Techniques for improving overlay accuracy by using device correlated metrology targets as reference

Abstract

Abstract. The performance of overlay metrology as total measurement uncertainty, design rule compatibility, device correlation, and measurement accuracy has been challenged at the 2× nm node and below. The process impact on overlay metrology is becoming critical, and techniques to improve measurement accuracy become increasingly important. We present a methodology for improving the overlay accuracy. A propriety quality metric, Qmerit, is used to identify overlay metrology measurement settings with the least process impacts and reliable accuracies. Using the quality metric, a calibration method, Archer self-calibration, is then used to remove the inaccuracies. Accuracy validation can be achieved by correlation to reference overlay data from another independent metrology source such as critical dimension-scanning electron microscopy data collected on a device correlated metrology hybrid target or by electrical testing. Additionally, reference metrology can also be used to verify which measurement conditions are the most accurate. We provide an example of such a case. © The Authors. IntroductionAt imaging based overlay (OVL) metrology, a propriety quality metric, called "Qmerit," can be used to quantify target process imperfections. The metric employed in order to identify the optimal measurement conditions which are less sensitive to process impacts and therefore report the most accurate OVL values. This quality metric can be used in comparative analysis for a range of overlay target designs and metrology settings, thereby identifying good candidate combinations of target designs and metrology settings. The accuracy of the results of each target design and metrology setting is then verified by critical dimension-scanning electron microscopy (CDSEM) data collected on a device correlated metrology (DCM) hybrid target. Furthermore, simulation of the light spectrum behavior per target geometry and film stack information also supports the target designs and metrology settings selection based on the anticipated precision.Using the quality metric results (Qmerit), an innovative calibration method, the Archer self-calibration (ASC), is used to remove inaccuracies. Using the measurement information from various target or metrology settings, the calibration methodology estimates the inaccuracies and calibrates the overlay data for the most accurate behavior. This in turn results in significant improvement in correlation to reference CDSEM data measured on a DCM target for all available targets and metrology settings combinations.

Lithographic imaging-driven pattern edge placement errors at the 10-nm node

“…Total overlay budget of images projected by the scanners combines impacts of overlay and imaging. 15 Imaging contributes to EPEs through variations of the image dimensions, i.e., CD uniformity variations, shifting the pattern edges relative to the image center and by displacement of the images relative to their target locations. 9 In addition to exposure overlay, imaging contributes to EPEs through CD variations, directly impacting placement of the pattern edges.…”