Chinese Journal of Applied Chemistry ›› 2021, Vol. 38 ›› Issue (9): 1199-1208.DOI: 10.19894/j.issn.1000-0518.210121

• Full Papers • Previous Articles    

Analysis of Defects in Block Copolymer Films by a Convolution Algorithm

TIAN Xin1,2, LAI Han-Wen1,2, LIU Ya-Dong1*, JI Sheng-Xiang1,2*   

  1. 1Key Laboratory of Polymer Ecomaterials, Changchun Institute of Applied Chemistry Chinese Academy of Sciences, Changchun 130022, China
    2University of Science and Technology of China, Hefei 230026, China
  • Received:2021-03-17 Accepted:2021-04-12 Published:2021-09-01 Online:2021-09-06
  • Supported by:
    National Natural Science Foundation of China (Nos.51973212, 51773201), the Department of Science and Technology of Jilin Province (No.20200301017RQ), the Bureau of Science and Technology of Changchun (No.19SS005) and the Joint Program of CAS-Jilin Province (No.2019SYHZ0002)

Abstract: Directed self-assembly (DSA) of block copolymers (BCP) is one of the potential methods to manufacture sub-10 nm structures for semiconductors. However, the lack of tools in labs makes it difficult to quantitatively analyze defects and defect densities in BCP films prepared by self-assembly and DSA. Inspired by the general image processing method, image enhancement and template matching, a convolution algorithm was developed to detect defects in the scanning electron microscopy (SEM) images of BCP films and count the densities of each types of defects. Defects and artificial noises are accurately distinguished as verified by hand. The dot, terminal point and junction defects are automatically counted without any error in most SEM images by this algorithm. In order to get the reliable and reproducible results, the ratio of the BCP period (L0) to nanometers per pixel (NPP) needs to be >6.69 and the smallest image area is 1.5 μm2. Finally, direct comparison of the two algorithms on our workstation shows that the compute speed of the convolution algorithm is about 136~147 times faster than that of the adjacent pixel determination algorithm.

Key words: Block copolymer, Self-assembly, Directed self-assembly, Convolution, Defect statistics

CLC Number: