Science and Technology of Advanced Materials: Methods最新文献_第6页

Autonomous synthesis system integrating theoretical, informatics, and experimental approaches for large-magnetic-anisotropy materials 自主合成系统集成理论，信息学和实验方法的大磁各向异性材料

Science and Technology of Advanced Materials: Methods Pub Date : 2022-06-30 DOI: 10.1080/27660400.2022.2094698

Daigo Furuya, Takuya Miyashita, Yoshio Miura, Yuma Iwasaki, M. Kotsugi

{"title":"Autonomous synthesis system integrating theoretical, informatics, and experimental approaches for large-magnetic-anisotropy materials","authors":"Daigo Furuya, Takuya Miyashita, Yoshio Miura, Yuma Iwasaki, M. Kotsugi","doi":"10.1080/27660400.2022.2094698","DOIUrl":"https://doi.org/10.1080/27660400.2022.2094698","url":null,"abstract":"ABSTRACT We developed an autonomous and efficient system for synthesising ferromagnetic materials with large magnetocrystalline anisotropy by integrating theoretical, informatics, and experimental approaches. By combining the first-principles calculation of the magnetic anisotropy with Bayesian optimisation, we virtually screened candidate materials, comprising four elements and four-layer periods, from various magnetic multilayers. We employed the expected improvement as the acquisition function and Matern52 as the kernel function, to develop a robust machine learning model. We fabricated the top three predicted magnetic materials under laboratory conditions by monoatomic layer deposition and evaluated their magnetic anisotropy using a superconducting quantum interference device (SQUID). Ultimately, we demonstrated that [Fe/Co/Fe/Ni]13 is a novel ferromagnetic material whose magnetic anisotropy exceeds that of L10-FeNi- and L10-FeCo-type alloys. Furthermore, the origin of the perpendicular magnetic anisotropy was derived from the spin-conserving as well as the spin-flip terms. We determined that Bayesian optimisation offers promising configurability features in terms of the electronic structure that extend beyond the empirical knowledge and human intuition. Graphical abstract","PeriodicalId":221393,"journal":{"name":"Science and Technology of Advanced Materials: Methods","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129599774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Systematic derivation of maximally orthogonalized supercells 最大正交化超级细胞的系统衍生

Science and Technology of Advanced Materials: Methods Pub Date : 2022-06-28 DOI: 10.1080/27660400.2022.2093094

Y. Hinuma

引用次数: 2

Topological representations of crystal structures: generation, analysis and implementation in the TopCryst system 晶体结构的拓扑表示:topcrystal系统的生成、分析和实现

Science and Technology of Advanced Materials: Methods Pub Date : 2022-06-23 DOI: 10.1080/27660400.2022.2088041

A. P. Shevchenko, Aleksandr A. Shabalin, Igor Yu. Karpukhin, V. Blatov

{"title":"Topological representations of crystal structures: generation, analysis and implementation in the TopCryst system","authors":"A. P. Shevchenko, Aleksandr A. Shabalin, Igor Yu. Karpukhin, V. Blatov","doi":"10.1080/27660400.2022.2088041","DOIUrl":"https://doi.org/10.1080/27660400.2022.2088041","url":null,"abstract":"ABSTRACT Main modern approaches to the topological representation of crystal structures of different chemical classes are overviewed. The problem of automated generation and analysis of such representations is discussed, and a new free web service is presented, which enables the user to describe topological features of crystal structures of any complexity and chemical composition in a fully automated mode. The service requires only an input file with crystallographic information in the standard CIF format and generates all reasonable representations of the structure by selecting structural units with rigorous algorithms. Then the representations are assigned to known topological types and relations to other crystal structures, which have to same architectures, are established. The service is interfaced to a set of topological databases, which in turn have gateways to world-wide crystallographic databases. A number of examples of topological analysis of different classes of chemical structures are presented, and an outlook is given for further development and applications of the service for big data analysis and data mining in crystal chemistry and materials science. GRAPHICAL ABSTRACT","PeriodicalId":221393,"journal":{"name":"Science and Technology of Advanced Materials: Methods","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126549626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 30

