公开(公告)号：US20220404711A1

公开(公告)日：2022-12-22

申请号：US17763698

申请日：2020-09-22

Applicant: ASML NETHERLANDS B.V.

Inventor： Ning GU ,  Liping REN ,  Kui-Jun HUANG ,  Jian WU

IPC: G03F7/20 ,  G05B13/02

Abstract: A method for monitoring performance of a manufacturing process is described. The method includes receiving one or more input signals that convey information related to geometry of a substrate generated by the manufacturing process; and determining, with a prediction model, variation in the manufacturing process based on the one or more input signals. A method for predicting substrate geometry associated with a manufacturing process is also described. The method includes receiving input information including geometry information and manufacturing process information for a substrate; and predicting, using a machine learning prediction model, output substrate geometry based on the input information. The method may further include tuning the predicted output substrate geometry. The tuning includes comparing the output substrate geometry to corresponding physical substrate measurements and/or predictions from a different non-machine learning prediction model, generating a loss function based on the comparison, and optimizing the loss function.

公开(公告)号：US20210247701A1

公开(公告)日：2021-08-12

申请号：US17053255

申请日：2019-05-21

Applicant: ASML NETHERLANDS B.V.

Inventor： Danying LI ,  Chi-Hsiang FAN ,  Adbalmohsen ELMALK ,  Youping ZHANG ,  Jay Jianhui CHEN ,  Kui-Jun HUANG

IPC: G03F7/20

Abstract: A method for determining a stack configuration for a substrate subjected to a patterning process. The method includes obtaining (i) measurement data of a stack configuration with location information on a printed substrate, (ii) a substrate model configured to predict a stack characteristic based on a location of the substrate, and (iii) a stack map including a plurality of stack configurations based on the substrate model. The method iteratively determines values of model parameters of the substrate model based on a fitting between the measurement data and the plurality of stack configurations of the stack map, and predicts an optimum stack configuration at a particular location based on the substrate model using the values of the model parameters.

公开(公告)号：US20250053097A1

公开(公告)日：2025-02-13

申请号：US18716806

申请日：2022-11-22

Applicant: ASML NETHERLANDS B.V.

Inventor： Kui-Jun HUANG ,  Liping REN

IPC: G03F7/00

Abstract: A correction to an error of overlay measurement which accounts for target structure asymmetry using a neural network is described. According to embodiments, an overlay measurement accuracy can be improved by accounting for multiple and/or asymmetric perturbations in the target structure. A trained neural network is described which generates a correction value for overlay measurement based on a measure of asymmetry. Based on an as-measured overlay measurement, which may not account for target structure asymmetry, and the correction value, a true overlay measurement is determined-which can exhibit improved accuracy and reduced uncertainty versus uncorrected values.