AI 中文总结
该研究依托法国DIADEM计划，采用AI驱动的混合HiPIMS/Pulsed-DC PVD工艺，构建元素无关模型，设计适用于极端环境低碳能源应用的高熵防护涂层，验证了工艺可行性与准确性。
AI 中文摘要
复杂高熵合金因在苛刻环境下具备优异的力学性能和耐腐蚀性，当前正受到广泛关注，尤其适用于无碳能源相关应用。然而，受其复杂性和“鸡尾酒效应”影响，采用试错法制备块状及薄膜形式的此类合金并不现实。人工智能的近期发展为其制备及性能调控提供了新可能。首先，本文概述了材料与数据科学领域的研究；随后介绍法国材料与数据科学融合计划DIADEM如何依托全国合成与表征平台网络（即DIADEM发现中心），开发适用于无碳能源应用（如核能、高温电解等）的创新涂层。本文重点介绍DIADEM-2D，这是一种采用共焦组合配置的4个阴极、基于人工智能驱动的混合高功率脉冲磁控溅射（HiPIMS）/脉冲直流物理气相沉积（Pulsed-DC PVD）工艺。我们利用文献中关于耐熔融盐腐蚀及核事故工况的数据确定高熵合金成分，构建了一个与元素无关的模型，该模型整合了沉积参数与涂层性能，可用于设计具有特定成分的防护涂层，并验证了该工艺的可行性与准确性。
英文摘要
Complex and high entropy alloys are attracting much attention currently thanks to their mechanical and corrosion resistance properties in harsh environments, in particular needed for carbon-free energy applications. However, their elaboration in bulk and in thin film form in a trial-and-error approach is impractical due to their complexity and the cocktail effect. The recent development of artificial intelligence brings a new possibility for their elaboration and adjustment of their properties. Firstly, we present an overview of Materials and data science research. Then we describe how DIADEM - French initiative for Materials and Data science convergence - tackles the development of innovative coatings for carbon-free energy applications (nuclear, high temperature electrolysis, ...) thanks to the development of a nationwide network of synthesis and characterization platforms - the DIADEM discovery hub. We describe in particular DIADEM-2D, an AI-driven Hybrid HiPIMS/Pulsed-DC PVD process using 4 cathodes in confocal combinatorial configuration. We present the high entropy alloy determination using data from the literature for corrosion resistance in molten salt media and nuclear accidental conditions. An element-independent model gathering deposition parameters and coating properties has been implemented allowing the design of protective coatings with a particular composition. We demonstrate the feasibility of this process and its accuracy.
