Patents by Inventor Chenxi Lin
Chenxi Lin has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11947266Abstract: A method for determining a correction relating to a performance metric of a semiconductor manufacturing process, the method including: obtaining a set of pre-process metrology data; processing the set of pre-process metrology data by decomposing the pre-process metrology data into one or more components which: a) correlate to the performance metric; or b) are at least partially correctable by a control process which is part of the semiconductor manufacturing process; and applying a trained model to the processed set of pre-process metrology data to determine the correction for the semiconductor manufacturing process.Type: GrantFiled: November 14, 2019Date of Patent: April 2, 2024Assignee: ASML NETHERLANDS B.V.Inventors: Nicolaas Petrus Marcus Brantjes, Matthijs Cox, Boris Menchtchikov, Cyrus Emil Tabery, Youping Zhang, Yi Zou, Chenxi Lin, Yana Cheng, Simon Philip Spencer Hastings, Maxim Philippe Frederic Genin
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Publication number: 20240069450Abstract: A method and apparatus for training a defect location prediction model to predict a defect for a substrate location is disclosed. A number of datasets having data regarding process-related parameters for each location on a set of substrates is received. Some of the locations have partial datasets in which data regarding one or more process-related parameters is absent. The datasets are processed to generate multiple parameter groups having data for different sets of process-related parameters. For each parameter group, a sub-model of the defect location prediction model is created based on the corresponding set of process-related parameters and trained using data from the parameter group. A trained sub-model(s) may be selected based on process-related parameters available in a candidate dataset and a defect prediction may be generated for a location associated with the candidate dataset using the selected sub-model.Type: ApplicationFiled: December 8, 2021Publication date: February 29, 2024Applicant: ASML Netherlands B.V.Inventors: Nabeel Noor MOIN, Chenxi LIN, Yi ZOU
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Publication number: 20230401694Abstract: A method and apparatus for identifying locations to be inspected on a substrate is disclosed. A defect location prediction model is trained using a training dataset associated with other substrates to generate a prediction of defect or non-defect and a confidence score associated with the prediction for each of the locations based on process-related data associated with the substrates. Those of the locations determined by the defect location prediction model as having confidences scores satisfying a confidence threshold are added to a set of locations to be inspected by an inspection system. After the set of locations are inspected, the inspection results data is obtained, and the defect location prediction model is incrementally trained by using the inspection results data and process-related data for the set of locations as training data.Type: ApplicationFiled: November 2, 2021Publication date: December 14, 2023Applicant: ASML NETHERLANDS B.V.Inventors: Chenxi LIN, Yi ZOU, Tanbir HASAN, Huina XU, Ren-Jay KOU, Nabeel Noor MOIN, Kourosh NAFISI
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Patent number: 11803127Abstract: A method for determining a root cause affecting yield in a process for manufacturing devices on a substrate, the method including: obtaining yield distribution data including a distribution of a yield parameter across the substrate or part thereof; obtaining sets of metrology data, each set including a spatial variation of a process parameter over the substrate or part thereof corresponding to a different layer of the substrate; comparing the yield distribution data and metrology data based on a similarity metric describing a spatial similarity between the yield distribution data and an individual set out of the sets of the metrology data; and determining a first similar set of metrology data out of the sets of metrology data, being the first set of metrology data in terms of processing order for the corresponding layers, which is determined to be similar to the yield distribution data.Type: GrantFiled: November 4, 2019Date of Patent: October 31, 2023Assignee: ASML NETHERLANDS B.V.Inventors: Chenxi Lin, Cyrus Emil Tabery, Hakki Ergün Cekli, Simon Philip Spencer Hastings, Boris Menchtchikov, Yi Zou, Yana Cheng, Maxime Philippe Frederic Genin, Tzu-Chao Chen, Davit Harutyunyan, Youping Zhang
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Patent number: 11754931Abstract: A method for determining a correction for an apparatus used in a process of patterning substrates, the method including: obtaining a group structure associated with a processing history and/or similarity in fingerprint of to be processed substrates; obtaining metrology data associated with a plurality of groups within the group structure, wherein the metrology data is correlated between the groups; and determining the correction for a group out of the plurality of groups by applying a model to the metrology data, the model including at least a group-specific correction component and a common correction component.Type: GrantFiled: March 18, 2020Date of Patent: September 12, 2023Assignee: ASML NETHERLANDS B.V.Inventors: Roy Werkman, David Frans Simon Deckers, Simon Philip Spencer Hastings, Jeffrey Thomas Ziebarth, Samee Ur Rehman, Davit Harutyunyan, Chenxi Lin, Yana Cheng