NIMS fatigue data sheet on gigacycle fatigue properties of A6061-T6 (Al-1.0Mg-0.6Si) aluminium alloy at high stress ratios 高应力比下A6061-T6 (Al-1.0Mg-0.6Si)铝合金千兆周疲劳性能的NIMS疲劳数据表

Science and Technology of Advanced Materials: Methods Pub Date : 2022-06-07 DOI: 10.1080/27660400.2022.2085020

H. Hirukawa, Y. Furuya, Hideaki Nishikawa, N. Nagashima, Etsuo Takeuchi

{"title":"NIMS fatigue data sheet on gigacycle fatigue properties of A6061-T6 (Al-1.0Mg-0.6Si) aluminium alloy at high stress ratios","authors":"H. Hirukawa, Y. Furuya, Hideaki Nishikawa, N. Nagashima, Etsuo Takeuchi","doi":"10.1080/27660400.2022.2085020","DOIUrl":"https://doi.org/10.1080/27660400.2022.2085020","url":null,"abstract":"ABSTRACT The new fatigue data sheet, No. 132, discloses gigacycle fatigue properties of the A6061-T6 aluminium alloys at high stress ratios. The fatigue tests were conducted mainly by the ultrasonic fatigue testing at 20 kHz, while conventional fatigue tests at 100 Hz were also conducted for comparison. The fatigue test results indicated that fatigue limits were obscure in the A6061-T6 alloys. Many specimens failed at over 107 cycles, developing internal fractures as well as surface fractures. On the other hand, fatigue failures at over 109 cycles were very rare, suggesting the presence of new fatigue limits in the gigacycle region. The differences in fatigue test results were negligible between the 20 kHz and 100 Hz tests, demonstrating that the 20 kHz tests were comparable to the conventional fatigue tests on this material. The fatigue strengths evaluated by the stress amplitude were decreased according to increase in the stress ratios, while the degradation of the fatigue strengths was not so serious. The fatigue strengths were higher than the modified Goodman lines, meaning that the stress ratio effects could be estimated by conventional ways. GRAPHICAL ABSTRACT","PeriodicalId":221393,"journal":{"name":"Science and Technology of Advanced Materials: Methods","volume":"300 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116102494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

NIMS fatigue data sheet on gigacycle fatigue properties of SCr420 (0.20C-1.05Cr) carburizing steel for machine structural use 机械结构用sc420 (0.20C-1.05Cr)渗碳钢千兆周疲劳性能的NIMS疲劳数据表

Science and Technology of Advanced Materials: Methods Pub Date : 2022-06-06 DOI: 10.1080/27660400.2022.2085019

H. Hirukawa, Y. Furuya, Hideaki Nishikawa, N. Nagashima, Etsuo Takeuchi

{"title":"NIMS fatigue data sheet on gigacycle fatigue properties of SCr420 (0.20C-1.05Cr) carburizing steel for machine structural use","authors":"H. Hirukawa, Y. Furuya, Hideaki Nishikawa, N. Nagashima, Etsuo Takeuchi","doi":"10.1080/27660400.2022.2085019","DOIUrl":"https://doi.org/10.1080/27660400.2022.2085019","url":null,"abstract":"ABSTRACT The new fatigue data sheet, No. 131, discloses gigacycle fatigue properties of the carburizing steel tested under rotating-bending conditions. This fatigue data sheet employed vacuum carburizing, as well as gas carburizing. Both as carburized and polished specimens were tested. In case of the polished specimens, two conditions of hardened layer depths were applied, i.e. deep and shallow cases. The fatigue test results demonstrated that gigacycle fatigue took place in the carburizing steel. Many specimens failed at over 107 cycles, ending in internal fractures. The origins of the internal fractures were oxide-type inclusions located in or beneath the hardened layer. The as carburized specimens of the vacuum carburizing revealed higher fatigue strength than those of the gas carburizing. One of the reasons of this improvement was fine microstructures created by the vacuum carburizing at around the surfaces. The polished specimens showed further high fatigue strength, developing more internal fractures. The deep case then revealed higher fatigue strength than the shallow case. In case of surface fractures, typical fatigue fracture surfaces were not observed, i.e. only intergranular fracture surfaces were observed in the hardened layers. Fish-eye patterns were observed in case of the internal fractures, while outsides of the fish-eye patterns were the intergranular fracture surfaces. Our interpretation was that the hardened layers were too brittle to allow conventional fatigue crack growth. In other word, the hardened layers were brittle-fractured immediately after the crack initiation, or only internal fatigue crack growth were allowed. Graphical abstract","PeriodicalId":221393,"journal":{"name":"Science and Technology of Advanced Materials: Methods","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115888769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Exploration of outliers in strength–ductility relationship of dual-phase steels 双相钢强度-延性关系异常值的探讨

