Abstract: Methods and systems for combining information present in measured images of semiconductor wafers with additional measurements of particular structures within the measured images are presented herein. In one aspect, an image-based signal response metrology (SRM) model is trained based on measured images and corresponding reference measurements of particular structures within each image. The trained, image-based SRM model is then used to calculate values of one or more parameters of interest directly from measured image data collected from other wafers. In another aspect, a measurement signal synthesis model is trained based on measured images and corresponding measurement signals generated by measurements of particular structures within each image by a non-imaging measurement technique.

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: 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 single patterned target and a multiple patterned target are measured, the collected data fit to a combined measurement model, and the value of a structural parameter indicative of a geometric error induced by the multiple patterning process is determined based on the fit. In some other examples, light having a diffraction order different from zero is collected and analyzed to determine the value of a structural parameter that is indicative of a geometric error induced by a multiple patterning process. In some embodiments, a single diffraction order different from zero is collected. In some examples, a metrology target is designed to enhance light diffracted at an order different from zero.

Abstract: Disclosed are apparatus and methods for determining a structure or process parameter value of a target of interest on a semiconductor wafer. A plurality of collection patterns are defined for a spatial light beam controller positioned at a pupil image plane of a metrology tool. For each collection pattern, a signal is collected from a sensor of the metrology tool, and each collected signal represents a combination of a plurality of signals that the spatial light beam controller samples, using each collection pattern, from a pupil image of the target of interest. The collection patterns are selected so that the pupil image is reconstructable based on the collection patterns and their corresponding collection signals. The collected signal for each of the collection patterns is analyzed to determine a structure or process parameter value for the target of interest.

Abstract: Methods and systems for monitoring parameters characterizing a set of hot spot structures fabricated at different locations on a semiconductor wafer are presented herein. The hot spot structures are device structures that exhibit sensitivity to process variations and give rise to limitations on permissible process variations that must be enforced to prevent device failures and low yield. A trained hot spot measurement model is employed to receive measurement data generated by one or more metrology systems at one or more metrology targets and directly determine values of one or more hot spot parameters. The hot spot measurement model is trained to establish a functional relationship between one or more characteristics of a hot spot structure under consideration and corresponding measurement data associated with measurements of at least one metrology target on the same wafer. A fabrication process parameter is adjusted based on the value of a measured hot spot parameter.

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 single patterned target and a multiple patterned target are measured, the collected data fit to a combined measurement model, and the value of a structural parameter indicative of a geometric error induced by the multiple patterning process is determined based on the fit. In some other examples, light having a diffraction order different from zero is collected and analyzed to determine the value of a structural parameter that is indicative of a geometric error induced by a multiple patterning process. In some embodiments, a single diffraction order different from zero is collected. In some examples, a metrology target is designed to enhance light diffracted at an order different from zero.

Abstract: Methods and systems for building and using a parameter isolation model to isolate measurement signal information associated with a parameter of interest from measurement signal information associated with incidental model parameters are presented herein. The parameter isolation model is trained by mapping measurement signals associated with a first set of instances of a metrology target having known values of a plurality of incidental model parameters and known values of a parameter of interest to measurement signals associated with a second set of instances of the metrology target having nominal values of the plurality of incidental model parameters and the known values of the parameter of interest. The trained parameter isolation model receives raw measurement signals and isolates measurement signal information associated with a specific parameter of interest for model-based parameter estimation.

Abstract: Disclosed are apparatus and methods for determining optimal focus for a photolithography system. A plurality of optical signals are acquired from a particular target located in a plurality of fields on a semiconductor wafer, and the fields were formed using different process parameters, including different focus values. A feature is extracted from the optical signals related to changes in focus. A curve is fitted to the extracted feature of the optical signals as a function of focus. An extreme point in the curve is determined and reported as an optimal focus for use in the photolithography system.

Abstract: Disclosed are apparatus and methods for determining optimal focus for a photolithography system. A plurality of optical signals are acquired from a particular target located in a plurality of fields on a semiconductor wafer, and the fields were formed using different process parameters, including different focus values. A feature is extracted from the optical signals related to changes in focus. A symmetric curve is fitted to the extracted feature of the optical signals as a function of focus. An extreme point in the symmetric curve is determined and reported as an optimal focus for use in the photolithography system.

Abstract: A spectroscopic beam profile metrology system simultaneously detects measurement signals over a large wavelength range and a large range of angles of incidence (AOI). In one aspect, a multiple wavelength illumination beam is reshaped to a narrow line shaped beam of light before projection onto a specimen by a high numerical aperture objective. After interaction with the specimen, the collected light is passes through a wavelength dispersive element that projects the range of AOIs along one direction and wavelength components along another direction of a two-dimensional detector. Thus, the measurement signals detected at each pixel of the detector each represent a scatterometry signal for a particular AOI and a particular wavelength. In another aspect, a hyperspectral detector is employed to simultaneously detect measurement signals over a large wavelength range, range of AOIs, and range of azimuth angles.

