Chinese Journal of Lasers, Volume. 44, Issue 1, 103001(2017)

Identifying Defects in Thin Film of High Power Laser Lens by Using Near Field Microimaging Method

Bai Zhongchen1、*, Huang Zhaoling1, Hao Licai2, Lu Anjiang2, and Qin Shuijie1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    The surface flaws and internal knots in a film of high power laser lens are experimentally measured by using a near field micro-image method, and their formation mechanisms are analyzed as well. The evanescent waves radiated by a conic tip at a 100 nm diameter interact with the defects embedded in the films. After the evanescent waves are converted into radiation waves, they are collected by the objective lens and imaged point by point in the far field. Atomic force microscopy (AFM) images and scanning near-field optical microscopy (SNOM) images on the surface of the thin film are obtained synchronously, so as to visually identify the physical mechanisms of the defects formation. The results show that the surface flaw and the internal knot in thin film are accurately identified at the same time in effective interacting areas of evanescent wave. By comparing AFM result with SNOM result, we find that the surface flaw of substrate accumulates the residual stress in the processing of coating, which results in a layered cracking on the surface of film. The crosswise profile scale of single minimum flaw is 165 nm, which is beyond experimental detection precision of traditional far field detection. In addition, the high hot spot in SNOM graph shows that refractive index of knots exist in the thin film is higher than that in substrate.

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    Bai Zhongchen, Huang Zhaoling, Hao Licai, Lu Anjiang, Qin Shuijie. Identifying Defects in Thin Film of High Power Laser Lens by Using Near Field Microimaging Method[J]. Chinese Journal of Lasers, 2017, 44(1): 103001

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    Paper Information

    Category: materials and thin films

    Received: Sep. 29, 2016

    Accepted: --

    Published Online: Jan. 10, 2017

    The Author Email: Zhongchen Bai (yufengvc@163.com)

    DOI:10.3788/CJL201744.0103001

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