A method for determining a vertical position of a structure on a substrate with respect to a nominal vertical position is disclosed. The method comprises obtaining complex field data relating to scattered radiation from said structure, for a plurality of different wavelengths, determining variation in a phase parameter with wavelength from said complex field data; and determining said vertical position with respect to a nominal vertical position from the determined variation in phase with wavelength.

The present disclosure provides a method and a system for obtaining OCD. The system inputs a plurality of first spectra associated with a first semiconductor structure into the first optical transformation model to output a plurality of first structure parameters; update the first structure parameters based on at least one physical parameter associated with the first semiconductor structure; establish a second optical transformation model according to the updated first structure parameters and the corresponding first spectra; and store the second optical transformation model for later OCD generation.

In a method to obtain information to control a manufacturing process for a stacked semiconductor device including several semiconductor layers requiring electrically interconnection, sample data of a semiconductor device sample to be inspected are provided. An X-ray imaging scan of the sample obtaining respective X-ray imaging data is performed. Sample detail information of sample details of the sample are gathered from the X-ray imaging data which are vital for the manufacturing process. Multiple Regions of Interest (ROIs) are identified from the gathered sample detail information by processing data resulting from an ROI identification model, such ROI identification model being previously trained in a machine learning process. Metrology data are extracted from the identified ROIs by processing data resulting from a metrology model, such metrology model being previously trained in a machine learning process. With such method, a process time to obtain the required information to control the manufacturing process can be reduced.

Disclosed is a method of updating of a first model by training a second model, the first model relating to a first process range and trained using a first set of measurement signals relating to a first set of structures. The method comprises: obtaining a second set of measurement signals, the second set of measurement signals relating to a second set of structures comprising said first set of structures or a subset thereof; and training the second model using said second set of measurement signals and corresponding reference values for the parameter of interest as training data. The training comprises optimizing a cost function in terms of the second model while constraining the second model to infer values for the parameter of interest from the first set of measurement signals.

A metrology system may include a controller to receive two or more images of the overlay target from one or more detectors of an optical sub-system, the overlay target including first and second periodic features generated with different measurement conditions, each measurement condition associated with at least one of a sample focal distance or a configuration of diffraction orders of the illumination by the overlay target that contributes to the associated image. The controller may further calculate an amplitude asymmetry associated of opposing diffraction orders of the illumination by the overlay target based on the two or more images and one or more quality metrics associated with the overlay target based on the amplitude asymmetry.

An analytical method and an analytical apparatus for quantitatively calculating line edge roughness of plasmon super diffraction photolithography. The method includes: determining a theoretical point spread function of a light source based on field intensity distribution of the light source at an exit plane of a focusing element of the plasmon super diffraction photolithography; determining multiple transverse widths of spots in a spot-mapping pattern based on the spot-mapping pattern; determining actual point spread functions corresponding to the multiple transverse widths, based on the theoretical point spread function and the multiple transverse widths; and establishing an analytical equation of line edge roughness of the plasmon super diffraction photolithography based on the variation due to line edge roughness, an exposure dose of each line pattern, the near-field photoresist contrast, and the logarithmic slope of each line pattern. Applicability of surface plasma super diffraction photolithography technology is greatly improved.

An optical metrology system may include illumination optics to direct pairs of mutually-coherent illumination beams to an optical metrology target, where the optical metrology target includes sets of periodic features having features with periodicity along different measurement directions. A pair of mutually-coherent illumination beams has opposing azimuth incidence angles and a common altitude incidence angle, where the azimuth incidence angles are rotated with respect to the measurement directions. The system may further generate dark-field images of the optical metrology target, where an image of a periodic structures is formed as a sinusoidal interference pattern generated by interference of a single non-zero diffraction order of light from each of the illumination beams within a pair of mutually-coherent illumination beams. A controller may generate optical metrology measurements along the measurement directions based on the images. The system may mitigate an impact of zero-order side lobes through blocking or image filtering.

A method for performing a lithographic apparatus setup calibration and/or drift correction for a specific lithographic apparatus of a population of lithographic apparatuses to be used in a manufacturing process for manufacturing an integrated circuit extending across a plurality of layers on a substrate. The method includes determining a spatial error distribution of an apparatus parameter across spatial coordinates on the substrate for each lithographic apparatus of the population of lithographic apparatuses and/or each layer of the plurality of layers; determining a reference distribution by aggregating each of the spatial error distributions to optimize the reference distribution such that a spatial distribution of a parameter of interest of the manufacturing process is co-optimized across the population of lithographic apparatuses and/or plurality of layers; and using the reference distribution as a target distribution for the apparatus parameter for each lithographic apparatus and/or layer.

Disclosed is an imaging method comprising obtaining a set of primary deconvolution kernels or a set of impulse responses relating to an optical system used to capture said image; obtaining said image signal, said image signal being subject to one or more imaging effects including at least one or more non-isoplanatic imaging effects; performing a low-rank approximation on said set of primary deconvolution kernels or impulse responses to determine respectively a set of deconvolution modes or a set of impulse response modes, each deconvolution mode comprising a modal secondary deconvolution kernel and a modal weight function and each impulse response mode comprising a modal impulse response and a modal inverse weight function; obtaining at least approximated imaging effect-free object information related to said object by applying said modal secondary deconvolution kernels and modal weight functions or said modal impulse responses and modal inverse weight functions to said image signal.

A method and system for optimizing a metrology algorithm used by an inspection tool for inspecting predetermined sites of a semiconductor wafer during fabrication so as to allow repetitive and consistent inspection for multiple sites of the wafer by both a single inspection tool of a given type using the metrology algorithm and also across a fleet of different inspection tools of the same type using the metrology algorithm. An aggregate loss function is computed from a sum of component loss functions. In one aspect, each component loss function is amplified by a non-linear function that applies a positive gain for in-range measurements and for out-of-range measurements, applies a steep penalty that swamps any cumulative gains associated with other component loss functions. In another aspect, distribution-based metrics are used to measure similarity between two distributions of measurements for multiple locations across two different tools.