We present an advanced approach for the thermodynamic modeling of metal hydrides within the Calculation of Phase Diagrams (CALPHAD) framework. As the traditional CALPHAD method requires significant and time-consuming manual input, often introducing biases into the assessment process, we present a novel solution to automate this. The core of our approach is the development of an open-source, Python-based computational tool designed to calculate para-equilibrium states in hydrogen-multicomponent phases. This tool facilitates a semi-automatic pathway to enhance the CALPHAD evaluation procedure, significantly reducing manual input. We validated our approach by rapidly assessing the (Ce,La)Ni₅–H system, a representative material system with significant implications for metal hydride-based hydrogen applications. Our method confirms existing data and reveals new insights into this system’s sorption properties and phase behavior. Using our Python-based tool to optimize parameter sets and calculate Pressure-Composition-Isotherms (PCI), we demonstrate the feasibility of predicting temperature-dependent plateau pressures and hydrogen capacities of multicomponent metal hydrides. This work holds significant potential for future applications in designing hydrogen storage materials, predicting their properties, and extending the methodology to other metal hydride systems.

中文翻译：

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推进氢准平衡中多组分相的热力学建模


我们提出了一种在相图计算 （CALPHAD） 框架内对金属氢化物进行热力学建模的高级方法。由于传统的 CALPHAD 方法需要大量且耗时的手动输入，通常会在评估过程中引入偏差，因此我们提出了一种新的解决方案来自动化这一点。我们方法的核心是开发一种基于 Python 的开源计算工具，旨在计算氢多组分相中的准平衡状态。该工具有助于实现半自动途径来增强 CALPHAD 评估程序，从而显著减少手动输入。我们通过快速评估 （Ce，La）Ni_5-H 系统来验证我们的方法，这是一种对金属氢化物基氢应用具有重要意义的代表性材料系统。我们的方法证实了现有数据，并揭示了对该系统的吸附特性和相行为的新见解。使用基于 Python 的工具来优化参数集并计算压力-成分-等温线 （PCI），我们证明了预测多组分金属氢化物与温度相关的平台压力和氢容量的可行性。这项工作在设计储氢材料、预测其特性以及将该方法扩展到其他金属氢化物系统方面具有巨大的应用潜力。