26 September 2016 Improvement of Electron Beam Lithography modeling for overdose exposures by using Dill transformation
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Abstract
In Electron Beam Lithography (EBL), the modeling of the Proximity Effects (PE) is the key to successfully print patterns of different size and density at the desired dimension. Although current PE models are increasingly efficient for nominal process conditions, they do not allow covering a broad exposure dose range, which would be interesting for extending the process window, for instance. This paper shows how to improve the accuracy of the dimension estimations of overexposed patterns by EBL by adding a new term to the existing compact model. This advanced compact model was inspired by the chemical mechanisms that activate the acid generator embedded in the resist during the EBL exposure. Most of the existing compact models use the electronic Aerial Image (E AEI) calculated by the convolution product of the patterns geometry with a Point Spread Function (PSF) and extract pattern contours using a threshold value to model the non-linear resist behavior [1]. Here the patterns contours are simulated using an Acid Aerial Image (A AEI) calculated from the initial E_AEI complemented by the Dill transformation [1]. A strong impact is expected at high exposure doses but no changes should occur on patterns exposed close to their nominal dose. The modeling and calibration capabilities of Inscale® software was used to validate the new model with experimental measurements. Calibration and simulations obtained with both standard model and advanced model were compared on a test design. First it shows that after calibration the PSF of the two models are similar, meaning that physics is consistent for both models. The new advanced model allows maintaining the accuracy at nominal dose but increases the overall accuracy by 62 % for a process window of dose with latitude extended up to 20%.
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Mohamed Abaidi, Mohamed Saib, Jean-Hervé Tortai, Patrick Schiavone, "Improvement of Electron Beam Lithography modeling for overdose exposures by using Dill transformation", Proc. SPIE 9985, Photomask Technology 2016, 998507 (26 September 2016); doi: 10.1117/12.2240928; https://doi.org/10.1117/12.2240928
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