Ir Kusnadi

Intensive 2D SEM model calibration for 45nm and beyond

Conventional site-base model calibration approaches have worked fine from the 180nm down to the 65nm technology nodes, but with the first 45nm technology nodes rapidly approaching, site-based model calibration techniques may not capture the details contained in these 2D-intensive designs. Due to the compaction of designs, we have slowly progressed from 1D-intensive gates, which were site-based friendly, to very complex and sometimes ornate 2D-gate regions. To compound the problem, these 2D-intensive gate regions are difficult to measure resulting in metrology-induced error when attempting to add these regions to the model calibration data. To achieve the sub-nanometer model accuracy required at this node, a model calibration technique must be able to capture the curvature induced by the process and the design in these gate regions. A new approach in model calibration had been developed in which images from a scanning electron microscope (SEM) are used together with the conventional site-base to calibrate models instead of the traditional single critical dimension (CD) approach. The advantage with the SEM-image model calibration technique is that every pixel in the SEM image contributes as CD information improving model robustness. Now the ornate gate regions could be utilized as calibration features allowing the acquisition of fine curvature in the design. This paper documents the issues of the site-base model calibration technique at the 45nm technology node and beyond. It also demonstrates the improvement in model accuracy for critical gate regions over the traditional modeling technique, and it shows the best know methods to achieve the utmost accuracy. Lastly, this paper shows how SEM-based modeling quantifies modeling error in these complex 2D regions.

Challenges of OPC model calibration from SEM contours

Traditionally OPC models are calibrated to match CD measurements from selected test pattern locations. This demand for massive CD data drives advances in metrology. Considerable progress has recently been achieved in complimenting this CD data with SEM contours. Here we propose solutions to some challenges that emerge in calibrating OPC models from the experimental contours. We discuss and state the minimization objective as a measure of the distance between simulation and experimental contours. The main challenge is to correctly process inevitable gaps, discontinuities and roughness of the SEM contours. We discuss standardizing the data interchange formats and procedures between OPC and metrology vendors.

Feedback flow to improve model-based OPC calibration test patterns

Process models are responsible for the prediction of the latent image in the resist in a lithographic process. In order for the process model to calculate the latent image, information about the aerial image at each layout fragment is evaluated first and then some aerial image characteristics are extracted. These parameters are passed to the process models to calculate wafer latent image. The process model will return a threshold value that indicates the position of the latent image inside the resist, the accuracy of this value will depend on the calibration data that were used to build the process model in the first place. The calibration structures used in building the models are usually gathered in a single layout file called the test pattern. Real raw data from the lithographic process are measured and attached to its corresponding structure in the test pattern, this data is then applied to the calibration flow of the models. In this paper we present an approach to automatically detect patterns that are found in real designs and have considerable aerial image parameters differences with the nearest test pattern structure, and repair the test patterns to include these structures. This detect-and-repair approach will guarantee accurate prediction of different layout fragments and therefore correct OPC behavior.

Contour quality assessment for OPC model calibration

Site-based SEM measurements produce accurate OPC models in 180nm to 65nm technology nodes, but the lack of 2D information has prompted for new calibration methods for sub 65nm designs. A hybrid technique using site-based SEM measurements together with SEM contours has been developed to produce more accurate OPC models. Contour samples account for 2D effects while CD sites provide high accuracy 1D measurements. SEM contours are prone to sampling and processing errors as well as extensive calibration run time. We develop a method to filter out inferior samples prior to model calibration to effectively decrease calibration runtime and increase model accuracy. Fitness and coverage metrics are used to assess the quality of the contour data in order to select the best subset of the calibration contours. Our results demonstrate a selection routine that consistently performs better than picking contours at random, and we discuss the trade-offs between coverage, accuracy and runtime with respect to model quality.

