Model-based assist feature placement for 32nm and 22nm technology nodes using inverse mask technology

Amyn Poonawala; Benjamin Painter; Chip Kerchner

doi:10.1117/12.829717

30 September 2009 Model-based assist feature placement for 32nm and 22nm technology nodes using inverse mask technology

Amyn Poonawala, Benjamin Painter, Chip Kerchner

Proceedings Volume 7488, Photomask Technology 2009; 748814 (2009) https://doi.org/10.1117/12.829717
Event: SPIE Photomask Technology, 2009, Monterey, California, United States

Abstract

Inverse imaging has been long known to provide a true mathematical solution to the mask design problem. However, it is often times marred by problems like high run-time, mask manufacturability costs, and non-invertible models. In this paper, we propose a mask synthesis flow for advanced lithography nodes, which capitalizes on the inverse mask solution while still overcoming all the above problems. Our technique uses inverse mask technology (IMT) to calculate an inverse mask field containing all the useful information about the AF solution. This field is fed to a polygon placement algorithm to obtain initial AF placements, which are then cooptimized with the main features during an OPC/AF print-fix routine to obtain the final mask solution. The proposed flow enables process window maximization via IMT while guaranteeing fully MRC compliant masks. We present several results demonstrating the superiority of this approach. We also compare our IMT-AFs with the best AF solution obtained using extensive brute-force search (via a first principles simulator, S-litho), and prove that our solution is optimum.

Citation Download Citation

Amyn Poonawala, Benjamin Painter, and Chip Kerchner "Model-based assist feature placement for 32nm and 22nm technology nodes using inverse mask technology", Proc. SPIE 7488, Photomask Technology 2009, 748814 (30 September 2009); https://doi.org/10.1117/12.829717

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