Development and testing of algorithms for predicting the glass-forming ability in the multicomponent Sc-Gd-Co-Al metallic alloys

IF 4.3 2区 材料科学 Q2 CHEMISTRY, PHYSICAL Intermetallics Pub Date : 2024-10-12 DOI:10.1016/j.intermet.2024.108522
A.V. Maiorova, V.A. Bykov, P.V. Kotenkov
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Abstract

To reduce material costs, it is vital to develop reliable theoretical methods for predicting glass formation regions in multicomponent metal systems. We have developed a new model for predicting the compositions of quaternary amorphous metallic glasses and applied it to the Gd-Sc-Co-Al system. The proposed model parameters Θij1,2(xi),Θij1,2(xj) make it possible to predict the location of glass-forming compositions by finding the minimum of the PHSS parameter multiplication by the geometric coefficient Γ1,2, Γ1,2. The alloy with the composition Sc33Gd32Co19Al16 was successfully predicted and cast as a glass rod with a lateral size of 3 mm. According to the results of X-ray diffraction and thermal analysis, the sample Sc33Gd32Co19Al16 is an amorphous material with the lowest crystallinity index (4.3 %). The proposed approach can be used as a predictive model for determining glass-forming compositions in various quaternary metal systems.
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开发和测试用于预测多组分 Sc-Gd-Co-Al 金属合金玻璃化能力的算法
为了降低材料成本,开发可靠的理论方法来预测多组分金属体系中的玻璃形成区域至关重要。我们开发了一种预测四元无定形金属玻璃成分的新模型,并将其应用于 Gd-Sc-Co-Al 体系。所提出的模型参数Θi-j1,2(xi),Θi-j1,2(xj)可以通过寻找 PHSS 参数乘以几何系数Γ1,2, Γ1,2 的最小值来预测玻璃形成成分的位置。成功地预测出了成分为 Sc33Gd32Co19Al16 的合金,并将其铸造成横向尺寸为 3 毫米的玻璃棒。根据 X 射线衍射和热分析结果,样品 Sc33Gd32Co19Al16 是结晶度指数最低(4.3%)的无定形材料。所提出的方法可用作确定各种四价金属体系中玻璃形成成分的预测模型。
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来源期刊
Intermetallics
Intermetallics 工程技术-材料科学:综合
CiteScore
7.80
自引率
9.10%
发文量
291
审稿时长
37 days
期刊介绍: This journal is a platform for publishing innovative research and overviews for advancing our understanding of the structure, property, and functionality of complex metallic alloys, including intermetallics, metallic glasses, and high entropy alloys. The journal reports the science and engineering of metallic materials in the following aspects: Theories and experiments which address the relationship between property and structure in all length scales. Physical modeling and numerical simulations which provide a comprehensive understanding of experimental observations. Stimulated methodologies to characterize the structure and chemistry of materials that correlate the properties. Technological applications resulting from the understanding of property-structure relationship in materials. Novel and cutting-edge results warranting rapid communication. The journal also publishes special issues on selected topics and overviews by invitation only.
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