Abstract: A system and method for recognition of images may include the use of alignment markers. The image recognized may be a pattern from an array, a character, a number, a shape, and/or irregular shapes. The pattern may be formed by elements in an array such as an identification marking and/or a sensor array. More particularly, the system and method relate to discriminating between images by accounting for the orientation of the image. The size and/or location of alignment markers may provide information about the orientation of an image. Information about the orientation of an image may reduce false recognitions. The system and method of image recognition may be used with identification markings, biosensors, micro-fluidic arrays, and/or optical character recognition systems.

Abstract: Optical simulation can be performed employing a calibrated printing model, in which a unique phase transmission value is assigned to each type of sub-resolution assist features (SRAFs). The printing model can be calibrated employing a mask including multiple test patterns. Each test pattern is defined by a combination of a main feature, at least one SRAF applied to the main feature, and the geometrical relationship between the main feature and the at least one SRAF. Generation of the phase transmission values for each SRAF can be performed by fitting a printing model employing phase shift values and/or transmission values for SRAFs with measured printed feature dimensions as a function of defocus and/or with measured SRAF printing behavior on a printed photoresist layer. A properly calibrated printing model can predict the printed feature dimensions, shift in the best focus, and presence or absence of printed SRAFs.

Abstract: Optical simulation can be performed employing a calibrated printing model, in which a unique phase transmission value is assigned to each type of sub-resolution assist features (SRAFs). The printing model can be calibrated employing a mask including multiple test patterns. Each test pattern is defined by a combination of a main feature, at least one SRAF applied to the main feature, and the geometrical relationship between the main feature and the at least one SRAF. Generation of the phase transmission values for each SRAF can be performed by fitting a printing model employing phase shift values and/or transmission values for SRAFs with measured printed feature dimensions as a function of defocus and/or with measured SRAF printing behavior on a printed photoresist layer. A properly calibrated printing model can predict the printed feature dimensions, shift in the best focus, and presence or absence of printed SRAFs.

Abstract: A system and method for recognition of images may include the use of alignment markers. The image recognized may be a pattern from an array, a character, a number, a shape, and/or irregular shapes. The pattern may be formed by elements in an array such as an identification marking and/or a sensor array. More particularly, the system and method relate to discriminating between images by accounting for the orientation of the image. The size and/or location of alignment markers may provide information about the orientation of an image. Information about the orientation of an image may reduce false recognitions. The system and method of image recognition may be used with identification markings, biosensors, micro-fluidic arrays, and/or optical character recognition systems.

Abstract: Embodiments of the present invention provide a method of placing printing assist features in a mask layout. The method includes providing a design layout having one or more designed features; generating a set of parameters, the set of parameters being associated with one or more printing assist features (PrAFs); adding the one or more PrAFs of the set of parameters to the design layout to produce a modified design layout; performing simulation of the one or more PrAFs and the one or more designed features on the modified design layout; verifying whether the one or more PrAFs are removable based on results of the simulation; and creating a set of PrAF placement rules based on the set of parameters, if the one or more PrAFs are verified as removable. The set of PrAF placement rules may be used in creating a final set of PrAF features to be used for creating the mask layout.

Abstract: Integrated circuits and methods of manufacture and design thereof are disclosed. For example, a method of manufacturing includes depositing a gate material over a semiconductor substrate, and depositing a first resist layer over the gate material. A first mask is used to pattern the first resist layer to form first and second resist features. The first resist features include pattern for gate lines of the semiconductor device and the second resist features include printing assist features. A second mask is used to form a resist template; the second mask removes the second resist features.

Abstract: A system and method for recognition of images may include the use of alignment markers. The image recognized may be a pattern from an array, a character, a number, a shape, and/or irregular shapes. The pattern may be formed by elements in an array such as an identification marking and/or a sensor array. More particularly, the system and method relate to discriminating between images by accounting for the orientation of the image. The size and/or location of alignment markers may provide information about the orientation of an image. Information about the orientation of an image may reduce false recognitions. The system and method of image recognition may be used with identification markings, biosensors, micro-fluidic arrays, and/or optical character recognition systems.

Abstract: A system and method for recognition of images may include the use of alignment markers. The image recognized may be a pattern from an array, a character, a number, a shape, and/or irregular shapes. The pattern may be formed by elements in an array such as an identification marking and/or a sensor array. More particularly, the system and method relate to discriminating between images by accounting for the orientation of the image. The size and/or location of alignment markers may provide information about the orientation of an image. Information about the orientation of an image may reduce false recognitions. The system and method of image recognition may be used with identification markings, biosensors, micro-fluidic arrays, and/or optical character recognition systems.

