吸附
陶瓷
Atom(片上系统)
合金
氧气
材料科学
扩散
难熔金属
化学物理
耐火材料(行星科学)
氧原子
化学工程
物理化学
化学
冶金
分子
热力学
计算机科学
物理
有机化学
工程类
嵌入式系统
作者
Daming Yan,Yang Yang,Xiangdong Ding,Turab Lookman,Hongxiang Zong,Jun Sun
标识
DOI:10.1016/j.commatsci.2023.112037
摘要
The initial oxidation process of refractory alloy ceramics is closely related to their intrinsic properties such as surface adsorption or diffusion of oxygen atoms. We devise a machine learning model that predicts the full spectrum of adsorption energies for an oxygen atom on HfC1−xNx ceramic surfaces with quantum accuracy. With this approach, we show that the chemical complexity of carbonitride makes HfC1−xNx ceramics exhibit multiple types of adsorption sites with competing oxygen adsorption energies, leading to fewer preferable adsorption sites. In particular, we find that heavily doped N can change the stable adsorption site from the 3-fold hollow between metals and C atoms (MMC) to the top of Hf atoms (top-Hf), and the total number of preferable adsorption sites is regulated by their competing energies. In this scenario, we predict HfC0.76N0.24 has superior anti-oxidation performance, consistent with existing experimental measurements. Our findings can stimulate new strategies to enhance the oxidation resistance of refractory alloy ceramics.
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