Applying Machine Learning Models on Metrology Data for Predicting Device Electrical Performance

no code implementations • 20 Nov 2023 • Bappaditya Dey, Anh Tuan Ngo, Sara Sacchi, Victor Blanco, Philippe Leray, Sandip Halder

The goal of this work is of two-fold as, (a) to quantify the impact of overlay on capacitance and (b) to see if we can predict the final capacitance measurements with selected machine learning models at an early stage.

Deep learning denoiser assisted roughness measurements extraction from thin resists with low Signal-to-Noise Ratio(SNR) SEM images: analysis with SMILE

no code implementations • 23 Oct 2023 • Sara Sacchi, Bappaditya Dey, Iacopo Mochi, Sandip Halder, Philippe Leray

The technological advance of High Numerical Aperture Extreme Ultraviolet Lithography (High NA EUVL) has opened the gates to extensive researches on thinner photoresists (below 30nm), necessary for the industrial implementation of High NA EUVL.

Denoising