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Determination of nano-roughness of carbon fibers by atomic force microscopy

机译:原子力显微镜测定碳纤维的纳米粗糙度

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摘要

We present a novel approach to determine the surface roughness on varying scales using atomic force microscopy data. The key factor is to find a suitable background correction for the desired scale. Using the example of the surface of sized and unsized high-tenacity carbon fibers, we present an easy method to find backgrounds for widely varying scales and to evaluate respective topography and surface roughness with the same lateral resolution as the microscope itself. The analysis is done by subtracting a tunable background from the respective height data. By choosing an appropriate background to investigate the surface topography of a carbon fiber on a nm-scale, only small nano-structures with a width of around 20 nm remain after the background subtraction. Evaluating the mean roughness R _a of these nano-structures, sized carbon fibers show an overall value of around 0.1 nm while unsized carbon fibers a value of around 0.4 nm. Total background corrected height analysis shows an even distribution of these nano-structures along the fibrils of the unsized fibers, whereas for the sized fibers the nano-structures are not present. The presented method allows analysis and visualization of the distribution of nano-structures on a carbon fiber surface for the first time. This feature is used to visualize the distribution of the sizing and can further be used to investigate the influence of different production parameters on the fiber topography or to evaluate the contribution of mechanical interlocking to the interfacial strength.
机译:我们提出了一种新颖的方法来确定使用原子力显微镜数据在不同尺度上的表面粗糙度。关键因素是为所需比例找到合适的背景校正。以大小和大小未变的高强度碳纤维的表面为例,我们提出了一种简便的方法来查找各种尺度变化的背景,并以与显微镜本身相同的横向分辨率评估相应的地形和表面粗糙度。通过从相应的高度数据中减去可调背景来完成分析。通过选择合适的背景来研究碳纤维的纳米级表面形貌,在扣除背景后仅剩下宽度约20 nm的小纳米结构。评价这些纳米结构的平均粗糙度R_a,上浆的碳纤维的总值约为0.1nm,而未上浆的碳纤维的值约为0.4nm。总本底校正高度分析显示,这些纳米结构沿着未上浆纤维的原纤维均匀分布,而对于上浆纤维,则不存在纳米结构。提出的方法允许首次分析和可视化碳纤维表面上的纳米结构的分布。此功能用于可视化上浆的分布,还可以用于调查不同生产参数对纤维形貌的影响,或评估机械互锁对界面强度的作用。

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