For leading edge technology node, many proximity effects during mask manufacturing process will change the mask details. Model-based Mask error correction (MEC) is needed for ensuring the mask fidelity. With the development of multi beam mask writers (MBMW), curvilinear mask offers many quality and performance advantages over Manhattan mask. It offers superior process window comparing to Manhattan mask for EUV process. In this paper, we discuss the results of model based curvilinear MEC based on Proteus platform. The quality and performance were compared between conventional compact model and Machine-Learning (ML) models. ML-based model can be accurately predicting mask printing signatures otherwise could not be predicted by convection compact model. Integrating MEC into Proteus platform offers seamless flow between different applications, like OPC, ILT and RET while preserve the device hierarchy.
Curvilinear OPC has been developed for improved process window, more freedom in mask constraint and better MRC enforcement. Combined Curve OPC with ILT can further improve mask synthesis flow. We demonstrate hybrid curve OPC/ILT flows for more flexible deployment. High NA OPC together with anamorphic MRC can be well handled in this platform. Curve OPC can be deployed in co-optimization flow like litho-etch OPC, process window aware OPC, etc. Correction of any angle layout is challenging. We present our OPC solutions in handle of any angle layout and demonstrate good correction results.
For the past few decades, PPA (performance, power, and area) demand of computation infrastructure has been driving exponential increase of chip density. In recent years, the challenges of printability and process window for advanced manufacturing node continuously motivated innovations in reticle enhancement techniques, notably the adoption of inverse lithography technology (ILT) and curvilinear mask. We have observed a few challenges: 1) ILT provides unmatched quality of results but does incur additional computation time to manage; 2) for curvilinear mask, though the benefits are evident, the associated data volume is very large; and 3) mask consistency remains a critical component for design manufacturability. To utilize the advanced RET techniques to their full potential, it is crucial to identify the repeating structures in design layout and reuse the correction result, getting three benefits at the same time: reducing mask preparation runtime, reducing mask data volume, and improving mask consistency. Conventional layout repetition analysis is based on native design hierarchy. However, in many cases, the input layout for mask synthesis flows is either completely stripped of hierarchy or contains sub-optimal hierarchy. Some layout hierarchy can be detected and reconstructed using manual methods such as using user generated pattern library of highly repeating structures in conjunction with pattern matching technology. However, the preparation of such libraries is a formidable effort, and a significant number of repetitions in designs will be overlooked by this approach. In this paper, we investigate the automatic detection of repeating geometry structures and formed a hierarchy that is optimized for mask synthesis. The detection supports any process layer and both Manhattan and all-angle designs. The engine detects repeating regions of arbitrary shape. The detected repeating structures can also be applied within the chip or across chips to accelerate correction to further improve mask consistency. By scaling well to hundreds of processors, the distributed hierarchy extraction is very efficient for a full chip layout. For highly repetitive layouts, mask synthesis runtime reduction of more than an order of magnitude has been observed by performing this hierarchy extraction.
In advanced semiconductor memory manufacturing, the feature size keeps aggressively shrinking, creating problems in the fabrication process and leading to decreasing yield. Three key factors that can impact memory process and yield are lithographic process window, full field CD uniformity (CDU), and correction run time performance. In this paper, we describe and present a mask processing technique utilizing a) global array detect (GAD) for detecting and optimizing cell repetition, b) periodic boundary condition (PBC) for preserving simulation and mask symmetry, and c) cell-level ILT (CLILT) flow to process repeated cell regions and blend various design parts. With GAD + PBC + CL-ILT processing, we can achieve a perfectly consistent mask array region with enlarged process window and minimum local CD variation for a full field mask. Moreover, with fewer pattern units (called templates) to process, we can complete full chip ILT with reasonable time and compute resources compared to OPC full chip correction. In this paper, we show simulation and wafer print results including pattern fidelity, process window, mask consistency, and run time data.
