Abstract:
Systems and methods for providing improved scanner corrections are disclosed. Scanner corrections provided in accordance with the present disclosure may be referred to as wafer geometry aware scanner corrections. More specifically, wafer geometry and/or wafer shape signature information are utilized to improve scanner corrections. By removing the wafer geometry as one of the error sources that may affect the overlay accuracy, better scanner corrections can be obtained because one less contributing factor needs to be modeled.
Abstract:
Systems and methods for prediction of in-plane distortions (IPD) due to wafer shape in semiconductor wafer chucking process is disclosed. A process to emulate the non-linear finite element (FE) contact mechanics model based IPD prediction is utilized in accordance with one embodiment of the present disclosure. The emulated FE model based prediction process is substantially more efficient and provides accuracy comparable to the FE model based IPD prediction that utilizes full-scale 3-D wafer and chuck geometry information and requires computation intensive simulations. Furthermore, an enhanced HOS IPD/OPD prediction process based on a series of Zernike basis wafer shape images is also disclosed.
Abstract:
Systems and methods for providing micro defect inspection capabilities for optical systems are disclosed. Each given wafer image is filtered, treated and normalized prior to performing surface feature detection and quantification. A partitioning scheme is utilized to partition the wafer image into a plurality of measurement sites and metric values are calculated for each of the plurality of measurement sites. Furthermore, transformation steps may also be utilized to extract additional process relevant metric values for analysis purposes.
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 controller is configured to perform at least a first characterization process prior to at least one discrete backside film deposition process on a semiconductor wafer; perform at least an additional characterization process following the at least one discrete backside film deposition process; determine at least one of a film force or one or more in-plane displacements for at least one discrete backside film deposited on the semiconductor wafer via the at least one discrete backside film deposition process based on the at least the first characterization process and the at least the additional characterization process; and provide at least one of the film force or the one or more in-plane displacements to at least one process tool via at least one of a feed forward loop or a feedback loop to improve performance of one or more fabrication processes.
Abstract:
Systems and methods for prediction of in-plane distortions (IPD) due to wafer shape in semiconductor wafer chucking process is disclosed. A series of Zernike basis wafer shapes process to emulate the non-linear finite element (FE) contact mechanics model based IPD prediction is utilized in accordance with one embodiment of the present disclosure. The emulated FE model based prediction process is substantially more efficient and provides accuracy comparable to the FE model based IPD prediction that utilizes full-scale 3-D wafer and chuck geometry information and requires computation intensive simulations. Furthermore, an enhanced HOS IPD/OPD prediction process based on a series of Zernike basis wafer shape images is also disclosed.
Abstract:
Systems and methods for prediction of in-plane distortions (IPD) due to wafer shape in semiconductor wafer chucking process is disclosed. A process to emulate the non-linear finite element (FE) contact mechanics model based IPD prediction is utilized in accordance with one embodiment of the present disclosure. The emulated FE model based prediction process is substantially more efficient and provides accuracy comparable to the FE model based IPD prediction that utilizes full-scale 3-D wafer and chuck geometry information and requires computation intensive simulations. Furthermore, an enhanced HOS IPD/OPD prediction process based on a series of Zernike basis wafer shape images is also disclosed.
Abstract:
Prediction based systems and methods for optimizing wafer chucking and lithography control are disclosed. Distortions predicted to occur when a wafer is chucked by a chucking device are calculated and are utilized to control chucking parameters of the chucking device. Chucking parameters may include chucking pressures and chucking sequences. In addition, predicted distortions may also be utilized to facilitate application of anticipatory corrections. Controlling chucking parameters and/or applying anticipatory corrections help reducing or minimizing overlay errors.
Abstract:
Systems and methods for providing micro defect inspection capabilities for optical systems are disclosed. Each given wafer image is filtered, treated and normalized prior to performing surface feature detection and quantification. A partitioning scheme is utilized to partition the wafer image into a plurality of measurement sites and metric values are calculated for each of the plurality of measurement sites. Furthermore, transformation steps may also be utilized to extract additional process relevant metric values for analysis purposes.
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.