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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Published in | 1990 IJCNN International Joint Conference on Neural Networks pp. 7 - 14 vol.1 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
1990
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Online Access | Get full text |
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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 |
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DOI: | 10.1109/IJCNN.1990.137536 |