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Publication number: 20230273529Abstract: Generating a control output for a patterning process is described. A control input is received. The control input is for controlling the patterning process. The control input includes one or more parameters used in the patterning process. The control output is generated with a trained machine learning mod& based on the control input, The machine learning model is trained with training data generated from simulation of the patterning process and/or actual process data, The training data includes 1) a plurality of training control inputs corresponding to a plurality of operational conditions of the patterning process, where the plurality of operational conditions of the patterning process are associated with operational condition specific behavior of the patterning process over time, and 2) training control outputs generated using a physical model based on the training control inputs.Type: ApplicationFiled: June 14, 2021Publication date: August 31, 2023Applicant: ASML NETHERLANDS B.V.Inventors: Satej Subhash KHEDEKAR, Henricus Jozef CASTELIJNS, Anjan Prasad GANTAPARA, Stephen Henry BOND, Seyed Iman MOSSAVAT, Alexander YPMA, Gerald DICKER, Ewout Klaas STEINMEIER, Chaoqun GUO, Chenxi LIN, Hongwei CHEN, Zhaoze LI, Youping ZHANG, Yi ZOU, Koos VAN BERKEL, Joost Johan BOLDER, Arnaud HUBAUX, Andriy Vasyliovich HLOD, Juan Manuel GONZALEZ HUESCA, Frans Bernard AARDEN
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Patent number: 11714357Abstract: A method and associated computer program for predicting an electrical characteristic of a substrate subject to a process. The method includes determining a sensitivity of the electrical characteristic to a process characteristic, based on analysis of electrical metrology data including electrical characteristic measurements from previously processed substrates and of process metrology data including measurements of at least one parameter related to the process characteristic measured from the previously processed substrates; obtaining process metrology data related to the substrate describing the at least one parameter; and predicting the electrical characteristic of the substrate based on the sensitivity and the process metrology data.Type: GrantFiled: June 30, 2021Date of Patent: August 1, 2023Assignee: ASML NETHERLANDS B.V.Inventors: Alexander Ypma, Cyrus Emil Tabery, Simon Hendrik Celine Van Gorp, Chenxi Lin, Dag Sonntag, Hakki Ergün Cekli, Ruben Alvarez Sanchez, Shih-Chin Liu, Simon Philip Spencer Hastings, Boris Menchtchikov, Christiaan Theodoor De Ruiter, Peter Ten Berge, Michael James Lercel, Wei Duan, Pierre-Yves Jerome Yvan Guittet
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Patent number: 11443083Abstract: Methods of identifying a hot spot from a design layout or of predicting whether a pattern in a design layout is defective, using a machine learning model. An example method disclosed herein includes obtaining sets of one or more characteristics of performance of hot spots, respectively, under a plurality of process conditions, respectively, in a device manufacturing process; determining, for each of the process conditions, for each of the hot spots, based on the one or more characteristics under that process condition, whether that hot spot is defective; obtaining a characteristic of each of the process conditions; obtaining a characteristic of each of the hot spots; and training a machine learning model using a training set including the characteristic of one of the process conditions, the characteristic of one of the hot spots, and whether that hot spot is defective under that process condition.Type: GrantFiled: April 20, 2017Date of Patent: September 13, 2022Assignee: ASML Netherlands B.V.Inventors: Jing Su, Yi Zou, Chenxi Lin, Stefan Hunsche, Marinus Jochemsen, Yen-Wen Lu, Lin Lee Cheong
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Publication number: 20220277116Abstract: Methods of identifying a hot spot from a design layout or of predicting whether a pattern in a design layout is defective, using a machine learning model. An example method disclosed herein includes obtaining sets of one or more characteristics of performance of hot spots, respectively, under a plurality of process conditions, respectively, in a device manufacturing process; determining, for each of the process conditions, for each of the hot spots, based on the one or more characteristics under that process condition, whether that hot spot is defective; obtaining a characteristic of each of the process conditions; obtaining a characteristic of each of the hot spots; and training a machine learning model using a training set including the characteristic of one of the process conditions, the characteristic of one of the hot spots, and whether that hot spot is defective under that process condition.Type: ApplicationFiled: May 13, 2022Publication date: September 1, 2022Applicant: ASML NETHERLANDS B.V.Inventors: Jing SU, Yi Zou, Chenxi Lin, Stefan Hunsche, Marinus Jochemsen, Yen-Wen Lu, Lin Lee Cheong