Science and Technology of Advanced Materials: Methods Pub Date : 2022-05-30 DOI: 10.1080/27660400.2022.2080483

T. Shiraiwa, Shoya Kato, F. Briffod, M. Enoki

{"title":"Exploration of outliers in strength–ductility relationship of dual-phase steels","authors":"T. Shiraiwa, Shoya Kato, F. Briffod, M. Enoki","doi":"10.1080/27660400.2022.2080483","DOIUrl":"https://doi.org/10.1080/27660400.2022.2080483","url":null,"abstract":"ABSTRACT To overcome the trade-off relationship between tensile strength and elongation of dual-phase steels, three exploratory techniques were utilized: Bayesian optimization (BO), BoundLess Objective-free eXploration (BLOX), and one-class support vector machine (OCSVM). The BO is an optimization method using Gaussian process regression, and the BLOX and OCSVM are designed for finding out-of-trend materials. Initially, a large number of synthetic phase distributions of ferrite and martensite were prepared by the Gaussian random field method. Feature importance analysis was then performed to extract microstructural descriptors used as explanatory variables in the explorations. The results revealed that the volume fraction of martensite, the higher-order principal component of the spatial correlation function, and the first principal component of the persistent homology are important in predicting the product of strength and elongation (TS × EL). In the three exploration methods, crystal plasticity finite element analyses with a ductile damage model were repeatedly performed to predict strength and elongation. The BO and OCSVM successfully found microstructures with TS × EL much higher than those of random search in a limited number of iterations. The microstructures discovered in the explorations indicated that two approaches to material design are effective in improving tensile properties of dual-phase steels: uniformly dispersing the fine hard phase and constructing a lamellar structure of the hard and soft phases. GRAPHICAL ABSTRACT","PeriodicalId":221393,"journal":{"name":"Science and Technology of Advanced Materials: Methods","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115199130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Machine learning of fake micrographs for automated analysis of crystal growth process 假显微照片的机器学习，用于晶体生长过程的自动分析

Science and Technology of Advanced Materials: Methods Pub Date : 2022-05-27 DOI: 10.1080/27660400.2022.2082235

T. Ishiyama, T. Imajo, T. Suemasu, K. Toko

{"title":"Machine learning of fake micrographs for automated analysis of crystal growth process","authors":"T. Ishiyama, T. Imajo, T. Suemasu, K. Toko","doi":"10.1080/27660400.2022.2082235","DOIUrl":"https://doi.org/10.1080/27660400.2022.2082235","url":null,"abstract":"ABSTRACT Material informatics is being applied to crystal engineering, which is a core technology in electronics. Micrographs particularly provide important insights; however, they have not benefited significantly from material informatics because of the efforts required to acquire huge numbers of data. Herein, we propose a fast and automated analysis technique for micrographs showing the crystallization process of semiconductor thin films. We automatically generated fake micrographs and trained the crystal domain recognition capability on 10 different machine learning models. Experimentally obtained micrographs were analyzed using the developed model, which correctly determined the domain size and nuclei density. The activation energies required for growth and nucleation were determined from the lateral growth velocity and nucleation frequency, the variations of which were smaller than those measured by humans. Therefore, the proposed analysis framework not only reduces the time required to derive the crystal growth properties, but also enables a high accuracy without human subjectivity. GRAPHICAL ABSTRACT","PeriodicalId":221393,"journal":{"name":"Science and Technology of Advanced Materials: Methods","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125276101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Creep properties and analysis of creep rupture data of 2.25Cr-1Mo-0.3V steels 2.25Cr-1Mo-0.3V钢蠕变性能及蠕变断裂数据分析

Science and Technology of Advanced Materials: Methods Pub Date : 2022-05-25 DOI: 10.1080/27660400.2022.2080484

