Disclosed is a method for characterizing a measurement apparatus for semiconductor lithography, comprising the following steps: performing a plurality of measurements, in particular of a marker property or die property (for example, registration values or CD values) determining a relationship between the width of a confidence interval of the measurement result from averaging and the number of elements of a subset of all the measurements carried out. Also disclosed is a measurement apparatus in which the method is applied.

Disclosed is a method of determining an orthonormalized structure of interest reference image. the orthonormalized structure of interest reference image for applying to a measured image of the structure of interest to correct for the effect of crosstalk from at least one nuisance structure. The method comprises determining a structure of interest reference image based on knowledge of the structure of interest; determining at least one nuisance structure reference image based on knowledge of the at least one nuisance structure; and orthonormalizing the structure of interest reference image to the at least one nuisance reference image to obtain the orthonormalized structure of interest reference image.

Various examples herein describe an apparatus and related method to track and correct alignment errors of features used on a substrate. For example, in various embodiments, the disclosed subject-matter is a method for measuring x-coordinates and y-coordinates of a number of features (such as vias) on a layer on the substrate for each of the layers formed on the substrate that are to underlie a subsequently formed layer; compare the x-coordinates and the y-coordinates on the layer to respective locations of a production file used to determine a planned location of the features for each of the respective layers; prepare offset data based on the comparison for each of the respective layers; and enter the offset data into a lithographic tool database to minimize or correct the alignment errors for each of the respective layers. Other systems, apparatuses, and methods are also disclosed.

Disclosed is a metrology method. The method comprises obtaining measurement data relating to measurement of at least one target using two or more different illumination profiles; and a respective parameter of interest value for a parameter of interest for each of said two or more different illumination profiles. The method described determining, from said measurement data, a respective measurement parameter deviation value for each of said two or more different illumination profiles, said measurement parameter deviation value describing a deviation in a measurement parameter with respect to a measurement parameter value attributed to a region of interest of said target or a sub-target thereof; determining a relationship for the target between the parameter of interest values and the measurement parameter deviation values; and determining one or both of a corrected parameter of interest value and a preferred illumination profile from said relationship.

An overlay metrology system includes a controller communicatively coupled to a first photodetector and a second photodetector. The controller may be configured to receive one or more signals from the first and second photodetector as an overlay target is scanned. The overlay target may include a plurality of measurement cells, where each measurement cell includes a grating-over-grating structure including a first-layer grating feature on a first layer of a sample and a second-layer grating feature on a second layer of the sample in an overlapping region. The first-layer grating feature and the second-layer grating feature may have a common pitch. The controller may be further configured to determine one or more differential signals between the first photodetector and the second photodetector for each measurement cell of the plurality of measurement cells and determine an overlay measurement based on the determined one or more differential signals.

Techniques for improving critical dimension metrology are disclosed herein. An example method includes emitting a radiation beam comprising (i) a primary beam that passes through a sample and scatters into a set of scattered beams and (ii) a reference beam. The method further includes detecting the reference beam and a portion of the set of scattered beams, wherein the reference beam and the portion of the set of scattered beams superimpose at the detector as a hologram of the sample to encode structural information associated with at least one lithographic pattern of the sample. The method further includes executing a dimensioning algorithm configured to: determine one or more critical dimensions of the sample based on one or more properties of the hologram and reconstruct a real-space image of the sample based on the hologram. The method further includes causing the critical dimensions or the real-space image to be displayed.

Methods and systems for calibrating simulated measurement signals generated by a parametric measurement model are described herein. Regression on real measurement signals is performed using a parametric model. The residual fitting error between the real measurement signals and simulated measurement signals generated by the parametric model characterizes the error of the parametric model at each set of estimated values of the one or more floating parameters. Simulated measurement signals are generated by the parametric model at specified values of the floating parameters. A residual fitting error associated with the simulated measurement signals generated at the specified values of the floating parameters is derived from the residual fitting errors calculated by the regression on the real measurement signals. The simulated measurement signals are calibrated by adding the residual fitting error to the uncalibrated, simulated measurement signals. The calibrated, simulated measurement signals improve the accuracy of measurements and measurement recipe development.

An illumination compensation method, comprising: acquiring working gaps between an imaging film stack and a mask in an exposure imaging system; calculating imaging light field intensities of a photoresist layer in the imaging film stack corresponding to the different working gaps, and, constructing a functional dependence of imaged pattern critical dimension in the photoresist layer of the imaging film stack on the working gap based on said imaging light field intensity critical dimension; calculating compensation parameters required for illumination light according to the said functional dependence of imaged pattern critical dimension on working gap; and, performing illumination compensation on the exposure imaging system according to the compensation parameters.

Automated model term selection may use lasso regression for selecting model terms and a cross-validation scheme to optimize a regularization parameter of the lasso regression. A value of the regularization parameter may be selected by cross-validating the regularization parameter across a range of possible values using metrology measurements of a sample. A modeled correction may be generated based on the metrology measurements and the value of the regularization parameter using the regression. The regression may reduce a residual between the modeled correction and the metrology measurements. The model terms may include a sub-set of possible model terms up to a maximum order. Selecting the model terms from the possible model terms may prevent overfitting the modeled correction. The regularization parameter may control the number of the model terms which are selected.

A method of inspecting a risk of printing defective pattern in photolithography process, including generating an intensity curve of a photomask pattern in aerial image simulation, wherein the intensity curve is provided with a primary trough and a secondary troughs adjacent to the primary trough, the aerial image simulation is provided with a threshold intensity intersecting one of the secondary troughs to define an intensity region, partitioning the intensity region into multiple rectangular fragments, summing up areas of the rectangular fragments to obtain a total area, and determining the photomask pattern having no risk of forming defective pattern if the total area is smaller than a spec value and determining the photomask pattern having risk of forming defective pattern if the total area is larger than the spec value.