High-accuracy optical proximity correction modeling using advanced critical dimension scanning electron microscope–based contours in next-generation lithography

Optical proximity correction (OPC) modeling is traditionally based on critical dimension (CD) measurements. As design rules shrink and process windows become smaller, there is an unavoidable increase in the complexity of OPC resolution enhancement technique (RET) schemes required to enable design printability. The number of measurement points for OPC modeling has increased to several hundred points per layer, and metrology requirements are no longer limited to simple 1-D measurements. Contour-based OPC modeling has recently arisen as an alternative to the conventional CD-based method. In this work, the technology of contour alignment and averaging is extended to arbitrary 2-D structures. Furthermore, the quality of scanning electron microscope (SEM) contours is significantly improved in cases where the image has both horizontal and vertical edges (as is the case for most 2-D structures) by a new SEM image method, which we call fine SEM edge (FSE). OPC model calibration is done using SEM contours from 2-D structures. Then, the effectiveness of contour-based calibration is examined by doing model verification. The experimental results of the model quality with innovative SEM contours that was developed by Hitachi High-Technologies Corporation (Ibaraki-ken, Japan) are reported. This combination of advanced alignment and averaging, and FSE technologies, makes the best use of the advantage of contour-based OPC-modeling, and should be of use for next-generation lithography.

Contour-based self-aligning calibration of OPC models

SEM contours are used to complement CD measurements in OPC model calibration. This is done to capture 2D information about printed features into the model while CD measurement data is kept to maintain accuracy for 1D features. As the method progresses, there are emerging challenges that are normally not found in CD based calibration. One such challenge is the need to align SEM contours with calibration features. This is particularly important in determining model accuracy since contour calibration typically involves a cost function that compares the SEM contours to the simulated print images. This work explores a technique to include contour alignment errors into the calibration cost function. For each contour and its corresponding simulated print, the cost function returns an error value for a given set of model parameters. The error represents how well the model simulation compared to input contour. In addition, it also contains information on how far or how close the contour is aligned to simulation. Misalignment is to be eliminated on the fly during calibration and to be reported at the end of calibration. In this paper we describe the proposed technique and compare the results of calibration between aligned and misaligned contour data.

SEM-contour based mask modeling

With the push toward the 32nm node, OPC modeling must respond in kind with additional accuracy enhancements. One area of lithographic modeling that has basically gone unchecked is mask fidelity. Mask linearity is typically built into the OPC model since the calibration data contain this information, but mask pattern fidelity is almost impossible to quantify for OPC modeling. Mask fidelity is the rounding and smoothing of the mask features relative to the post-OPC layout intent, and there is no robust metric available to quantify these effects. With the introduction of contour-based model calibration, mask fidelity modeling is possible. This work evaluates techniques to quantify mask modeling and methods to gauge the accuracy improvement that mask fidelity modeling would project into the lithographic process using contour-based mask model calibration.

The assessment of the impact of mask pattern shape variation on the OPC-modeling by using SEM-Contours from wafer and mask

As design rules shrink, Optical Proximity Correction (OPC) becomes complicated. As a result, measurement points have increased, and improving the OPC model quality has become more difficult. From the viewpoint of decreasing OPC calibration runtime and improving OPC model quality concurrently, Contour-based OPC-modeling is superior to CD-based OPC-modeling, because Contour-based OPC-modeling uses shape based rich information. Hence, Contour-based OPC-modeling is imperative in the next generation lithography, as reported in SPIE2010. In this study, Mask SEM-contours were input into OPC model calibration in order to verify the impact of mask pattern shape on the quality of the OPC model. Advanced SEM contouring technology was applied to both of Wafer CD-SEM and Mask CD-SEM in examining the effectiveness of OPC model calibration. The evaluation results of the model quality will be reported. The advantage of Contour based OPC modeling using Wafer SEM-Contour and Mask SEM-Contour in the next generation computational lithography will be discussed.

Circuit-based SEM Contour OPC Model Calibration

In order to achieve the necessary OPC model accuracy, the requisite number of SEM CD measurements has exploded with each technology generation. At 65 nm and below, the need for OPC and/or manufacturing verification models for several process conditions (focus, exposure) further multiplies the number of measurements required. SEM-contour based OPC model calibration has arisen as a powerful approach to deliver robust and accurate OPC models since every pixel now adds information for input into the model, substantially increasing the parameter space coverage. To date however, SEM contours have been used to supplement the hundreds or thousands of discreet CD measurements to deliver robust and accurate models. While this is still perhaps the optimum path for high accuracy, there are some cases where OPC test patterns are not available, and the use of existing circuit patterns is desirable to create an OPC model. In this work, SEM contours of in-circuit patterns are utilized as the sole data source for OPC model calibration. The use scenario involves 130 nm technology which was initially qualified for production with the use of rule-based OPC, but is shown to benefit from model based OPC. In such a case, sub-nanometer accuracy is not required, and in-circuit features can enable rapid development of sufficiently accurate models to provide improved process margin in manufacturing.