Abstract: The present subject matter at least describes a method and a system (300, 1200) of performing speech-recognition in an electronic device having an embedded speech recognizer. The method comprises receiving an input-audio comprising speech at a device. In real-time, at-least one speech-recognition module is selected within at least one of the device and a server for recognition of at least a portion of the received speech based on a criteria defined in terms of a) past-performance of speech-recognition modules within the device and server; b) an orator of speech; and c) a quality of service associated with at least one of the device and a networking environment thereof. Based upon the selection of the server, output of the selected speech-recognition modules within the device are selected for processing by corresponding speech-recognition modules of the server. An uttered-speech is determined within the input-audio based on output of the selected speech-recognition modules of the device or the server.

Abstract: Provided herein are sunscreen formulations containing a metal oxide sunscreen, squalane, and an antioxidant. The sunscreen formulations provided have increased SPF per unit mass of the metal oxide compared to sunscreen formulations that contain metal oxide without the addition of squalane and antioxidant. Also provided are methods of preventing UV damages to skin involving the application of the sunscreen formulation.

Abstract: Provided herein are sunscreen formulations containing a metal oxide sunscreen, squalane, and an antioxidant. The sunscreen formulations provided have increased SPF per unit mass of the metal oxide compared to sunscreen formulations that contain metal oxide without the addition of squalane and antioxidant. Also provided are methods of preventing UV damages to skin involving the application of the sunscreen formulation.

Abstract: The present subject matter at least describes a method and a system (300, 1200) of performing speech-recognition in an electronic device having an embedded speech recognizer. The method comprises receiving an input-audio comprising speech at a device. In real-time, at-least one speech-recognition module is selected within at least one of the device and a server for recognition of at least a portion of the received speech based on a criteria defined in terms of a) past-performance of speech-recognition modules within the device and server; b) an orator of speech; and c) a quality of service associated with at least one of the device and a networking environment thereof. Based upon the selection of the server, output of the selected speech-recognition modules within the device are selected for processing by corresponding speech-recognition modules of the server. An uttered-speech is determined within the input-audio based on output of the selected speech-recognition modules of the device or the server.

Abstract: A method for correcting a lithographic pattern includes selecting, by a processor, first stage input factors for utilization with a first computer-implemented model. The processor measures pattern data from existing measured dimensions of a semiconductor to obtain values for the first stage input factors and the first model against the measured pattern data. The processor applies the calibrated first model to predict printed dimensions and the printed dimensions from applying the calibrated first model comprise residuals. The processor establishes, based on the residuals, second stage input factors for a second model and calibrates the second model against the measured pattern data to predict deviations of the printed dimensions from the printed dimensions from the first stage input factors by utilizing the second stage input factors. The method produces predicted printed dimensions of a lithographic pattern by using the second model to revise the printed dimensions of the first model.

Abstract: A method for correcting a lithographic pattern includes selecting, by a processor, first stage input factors for utilization with a first computer-implemented model. The processor measures pattern data from existing measured dimensions of a semiconductor to obtain values for the first stage input factors and the first model against the measured pattern data. The processor applies the calibrated first model to predict printed dimensions and the printed dimensions from applying the calibrated first model comprise residuals. The processor establishes, based on the residuals, second stage input factors for a second model and calibrates the second model against the measured pattern data to predict deviations of the printed dimensions from the printed dimensions from the first stage input factors by utilizing the second stage input factors. The method produces predicted printed dimensions of a lithographic pattern by using the second model to revise the printed dimensions of the first model.

Abstract: A method of mask correction where two independent process models are analyzed and co-optimized simultaneously. In the method, a first lithographic process model simulation is run on a computer system that results in generating a first mask size in a first process window. Simultaneously, a second hard mask open etch process model simulation is run resulting in generating a second mask size in a second process window. Each first lithographic process model and second hard mask open etch process model simulations are analyzed in a single iterative loop and a common process window (PW) optimized between lithography and etch is obtained such that said first mask size and second mask size are centered between said common PW. Further, an etch model form is generated that accounts for differences in an etched pattern due to variation in three-dimensional photoresist profile, the model form including both optical and density terms that directly relate to an optical image.

