Abstract:
A method for enabling more accurate measurements of localized features on wafers is disclosed. The method includes: a) performing high order surface fitting to more effectively remove the low frequency shape components and also to reduce possible signal attenuations commonly observed from filtering; b) constructing and applying a proper two dimensional LFM window to the residual image from the surface fitting processing stage to effectively reduce the residual artifacts at the region boundaries; c) calculating the metrics of the region using the artifact-reduced image to obtain more accurate and reliable measurements; and d) using site-based metrics obtained from front and back surface data to quantify the features of interest. A method for filtering data from measurements of localized features on wafers is disclosed. This method includes an algorithm designed to adjust the filtering behavior according to the statistics of extreme data samples. A method for utilizing the 2D window and the data filtering to yield a more robust and more accurate Localized Feature quantification methodology is disclosed.
Abstract:
Systems and methods for predicting and controlling pattern quality data (e.g., critical dimension and/or pattern defectivity) in patterned wafers using patterned wafer geometry (PWG) measurements are disclosed. Correlations between PWG measurements and pattern quality data measurements may be established, and the established correlations may be utilized to provide pattern quality data predictions for a given wafer based on geometry measurements obtained for the give wafer. The predictions produced may be provided to a lithography tool, which may utilize the predictions to correct focus and/or title errors that may occur during the lithography process.
Abstract:
Predictive modeling based focus error prediction method and system are disclosed. The method includes obtaining wafer geometry measurements of a plurality of training wafers and grouping the plurality of training wafers to provide at least one training group based on relative homogeneity of wafer geometry measurements among the plurality of training wafers. For each particular training group of the at least one training group, a predictive model is develop utilizing non-linear predictive modeling. The predictive model establishes correlations between wafer geometry parameters and focus error measurements obtained for each wafer within that particular training group, and the predictive model can be utilized to provide focus error prediction for an incoming wafer belonging to that particular training group.
Abstract:
Wafer geometry measurement tools and methods for providing improved wafer geometry measurements are disclosed. Wafer front side, backside and flatness measurements are taken into consideration for semiconductor process control. The measurement tools and methods in accordance with embodiments of the present disclosure are suitable for handling any types of wafers, including patterned wafers, without the shortcomings of conventional metrology systems.
Abstract:
Systems and methods for prediction and measurement of overlay errors are disclosed. Process-induced overlay errors may be predicted or measured utilizing film force based computational mechanics models. More specifically, information with respect to the distribution of film force is provided to a finite element (FE) model to provide more accurate point-by-point predictions in cases where complex stress patterns are present. Enhanced prediction and measurement of wafer geometry induced overlay errors are also disclosed.
Abstract:
A method for enabling more accurate measurements of localized features on wafers is disclosed. The method includes: a) performing high order surface fitting to more effectively remove the low frequency shape components and also to reduce possible signal attenuations commonly observed from filtering; b) constructing and applying a proper two dimensional LFM window to the residual image from the surface fitting processing stage to effectively reduce the residual artifacts at the region boundaries; c) calculating the metrics of the region using the artifact-reduced image to obtain more accurate and reliable measurements; and d) using site-based metrics obtained from front and back surface data to quantify the features of interest. A method for filtering data from measurements of localized features on wafers is disclosed. This method includes an algorithm designed to adjust the filtering behavior according to the statistics of extreme data samples. A method for utilizing the 2D window and the data filtering to yield a more robust and more accurate Localized Feature quantification methodology is disclosed.
Abstract:
Wafer geometry measurement tools and methods for providing improved wafer geometry measurements are disclosed. Wafer front side, backside and flatness measurements are taken into consideration for semiconductor process control. The measurement tools and methods in accordance with embodiments of the present disclosure are suitable for handling any types of wafers, including patterned wafers, without the shortcomings of conventional metrology systems.
Abstract:
Systems and methods for prediction and measurement of overlay errors are disclosed. Process-induced overlay errors may be predicted or measured utilizing film force based computational mechanics models. More specifically, information with respect to the distribution of film force is provided to a finite element (FE) model to provide more accurate point-by-point predictions in cases where complex stress patterns are present. Enhanced prediction and measurement of wafer geometry induced overlay errors are also disclosed.