AVS 46th International Symposium
    Manufacturing Science and Technology Group Wednesday Sessions
       Session MS-WeA

Paper MS-WeA10
Linking Process and Structure using Automated Analysis of AFM Images

Wednesday, October 27, 1999, 5:00 pm, Room 611

Session: Metrology II
Presenter: D.A. Chernoff, Advanced Surface Microscopy, Inc.
Authors: D.A. Chernoff, Advanced Surface Microscopy, Inc.
D.L. Burkhead, Advanced Surface Microscopy, Inc.
C.S. Cook, Advanced Surface Microscopy, Inc.
Correspondent: Click to Email
By volume of product, the optical disc industry is the largest nanotechnology activity today. On DVDs (Digital Versatile Discs), the smallest features are about 400 nm long, 320 nm wide, 120 nm high, with a track pitch of 740 nm. Consumers need optical discs whose electrical performance during playback is consistently within specifications. Existing disc analyzers report electrical test results and engineers respond to deviations by adjusting process variables. This method provides only indirect control because the process variables determine the microstructure of the master, stamper and replica and it is that microstructure which determines ultimate electrical performance. A method is needed to examine microstructure so that one can see how each process variable affects various aspects of microstructure and to see how each aspect of microstructure affects performance. Automated, high accuracy analysis of Atomic Force Microscope (AFM) images provides the missing link. We measured the following parameters: track pitch, bump height, bump width and length (at various threshold levels), bump length, and four sidewall slope angles, in each case reporting mean, standard deviation and other statistics. From each 10 um image of a DVD stamper, containing about 100 bumps, we tabulated about 1000 values. Bump width increased with bump length, correlating with a corresponding increase in amplitude with pulse duration when a finished disc is played. Where sidewall angle deviated from the norm, we reviewed the image data to identify the specific nature of the defect. The results were statistically robust not only for mean values, but also for standard deviations, so that we could compare process variation from different pieces of equipment. Thus, feature geometry will no longer be a hidden variable in the path between controlling production equipment and observing the good or bad electrical performance of a finished disc.