, nanodevices, and composite materials.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"251 ","pages":"Article 113742"},"PeriodicalIF":3.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143352664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DFT+U insights into the structural, surface and hydrogen fluoride adsorptions on Li2MnO3 for Li-ion batteries

IF 3.1 3区材料科学

Computational Materials Science Pub Date : 2025-02-03 DOI: 10.1016/j.commatsci.2025.113721

Brian Ramogayana , Khomotso P. Maenetja , Phuti E. Ngoepe

{"title":"DFT+U insights into the structural, surface and hydrogen fluoride adsorptions on Li2MnO3 for Li-ion batteries","authors":"Brian Ramogayana , Khomotso P. Maenetja , Phuti E. Ngoepe","doi":"10.1016/j.commatsci.2025.113721","DOIUrl":"10.1016/j.commatsci.2025.113721","url":null,"abstract":"<div><div>The formation of acidic hydrogen fluoride (HF) upon liquid electrolyte decomposition results in Li-Mn-O cathode material degradations and capacity fading during cycling. Even with the extensive research on electrolyte decomposition, degradation mechanisms, and capacity retention improvement strategies, further research is required to comprehend the surface interactions of HF with the layered Li-rich Mn-based Li<sub>2</sub>MnO<sub>3</sub> cathode material. Hence, this work discusses the surface properties and effect of HF adsorption on the major Li<sub>2</sub>MnO<sub>3</sub> surface using the density functional theory (DFT) method. During single HF adsorption, the molecule spontaneously dissociates to form Li-F and H-O species on the surface with an average adsorption energy (<em>E</em><sub>ads</sub>) of −1.90 eV. However, increasing the HF surface coverage (<span><math><mrow><mi>θ</mi></mrow></math></span>) generally resulted in a decrease in <em>E</em><sub>ads</sub>, whereas for the full monolayer, we observed a slight drop with reference to the <span><math><mrow><mi>θ</mi></mrow></math></span> = 0.33. It can be noted that the incorporation of HF enhances the stability of the (001) surface, which improves with an increase in surface coverage. The calculated work function increases with an increase in surface coverage, with a slight drop upon full coverage, suggesting a decrease in reactivity compared to the pristine (001) surface. Upon attaining a monolayer, the newly formed Li-F species on the surface greatly relaxed outwards with the highest average charge accumulation of −0.191 <em>e</em><sup>-</sup>. The electronic density of states shows no effect of HF surface adsorptions on the bandgap, however, the emergence of Li-F and H-O peaks on the valence band. Our results provide a closer look into the surface properties and HF interactions with the major Li<sub>2</sub>MnO<sub>3</sub> surface for aqueous lithium-ion battery.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"251 ","pages":"Article 113721"},"PeriodicalIF":3.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143290238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0