Computation of proximity effect corrections in electron beam lithography by a neural network

The proximity effect, caused by electron-beam backscattering during resist exposure, can be compensated for by appropriate local changes in the incident beam dose, but the optimal correction, found iteratively, requires a prohibitively long time for realistic pattern sizes. A neural network has been...

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Bibliographic Details
Published in1990 IJCNN International Joint Conference on Neural Networks pp. 7 - 14 vol.1
Main Authors Frye, R.C., Rietman, E.A., Cummings, K.D.
Format Conference Proceeding
LanguageEnglish
Published 1990
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Summary:The proximity effect, caused by electron-beam backscattering during resist exposure, can be compensated for by appropriate local changes in the incident beam dose, but the optimal correction, found iteratively, requires a prohibitively long time for realistic pattern sizes. A neural network has been used to perform these corrections, resulting in a significant decrease in computation time. The correction was first computed for a small test pattern using an iterative method. This solution was used as a training set for an adaptive, feedforward neural network, using back-propagation learning. After training, the network computed the same correction as the iterative method, but in a much shorter time
DOI:10.1109/IJCNN.1990.137536