CEITEC, Masaryk University, Kamenice 5, 625 00, Brno, Czech Republic.
CEITEC, Brno University of Technology, Purkyňova 123, 612 00, Brno, Czech Republic.
Sci Rep. 2020 Sep 17;10(1):15294. doi: 10.1038/s41598-020-72171-8.
Surface roughness plays an important role in various fields of nanoscience and nanotechnology. However, the present practices in roughness measurements, typically based on some Atomic Force Microscopy measurements for nanometric roughness or optical or mechanical profilometry for larger scale roughness significantly bias the results. Such biased values are present in nearly all the papers dealing with surface parameters, in the areas of nanotechnology, thin films or material science. Surface roughness, most typically root mean square value of irregularities Sq is often used parameter that is used to control the technologies or to link the surface properties with other material functionality. The error in estimated values depends on the ratio between scan size and roughness correlation length and on the way how the data are processed and can easily be larger than 10% without us noting anything suspicious. Here we present a survey of how large is the problem, detailed analysis of its nature and suggest methods to predict the error in roughness measurements and possibly to correct them. We also present a guidance for choosing suitable scan area during the measurement.
表面粗糙度在纳米科学和纳米技术的各个领域都起着重要的作用。然而，目前的粗糙度测量方法，通常基于原子力显微镜测量进行纳米级粗糙度测量，或者基于光学或机械轮廓测量进行较大尺度粗糙度测量，这些方法都会显著影响测量结果。在几乎所有涉及表面参数的纳米技术、薄膜或材料科学领域的论文中，都存在这些有偏差的值。表面粗糙度，最典型的是均方根值 Sq，通常是用于控制技术或将表面性能与其他材料功能联系起来的参数。估计值的误差取决于扫描尺寸与粗糙度相关长度的比值，以及数据处理的方式，在没有注意到任何可疑之处的情况下，误差很容易超过 10%。在这里，我们展示了这个问题有多大，详细分析了其性质，并提出了预测粗糙度测量误差并可能对其进行修正的方法。我们还为测量过程中选择合适的扫描区域提供了指导。
