Abstract: A method for generating metrology sampling scheme for a patterning process, the method including: obtaining a parameter map of a parameter of a patterning process for a substrate; decomposing the parameter map to generate a fingerprint specific to an apparatus of the patterning process and/or a combination of apparatuses of the patterning process; and based on the fingerprint, generating a metrology sampling scheme for a subsequent substrate at the apparatus of the patterning process and/or the combination of apparatuses of the patterning process, wherein the sampling scheme is configured to distribute sampling points on the subsequent substrate so as to improve a metrology sampling density.

Abstract: A method for configuring a semiconductor manufacturing process, the method including: obtaining a first value of a first parameter based on measurements associated with a first operation of a process step in the semiconductor manufacturing process and a first sampling scheme; using a recurrent neural network to determine a predicted value of the first parameter based on the first value; and using the predicted value of the first parameter in configuring a subsequent operation of the process step in the semiconductor manufacturing process.

Abstract: A method and associated computer program and apparatuses for determining a correction for at least one control parameter, the at least one control parameter for controlling a semiconductor manufacturing process so as to manufacture semiconductor devices on a substrate. The method includes: obtaining metrology data relating to the semiconductor manufacturing process or at least part thereof; obtaining associated data relating to the semiconductor manufacturing process or at least part thereof, the associated data providing information for interpreting the metrology data; and determining the correction based on the metrology data and the associated data, wherein the determining is such that the determined correction depends on a degree to which a trend and/or event in the metrology data should be corrected based on the interpretation of the metrology data.

Abstract: A method for configuring a semiconductor manufacturing process, the method comprising: obtaining a plurality of first values of a first parameter based on successive measurements associated with a first operation of a process step in the semiconductor manufacturing process; using a causal convolutional neural network to determine a predicted value of a second parameter based on the first values; and using the predicted value of the second parameter in configuring a subsequent operation of the process step in the semiconductor manufacturing process.

Abstract: A method to determine a performance indicator indicative of alignment performance of a processed substrate. The method includes obtaining measurement data including a plurality of measured position values of alignment marks on the substrate and calculating a positional deviation between each measured position value and a respective expected position value. These positional deviations are used to determine a directional derivative between the alignment marks, and the directional derivatives are used to determine at least one directional derivative performance indicator.

Abstract: A method and associated apparatuses for optimizing a sampling scheme which defines sampling locations on a bonded substrate, having undergone a wafer to wafer bonding process. The method includes determining a sampling scheme for a metrology process and optimizing the sampling scheme with respect to a singularity defined by a large overlay error and/or grid deformation at a central location on the bonded substrate to obtain a modified sampling scheme.

Abstract: A method for determining a correction to a patterning process. The method includes obtaining a plurality of qualities of the patterning process (e.g., a plurality of parameter maps, or one or more corrections) derived from metrology data and data of an apparatus used in the patterning process, selecting, by a hardware computer system, a representative quality from the plurality of qualities, and determining, by the hardware computer system, a correction to the patterning process based on the representative quality.

Abstract: A method for determining lithographic matching performance includes obtaining first monitoring data from recurrent monitoring for stability control for an available EUV scanner. For a DUV scanner, second monitoring data is similarly obtained from recurrent monitoring for stability control. The EUV first monitoring data are in a first layout. The DUV second monitoring data are in a second layout. A cross-platform overlay matching performance between the first lithographic apparatus and the second lithographic apparatus is determined based on the first monitoring data and the second monitoring data. This is done by reconstructing the first and/or second monitoring data into a common layout to allow comparison of the first and second monitoring data.

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.

Abstract: A method of optimizing an apparatus for multi-stage processing of product units such as wafers, the method includes: receiving object data representing one or more parameters measured across the product units and associated with different stages of processing of the product units; and determining fingerprints of variation of the object data across the product units, the fingerprints being associated with different respective stages of processing of the product units. The fingerprints may be determined by decomposing the object data into components using principal component analysis for each different respective stage; analyzing commonality of the fingerprints through the different stages to produce commonality results; and optimizing an apparatus for processing product units based on the commonality results.

