Adhesion optimization of DLC thin films through conditioning of steel surfaces by plasma nitriding
Adhesion optimization of DLC thin films through conditioning of steel surfaces by plasma nitriding
批准号:
422219047
负责人:
Professor Dr. Günter Bräuer
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2019
资助国家:
德国
项目状态:
已结题
起止时间:
2018-12-31 至 2021-12-31
中文摘要
类金刚石碳膜(DLC)由于其优异的性能在许多摩擦学应用中是必不可少的。在许多情况下,不理想的附着力和机械负荷能力限制了它们的应用。迄今为止,DLC涂层很少使用的一种解决方案是预处理等离子体氮化。除了改善支撑效果外,还观察到涂层附着力的改善。以前很少使用这种方法的原因是结果的可重复性差以及对其粘附性的了解程度低。本项目旨在鉴定、描述和评估DLC膜在等离子体氮化钢表面的附着标准。初步工作表明,等离子体氮化钢表面可以使DLC涂层具有非常好的附着力,而无需进一步详细说明。但在渗氮过程中,通过选择合适的参数,可以有针对性地调整表面的改性。这些结果构成了以下工作假设的基础:•DLC涂层的附着力改善是由表面结构的变化引起的,这是等离子体氮化过程的结果。这些变化包括网格结构的变化、碳的溶解度和扩散速率的变化、反应条件的变化以及相变的变化。•这些变化与涂层附着力之间的相关性在很大程度上仍然未知,但可以通过实验确定。•将特别注意碳的溶解度,这是导致涂层过程中扩散过程增加的原因,因此对涂层的附着力有积极影响。从这些工作假设中,衍生出子目标并列出如下。深入了解渗氮参数与微观组织和材料性能之间的关系。考虑微观结构的等离子体渗氮和DLC涂层扩散过程建模。解释通过等离子体氮化产生的表面修饰与DLC涂层的附着力之间的联系。确定DLC涂层的合适改性,使其在等离子体氮化表面上具有良好的附着力。为达到上述目的,选择了合适的钢,在不同的工艺参数下进行了等离子渗氮处理,并对其边缘层成分进行了分析。然后在规定的条件下用PACVD工艺对氮化样品进行DLC涂层,并检测涂层的附着力。从检查的结果被纳入建模和模拟过程中发生的氮化在材料中。此外,还开发了一个模型概念,该模型概念结合了各种调查的结果。这允许识别和评估对氮化和涂层工艺有重大影响的影响参数
英文摘要
Diamond-like carbon films (DLC) are essential due to their excellent properties in many tribological applications. In many cases, unsatisfactory adhesion and mechanical load capacity limits their application. One solution, rarely used until now with DLC coatings is pretreatment plasma nitriding. In addition to an improved supportive effect, an improved coating adhesion was also observed. Reasons for the previously seldom use of this approach is the poor reproducibility of results and the low level of knowledge about its adhesion.The aim of this project is the identification, description and assessment of the adhesion criteria of DLC films on plasma-nitrided steel surfaces. Preliminary work has shown that plasma nitriding of steel surfaces allows for a very good adhesion of DLC coatings, without going into further detail. However, it was determined that the modifications of the surface by suitable selection of parameters can be specifically adjusted during the nitriding process. These results form the basis for the following working hypotheses:• The improved adhesion of DLC coatings is caused by changes to the surface structure, which is a result of the plasma nitriding process. These include changes of the grid structure, the solubility and diffusion rate of carbon, the reaction conditions and also phase transformations.• The correlations between these changes and the adhesion of the coatings are still largely unknown, but can be experimentally determined.• Special attention will be paid to the carbon solubility, which is responsible for an increase of diffusion processes during the coating process and therefore has a positive influence on the adhesion of the coating. From these working hypotheses, sub-objectives are derived and listed in the following.1. To reach a deeper understanding of the link between the nitriding parameters and the resulting microstructure and material properties.2. The modeling of diffusion processes during plasma nitriding and DLC coating, taking the micro-structure into account.3. Explanation of the connections between the resulting surface modifications through plasma nitriding and the adhesion of the DLC coatings.4. The identification of suitable modifications of DLC coatings, that allow a good adhesion on plasma-nitrided surfaces.To achieve these objectives, suitable steels are selected, under variation of process parameters, plasma nitrided and their edge layer composition is analyzed. Then the nitrided samples are DLC coated in a PACVD process under defined conditions and the coatings adhesion is examined after-wards. The findings from the examinations are incorporated in the modeling and simulation of the processes taking place during nitriding in the material. Also a model concept is developed that com-bines the results of the various investigations. This allows the identification and evaluation of the influencing parameters of the nitriding and coating processes that have a significant influen
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