Abstract: Methods and systems for compensating for uncertainty in illumination angle of incidence to enable accurate measurements of semiconductor structures are described herein. In one aspect, measurements are performed at one or more nominal angles of incidence, an actual angle of incidence corresponding to each measurement is estimated, and a value of a parameter of interest characterizing a measured structure is estimated based at least in part on the collected measurement data and the actual angle of incidence. In some examples, an actual angle of incidence is directly measured. In some other examples, an actual angle of incidence is estimated from measurement data collected over a range of nominal illumination angles of incidence. In some other examples, an actual angle of incidence with respect to a tilted structure is estimated from measurement data collected over a range of nominal illumination angles of incidence.

Abstract: Methods and systems for determining random variation in one or more structures on a specimen are provided. One method includes determining characteristic(s) of output generated by an output acquisition subsystem for structure(s) formed on a specimen and simulating the characteristic(s) of the output with initial parameter values for the structure(s). The method also includes determining parameter values of the structure(s) formed on the specimen as the initial parameter values that resulted in the simulated characteristic(s) that best match the determined characteristic(s). The determined parameter values are responsive to random variation in parameter(s) of the structure(s) on the specimen.

Abstract: Methods and systems for performing X-ray model based scatterometry measurements of semiconductor structures with reduced computational effort are described herein. More specifically, measured detector image data is transformed to diffraction order efficiency data. The measured diffraction order efficiency data is compared with a parameter-efficiency library including simulated diffraction order efficiency data and associated sets of specimen parameter values. One or more sets of specimen parameter values are selected as seed values for regression on the measured detector image data based on the fit between the measured and simulated diffraction order efficiency data. The seed values are provided as initial values of one or more parameters of interest for the first iteration of the regression. The seed values enable the image based regression to converge to the global minimum with a dramatically reduced number of iterations.

Abstract: A system includes a radiation source that generates radiation having at least one wavelength from 0.1 to 100 nm. One or more rotating elements change polarization of the radiation and/or relative phase between two polarizations of the radiation. A stage is configured to hold a workpiece in a path of the radiation. At least one detector receives spectral reflection and scattering radiation from the workpiece.

Abstract: Methods and systems for determining random variation in one or more structures on a specimen are provided. One method includes determining characteristic(s) of output generated by an output acquisition subsystem for structure(s) formed on a specimen and simulating the characteristic(s) of the output with initial parameter values for the structure(s). The method also includes determining parameter values of the structure(s) formed on the specimen as the initial parameter values that resulted in the simulated characteristic(s) that best match the determined characteristic(s). The determined parameter values are responsive to random variation in parameter(s) of the structure(s) on the specimen.

Abstract: Methods and systems for determining random variation in one or more structures on a specimen are provided. One method includes determining characteristic(s) of output generated by an output acquisition subsystem for structure(s) formed on a specimen and simulating the characteristic(s) of the output with initial parameter values for the structure(s). The method also includes determining parameter values of the structure(s) formed on the specimen as the initial parameter values that resulted in the simulated characteristic(s) that best match the determined characteristic(s). The determined parameter values are responsive to random variation in parameter(s) of the structure(s) on the specimen.

Abstract: An inspection system may receive first measurement data of training samples after a first process step with an in-line measurement sub-system, where the first process step is prior to fabrication of a test feature on the one or more training samples; and receive second measurement data of the test feature after a second process step, where the second process step is after fabrication of the test feature. An inspection system may determine delta metrics associated with the first and second measurement data for the test feature. An inspection system may generate a measurement model for determining metrology measurements of the test feature based on at least one of the second measurement data or the delta metrics. An inspection system may determine values of the metrology measurements for additional instances of the test feature based on at least one of the second measurement data or the delta metrics.

Abstract: Methods and systems for performing X-ray model based scatterometry measurements of semiconductor structures with reduced computational effort are described herein. More specifically, measured detector image data is transformed to diffraction order efficiency data. The measured diffraction order efficiency data is compared with a parameter-efficiency library including simulated diffraction order efficiency data and associated sets of specimen parameter values. One or more sets of specimen parameter values are selected as seed values for regression on the measured detector image data based on the fit between the measured and simulated diffraction order efficiency data. The seed values are provided as initial values of one or more parameters of interest for the first iteration of the regression. The seed values enable the image based regression to converge to the global minimum with a dramatically reduced number of iterations.

Abstract: Methods and systems for performing measurements of stacked semiconductor structures, e.g., stacked memory and logic structures, based on X-Ray transmission scatterometry measurement data are described herein. In some examples, the scattering response of logic structures is modelled directly in signal space by a mathematical expression including a relatively small number of weighted basis functions. The scattering response of the logic structures and the scattering response of the memory structures determined by an electromagnetic response model are combined, e.g., by summation or convolution. The combined modelled signals are compared to the measured signals at the detector to generate an error signal. The error signal is employed to drive a regression analysis employed to optimize parameter values characterizing the memory structures, values of the weighting coefficients of the signal space model, or both. In other examples, the scattering response of the logic structures is known, and a model is not needed.

Abstract: Optical elements that efficiently propagate x-ray radiation over a desired energy range and reject radiation outside the desired energy range are presented herein. In one aspect, one or more optical elements of an x-ray based system include an integrated optical filter including one or more material layers that absorb radiation having energy outside the desired energy band. In general, the integrated filter improves the optical performance of an x-ray based system by suppressing reflectivity within infrared (IR), visible (vis), ultraviolet (UV), extreme ultraviolet (EUV) portions of the spectrum, or any other undesired wavelength region. In a further aspect, one or more diffusion barrier layers prevent degradation of the integrated optical filter, prevent diffusion between the integrated optical filter and other material layers, or both. In some embodiments, the thickness of one or more material layers of an integrated optical filter vary over the spatial area of the filter.

