No abstract

A line edge roughness analysis software is developed based on the Canny edge detection algorithm with a double threshold, where threshold values are obtained by Otsu's method. The performance of the software is demonstrated on features with a 200-nm nominal pitch generated by current-controlled, field-emission scanning probe lithography. Two lithographic modes are applied: (a) direct self-development positive mode and (b) image reversal mode. Atomic force imaging is used to analyze the line edge roughness. This is followed by a benchmarking study, where findings are compared to those provided by METROLER software (Fractilia, LLC). This work is the first report on both line edge roughness involving imaging using the same exposure setup and latent image line edge roughness-made possible thanks to the resolving power of imaging through noncontact AFM. The authors are presenting a comparison of patterning through image reversal of the calixarene molecular glass resist from negative-tone to positive-tone as well as direct-write. In image reversal, a close match was observed between the proposed analysis and METROLER software for line edge roughness and linewidth.