K. Sawada, Y. Taniuchi, K. Sekido, Takehiro Nojima, K. Kimura

{"title":"Creep properties and analysis of creep rupture data of 2.25Cr-1Mo-0.3V steels","authors":"K. Sawada, Y. Taniuchi, K. Sekido, Takehiro Nojima, K. Kimura","doi":"10.1080/27660400.2022.2080484","DOIUrl":"https://doi.org/10.1080/27660400.2022.2080484","url":null,"abstract":"ABSTRACT Tensile properties and creep rupture data were obtained for four heats of 2.25Cr-1Mo-0.3 V steels used for high-temperature and high-pressure hydrotreatment reactor vessels. Tensile tests at room temperature to 650°C were performed in accordance with JIS G 0567. Creep tests at 450 to 600°C were conducted in accordance with JIS Z 2271. Large heat-to-heat variations of tensile and creep rupture data were found with the different heat treatment conditions. However, no large difference in creep rupture ductility was observed among the heats. Regression analysis was applied to the tensile test data of each heat because of the large heat-to-heat variations. The creep rupture data of heats VdA and VdB were separately fitted to the regression equation of logarithmic stress using the time-temperature parameters of Larson–Miller, Orr–Sherby–Dorn and Manson–Haferd to estimate the 100,000 h creep rupture strength. The appropriate time-temperature parameter and degree of regression equation were selected based on the fitting accuracy and simplicity of regression equation. The value of 67% of the 100,000 h creep rupture strength was compared with the current allowable stress specified in codes and standards. Graphical abstract","PeriodicalId":221393,"journal":{"name":"Science and Technology of Advanced Materials: Methods","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132577572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Skill-Agnostic analysis of reflection high-energy electron diffraction patterns for Si(111) surface superstructures using machine learning 利用机器学习技术对Si(111)表面上层结构的反射高能电子衍射图进行技能不可知分析

Science and Technology of Advanced Materials: Methods Pub Date : 2022-05-24 DOI: 10.1080/27660400.2022.2079942

Asako Yoshinari, Yuma Iwasaki, M. Kotsugi, S. Sato, N. Nagamura

{"title":"Skill-Agnostic analysis of reflection high-energy electron diffraction patterns for Si(111) surface superstructures using machine learning","authors":"Asako Yoshinari, Yuma Iwasaki, M. Kotsugi, S. Sato, N. Nagamura","doi":"10.1080/27660400.2022.2079942","DOIUrl":"https://doi.org/10.1080/27660400.2022.2079942","url":null,"abstract":"ABSTRACT Reflection high-energy electron diffraction (RHEED) data are important for the in-situ characterization of surface conditions during physical vapor deposition. Surface superstructures obtained by adsorbing exotic atoms onto a clean silicon surface, which exhibit various physical properties, were identified using RHEED. However, this information is too abundant for quantitative analysis; therefore, scientists rely on their expertise to interpret RHEED patterns to assess surface structures and evaluate film thickness, and a large amount of information remains unused. In this study, we adapted machine learning for a RHEED pattern dataset of a clean Si(111) surface during indium deposition in molecular-beam epitaxy growth to use the entire RHEED pattern image information and investigated appropriate machine leaning analysis methods. First, we aimed to determine RHEED pattern similarities in the dataset. Then, five structural phases, 7 × 7 (clean surface), √3×√3, √31×√31, 4 × 1, and 4 × 1 (Room Temperature), were automatically detected by hierarchical clustering using Ward’s method. Next, we aimed to extract the information for each surface superstructure from the dataset. Using non-negative matrix factorization, we successfully estimated the optimal forming conditions for each surface superstructure separately more accurately than the conventional methods. Our proposed strategies could be widely applied to surface structural analysis. GRAPHICAL ABSTRACT","PeriodicalId":221393,"journal":{"name":"Science and Technology of Advanced Materials: Methods","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123198445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Inverse estimation of parameters for the magnetic domain via dynamics matching using visual-perceptive similarity 利用视觉感知相似度进行动态匹配的磁域参数逆估计

Science and Technology of Advanced Materials: Methods Pub Date : 2022-05-17 DOI: 10.1080/27660400.2022.2075685

Ryo Murakami, M. Mizumaki, I. Akai, Hayaru Shouno

引用次数: 0