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An informatics guided classification of miscible and immiscible binary alloy systems
Zhang, R. F.; Kong, X. F.; Wang, H. T.; Zhang, S. H.; Legut, D.; Sheng, S. H.; Srinivasan, S.; Rajan, K.; Germann, T. C.; Zhang, RF (reprint author), Beihang Univ, Sch Mat Sci & Engn, Beijing 100191, Peoples R China.; Zhang, RF (reprint author), Beihang Univ, Int Res Inst Multidisciplinary Sci, Beijing 100191, Peoples R China.
2017-08-29
Source PublicationNATURE PUBLISHING GROUP
ISSN2045-2322
Volume7Pages:-
AbstractThe classification of miscible and immiscible systems of binary alloys plays a critical role in the design of multicomponent alloys. By mining data from hundreds of experimental phase diagrams, and thousands of thermodynamic data sets from experiments and high-throughput first-principles (HTFP) calculations, we have obtained a comprehensive classification of alloying behavior for 813 binary alloy systems consisting of transition and lanthanide metals. Among several physics-based descriptors, the slightly modified Pettifor chemical scale provides a unique two-dimensional map that divides the miscible and immiscible systems into distinctly clustered regions. Based on an artificial neural network algorithm and elemental similarity, the miscibility of the unknown systems is further predicted and a complete miscibility map is thus obtained. Impressively, the classification by the miscibility map yields a robust validation on the capability of the well-known Miedema's theory (95% agreement) and shows good agreement with the HTFP method (90% agreement). Our results demonstrate that a state-of-the-art physics-guided data mining can provide an efficient pathway for knowledge discovery in the next generation of materials design.; The classification of miscible and immiscible systems of binary alloys plays a critical role in the design of multicomponent alloys. By mining data from hundreds of experimental phase diagrams, and thousands of thermodynamic data sets from experiments and high-throughput first-principles (HTFP) calculations, we have obtained a comprehensive classification of alloying behavior for 813 binary alloy systems consisting of transition and lanthanide metals. Among several physics-based descriptors, the slightly modified Pettifor chemical scale provides a unique two-dimensional map that divides the miscible and immiscible systems into distinctly clustered regions. Based on an artificial neural network algorithm and elemental similarity, the miscibility of the unknown systems is further predicted and a complete miscibility map is thus obtained. Impressively, the classification by the miscibility map yields a robust validation on the capability of the well-known Miedema's theory (95% agreement) and shows good agreement with the HTFP method (90% agreement). Our results demonstrate that a state-of-the-art physics-guided data mining can provide an efficient pathway for knowledge discovery in the next generation of materials design.
description.department[zhang, r. f. ; kong, x. f. ; zhang, s. h. ; sheng, s. h.] beihang univ, sch mat sci & engn, beijing 100191, peoples r china ; [zhang, r. f. ; kong, x. f. ; zhang, s. h. ; sheng, s. h.] beihang univ, int res inst multidisciplinary sci, beijing 100191, peoples r china ; [wang, h. t.] chinese acad sci, inst met res, cas key lab nucl mat & safety assessment, shenyang 110016, liaoning, peoples r china ; [legut, d.] vsb tech univ ostrava, ctr it4innovat, cz-70833 ostrava, czech republic ; [legut, d.] vsb tech univ ostrava, nanotechnol ctr, cz-70833 ostrava, czech republic ; [srinivasan, s.] iowa state univ, inst plant sci, 2031 roy j carver co lab, ames, ia 50011 usa ; [rajan, k.] suny buffalo, dept mat design & innovat, 311 bell hall, buffalo, ny 14260 usa ; [germann, t. c.] los alamos natl lab, theoret div, los alamos, nm 87545 usa
Subject AreaMultidisciplinary Sciences
Funding OrganizationNational Natural Science Foundation of China (NFSC) [51471018, 51672015]; National Key Research and Development Program of China [2016YFC1102500, 2017YFB0702100]; National Thousand Young Talents Program of China; Fundamental Research Funds for the Central Universities; Ministry of Education, Youth and Sports from the Large Infrastructures for Research, Experimental Development and Innovations project "IT4 Innovations National Supercomputing Center" [LM2015070]; Grant Agency of the Czech Republic [17-23964 S]
Indexed BySCI
Language英语
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/79135
Collection中国科学院金属研究所
Corresponding AuthorZhang, RF (reprint author), Beihang Univ, Sch Mat Sci & Engn, Beijing 100191, Peoples R China.; Zhang, RF (reprint author), Beihang Univ, Int Res Inst Multidisciplinary Sci, Beijing 100191, Peoples R China.
Recommended Citation
GB/T 7714
Zhang, R. F.,Kong, X. F.,Wang, H. T.,et al. An informatics guided classification of miscible and immiscible binary alloy systems[J]. NATURE PUBLISHING GROUP,2017,7:-.
APA Zhang, R. F..,Kong, X. F..,Wang, H. T..,Zhang, S. H..,Legut, D..,...&Zhang, RF .(2017).An informatics guided classification of miscible and immiscible binary alloy systems.NATURE PUBLISHING GROUP,7,-.
MLA Zhang, R. F.,et al."An informatics guided classification of miscible and immiscible binary alloy systems".NATURE PUBLISHING GROUP 7(2017):-.
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