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Publication number: 20220252988Abstract: A method for determining a correction for an apparatus used in a process of patterning substrates, the method including: obtaining a group structure associated with a processing history and/or similarity in fingerprint of to be processed substrates; obtaining metrology data associated with a plurality of groups within the group structure, wherein the metrology data is correlated between the groups; and determining the correction for a group out of the plurality of groups by applying a model to the metrology data, the model including at least a group-specific correction component and a common correction component.Type: ApplicationFiled: March 18, 2020Publication date: August 11, 2022Applicant: ASML NETHERLANDS B.V.Inventors: Roy WERKMAN, David Frans Simon DECKERS, Simon Philip Spencer HASTINGS, Jeffrey Thomas ZIEBARTH, Samee Ur REHMAN, Davit HARUTYUNYAN, Chenxi LIN, Yana CHENG
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Publication number: 20220026810Abstract: A method for determining a correction relating to a performance metric of a semiconductor manufacturing process, the method including: obtaining a set of pre-process metrology data; processing the set of pre-process metrology data by decomposing the pre-process metrology data into one or more components which: a) correlate to the performance metric; or b) are at least partially correctable by a control process which is part of the semiconductor manufacturing process; and applying a trained model to the processed set of pre-process metrology data to determine the correction for the semiconductor manufacturing process.Type: ApplicationFiled: November 14, 2019Publication date: January 27, 2022Applicant: ASML NETHERLANDS B.V.Inventors: Nicolaas Petrus Marcus BRANTJES, Matthijs COX, Boris MENCHTCHIKOV, Cyrus Emil TABERY, Youping ZHANG, Yi ZOU, Chenxi LIN, Yana CHENG, Simon Philip Spencer HASTINGS, Maxim Philippe Frederic GENIN
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Publication number: 20220011728Abstract: A method for predicting yield relating to a process of manufacturing semiconductor devices on a substrate, the method including: obtaining a trained first model which translates modeled parameters into a yield parameter, the modeled parameters including: a) a geometrical parameter associated with one or more selected from: a geometric characteristic, dimension or position of a device element manufactured by the process and b) a trained free parameter; obtaining process parameter data including data regarding a process parameter characterizing the process; converting the process parameter data into values of the geometrical parameter; and predicting the yield parameter using the trained first model and the values of the geometrical parameter.Type: ApplicationFiled: October 30, 2019Publication date: January 13, 2022Inventors: Youping ZHANG, Boris MENCHTCHIKOV, Cyrus Emil TABERY, Yi ZOU, Chenxi LIN, Yana CHENG, Simon Philip Spencer HASTINGS, Maxime Philippe Frederic GENIN
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Publication number: 20210397172Abstract: A method for analyzing a process, the method including obtaining a multi-dimensional probability density function representing an expected distribution of values for a plurality of process parameters; obtaining a performance function relating values of the process parameters to a performance metric of the process; and using the performance function to map the probability density function to a performance probability function having the process parameters as arguments.Type: ApplicationFiled: October 30, 2019Publication date: December 23, 2021Applicant: ASML NETHERLANDS B.V.Inventors: Abraham SLACHTER, Wim Tjibbo TEL, Daan Maurits SLOTBOOM, Vadim Yourievich TIMOSHKOV, Koen Wilhelmus Cornelis Adrianus VAN DER STRATEN, Boris MENCHTCHIKOV, Simon Philip Spencer HASTINGS, Cyrus Emil TABERY, Maxime Philippe Frederic GENIN, Youping ZHANG, Yi ZOU, Chenxi LIN, Yana CHENG
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Publication number: 20210389677Abstract: A method for determining a root cause affecting yield in a process for manufacturing devices on a substrate, the method including: obtaining yield distribution data including a distribution of a yield parameter across the substrate or part thereof; obtaining sets of metrology data, each set including a spatial variation of a process parameter over the substrate or part thereof corresponding to a different layer of the substrate; comparing the yield distribution data and metrology data based on a similarity metric describing a spatial similarity between the yield distribution data and an individual set out of the sets of the metrology data; and determining a first similar set of metrology data out of the sets of metrology data, being the first set of metrology data in terms of processing order for the corresponding layers, which is determined to be similar to the yield distribution data.Type: ApplicationFiled: November 4, 2019Publication date: December 16, 2021Applicant: ASML NETHERLANDS B.V.Inventors: Chenxi LIN, Cyrus Emil TABERY, Hakki Ergün CEKLI, Simon Philip Spencer HASTINGS, Boris MENCHTCHIKOV, Yi ZOU, Yana CHENG, Maxime Philippe Frederic GENIN, Tzu-Chao CHEN, Davit HARUTYUNYAN, Youping ZHANG
