Validation of inverse lithography technology (ILT) and its adaptive SRAF at advanced technology nodes

Pang, Liang; Dai, Grace; Cecil, Tom; Dam, Thuc; Cui, Ying; Hu, Peter; Chen, Dongxue; Baik, Ki‐Ho; Peng, Danping

doi:10.1117/12.775084

Cited by 27 publications

(13 citation statements)

References 8 publications

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“…When imaging at subwavelength, resolution enhancement technologies (RET) such as OPC, Phase Shift Masks (PSM), sub-resolution assist features (SRAFs), Source Mask Optimization (SMO), and Inverse Lithography Technology (ILT), are often required, adding complexity to the mask [1][2][3][4][5][6][7][8]. [Fig 3] shows an example of how the use of ILT can substantially increase litho process windows.…”

Section: Introductionmentioning

confidence: 99%

Computational inspection applied to a mask inspection system with advanced aerial imaging capability

et al. 2010

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Traditional patterned mask inspection has been off-wavelength. For the better part of the past 25years mask inspection systems never adhered to the wavelength of the exposure tools. While in the days of contact and proximity printing this was not a major issue, with the arrival of steppers and scanners and the slow migration from 436nm, 405nm, 365nm and 248nm to ultimately 193nm, on-wavelength inspection has become a necessity. At first there was the option with defect and printline review using an at-wavelength AIMS tool [Fig 1], but now the industry has moved towards Patterned Mask Inspection to be at-wavelength too. With ever decreasing wavelength, more and more materials have become opaque, and especially the 266/257nm inspection to 193nm printing wavelength has proven to be a reliability issue. The industry took a major step forward with the adoption of at-wavelength aerial inspection, a paradigm shift in mask inspection, as it uses a hardware emulation to parallel the scanner's true illumination settings [Fig 2]. The technology has found wide-spread acceptance by now, and 19xnm inspection is now the industry standard. Maskshop [outgoing] captive/ merchant 1 st path: -d2db -d2d +AIMS review [193nm] 2 nd path -contam/repair off-O: -488/ -365/257nm High Resolution Aerial image Profile cross-section plot: Red: defect, Blue: referenceFig 1: Traditional O mismatch in mask inspection Fig 2: Paradigm Shift: at-O inspection in aerial modeHowever, with the ever advancing technology nodes, such as 32nm and 22nm, aggressive OPC and Sub-Resolution Assist Features (SRAFs) are required. Their use results in significantly increased mask complexity, challenging mask defect dispositioning more than ever. To address these challenges in mask inspection and defect dispositioning, new mask inspection technologies have been developed that not only provide high resolution masks imaged at the same wavelength as the scanner, but that also provide aerial images by using both: software simulation and hardware emulation.

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Section: Introductionmentioning

confidence: 99%

Computational inspection applied to a mask inspection system with advanced aerial imaging capability

et al. 2010

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“…When imaging sub-wavelength patterns, resolution enhancement technologies (RET) such as OPC, Phase Shift Masks (PSM), sub-resolution assist features (SRAFs), Source Mask Optimization (SMO), and Inverse Lithography Technology (ILT), are often required, adding complexity to the mask [1][2][3][4][5][6][7][8]. Complex multilayer structure of mask blanks adds complexity in the case of EUV lithography.…”

Section: Introductionmentioning

confidence: 99%

Expanding the applications of computational lithography and inspection (CLI) in mask inspection, metrology, review, and repair

Pang

Peng

et al. 2011

SPIE Proceedings

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Mask manufacturers will be impacted by two significant technology requirements at 22nm and below: The first is more extensive use of resolution enhancement technologies (RET), such as OPC or Inverse Lithography Technology (ILT), and Source Mask Optimization (SMO); the second is EUV technology. Both will create difficulties for mask inspection, defect disposition, metrology, review, and repair. For example, the use of ILT and SMO significantly increases mask complexity, making mask defect disposition more challenging than ever. EUV actinic inspection and AIMS TM will not be available for at least a few years, which makes EUV defect inspection and disposition more difficult, particularly regarding multilayer defects. Computational Lithography and Inspection (CLI), which has broad applications in mask inspection, metrology, review, and repair, has become essential to fill this technology gap. In this paper, several such CLI applications are presented and discussed.

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“…10 In subsequent years, Poonawala and Milanfar designed the model-based optical proximity correction (OPC) system and introduced the steepest descent (SD) algorithm for the optimization framework. 29,30 Recently, the level set approach 31,32 has been actively explored as a feasible alternative to tackle the inverse lithography problem, 33,34 and Shen et al 35 provided a complete but conventional level set formulation of this problem. [19][20][21] Meanwhile, the optimization algorithm was improved with an active set method by Chan et al, 22 with a hotspot-and robustness-aware method using a weighted scheme by Li et al, 23 combined with an augmented Lagrangian method by Li et al 24 Moreover, the robustness of inverse imaging is improved through the use of stochastic gradient descent.…”

Section: Introductionmentioning

confidence: 99%

Level-set-based inverse lithography for mask synthesis using the conjugate gradient and an optimal time step

Liu

Xia

et al. 2013

Journal of Vacuum Science &Amp; Technology B, Nanotechnology and Microelectronics: Materials, Processing, Measurement, and Phen

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Inverse mask synthesis is achieved by minimizing a cost function on the difference between the output and desired patterns. Such a minimization problem can be solved by a level-set method where the boundary of the pattern is iteratively evolved. However, this evolution is timeconsuming in practice and usually converges to a local minimum. The velocity of the boundary evolution and the size of the evolution step, also known as the descent direction and the step size in optimization theory, have a dramatic influence on the convergence properties. This paper focuses on developing a more efficient algorithm with faster convergence and improved performance such as smaller pattern error, lower mean edge placement error, wider defocus band, and higher normalized image log slope. These improvements are accomplished by employing the conjugate gradient of the cost function as the evolution velocity, and by introducing an optimal time step for each iteration of the boundary evolution. The latter is obtained from an extended Euler time range by using a line search method. The authors present simulations demonstrating the efficacy of these two improvements.

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Validation of inverse lithography technology (ILT) and its adaptive SRAF at advanced technology nodes

Cited by 27 publications

References 8 publications

Computational inspection applied to a mask inspection system with advanced aerial imaging capability

Computational inspection applied to a mask inspection system with advanced aerial imaging capability

Expanding the applications of computational lithography and inspection (CLI) in mask inspection, metrology, review, and repair

Level-set-based inverse lithography for mask synthesis using the conjugate gradient and an optimal time step

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