Process window modeling using compact models

Torres, J. Andres; Roessler, Thomas; Granik, Yuri

doi:10.1117/12.568354

Cited by 7 publications

(4 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…the off-focus dimensions has been beneficial for Scatter Bar (SBAR) rule optimization [1] as well for OPC correction in advanced memory chip production [2] as well as random logic design manufacturing [3]. It is also a powerful tool to improve design and OPC verification: Readily available modeling strategies including variable threshold models used in this study as well as compact models [2] yield accurate process window models by adding a relatively small number of additional SEM measurements characterizing the process window. Using process window models for advanced verification improves the predictability of weak-points in the design and proves that a given OPC correction result is offering the maximum process window for manufacturing.…”

Section: Resultsmentioning

confidence: 96%

A novel methodology for model-based OPC verification

Huang

Liao

Chou³

et al. 2008

SPIE Proceedings

View full text Add to dashboard Cite

Model-based optical proximity correction (OPC) is an indispensable production tool enabling successful extension of photolithography down to sub-80nm regime. Commercial OPC software has established clear procedures to produce accurate OPC models at best focus condition. However, OPC models calibrated at best focus condition sometimes fail to prevent catastrophic circuit failure due to patterning short & open caused by accidental shifts of dose/ focus within the corners of allowed processes window.A novel model-based OPC verification methodology is presented in this work, which precisely pinpoints post OPC photolithography failures in VLSI circuits through the entire lithographic process window. By application of a critical photolithography process window model in OPC verification software, we successfully uncovered all weak points of a design prior tape out, eliminating high risk of circuits open & shorts at the extreme corner of the lithographic process window in any complex circuit layout environment. The process window-related information is usually not taken into consideration when running OPC verification procedures with models calibrated at nominal process condition. Intensive review of the critical dimension (CD) and top-view SEM micrographs from the weak points indicate matching between post OPC simulation and measurements. Using a single highly accurate process window resist model provides a reliable OPC verification methodology when used in a field-or grid-based simulation engine ensuring manufacturability within the largest possible process window for any modern critical design.

show abstract

Section: Resultsmentioning

confidence: 96%

A novel methodology for model-based OPC verification

Huang

Liao

Chou³

et al. 2008

SPIE Proceedings

View full text Add to dashboard Cite

show abstract

“…[5][6][7][8] The schematic diagram of the conventional calibration methodology flow is shown on Fig. [5][6][7][8] The schematic diagram of the conventional calibration methodology flow is shown on Fig.…”

Section: Methodsmentioning

confidence: 99%

“…5 The successful PW aware OPC model is an accurately calibrated model which is a continuous function of defocus and dose. [5][6][7][8] However, there is no guarantee that such models can accurately predict process conditions other than those used in model calibration. 6 In principle, PW capable OPC models can be modeled using conventional calibration methodologies by calibrating the models on multiple process conditions across the focusexposure matrix (FEM).…”

Section: Introductionmentioning

confidence: 99%

Process window modeling using focus balancing technique

Isoyan¹,

Croffie²,

Melvin³

2011

Journal of Vacuum Science & Technology B, Nanotechnology an

View full text Add to dashboard Cite

In this work, we present a methodology for process window capable optical proximity correction (OPC) compact model building which requires only one nominal process condition empirical data for model calibration, and enables full and predictable extrapolation to any process condition within focus-exposure matrix. In order to ensure modeling success, a focus and dose balancing techniques are used during model calibration. The model optimization method is based on a stepwise fitting methodology where staged optimization of the OPC model components is used. Model components are added during the OPC model calibration starting with more physical components, such as mask and optics, followed by resist components. In each optimization stage, a component is optimized using global regression methods. The optimized parameters regressed in a small range about their optimal values during subsequent model component optimization. The effectiveness of this approach in terms of accurate correction, process window interpolation and extrapolation were compared with conventional fitting methods through computational experiments. Prediction of measured verification patterns were used to assess the calibrated model quality.

show abstract

“…Since measurement errors are unavoidable, two models calibrated at slightly different process conditions might have dramatic difference on the simulation results.We address the first problem by introducing a new variational lithography model (VLIM) in Section III A. The concepts of calibrating the models across the process window has been proposed[46,47]. But no details on the calibration methods were revealed.…”

mentioning

confidence: 99%

True process variation aware optical proximity correction with variational lithography modeling and model calibration

Shi

Pan

2007

J. Micro/Nanolith. MEMS MOEMS

View full text Add to dashboard Cite

Optical proximity correction (OPC) is one of the most widely used Resolution Enhancement Techniques (RET) in nanometer designs to improve subwavelength printability. Conventional model-based OPC assumes nominal process conditions without considering process variations because of the lack of variational lithography models. A simple method to improve OPC results under process variations is to sample multiple process conditions across the process window, which requires long runtime. We derive a variational lithography model (VLIM) which can simulate across the process window without much runtime overhead compared to the conventional lithography models. To match the model to experimental data, we demonstrate VLIM calibration method. The calibrated model has accuracy comparable to non-variational models, but it has the advantage of taking process variations into consideration. We introduce the variational edge placement error (V-EPE) metrics based on the model, a natural extension to the edge placement error (EPE) used in conventional OPC algorithms. A true process-variation aware OPC (PV-OPC) framework is proposed using the V-EPE metric. Due to the analytical nature of VLIM, our PV-OPC is only about 2-3× slower than the conventional OPC, but it explicitly considers the two main sources of process variations (exposure dose and focus variations) during OPC. Thus our post PV-OPC results are much more robust than the conventional OPC ones, in terms of both geometric printability and electrical characterization under process variations.

show abstract

Process window modeling using compact models

Cited by 7 publications

References 1 publication

A novel methodology for model-based OPC verification

A novel methodology for model-based OPC verification

Process window modeling using focus balancing technique

True process variation aware optical proximity correction with variational lithography modeling and model calibration

Contact Info

Product

Resources

About