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Effective metrology and standard of the surface roughness of micro/nanoscale waveguides with confocal laser scanning microscopy
Optics Letters ( IF 3.6 ) Pub Date : 2019-02-04 , DOI: 10.1364/ol.44.000747
DeGui Sun , Hongpeng Shang , Huilin Jiang

Surface roughness is one of the important parameters affecting the optical scattering loss of dielectric waveguides. Despite extensive research interests in correlating optical losses with surface roughness, not much research focus has been dedicated to the study of an accurate metrology and measurement standard for the characterization of waveguide roughness. In this Letter, we report an effective metrology for the measurement of waveguide surface roughness, using confocal laser scanning microscopy (CLSM). We also provide the definition of surface roughness relevant to CLSM terminology based on the measured peak-to-valley (P-V) values, which can be correlated to the conventional root-mean-square roughness, by employing multi-dimensional statistical models. Finally, we demonstrate the use of CLSM metrology in measuring two-dimensional roughness of 10 μm×6 μm silica waveguides, showing an average top surface roughness of 0.151 μm and an average sidewall roughness of 0.203 μm. For comparison, the scanning electron microscopy (SEM) measurements are also carried out for the same waveguide samples, and then the measured sidewall roughness values are in the range of 0.08–0.12 μm. Since SEM measures only the amplitude of roughness profile, while CLSM measures the P-V value, after doubling the SEM value, these two methods can provide comparable results of roughness.

中文翻译:

共焦激光扫描显微镜对微米/纳米尺度波导表面粗糙度的有效计量和标准

表面粗糙度是影响介电波导的光散射损耗的重要参数之一。尽管在将光学损耗与表面粗糙度相关联方面有广泛的研究兴趣,但是没有太多的研究重点致力于用于表征波导粗糙度的精确计量和测量标准。在这封信中,我们报告了使用共聚焦激光扫描显微镜(CLSM)测量波导表面粗糙度的有效度量衡。我们还基于测得的峰谷(PV)值提供了与CLSM术语相关的表面粗糙度的定义,可以使用多维统计模型将其与常规的均方根粗糙度相关联。最后,我们演示了CLSM计量学在测量工件的二维粗糙度中的用途。10 微米×6 微米石英波导,其平均顶表面粗糙度为0.151μm,平均侧壁粗糙度为0.203μm。为了进行比较,还对相同的波导样品进行了扫描电子显微镜(SEM)测量,然后测得的侧壁粗糙度值在0.08-0.12μm的范围内。由于SEM仅测量粗糙度轮廓的幅度,而CLSM则测量PV值,因此在将SEM值加倍后,这两种方法可以提供可比较的粗糙度结果。
更新日期:2019-02-15
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