The Mask Data Correctness Check (MDCC) is a reticle-level, multi-layer DRC-like check evolved from mask rule
check (MRC). The MDCC uses extended job deck (EJB) to achieve mask composition and to perform a detailed check
for positioning and integrity of each component of the reticle. Different design patterns on the mask will be mapped to
different layers. Therefore, users may be able to review the whole reticle and check the interactions between different
designs before the final mask pattern file is available. However, many types of MDCC check results, such as errors from
overlapping patterns usually have very large and complex-shaped highlighted areas covering the boundary of the design.
Users have to load the result OASIS file and overlap it to the original database that was assembled in MDCC process on
a layout viewer, then search for the details of the check results. We introduce a quick result-reviewing method based on
an html format report generated by Calibre® RVE. In the report generation process, we analyze and extract the essential
part of result OASIS file to a result database (RDB) file by standard verification rule format (SVRF) commands.
Calibre® RVE automatically loads the assembled reticle pattern and generates screen shots of these check results. All the
processes are automatically triggered just after the MDCC process finishes. Users just have to open the html report to
get the information they need: for example, check summary, captured images of results and their coordinates.
The mask composition checking flow is an evolution of the traditional mask rule check (MRC). In order to differentiate
the flow from MRC, we call it Mask Data Correctness Check (MDCC). The mask house does MRC only to identify
process limitations including writing, etching, metrology, etc. There still exist many potential errors that could occur
when the frame, main circuit and dummies all together form a whole reticle. The MDCC flow combines the design rule
check (DRC) and MRC concepts to adapt to the complex patterns in today’s wafer production technologies. Although
photomask data has unique characteristics, the MRC tool in Calibre® MDP can easily achieve mask composition by using
the Extended MEBES job deck (EJB) format. In EJB format, we can customize the combination of any input layers
in an IC design layout format, such as OASIS. Calibre MDP provides section-based processing for many standard verification
rule format (SVRF) commands that support DRC-like checks on mask data. Integrating DRC-like checking with
EJB for layer composition, we actually perform reticle-level DRC, which is the essence of MDCC. The flow also provides
an early review environment before the photomask pattern files are available. Furthermore, to incorporate the
MDCC in our production flow, runtime is one of the most important indexes we consider. When the MDCC is included
in the tape-out flow, the runtime impact is very limited. Calibre, with its multi-threaded processes and good scalability, is
the key to achieving acceptable runtime. In this paper, we present real case runtime data for 28nm and 14nm technology
nodes, and prove the practicability of placing MDCC into mass production.
KEYWORDS: Optical proximity correction, Photomasks, Manufacturing, Data processing, Front end of line, Back end of line, Visualization, Design for manufacturability, Integrated circuits, Semiconductors
Delivering mask ready OPC corrected data to the mask shop on-time is critical for a foundry to meet the cycle time commitment for a new product. With current OPC compute resource sharing technology, different job scheduling algorithms are possible, such as, priority based resource allocation and fair share resource allocation. In order to maximize computer cluster efficiency, minimize the cost of the data processing and deliver data on schedule, the trade-offs of each scheduling algorithm need to be understood. Using actual production jobs, each of the scheduling algorithms will be tested in a production tape-out environment. Each scheduling algorithm will be judged on its ability to deliver data on schedule and the trade-offs associated with each method will be analyzed. It is now possible to introduce advance scheduling algorithms to the OPC data processing environment to meet the goals of on-time delivery of mask ready OPC data while maximizing efficiency and reducing cost.
Temporal drift in the mask manufacturing process has been observed in CD measurements collected at different times.
Most of this is corrected through global sizing and dose adjustments resulting in small mean-to-target (MTT) residual
errors. However, this procedure does not account for a detectable change in the proximity behavior of the mask
process. This paper discusses a procedure for detecting and monitoring the proximity behavior of a process using an
targeted sampling plan. It also proposes a procedure to correct for drifts in proximity behavior if it is predictable and
systematic.
The use of sub-resolution assist features (SRAFs) is a necessary and effective
technique to mitigate the proximity effects resulting from low-k1 imaging with
aggressive illumination schemes. This paper investigates the application of one
implementation of Inverse Lithography Technology (ILT) to determine optimized SRAF
placement and size. In contrast to traditional rule-based methods in which SRAF
placement and size are typically predetermined and frozen in place, unmodified during
OPC, ILT allows for the simultaneous placement and sizing of SRAFs during target
inversion to maximize image quality while also maintaining margin against sidelobe
printing. Furthermore, ILT enables SRAF placement for random as well as periodic
patterns. In this paper, SRAF placement using this approach is studied through
simulations. The computed mask and simulation results are shown to illustrate
effectiveness of ILT-generated SRAF features.
An implementation of inverse lithography technology is studied with special attention to
illustrating and analyzing the placement, accuracy, and efficacy of subresolution assist elements.
One-dimensional placement through pitch is characterized, and 2D capability is demonstrated for
repeated patterns. Differences between the methods of mask preparation afforded by this system
as compared to current practices are described.
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