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Patent number: 11183434Abstract: A method where deviations of a characteristic of an image simulated by two different process models or deviations of the characteristic simulated by a process model and measured by a metrology tool, are used for various purposes such as to reduce the calibration time, improve the accuracy of the model, and improve the overall manufacturing process.Type: GrantFiled: December 13, 2017Date of Patent: November 23, 2021Assignee: ASML Netherlands B.V.Inventors: Yu Cao, Yi Zou, Chenxi Lin
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Patent number: 11181829Abstract: A method for determining a control parameter for an apparatus used in a semiconductor manufacturing process, the method including: obtaining performance data associated with a substrate subject to the semiconductor manufacturing process; obtaining die specification data including values of an expected yield of one or more dies on the substrate based on the performance data and/or a specification for the performance data; and determining the control parameter in dependence on the performance data and the die specification data. Advantageously, the efficiency and/or accuracy of processes is improved by determining how to perform the processes in dependence on dies within specification.Type: GrantFiled: July 30, 2018Date of Patent: November 23, 2021Assignee: ASML Netherlands B.V.Inventors: Cyrus Emil Tabery, Hakki Ergün Cekli, Simon Hendrik Celine Van Gorp, Chenxi Lin
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Publication number: 20210357566Abstract: A method of generating a characteristic pattern for a patterning process and training a machine learning model. The method for generating the characteristic pattern includes obtaining a trained generator model configured to generate a characteristic pattern (e.g., a hot spot pattern), and an input pattern; and generating, via simulation using the trained generator model (e.g., CNN), the characteristic pattern based on the input pattern, wherein the input pattern can be a random vector and/or a class of pattern.Type: ApplicationFiled: October 8, 2019Publication date: November 18, 2021Applicant: ASML NETHERLAND B.V.Inventors: Mark Christopher SIMMONS, Chenxi LIN, Jen-Yi WUU
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Publication number: 20210325788Abstract: A method and associated computer program for predicting an electrical characteristic of a substrate subject to a process. The method includes determining a sensitivity of the electrical characteristic to a process characteristic, based on analysis of electrical metrology data including electrical characteristic measurements from previously processed substrates and of process metrology data including measurements of at least one parameter related to the process characteristic measured from the previously processed substrates; obtaining process metrology data related to the substrate describing the at least one parameter; and predicting the electrical characteristic of the substrate based on the sensitivity and the process metrology data.Type: ApplicationFiled: June 30, 2021Publication date: October 21, 2021Applicant: ASML NETHERLANDS B.V.Inventors: Alexander YPMA, Cyrus Emil TABERY, Simon Hendrik Celine VAN GORP, Chenxi LIN, Dag SONNTAG, Hakki Ergün CEKLI, Ruben ALVAREZ SANCHEZ, Shih-Chin LIU, Simon Philip Spencer HASTINGS, Boris MENCHTCHIKOV, Christiaan Theodoor DE RUITER, Peter TEN BERGE, Michael James LERCEL, Wei DUAN, Pierre-Yves Jerome Yvan GUITTET
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Patent number: 11086229Abstract: A method and associated computer program for predicting an electrical characteristic of a substrate subject to a process. The method includes determining a sensitivity of the electrical characteristic to a process characteristic, based on analysis of electrical metrology data including electrical characteristic measurements from previously processed substrates and of process metrology data including measurements of at least one parameter related to the process characteristic measured from the previously processed substrates; obtaining process metrology data related to the substrate describing the at least one parameter; and predicting the electrical characteristic of the substrate based on the sensitivity and the process metrology data.Type: GrantFiled: March 29, 2018Date of Patent: August 10, 2021Assignee: ASML Netherlands B.V.Inventors: Alexander Ypma, Cyrus Emil Tabery, Simon Hendrik Celine Van Gorp, Chenxi Lin, Dag Sonntag, Hakki Ergün Cekli, Ruben Alvarez Sanchez, Shih-Chin Liu, Simon Philip Spencer Hastings, Boris Menchtchikov, Christiaan Theodoor De Ruiter, Peter Ten Berge, Michael James Lercel, Wei Duan, Pierre-Yves Jerome Yvan Guittet
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Patent number: D918872Type: GrantFiled: June 10, 2019Date of Patent: May 11, 2021Assignee: HUAWEI TECHNOLOGIES CO., LTD.Inventors: Chenxi Lin, Ying Zhao, SangHyun Jeong