Mr. Frederick Frederick Profile

Frederick Frederick

Student at NTUST

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Proceedings Article | 28 March 2017 Paper

Constructing freeform source through the combination of neural network and binary ant colony optimization

Frederick Lie, Hung-Fei Kuo

Proceedings Volume 10147, 101471M (2017) https://doi.org/10.1117/12.2257944

KEYWORDS: Optimization (mathematics), Artificial neural networks, Computational lithography, Probability theory, Neural networks, Immersion lithography, Neurons, Photomasks, Lithography, Nanoimprint lithography

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Source Optimization is a key techniques to enhance the process window in ArF 193i-nm lithography process. This paper proposes a source optimization algorithm combining metaheuristic-based binary ant colony source optimization (BACO) and an artificial neural network (ANN). The purpose of this study is to establish the optimal freeform source for improving the process window of the critical patterns and maintaining the quality of aerial images. The source plane is pixelated and divided into 25 sectors. In this study, a set of the input data for training the ANN includes the pattern edge contours resulting from the various process conditions with respect to each searching agent at each iteration. The trained ANN selects sectors with effective pixel sources illuminating the target pattern to enhance the aerial image quality and improve the process window. The combination of the B-ACO and ANN methods decreases the searching space and speed up the convergence of the B-ACO. PROLITHTM (KLA-Tencor) is used to calculate the aerial image when using the optimized freeform source. The developed algorithm is tested using the 17 clips of 1D line/space pattern with various line widths, pitches and line orientations. The testing pattern includes nine horizontal line features and eight vertical line features. The minimum line width is 40 nm with a pitch of 80nm, and the maximum linewidth is 120nm with a pitch of 500nm. An optimized freeform source is simultaneously constructed for these 17 clips. The imaging performance for these 17 clips is presented.

Proceedings Article | 18 March 2015 Paper

Pixel-based ant colony algorithm for source mask optimization

Hung-Fei Kuo, Wei-Chen Wu, Frederick Li

Proceedings Volume 9426, 94260M (2015) https://doi.org/10.1117/12.2085525

KEYWORDS: Source mask optimization, Artificial intelligence, Electroluminescence, Resolution enhancement technologies, Photomasks, Metrology, Lithography, Evolutionary algorithms, Distortion, Extreme ultraviolet lithography

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Source mask optimization (SMO) was considered to be one of the key resolution enhancement techniques for node technology below 20 nm prior to the availability of extreme-ultraviolet tools. SMO has been shown to enlarge the process margins for the critical layer in SRAM and memory cells. In this study, a new illumination shape optimization approach was developed on the basis of the ant colony optimization (ACO) principle. The use of this heuristic pixel-based ACO method in the SMO process provides an advantage over the extant SMO method because of the gradient of the cost function associated with the rapid and stable searching capability of the proposed method. This study was conducted to provide lithographic engineers with references for the quick determination of the optimal illumination shape for complex mask patterns. The test pattern used in this study was a contact layer for SRAM design, with a critical dimension and a minimum pitch of 55 and 110 nm, respectively. The optimized freeform source shape obtained using the ACO method was numerically verified by performing an aerial image investigation, and the result showed that the optimized freeform source shape generated an aerial image profile different from the nominal image profile and with an overall error rate of 9.64%. Furthermore, the overall average critical shape difference was determined to be 1.41, which was lower than that for the other off-axis illumination exposure. The process window results showed an improvement in exposure latitude (EL) and depth of focus (DOF) for the ACO-based freeform source shape compared with those of the Quasar source shape. The maximum EL of the ACO-based freeform source shape reached 7.4% and the DOF was 56 nm at an EL of 5%.

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