Mr. Ramana Murthy V.M. Pusuluri Profile

Ramana Murthy V.M. Pusuluri

Research Engineer

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Publications (3)

SPIE Journal Paper | 28 April 2018

Multiple stages of regression to improve accuracy in calibrated lithography process models

Pardeep Kumar, Alan Rosenbluth, Ramana Murthy Pusuluri, Ramya Viswanathan, Babji Srinivasan, Nihar Mohapatra

JM3, Vol. 17, Issue 02, 023503, (April 2018) https://doi.org/10.1117/12.10.1117/1.JMM.17.2.023503

KEYWORDS: Calibration, Data modeling, Process modeling, Autoregressive models, Lithography, Photomasks, Statistical modeling, Monte Carlo methods, Photoresist processing, Optical proximity correction

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A two-stage approach is introduced to improve the accuracy of compact patterning models used in large-scale computational lithography. Each of the two stages uses a separate empirically calibrated regression model whose accuracy at predicting printed feature dimensions has been proven in the usual standalone (single stage) mode. For the first model stage, we choose an established regularized regression model of the kind that accounts for resist non-idealities by suitably modifying the pre-thresholded exposing dose pattern, with the model basis functions taking the form of modified convolutions of adjustable kernels with the optical image. A different class of regression model is used in the second stage, namely a model that accounts for resist non-idealities by making a pattern-dependent local adjustment in the develop threshold, with the model basis functions being characteristic traits of the image trace along feature cutlines. However, rather than applying this second model in the usual mode where it adjusts the develop threshold applied to the exposing optical image, we use it to adjust a threshold that is applied to the improved effective dose distribution provided by the first-stage model. The effectiveness of the proposed method is verified by modeling pattern transfer of critical layers in 14- and 22-nm complementary metal–oxide–semiconductor (CMOS) technology. In our experience, little accuracy improvement is gained by expanding the complexity of standard single-stage models beyond the level of empirically proven model forms. However, even in a basic implementation, inclusion of a second stage of modeling will in itself reduce RMS error by ∼45 % in our 14-nm example. Moreover, accuracy improvement is further boosted to ∼55 % by adopting a minimax strategy in which the model is conservatively regularized according to the worst-case outcome in cross-validation tests but is calibrated according to the best-case outcome.

Proceedings Article | 23 May 2011 Paper

Evaluation of process variations on OPC model predictions

James Oberschmidt, Samit Barai, Tamer Desouky, Om Prakash Jaiswal, Aditya Padmawar, Ramana Murthy Pusuluri

Proceedings Volume 8081, 80810O (2011) https://doi.org/10.1117/12.897531

KEYWORDS: Photomasks, Data modeling, Calibration, Critical dimension metrology, Optical proximity correction, Process modeling, Semiconducting wafers, Lithography, Polarization, Wafer-level optics

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Proceedings Article | 20 May 2011 Paper

Efficient method for SRAF rule determination

Ramana Murthy V. Pusuluri, Pavan Bashaboina, James Oberschmidt

Proceedings Volume 8081, 80810T (2011) https://doi.org/10.1117/12.899900

KEYWORDS: SRAF, Electronic design automation, Resolution enhancement technologies, Computer simulations, Current controlled current source

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