In EUV lithography, the short wavelength and residual mirror surface roughness increase the flare levels across the slit. As a key research point, the flares of different exposure fields are carefully discussed by numerical simulation. To ensure the effectiveness and practicability of our simulations, the test patterns are generated according to the general design rules for 7nm technology node. The NILS, process variation band (PVB) and MEEFs from mask optimizations and source mask optimizations (SMO) results are compared. From the comparisons, the constant flare has a greater influence on NILS and PVB than that on MEEF. In contrast, the flare map caused more reduction on the MEEF values.
With each new technology node there is an increase in the number of layers requiring Optical Proximity Correction
(OPC) and verification. This increases the time spent on the mask tapeout flow which is already a lengthy portion of the
production flow. New technology nodes not only have additional layers that require OPC but most critical layers also
end up with more complex OPC requirements relative to previous generations slowing the tapeout flow even further. In
an effort to maintain acceptable turnaround time (TAT) more hardware resources are added at each node and electronic
design automation (EDA) suppliers are pushed to improve the software performance. The more we can parallelize
operations within the tapeout flow the more efficient we can be with the use of the CPU resources and drive down the
overall TAT. Traditional flows go through several cycles where data is broken up into templates, the templates are
distributed to compute farms for processing, pieced back together, and sometimes written to disk before starting the next
operation in the tapeout flow. During each of these cycles there are ramp up, ramp down, and input/output (I/O) times
that are incurred affecting the efficient use of hardware resources. This paper will explore the advantages of pipelining
the templates from one operation to the next in order to minimize these effects.
KEYWORDS: Model-based design, Atrial fibrillation, Optical proximity correction, Systems modeling, Image processing, Photomasks, Process modeling, System on a chip, Optical components, Image resolution
Demanding process window constraints have increased the need for effective assist feature placement algorithms that are robust and flexible. These algorithms must also allow for quick ramp up when changing nodes or illumination conditions. Placement based on the optical components of real process models has the potential to satisfy all of these requirements. We present enhancements to model-based assist feature algorithms. These enhancements include exploration of image-processing techniques that can be exploited for contact-via AF placement, model-based mask rule check (MRC) conflict resolution, the application of models to line-space patterns, and a novel placement technique for contact-via layers using a specially-built single modeling kernel.
As semiconductor manufacturing moves to the 90nm node and below, shrinking feature sizes and increasing IC complexity have combined to significantly stretch out the time needed to optimize and qualify process anchored OPC models and recipes. Process distortion and non-linearity become non-trivial issues and conspire to reduce the quality of the resulting corrections. Additionally, optimizing the OPC model and recipe on a limited set of test chip designs may not provide sufficient coverage across the range of designs to be produced in the process. Finally, the increased complexity of the transformation of the target pattern into a corrected mask pattern also increases the probability of system lithography errors. Fatal errors (pinch or bridge) or poor CD distribution may still occur. As a result, more than one reticle tape-out cycle is non uncommon to prove models and recipes that approach the center of process for a range of designs. In this paper, we describe a full-chip simulation based verification flow using a commercialized product that serves both OPC model and recipe development as well as post OPC verification after production release of the OPC.
As IC design rules shrink dramatically while the wavelength reduction in exposure systems can not keep up, extensive usage of Litho RET, Etch trimming and OPC techniques has become common practice in the integrated patterning flow. We examined a large number of CD measurement datasets of 90nm Contact layer ADI and AEI CD. As the etch bias is not a constant through pitch, AEI contribution has to be incorporated in the OPC model. Based on these datasets, we tried to develop a non-constant AEI model. In this paper, we investigated various strategies to streamline OPC modeling. Multiple regression method is used to fit CTR and CTE models. It was revealed that an extra long range Loading Kernel, additional to a well-fitted ADI model, may not successfully meet the fitting criteria we want. Mainly due to the fact that models with too many eigenvectors would have a tendency to over-fit-and-correct CD curves. We introduced an alternative approach by limiting the number of parameters in our model OPC algorithm. We achieved a 90nm Contact Model with OPC empirical data fitting error within +-2nm. Lastly, the wafer verification datasets showed only 3σ = 7.82 nm of through-pitch OPC residual error by using this Constant Threshold Etch Model, compared to simulation residue error 3σ of 8 nm.
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