Proceedings Article | 27 September 2021
KEYWORDS: Image quality, Scanning electron microscopy, Photomasks, Error analysis, Etching, Calibration, System identification, Semiconductors, Reticles, Process control
In semiconductor industry, CD-SEMs (critical dimension scanning electron microscopes) are key enablers for metrology and process control. Additional applications that exploit the potential of CD-SEM equipment have being developed – such as contour extraction algorithms, in order to continue to address the increasing metrology requirements of the semiconductor industry. An important example of the utilization of image information is the industry’s use of full contour extraction for various applications, such as MPC (mask process correction) modeling, OPC (optical proximity correction) modeling, and advanced measurement solutions, especially for newer technologies such as ILT (Inverse Lithography Technology), where the characteristics of the 2D curvilinear patterns are such that standard measurement solutions are no longer an option.
As mask errors become more and more critical, providing good measurements is critical for calibrating MPC models, estimating etch bias over complex features, providing CD uniformity analysis, among other. More complex patterns also lead to less robust measurements in traditional CD-SEMs requiring more refined algorithms and statistics control to achieve a good level of certainty. Tool drift can lead to a lack of focus during the image acquisition and induce a blur problem in the image, affecting the quality of the signal to be analyzed, and consequently misleading the measurements. These measurements can induce false statistics and lead to bad decisions in a fab environment.
Another important factor for considering over SEM images is the quality of the signal on the pattern edges. This characteristic may have a significant impact over the measurement results, also leading to errors in the production flow. For example, using wrong measurements for addressing etching recipes or for generating MPC models may induce errors in the mask fabrication process, reducing its overall quality. Therefore, being capable of identifying blur on SEM images as well as edge quality variation is an important tool for mask manufacturers to prevent from using erroneous measurements for the decisions required during the entire fabrication flow.
In this work, the impact of blur on CD-SEM measurements is evaluated. Also, the impact of the blur over the detection of pattern’s edges is demonstrated over experimental data, coming from three different mask production flows, with different etch signatures and acquisition conditions. The proposed approach enables removing untrustworthy measurements from a calibration or a verification set.