Abstract: A method for configuring a semiconductor manufacturing process, the method including: obtaining a first value of a first parameter based on measurements associated with a first operation of a process step in the semiconductor manufacturing process and a first sampling scheme; using a recurrent neural network to determine a predicted value of the first parameter based on the first value; and using the predicted value of the first parameter in configuring a subsequent operation of the process step in the semiconductor manufacturing process.

Abstract: A method of determining a sampling control scheme and/or a processing control scheme for substrates processed by a device. The method uses a fingerprint model and an evolution model to generate the control scheme. The fingerprint model is based on fingerprint data for a processing parameter of at least one substrate processed by a device, and the evolution model represents variation of the fingerprint data over time. The fingerprint model and the evolution model are analyzed and a sampling and/or processing control scheme is generated using the analysis. The sampling control scheme provides an indication for where and when to take measurements on substrates processed by the device. The processing control scheme provides an indication for how to control the processing of the substrate. Also, there is provided a method of determining which of multiple devices contributed to a fingerprint of a processing parameter.

Abstract: A method for configuring a semiconductor manufacturing process, the method including: obtaining a first value of a first parameter based on measurements associated with a first operation of a process step in the semiconductor manufacturing process and a first sampling scheme; using a recurrent neural network to determine a predicted value of the first parameter based on the first value; and using the predicted value of the first parameter in configuring a subsequent operation of the process step in the semiconductor manufacturing process.

Abstract: A method for determining a correction to a patterning process. The method includes obtaining a plurality of qualities of the patterning process (e.g., a plurality of parameter maps, or one or more corrections) derived from metrology data and data of an apparatus used in the patterning process, selecting, by a hardware computer system, a representative quality from the plurality of qualities, and determining, by the hardware computer system, a correction to the patterning process based on the representative quality.

Abstract: A method for generating metrology sampling scheme for a patterning process, the method including: obtaining a parameter map of a parameter of a patterning process for a substrate; decomposing the parameter map to generate a fingerprint specific to an apparatus of the patterning process and/or a combination of apparatuses of the patterning process; and based on the fingerprint, generating a metrology sampling scheme for a subsequent substrate at the apparatus of the patterning process and/or the combination of apparatuses of the patterning process, wherein the sampling scheme is configured to distribute sampling points on the subsequent substrate so as to improve a metrology sampling density.

Abstract: A method of optimizing an apparatus for multi-stage processing of product units such as wafers, the method includes: receiving object data representing one or more parameters measured across the product units and associated with different stages of processing of the product units; and determining fingerprints of variation of the object data across the product units, the fingerprints being associated with different respective stages of processing of the product units. The fingerprints may be determined by decomposing the object data into components using principal component analysis for each different respective stage; analyzing commonality of the fingerprints through the different stages to produce commonality results; and optimizing an apparatus for processing product units based on the commonality results.

Abstract: Disclosed is a method and associated inspection apparatus for detecting variations on a surface of a substrate. The method comprises providing patterned inspection radiation to a surface of a substrate. The inspection radiation is patterned such that an amplitude of a corresponding enhanced field is modulated in a manner corresponding to the patterned inspection radiation. The scattered radiation resultant from interaction between the enhanced field and the substrate surface is received and variations on the surface of the substrate are detected based on the interaction between the enhanced field and the substrate surface. Also disclosed is a method of detecting any changes to at least one characteristic of received radiation, the said changes being induced by the generation of a surface plasmon at said surface of the optical element.

Abstract: An optical system delivers illuminating radiation and collects radiation after interaction with a target structure on a substrate. A measurement intensity profile is used to calculate a measurement of the property of the structure. The optical system may include a solid immersion lens. In a method, the optical system is controlled to obtain a first intensity profile using a first illumination profile and a second intensity profile using a second illumination profile. The profiles are used to derive a correction for mitigating the effect of, e.g., ghost reflections. Using, e.g., half-moon illumination profiles in different orientations, the method can measure ghost reflections even where a solid immersion lens would cause total internal reflection. The optical system may include a contaminant detection system to control a movement based on received scattered detection radiation. The optical system may include an optical component having a dielectric coating to enhance evanescent wave interaction.