期刊
CRYSTALS
卷 11, 期 8, 页码 -出版社
MDPI
DOI: 10.3390/cryst11080891
关键词
Cr-Si-N compounds; structure prediction; global optimization; computational studies
资金
- Ministry of Education, Science and Technological Development of Serbia [1702001]
Several studies have shown that the addition of silicon into CrN can enhance its performance as a protective coating. This study investigated possible bulk phases of Cr2SiN4, revealing multiple energetically favorable structures and potential modifications. The research combined global explorations of the energy landscape, data mining, and the Primitive Cell approach for Atom Exchange method to identify promising candidates.
A number of studies have indicated that the implementation of Si in CrN can significantly improve its performance as a protective coating. As has been shown, the Cr-Si-N coating is comprised of two phases, where nanocrystalline CrN is embedded in a Si3N4 amorphous matrix. However, these earlier experimental studies reported only Cr-Si-N in thin films. Here, we present the first investigation of possible bulk Cr-Si-N phases of composition Cr2SiN4. To identify the possible modifications, we performed global explorations of the energy landscape combined with data mining and the Primitive Cell approach for Atom Exchange (PCAE) method. After ab initio structural refinement, several promising low energy structure candidates were confirmed on both the GGA-PBE and the LDA-PZ levels of calculation. Global optimization yielded six energetically favorable structures and five modifications possible to be observed in extreme conditions. Data mining based searches produced nine candidates selected as the most relevant ones, with one of them representing the global minimum in the Cr2SiN4. Additionally, employing the Primitive Cell approach for Atom Exchange (PCAE) method, we found three more promising candidates in this system, two of which are monoclinic structures, which is in good agreement with results from the closely related Si3N4 system, where some novel monoclinic phases have been predicted in the past.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据