Thermodynamic database for multi-principal element alloys within the system Al–Co–Cr–Fe–Mn–Ni–C

IF 1.9 3区 材料科学 Q4 CHEMISTRY, PHYSICAL
Bengt Hallstedt , Mehdi Noori , Fabian Kies , Felix Oppermann , Christian Haase
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引用次数: 0

Abstract

The development of multi-principal element alloys requires the navigation within a multi-dimensional composition space, which has proven to be challenging. Various methods to predict the state of an alloy, in particular if it is single-phase or not, have been tested with various success. The only approach that can consistently predict the constitution of an alloy, e.g. single-phase, multi-phase, intermetallics, is thermodynamic calculations using Calphad databases. Conventional Calphad databases, such as steel or Ni-base, are of limited use since they are developed for alloys with a specific base element. More suitable databases, such as TCHEA, have been developed, but their development is challenging since they require the inclusion of more subsystems than conventional databases. The predictive capability depends strongly on which elements are considered, and their development is still ongoing. A Calphad database including the elements Al, Co, Cr, Fe, Mn, Ni and C was built up from scratch using mostly assessments of binary and ternary systems from the literature, but with many amendments. This database covers a substantial fraction of the alloys investigated until now plus the element C that is usually not included, but can provide additional strengthening, either in solution or in the form of carbides.

Al-Co-Cr-Fe-Mn-Ni-C系多主元素合金热力学数据库
多主元素合金的开发需要在多维成分空间内导航,这已被证明是具有挑战性的。预测合金状态的各种方法,特别是预测合金是否为单相状态的方法,已经进行了各种成功的测试。唯一能够持续预测合金组成的方法,例如单相、多相、金属间化合物,是使用calphhad数据库进行热力学计算。传统的calphhad数据库,如钢或镍基数据库,用途有限,因为它们是为具有特定基元素的合金开发的。已经开发了更合适的数据库,例如TCHEA,但是它们的开发具有挑战性,因为它们需要包含比传统数据库更多的子系统。预测能力在很大程度上取决于考虑哪些因素,它们的发展仍在进行中。包括Al, Co, Cr, Fe, Mn, Ni和C元素在内的calphhad数据库是从头开始建立的,主要使用文献中的二元和三元体系的评估,但进行了许多修改。该数据库涵盖了迄今为止所研究的大部分合金,加上通常不包括的元素C,但可以提供额外的强化,无论是在溶液中还是以碳化物的形式。
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来源期刊
CiteScore
4.00
自引率
16.70%
发文量
94
审稿时长
2.5 months
期刊介绍: The design of industrial processes requires reliable thermodynamic data. CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) aims to promote computational thermodynamics through development of models to represent thermodynamic properties for various phases which permit prediction of properties of multicomponent systems from those of binary and ternary subsystems, critical assessment of data and their incorporation into self-consistent databases, development of software to optimize and derive thermodynamic parameters and the development and use of databanks for calculations to improve understanding of various industrial and technological processes. This work is disseminated through the CALPHAD journal and its annual conference.
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