METHODS AND APPARATUS FOR CONTROLLING A LITHOGRAPHIC PROCESS

    公开(公告)号:US20220091514A1

    公开(公告)日:2022-03-24

    申请号:US17424991

    申请日:2019-12-18

    Abstract: A method of determining a control parameter for a lithographic process is disclosed, the method includes: defining a substrate model for representing a process parameter fingerprint across a substrate, the substrate model being defined as a combination of basis functions including at least one basis function suitable for representing variation of the process parameter fingerprint between substrates and/or batches of substrates; receiving measurements of the process parameter across at least one substrate; calculating substrate model parameters using the measurements and the basis functions; and determining the control parameter based on the substrate model parameters and the similarity of the at least one basis function to a process parameter fingerprint variation between substrates and/or batches of substrates.

    Calibration Method for a Lithographic Apparatus

    公开(公告)号:US20200218170A1

    公开(公告)日:2020-07-09

    申请号:US16822870

    申请日:2020-03-18

    Abstract: A first substrate 2002 has a calibration pattern applied to a first plurality of fields 2004 by a lithographic apparatus. Further substrates 2006, 2010 have calibration patterns applied to further pluralities of fields 2008, 2012. The different pluralities of fields have different sizes and/or shapes and/or positions. Calibration measurements are performed on the patterned substrates 2002, 2006, 2010 and used to obtain corrections for use in controlling the apparatus when applying product patterns to subsequent substrates. Measurement data representing the performance of the apparatus on fields of two or more different dimensions (fields 2004, 2008, 2012 in this example) is gathered together in a database 2013 and used to synthesize the information needed to calibrate the apparatus for a new size. Calibration data is also obtained for different scan and step directions.

    METHOD FOR CHARACTERIZING DISTORTIONS IN A LITHOGRAPHIC PROCESS, LITHOGRAPHIC APPARATUS, LITHOGRAPHIC CELL AND COMPUTER PROGRAM

    公开(公告)号:US20190011842A1

    公开(公告)日:2019-01-10

    申请号:US16079404

    申请日:2017-02-22

    Abstract: A method of characterizing distortions in a lithographic process, and associated apparatuses. The method includes obtaining measurement data corresponding to a plurality of measurement locations on a substrate, the measurement data comprising measurements performed on a plurality of substrates, and comprising one or more measurements performed on one or more of the substrates for each of the measurement locations. For each of the measurement locations, a first quality value representing a quality metric and a noise value representing a noise metric is determined from the measurements performed at that measurement location. A plurality of distortion parameters is determined, each distortion parameter configured to characterize a systematic distortion in the quality metric and a statistical significance of the distortion parameters from the first quality value and from the noise value is determined. Systematic distortion is parameterized from the distortion parameters determined to be statistically significant.

    METHOD FOR OBTAINING TRAINING DATA FOR TRAINING A MODEL OF A SEMICONDUCTOR MANUFACTURING PROCESS

    公开(公告)号:US20210405544A1

    公开(公告)日:2021-12-30

    申请号:US17289290

    申请日:2019-09-26

    Abstract: A method for obtaining a training data set including synthetic metrology data, the training data set being configured for training of a model relating to a manufacturing process for manufacturing an integrated circuit. The method includes obtaining behavioral property data describing a behavior of a process parameter resultant from the manufacturing process and/or a related tool or effect. Additionally, or alternatively metrology data performed on a structure formed by the manufacturing process and/or a similar manufacturing process may be obtained. Using the behavioral property data and/or metrology data, synthetic metrology data is determined, which describes the effect of variations in the manufacturing process, and/or a related tool or effect on the process parameter. The model is trained using the training data set including the synthetic metrology data.

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