کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
544327 1450384 2012 4 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Automatic detection of photoresist residual layer in lithography using a neural classification approach
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر سخت افزارها و معماری
پیش نمایش صفحه اول مقاله
Automatic detection of photoresist residual layer in lithography using a neural classification approach
چکیده انگلیسی

Photolithography is a fundamental process in the semiconductor industry and it is considered as the key element towards extreme nanoscale integration. In this technique, a polymer photo sensitive mask with the desired patterns is created on the substrate to be etched. Roughly speaking, the areas to be etched are not covered with polymer. Thus, no residual layer should remain on these areas in order to insure an optimal transfer of the patterns on the substrate. In this paper, we propose a nondestructive method based on a classification approach achieved by artificial neural network for automatic residual layer detection from an ellipsometric signature. Only the case of regular defect, i.e. homogenous residual layer, will be considered. The limitation of the method will be discussed. Then, an experimental result on a 400 nm period grating manufactured with nanoimprint lithography is analyzed with our method.

Figure optionsDownload as PowerPoint slideHighlights
► Artificial neural network approach for optical signature classification.
► Detection of photoresist residual layer in lithography.
► Method for rapid identification of thin residual layer in nanoimprint lithography.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Microelectronic Engineering - Volume 97, September 2012, Pages 29–32
نویسندگان
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