Accurate characterization of image rippling is critical in early detection of back-end-of-line (BEOL) patterning weakpoints, as most defects are strongly associated with excessive rippling that does not get effectively compensated by optical proximity correction (OPC). We correlate image contour with design shapes to account for design geometry-dependent rippling signature, and explore the best practice of OPC fragmentation for BEOL geometries. Specifically, we predict the optimum contour as allowed by the lithographic process and illumination conditions and locate ripple peaks, valleys, and inflection points. This allows us to identify potential process weakpoints and segment the mask accordingly to achieve the best correction results.
As technology shrinks, the requirements placed on the post-OPC solution become so exacting that even small residual optical effects are significant. Simultaneously minimizing rippling and corner rounding cannot be accom- plished in parallel in wafer patterning especially when complex asymmetric pixelated sources are used. While either effect can be moderated by accurate application of optical proximity correction, they are both charac- teristic of unfiltered diffraction due to asymmetric illumination or design geometry and will remain inherent. Corrections that over emphasize reduced corner-rounding necessarily sacrifice edge convergence, resulting in a standing wave or unacceptable rippling along an entire edge. OPC can be used to reduce the magnitude of this rippling, but fragment placing is extremely critical. In this paper, we discuss optimized OPC fragmentation that offers balanced consideration to suppressing rippling and minimizing corner rounding. Specifically, we correlate design shapes with simulated post-OPC contours to account for design geometry-dependent rippling signature given existing illumination conditions. In contrast to adaptive fragmentation that relies on multiple iterations of simulation of intensity extrema redistribution, our method predicts the optimum contour as allowed by process and fragments the mask accordingly. The maximum imaging curvature resolvable by process coupled with the rippling signature, gives rise to the exact locations of the inflection points of the wafer contour. From there we achieve the best correction results by segmenting edges at the inflection points.
To provide insights into best practices of constructing an OPC recipe that suppresses wafer image rippling, we design versatile fragmentation rules with respect to the model-based resist image. Specifically, by recognizing that rippling effect exists before fragmentation, we conduct a coarse simulation with default engine settings and extract raw ripple sinusoidal components associated with signature geometries along all dimensions. The signal is predominantly optical, hence a good representation of the unfiltered diffraction. By referencing the rippling periodic features, we derive a global solution for fragmentation with full respect to geometrical boundary conditions. The methodology enables us to generate a robust fragmentation solution with minimum trial and error and improve target convergence especially along unfavorable dimensions.
Optical Proximity Correction (OPC) is a compute-intensive process used to generate photolithography mask shapes at advanced VLSI nodes. Previously, we reported a modified two-step OPC flow which consists of a first pattern replacement step followed by a model based OPC correction step [1]. We build on this previous work and show how this hybrid flow not only improves full chip OPC runtime, but also significantly improves mask correction consistency and overall mask quality. This is demonstrated using a design from the 20nm node, which requires the use of model based SRAF followed by model based OPC to obtain the full mask solution.
Full chip model based Optical Proximity Correction (OPC) at
advanced nodes involves iteratively modifying the drawn polygon shapes
while simulating them through complex optical and resist models. Due to
the computational complexity of the models and the large size of VLSI
designs, these mask simulations run for very long times. In this study we
propose a pattern replacement step to generate a partial mask solution
before applying model based OPC correction. Since the pattern replacement
step is very fast and model based OPC has to be applied only to a
portion of the design, total mask generation runtime is significantly reduced.
We treat the OPC engine with a classical dynamics perspective, and quantify its potential to converge in
all dimensions. The inherent engine weakness is thus taken into account for retargeting planning.
Specifically, we follow the one-dimensional helical spring model, and calculate the retarget amount as an
analogy to the spring restoring force, and eventually improve the wafer target convergence. Unlike
conventional measures, this methodology does not require patching or rebuilding the OPC engine,
therefore minimizes the cycle time. Meanwhile, it entails little risk by causing no impact on the mask
solution outside the retargeted region, thereby compartmentalizing the treatment.
Forces experienced by colloidal particles in an AC electric field such as dielectrophoresis (DEP) and
AC electro-osmosis (ACEO) have been widely investigated for their application in microfluidic
devices. In order to provide a more complete theoretical basis for such AC electrokinetic
mechanisms, we propose a method to quantify the two forces upon one individual particle using
optical tweezers as a force transducer and lock-in phase sensitive detection technique to allow high
selectivity. Using this method, we isolated the ACEO force from the DEP force for charged
polystyrene sphere in deionized (DI) water. ACEO free DEP crossover frequencies and a
comprehensive 2D-mapping of the frequency dependent ACEO forces are presented in this paper.
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