Abstract: Embodiments of the present invention provide a method for performing lumped-process model calibration. The method includes creating a plurality of sub-process models for a set of sub-processes; creating a lumped-process-model incorporating said set of sub-processes; calculating a first set of output patterns from a set of test patterns by using said plurality of sub-process models; calculating a second set of output patterns from said set of test patterns by using said lumped-process-model; and adjusting process parameters used in said lumped-process-model to calculate said second set of output patterns to match said first set of output patterns. A computer system for performing the lumped-process model calibration is also provided.

Abstract: Embodiments of the present invention provide a method of placing printing assist features in a mask layout. The method includes providing a design layout having one or more designed features; generating a set of parameters, the set of parameters being associated with one or more printing assist features (PrAFs); adding the one or more PrAFs of the set of parameters to the design layout to produce a modified design layout; performing simulation of the one or more PrAFs and the one or more designed features on the modified design layout; verifying whether the one or more PrAFs are removable based on results of the simulation; and creating a set of PrAF placement rules based on the set of parameters, if the one or more PrAFs are verified as removable. The set of PrAF placement rules may be used in creating a final set of PrAF features to be used for creating the mask layout.

Abstract: A system and method for recognition of images may include the use of alignment markers. The image recognized may be a pattern from an array, a character, a number, a shape, and/or irregular shapes. The pattern may be formed by elements in an array such as an identification marking and/or a sensor array. More particularly, the system and method relate to discriminating between images by accounting for the orientation of the image. The size and/or location of alignment markers may provide information about the orientation of an image. Information about the orientation of an image may reduce false recognitions. The system and method of image recognition may be used with identification markings, biosensors, micro-fluidic arrays, and/or optical character recognition systems.

Abstract: A system and method for recognition of images may include the use of alignment markers. The image recognized may be a pattern from an array, a character, a number, a shape, and/or irregular shapes. The pattern may be formed by elements in an array such as an identification marking and/or a sensor array. More particularly, the system and method relate to discriminating between images by accounting for the orientation of the image. The size and/or location of alignment markers may provide information about the orientation of an image. Information about the orientation of an image may reduce false recognitions. The system and method of image recognition may be used with identification markings, biosensors, micro-fluidic arrays, and/or optical character recognition systems.

Abstract: Embodiments of the present invention provide a method for performing lumped-process model calibration. The method includes creating a plurality of sub-process models for a set of sub-processes; creating a lumped-process-model incorporating said set of sub-processes; calculating a first set of output patterns from a set of test patterns by using said plurality of sub-process models; calculating a second set of output patterns from said set of test patterns by using said lumped-process-model; and adjusting process parameters used in said lumped-process-model to calculate said second set of output patterns to match said first set of output patterns. A computer system for performing the lumped-process model calibration is also provided.

Abstract: Integrated circuits and methods of manufacture and design thereof are disclosed. For example, a method of manufacturing includes depositing a gate material over a semiconductor substrate, and depositing a first resist layer over the gate material. A first mask is used to pattern the first resist layer to form first and second resist features. The first resist features include pattern for gate lines of the semiconductor device and the second resist features include printing assist features. A second mask is used to form a resist template; the second mask removes the second resist features.

Abstract: A system and method for recognition of images may include the use of alignment markers. The image recognized may be a pattern from an array, a character, a number, a shape, and/or irregular shapes. The pattern may be formed by elements in an array such as an identification marking and/or a sensor array. More particularly, the system and method relate to discriminating between images by accounting for the orientation of the image. The size and/or location of alignment markers may provide information about the orientation of an image. Information about the orientation of an image may reduce false recognitions. The system and method of image recognition may be used with identification markings, biosensors, micro-fluidic arrays, and/or optical character recognition systems.

Abstract: A system and method for recognition of images may include the use of alignment markers. The image recognized may be a pattern from an array, a character, a number, a shape, and/or irregular shapes. The pattern may be formed by elements in an array such as an identification marking and/or a sensor array. More particularly, the system and method relate to discriminating between images by accounting for the orientation of the image. The size and/or location of alignment markers may provide information about the orientation of an image. Information about the orientation of an image may reduce false recognitions. The system and method of image recognition may be used with identification markings, biosensors, micro-fluidic arrays, and/or optical character recognition systems.