Charge-dependent CALPHAD analysis of defect chemistry and carrier concentration for space charge layers

IF 1.9 3区 材料科学 Q4 CHEMISTRY, PHYSICAL
Samuel Krimmel , Richard Otis , Jian Luo , Yu Zhong
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Abstract

The development of conductive materials plays a crucial role in improving the efficiency of electrochemical processes. In polycrystalline materials, space charge layers (SCLs) adjacent to grain boundaries (GBs) often dictate charge transport behavior. This study explores relaxing the charge neutrality constraint in the CALculation of PHAse Diagrams (CALPHAD) approach as a new method to model the electrical conductivity effects of SCLs. A new charge-dependent defect chemistry analysis is applied to the wustite, magnetite, and hematite phases in the Fe–O binary system. Using pycalphad, charge-dependent results for the molar Gibbs energies, Brouwer diagrams, and charge carrier concentrations were determined for each phase at 1273K within the oxygen partial pressure stability ranges. With a negative charge of 0.16 × 10−19 C, the hematite and magnetite phases exhibit an increased charge carrier concentration. The opposite trend was observed for wustite. While further work is needed to quantify the electrical conductivity effects of the SCLs and GBs with this approach, it provides a robust thermodynamic foundation to rapidly develop and optimize conductive materials.

空间电荷层缺陷化学和载流子浓度的电荷依赖性 CALPHAD 分析
导电材料的开发在提高电化学过程的效率方面起着至关重要的作用。在多晶材料中,与晶界(GB)相邻的空间电荷层(SCL)往往决定了电荷传输行为。本研究探讨了放宽电荷中性约束的CALculation of PHAse Diagrams(CALPHAD)方法,以此作为模拟SCL导电效应的新方法。一种新的电荷依赖性缺陷化学分析被应用于 Fe-O 二元系统中的硅灰石、磁铁矿和赤铁矿相。利用 pycalphad,在 1273K 氧分压稳定范围内确定了每种相的摩尔吉布斯能、布鲁维图和电荷载流子浓度的电荷依赖性结果。当负电荷为 0.16 × 10-19 C 时,赤铁矿和磁铁矿相的电荷载流子浓度增加。而武钢则呈现出相反的趋势。虽然利用这种方法量化 SCL 和 GB 的导电效果还需要进一步的工作,但它为快速开发和优化导电材料提供了坚实的热力学基础。
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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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