Paper
5 April 2011 Performance of a bilinear photoresist model
Anatoly Burov, Min Shi, Jiang Yan, Wenfeng Sun
Author Affiliations +
Abstract
A bilinear photoresist model extends the approach of a convolution kernel-style process models to include second-order effects. Using effective acid concentration after post-exposure bake as the latent image we approximate the reactiondiffusion operator as a second order Volterra series. The series expansion is carried out for a calibrated photoresist model. Both the linear kernel and the Bilinear Resist Transfer Function (BRTF) are estimated at the same time using a set of pre-computed training images. The linear kernels of the Volterra series are found to have a Gaussian behavior, while the shape of BRTF appears to vary greatly depending on exact details of photoresist composition. Accuracy of the estimated photoresist operator is studied using process window matching at multiple sets of optical conditions. The estimated operator is applied to a set of validation aerial images and the resultant CD values are compared against full photoresist simulation. The bilinear model performance is found to be within 1 nm of the full photoresist model across the full range of dose and focus values.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Anatoly Burov, Min Shi, Jiang Yan, and Wenfeng Sun "Performance of a bilinear photoresist model", Proc. SPIE 7973, Optical Microlithography XXIV, 79732V (5 April 2011); https://doi.org/10.1117/12.879369
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Photoresist materials

Performance modeling

Process modeling

Calibration

Data modeling

Bidirectional reflectance transmission function

Image processing

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