Abstract: Optical elements that efficiently propagate x-ray radiation over a desired energy range and reject radiation outside the desired energy range are presented herein. In one aspect, one or more optical elements of an x-ray based system include an integrated optical filter including one or more material layers that absorb radiation having energy outside the desired energy band. In general, the integrated filter improves the optical performance of an x-ray based system by suppressing reflectivity within infrared (IR), visible (vis), ultraviolet (UV), extreme ultraviolet (EUV) portions of the spectrum, or any other undesired wavelength region. In a further aspect, one or more diffusion barrier layers prevent degradation of the integrated optical filter, prevent diffusion between the integrated optical filter and other material layers, or both. In some embodiments, the thickness of one or more material layers of an integrated optical filter vary over the spatial area of the filter.

Abstract: Methods and systems for performing model-less measurements of semiconductor structures based on scatterometry measurement data are described herein. Scatterometry measurement data is processed directly, without the use of a traditional measurement model. Measurement sensitivity is defined by the changes in detected diffraction images at one or more non-zero diffraction orders over at least two different illumination incidence angles. Discrete values of a scalar function are determined directly from measured images at each incidence angle. A continuous mathematical function is fit to the set of discrete values of the scalar function determined at each incidence angle. A value of a parameter of interest is determined based on analysis of the mathematical function. In some embodiments, the scalar function includes a weighting function, and the weighting values associated with weighting function are optimized to yield an accurate fit of the mathematical function to the scalar values.

Abstract: Methods and systems for estimating values of parameters of interest from X-ray scatterometry measurements with reduced computational effort are described herein. Values of parameters of interest are estimated by regression using a trained, machine learning (ML) based electromagnetic (EM) response model. A training data set includes sets of Design Of Experiments (DOE) values of parameters of interest and corresponding DOE values of a plurality of electromagnetic response metrics. In some examples, values of parameters of interest are determined from measured images based on regression using a sequence of trained ML based electromagnetic response models. In some examples, input values employed to train the ML based EM response model are scaled based on model output variation.

Abstract: Optical elements that efficiently propagate x-ray radiation over a desired energy range and reject radiation outside the desired energy range are presented herein. In one aspect, one or more optical elements of an x-ray based system include an integrated optical filter including one or more material layers that absorb radiation having energy outside the desired energy band. In general, the integrated filter improves the optical performance of an x-ray based system by suppressing reflectivity within infrared (IR), visible (vis), ultraviolet (UV), extreme ultraviolet (EUV) portions of the spectrum, or any other undesired wavelength region. In a further aspect, one or more diffusion barrier layers prevent degradation of the integrated optical filter, prevent diffusion between the integrated optical filter and other material layers, or both. In some embodiments, the thickness of one or more material layers of an integrated optical filter vary over the spatial area of the filter.

Abstract: Optical elements that efficiently propagate x-ray radiation over a desired energy range and reject radiation outside the desired energy range are presented herein. In one aspect, one or more optical elements of an x-ray based system include an integrated optical filter including one or more material layers that absorb radiation having energy outside the desired energy band. In general, the integrated filter improves the optical performance of an x-ray based system by suppressing reflectivity within infrared (IR), visible (vis), ultraviolet (UV), extreme ultraviolet (EUV) portions of the spectrum, or any other undesired wavelength region. In a further aspect, one or more diffusion barrier layers prevent degradation of the integrated optical filter, prevent diffusion between the integrated optical filter and other material layers, or both. In some embodiments, the thickness of one or more material layers of an integrated optical filter vary over the spatial area of the filter.

Abstract: Optical elements that efficiently propagate x-ray radiation over a desired energy range and reject radiation outside the desired energy range are presented herein. In one aspect, one or more optical elements of an x-ray based system include an integrated optical filter including one or more material layers that absorb radiation having energy outside the desired energy band. In general, the integrated filter improves the optical performance of an x-ray based system by suppressing reflectivity within infrared (IR), visible (vis), ultraviolet (UV), extreme ultraviolet (EUV) portions of the spectrum, or any other undesired wavelength region. In a further aspect, one or more diffusion barrier layers prevent degradation of the integrated optical filter, prevent diffusion between the integrated optical filter and other material layers, or both. In some embodiments, the thickness of one or more material layers of an integrated optical filter vary over the spatial area of the filter.

Abstract: Methods and systems for evaluating the geometric characteristics of patterned structures are presented. More specifically, geometric structures generated by one or multiple patterning processes are measured by two or more metrology systems in accordance with a hybrid metrology methodology. A measurement result from one metrology system is communicated to at least one other metrology systems to increase the measurement performance of the receiving system. Similarly, a measurement result from the receiving metrology system is communicated back to the sending metrology system to increase the measurement performance of the sending system. In this manner, measurement results obtained from each metrology system are improved based on measurement results received from other cooperating metrology systems. In some examples, metrology capability is expanded to measure parameters of interest that were previously unmeasurable by each metrology system operating independently.

Abstract: Methods and systems for evaluating the geometric characteristics of patterned structures are presented. More specifically, geometric structures generated by one or multiple patterning processes are measured by two or more metrology systems in accordance with a hybrid metrology methodology. A measurement result from one metrology system is communicated to at least one other metrology systems to increase the measurement performance of the receiving system. Similarly, a measurement result from the receiving metrology system is communicated back to the sending metrology system to increase the measurement performance of the sending system. In this manner, measurement results obtained from each metrology system are improved based on measurement results received from other cooperating metrology systems. In some examples, metrology capability is expanded to measure parameters of interest that were previously unmeasurable by each metrology system operating independently.