Abstract: A system, method and computer program product are provided for combining raw data from multiple metrology tools. Reference values are obtained for at least one parameter of a training component. Signals are collected for the at least one parameter of the training component, utilizing a first metrology tool and a different second metrology tool. Further, at least a portion the signals are transformed into a set of signals, and for each of the at least one parameter of the training component, a corresponding relationship between the set of signals and the reference values is determined and a corresponding training model is created therefrom. Signals from a target component are collected utilizing at least the first metrology tool and the second metrology tool, and each created training model is applied to the signals collected from the target component to measure parametric values for the target component.

Abstract: Methods and systems for measuring overlay error between structures formed on a substrate by successive lithographic processes are presented herein. Two overlay targets, each having programmed offsets in opposite directions are employed to perform an overlay measurement. Overlay error is measured based on zero order scatterometry signals and scatterometry data is collected from each target at two different azimuth angles. In addition, methods and systems for creating an image-based measurement model based on measured, image-based training data are presented. The trained, image-based measurement model is then used to calculate values of one or more parameters of interest directly from measured image data collected from other wafers. The methods and systems for image based measurement described herein are applicable to both metrology and inspection applications.

Abstract: Methods and systems for measuring overlay error between structures formed on a substrate by successive lithographic processes are presented herein. Two overlay targets, each having programmed offsets in opposite directions are employed to perform an overlay measurement. Overlay error is measured based on zero order scatterometry signals and scatterometry data is collected from each target at two different azimuth angles. In addition, methods and systems for creating an image-based measurement model based on measured, image-based training data are presented. The trained, image-based measurement model is then used to calculate values of one or more parameters of interest directly from measured image data collected from other wafers. The methods and systems for image based measurement described herein are applicable to both metrology and inspection applications.

Abstract: Methods and systems for measuring metrology targets smaller than the illumination spot size employed to perform the measurement are described herein. Collected measurement signals contaminated with information from structures surrounding the target area are reconstructed to eliminate the contamination. In some examples, measurement signals associated one or more small targets and one or more large targets located in close proximity to one another are used to train a signal reconstruction model. The model is subsequently used to reconstruct measurement signals from other small targets. In some other examples, multiple measurements of a small target at different locations within the target are de-convolved to estimate target area intensity. Reconstructed measurement signals are determined by a convolution of the illumination spot profile and the target area intensity. In a further aspect, the reconstructed signals are used to estimate values of parameters of interest associated with the measured structures.

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.

Abstract: Methods and systems for evaluating the capability of a measurement system to track measurement parameters through a given process window are presented herein. Performance evaluations include random perturbations, systematic perturbations, or both to effectively characterize the impact of model errors, metrology system imperfections, and calibration errors, among others. In some examples, metrology target parameters are predetermined as part of a Design of Experiments (DOE). Estimated values of the metrology target parameters are compared to the known DOE parameter values to determine the tracking capability of the particular measurement. In some examples, the measurement model is parameterized by principal components to reduce the number of degrees of freedom of the measurement model. In addition, exemplary methods and systems for optimizing the measurement capability of semiconductor metrology systems for metrology applications subject to process variations are presented.

Abstract: Methods and systems for estimating values of parameters of interest of actual device structures based on optical measurements of nearby metrology targets are presented herein. High throughput, inline metrology techniques are employed to measure metrology targets located near actual device structures. Measurement data collected from the metrology targets is provided to a trained signal response metrology (SRM) model. The trained SRM model estimates the value of one or more parameters of interest of the actual device structure based on the measurements of the metrology target. The SRM model is trained to establish a functional relationship between actual device parameters measured by a reference metrology system and corresponding optical measurements of at least one nearby metrology target. In a further aspect, the trained SRM is employed to determine corrections of process parameters to bring measured device parameter values within specification.

Abstract: In one embodiment, apparatus and methods for determining a parameter of a target are disclosed. A target having an imaging structure and a scatterometry structure is provided. An image of the imaging structure is obtained with an imaging channel of a metrology tool. A scatterometry signal is also obtained from the scatterometry structure with a scatterometry channel of the metrology tool. At least one parameter, such as overlay error, of the target is determined based on both the image and the scatterometry signal.

Abstract: Methods and systems for creating a measurement model based only on measured training data are presented. The trained measurement model is then used to calculate overlay values directly from measured scatterometry data. The measurement models receive scatterometry signals directly as input and provide overlay values as output. In some embodiments, overlay error is determined from measurements of design rule structures. In some other embodiments, overlay error is determined from measurements of specialized target structures. In a further aspect, the measurement model is trained and employed to measure additional parameters of interest, in addition to overlay, based on the same or different metrology targets. In some embodiments, measurement data from multiple targets, measurement data collected by multiple metrologies, or both, is used for model building, training, and measurement. In some embodiments, an optimization algorithm automates the measurement model building and training process.

Abstract: Methods and systems for creating an image-based measurement model based only on measured, image-based training data are presented. The trained, image-based measurement model is then used to calculate values of one or more parameters of interest directly from measured image data collected from other wafers. The image-based measurement models receive image data directly as input and provide values of parameters of interest as output. In some embodiments, the image-based measurement model enables the direct measurement of overlay error. In some embodiments, overlay error is determined from images of on-device structures. In some other embodiments, overlay error is determined from images of specialized target structures. In some embodiments, image data from multiple targets, image data collected by multiple metrologies, or both, is used for model building, training, and measurement. In some embodiments, an optimization algorithm automates the image-based measurement model building and training process.