Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Methods and systems for estimating a value of a quality metric indicative of one or more performance characteristics of a semiconductor measurement are presented herein. The value of the quality metric is normalized to ensure applicability across a broad range of measurement scenarios. In some embodiments, a value of a quality metric is determined for each measurement sample during measurement inference. In some embodiments, a trained quality metric model is employed to determine the uncertainty of defect classification. In some embodiments, a trained quality metric model is employed to determine the uncertainty of estimated parameters of interest, such as geometric, dispersion, process, and electrical parameters. In some examples, a quality metric is employed as a filter to detect measurement outliers. In some other examples, a quality metric is employed as a trigger to adjust a semiconductor process.

Abstract: Methods and systems for training and implementing metrology recipes based on performance metrics employed to quantitatively characterize the measurement performance of a metrology system in a particular measurement application. Performance metrics are employed to regularize the optimization process employed during measurement model training, model-based regression, or both. For example, the known distributions associated with important measurement performance metrics such as measurement precision, wafer mean, etc., are specifically employed to regularize the optimization that drives measurement model training. In a further aspect, a trained measurement model is employed to estimate values of parameters of interest based on measurements of structures having unknown values of one or more parameters of interest. In a further aspect, trained measurement model performance is validated with test data using error budget analysis.

Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Methods and systems for estimating a value of a quality metric indicative of one or more performance characteristics of a semiconductor measurement are presented herein. The value of the quality metric is normalized to ensure applicability across a broad range of measurement scenarios. In some embodiments, a value of a quality metric is determined for each measurement sample during measurement inference. In some embodiments, a trained quality metric model is employed to determine the uncertainty of defect classification. In some embodiments, a trained quality metric model is employed to determine the uncertainty of estimated parameters of interest, such as geometric, dispersion, process, and electrical parameters. In some examples, a quality metric is employed as a filter to detect measurement outliers. In some other examples, a quality metric is employed as a trigger to adjust a semiconductor process.

Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Methods and systems for training and implementing metrology recipes based on performance metrics employed to quantitatively characterize the measurement performance of a metrology system in a particular measurement application. Performance metrics are employed to regularize the optimization process employed during measurement model training, model-based regression, or both. For example, the known distributions associated with important measurement performance metrics such as measurement precision, wafer mean, etc., are specifically employed to regularize the optimization that drives measurement model training. In a further aspect, a trained measurement model is employed to estimate values of parameters of interest based on measurements of structures having unknown values of one or more parameters of interest. In a further aspect, trained measurement model performance is validated with test data using error budget analysis.

Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Methods and systems for estimating values of parameters of interest based on repeated measurements of a wafer during a process interval are presented herein. In one aspect, one or more optical metrology subsystems are integrated with a process tool, such as an etch tool or a deposition tool. Values of one or more parameters of interest measured while the wafer is being processed are used to control the process itself. The measurements are performed quickly and with sufficient accuracy to enable yield improvement of a semiconductor fabrication process flow. In one aspect, values of one or more parameters of interest are estimated based on spectral measurements of wafers under process using a trained signal response metrology (SRM) measurement model. In another aspect, a trained signal decontamination model is employed to generate decontaminated optical spectra from measured optical spectra while the wafer is being processed.

Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Various methods and systems for designing a restored smile are provided. One method includes receiving scan data of a patient's teeth, developing a digital model of the patient's teeth via a computing device, where the model represents the patient's teeth based upon the scan data, creating a dental treatment plan to restore one or more teeth from an initial condition to a successive condition, and wherein a final condition of the one or more is based on the one or more teeth having at least one planned additional restorative tooth structure provided therewith.

Abstract: Methods and systems for solving measurement models of complex device structures with reduced computational effort are presented. In some embodiments, a measurement signal transformation model is employed to compute transformed measurement signals from coarse measurement signals. The transformed measurement signals more closely approximate a set of measured signals than the coarse measurement signals. However, the coarse set of measured signals are computed with less computational effort than would be required to directly compute measurement signals that closely approximate the set of measured signals. In other embodiments, a measurement signal transformation model is employed to compute transformed measurement signals from actual measured signals. The transformed measurement signals more closely approximate the coarse measurement signals than the actual measured signals.

Abstract: A system, method and computer program product are provided for calibrating metrology tools. One or more design-of-experiments wafers is received for calibrating a metrology tool. A set of signals is collected by measuring the one or more wafers utilizing the metrology tool. A first transformation is determined to convert the set of signals to components, and a second transformation is determined to convert a set of reference signals to reference components. The set of reference signals is collected by measuring the one or more wafers utilizing a well-calibrated reference tool. A model is trained based on the reference components that maps the components to converted components, and the model, first transformation, and second transformation are stored in a memory associated with the metrology tool.

Abstract: A lithography system includes an illumination source and a set of projection optics. The illumination source directs a beam of illumination from an off-axis illumination pole to a pattern mask. The pattern mask includes a set of pattern elements to generate a set of diffracted beams including illumination from the illumination pole. At least two diffracted beams of the set of diffracted beams received by the set of projection optics are asymmetrically distributed in a pupil plane of the set of projection optics. The at least two diffracted beams of the set of diffracted beams are asymmetrically incident on the sample to form a set of fabricated elements corresponding to an image of the set of pattern elements. The set of fabricated elements on the sample includes one or more indicators of a location of the sample along an optical axis of the set of projection optics.

Abstract: Methods and systems for evaluating the performance of multiple patterning processes are presented. Patterned structures are measured and one or more parameter values characterizing geometric errors induced by the multiple patterning process are determined. In some examples, a primary, multiple patterned target is measured and a value of a parameter of interest is directly determined from the measured data by a Signal Response Metrology (SRM) measurement model. In some other examples, a primary, multiple patterned target and an assist target are measured and a value of a parameter of interest is directly determined from the measured data by a Signal Response Metrology (SRM) measurement model. In some other examples, a primary, multiple patterned target is measured at different process steps and a value of a parameter of interest is directly determined from the measured data by a Signal Response Metrology (SRM) measurement model.