Wataru Nagatomo

A new matching engine between design layout and SEM image of semiconductor device

Optical proximity correction (OPC) plays a vital role in the lithography process development of current semiconductor devices. OPC is utilized to achieve the ideal pattern shape because of the limitations of optical resolution. However, the lithography process design has become increasingly more complex due to the abundant use of OPC features. Hence, metrology requests for CD-SEM have also become more complex and diverse in order to characterize the critical OPC models. The number of measurement points for OPC model evaluation has increased to several hundred points per layer, and metrology requests for realized pattern shapes on the wafer are no longer simple one-dimensional measurements. Metrology requests include not only the traditional line width measurements, but also edge placement error (EPE) and corner rounding to identify line end shortening. Several researchers have proposed using the design layout as a template instead of the SEM image for the recipe creation of CD-SEM and EPE measurement. However, it is very difficult to achieve good matching results between the design layout and the SEM image in practical processing times. Hitachi High-Technologies has developed a robust and quick matching engine between the design layout and SEM image bitmap. The new system, incorporating this new matching engine, can automatically create a practical recipe from the coordinate information of measurement point and the design layout information, such as GDSII. As a result, the new system can vastly reduce the amount of time and number of operations required to generate a several-hundred point CD-SEM recipe for OPC evaluation. This study demonstrates the capability and presents evaluation results of this new matching engine. This new capability has proven to be a viable solution for OPC evaluation, and its efficiency will allow for quicker information turns between design and manufacturing.

Application of model-based library approach to Si3N4 hardmask measurements

The model-based library (MBL) matching technique was applied in hardmask linewidth metrology with a criticaldimension scanning electron microscope (CD-SEM). The MBL matching measures the edge positions and shapes of samples by comparing simulated images to measured images. To achieve reliable, stable measurements, two important simulation parameters were determined empirically. One was the beam width, and the other was a material parameter, the residual energy loss rate. This parameter is especially important for measurement of hardmask patterns, which have relatively high SEM image contrast. These simulation parameters were estimated so as to fit to actual SEM images, and then pinned to the estimated values during MBL matching. Hardmask patterns made of Si3N4 were measured by MBL matching with the estimated parameters. The accuracy of the measurements was evaluated by one-to-one comparison with atomic force microscope (AFM) results. The pattern profile deduced from only the top-down CD-SEM image with MBL matching agreed well with the AFM profile and a scanning transmission electron microscope (STEM) crosssectional image. The average measurement bias between the MBL matching and AFM results was 1.58 nm for the bottom CD and -0.64 nm for the top CD, with a standard deviation of about 1.3 nm.

CD-bias evaluation and reduction in CD-SEM linewidth measurements

A new image processing algorithm is proposed and applied to model-based library (MBL) matching to achieve precise and accurate linewidth measurements in critical-dimension scanning electron microscopy (CD-SEM). Image quality is very important in image-based metrology to obtain reliable measurements. However, CD-SEMs are constrained to use poor signal-to-noise ratio images to avoid electron-beam-induced damage. The proposed algorithm is a line edge roughness (LER) compensation averaging algorithm that averages scan lines taking LER into account. The algorithm preserves the edge-bloom shape, which contains 3-dimensional information on the target pattern, while noise is removed by averaging. Applying the algorithm to MBL matching is expected to improve the accuracy of measurement, since MBL matching reduces shape-dependent CD-bias by using the edge-bloom shape. The proposed technique was evaluated by simulation. Precision, accuracy, and relative accuracy were tested and compared to the conventional threshold method. Precision using the proposed technique was 0.49 nm (3σ), which was worse than the 0.23 nm obtained with the conventional method. However, the relative accuracy was 0.5 nm, which was significantly better than the 2.9 nm obtained with the conventional method. As a result, the total measurement error (root mean square of precision and relative accuracy) was reduced from 2.9 nm to 0.7 nm.

Automated CD-SEM recipe creation technology for mass production using CAD data

Critical Dimension Scanning Electron Microscope (CD-SEM) recipe creation needs sample preparation necessary for matching pattern registration, and recipe creation on CD-SEM using the sample, which hinders the reduction in test production cost and time in semiconductor manufacturing factories. From the perspective of cost reduction and improvement of the test production efficiency, automated CD-SEM recipe creation without the sample preparation and the manual operation has been important in the production lines. For the automated CD-SEM recipe creation, we have introduced RecipeDirector (RD) that enables the recipe creation by using Computer-Aided Design (CAD) data and text data that includes measurement information. We have developed a system that automatically creates the CAD data and the text data necessary for the recipe creation on RD; and, for the elimination of the manual operation, we have enhanced RD so that all measurement information can be specified in the text data. As a result, we have established an automated CD-SEM recipe creation system without the sample preparation and the manual operation. For the introduction of the CD-SEM recipe creation system using RD to the production lines, the accuracy of the pattern matching was an issue. The shape of design templates for the matching created from the CAD data was different from that of SEM images in vision. Thus, a development of robust pattern matching algorithm that considers the shape difference was needed. The addition of image processing of the templates for the matching and shape processing of the CAD patterns in the lower layer has enabled the robust pattern matching. This paper describes the automated CD-SEM recipe creation technology for the production lines without the sample preparation and the manual operation using RD applied in Sony Semiconductor Kyusyu Corporation Kumamoto Technology Center (SCK Corporation Kumamoto TEC).