Abstract: A method of mask correction where two independent process models are analyzed and co-optimized simultaneously. In the method, a first lithographic process model simulation is run on a computer system that results in generating a first mask size in a first process window. Simultaneously, a second hard mask open etch process model simulation is run resulting in generating a second mask size in a second process window. Each first lithographic process model and second hard mask open etch process model simulations are analyzed in a single iterative loop and a common process window (PW) optimized between lithography and etch is obtained such that said first mask size and second mask size are centered between said common PW. Further, an etch model form is generated that accounts for differences in an etched pattern due to variation in three-dimensional photoresist profile, the model form including both optical and density terms that directly relate to an optical image.

Abstract: In an approach for predicting a process fail limit for a semiconductor manufacturing process, a computer determines a potential working process condition for each of a plurality of process parameters varied in forming a test wafer feature. The computer determines a process sigma value for each of the plurality of process parameters in forming the test wafer feature and a measurement sigma value. The computer evaluates a set of measurements of the test wafer feature compared to an acceptable wafer feature dimension, where each measurement of the set of measurements is a pass or fail as compared to the acceptable wafer feature dimension. The computer determines whether one or more fails are evaluated compared to the acceptable wafer feature dimension. The computer produces a predicted process fail limit based, at least in part, on the evaluation of fails, the measurement sigma value, and a desired target sigma value.

Abstract: In an approach for predicting a process fail limit for a semiconductor manufacturing process, a computer determines a potential working process condition for each of a plurality of process parameters varied in forming a test wafer feature. The computer determines a process sigma value for each of the plurality of process parameters in forming the test wafer feature and a measurement sigma value. The computer evaluates a set of measurements of the test wafer feature compared to an acceptable wafer feature dimension, where each measurement of the set of measurements is a pass or fail as compared to the acceptable wafer feature dimension. The computer determines whether one or more fails are evaluated compared to the acceptable wafer feature dimension. The computer produces a predicted process fail limit based, at least in part, on the evaluation of fails, the measurement sigma value, and a desired target sigma value.

Abstract: Methods, program products, and systems for improving optical proximity correction (OPC) calibration, and automatically determining a minimal number of clips, are disclosed. The method can include using a computing device to perform actions including: calculating a total relevancy score for a projected sample plan including a candidate clip, and wherein the relevancy score is derived from at least one relevancy criterion and a relevancy weight; calculating a relevancy score for the candidate clip, the relevancy score for the candidate clip being a contribution from the candidate clip to the total relevancy score; and adding the candidate clip to a sample plan for the IC layout and removing the candidate clip from the plurality of clips in response a difference in relevancy score between the projected sample plan and one or more previous sample plans substantially fitting a non-linear relevancy score function.

Abstract: Methods, program products, and systems for improving optical proximity correction (OPC) calibration, and automatically determining a minimal number of clips, are disclosed. The method can include using a computing device to perform actions including: calculating a total relevancy score for a projected sample plan including a candidate clip, and wherein the relevancy score is derived from at least one relevancy criterion and a relevancy weight; calculating a relevancy score for the candidate clip, the relevancy score for the candidate clip being a contribution from the candidate clip to the total relevancy score; and adding the candidate clip to a sample plan for the IC layout and removing the candidate clip from the plurality of clips in response a difference in relevancy score between the projected sample plan and one or more previous sample plans substantially fitting a non-linear relevancy score function.

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: Printing risks for sub-lithographic assist features (SRAFs) can be predicted and minimized by employing an SRAF printing model, which is calibrated at a different image plane than an image plane at which a main feature model for predicting shapes of printed images of main features is calibrated. The optical model parameters of the main feature model and the SRAF printing model are calibrated separately such that the main feature model predicts the bottom CD and the SRAF printing model predicts the printing of SRAF features in a photoresist. Optionally, different degrees of printing risk can be assigned for different SRAF configurations.

Abstract: A method of training an Optical Proximity Correction (OPC) model comprises symmetrizing a complex design to be a test pattern having orthogonal symmetry. Symmetrizing may comprise establishing a axis of symmetry passing through the design, thereby dividing the design into two portions; deleting one of the two portions; and mirror-imaging the other of the two portions about the axis of symmetry. The design may be centered.

Abstract: A method of training an Optical Proximity Correction (OPC) model comprises symmetrizing a complex design to be a test pattern having orthogonal symmetry. Symmetrizing may comprise establishing a axis of symmetry passing through the design, thereby dividing the design into two portions; deleting one of the two portions; and mirror-imaging the other of the two portions about the axis of symmetry. The design may be centered.