In a dark-field metrology method using a small target, a characteristic of an image of the target, obtained using a single diffraction order, is determined by fitting a combination fit function to the measured image. The combination fit function includes terms selected to represent aspects of the physical sensor and the target. Some coefficients of the combination fit function are determined based on parameters of the measurement process and/or target. In an embodiment the combination fit function includes jinc functions representing the point spread function of a pupil stop in the imaging system.

Systems and methods for in-die metrology using target design patterns are provided. These systems and methods include selecting a target design pattern based on design data representing the design of an integrated circuit, providing design data indicative of the target design pattern to enable design data derived from the target design pattern to be added to second design data, wherein the second design data is based on the first design data. Systems and methods can further include causing structures derived from the second design data to be printed on a wafer, inspecting the structures on the wafer using a charged-particle beam tool, and identifying metrology data or process defects based on the inspection. In some embodiments the systems and methods further include causing the charged-particle beam tool, the second design data, a scanner, or photolithography equipment to be adjusted based on the identified metrology data or process defects.

The invention relates to a method for measuring a multilayered substrate (1, 1′, 1″), particularly with at least one structure (7, 7′, 7″, 7′″, 7.sup.IV, 7.sup.V) with critical dimensions, particularly with a surface structure (7, 7′, 7″, 7′″, 7.sup.IV, 7.sup.V) with critical dimensions, characterized in that the method has at least the following steps, particularly the following procedure:

producing (110) the substrate (1, 1′, 1″) with a plurality of layers (2, 3, 4, 5, 6, 6′, 6″), particularly with a structure (7, 7′, 7″, 7′″, 7.sup.IV, 7.sup.V), particularly with a structure (7, 7′, 7″, 7″′, 7.sup.IV, 7.sup.V) on a surface (6o, 6′o, 6″o) of an uppermost layer (6, 6′, 6″), wherein the dimensions of the layers and in particular the structures are known,

measuring (120) the substrate (1, 1′, 1″), and in particular the structure (7, 7′, 7″, 7′″, 71.sup.IV, 7.sup.V)) using at least one measuring technology,

creating (130) a simulation of the substrate using the measurement results from the measurement of the substrate (1, 1′, 1″),

comparing (140) the measurement results with simulation results from the simulation of the substrate (1, 1′, 1″),

optimizing the simulation (130) and renewed creation (130) of a simulation of the substrate using the measurement results from the measurement of the substrate (1, 1′, 1″), in the event that there is a deviation of the measurement results from the simulation results, or calculating (150) parameters of further substrates, in the event that the measurement results correspond to the simulation results.

The present disclosure relates to the determination of a pattern height of a pattern, which has been produced with extreme ultraviolet (EUV) lithography in a resist film. The determination is performed by using an electron beam (e-beam) system, in particular, by using a scanning electron microscope (SEM). In this respect, the disclosure provides a device for determining the pattern height, wherein the device comprising a processor. The processor is configured to obtain a SEM image of the pattern from an SEM. Further, the processor is configured to determine a contrast value related to the pattern based on the obtained SEM image. Subsequently, the processor is configured to determine the pattern height based on calibration data and the determined contrast value.

A method including: computing a value of a first variable of a pattern of, or for, a substrate processed by a patterning process by combining a fingerprint of the first variable on the substrate and a certain value of the first variable; and determining a value of a second variable of the pattern based at least in part on the computed value of the first variable.

Methods and systems for characterizing dimensions and material properties of semiconductor devices by transmission small angle x-ray scatterometry (TSAXS) systems having relatively small tool footprint are described herein. The methods and systems described herein enable Q space resolution adequate for metrology of semiconductor structures with reduced optical path length. In general, the x-ray beam is focused closer to the wafer surface for relatively small targets and closer to the detector for relatively large targets. In some embodiments, a high resolution detector with small point spread function (PSF) is employed to mitigate detector PSF limits on achievable Q resolution. In some embodiments, the detector locates an incident photon with sub-pixel accuracy by determining the centroid of a cloud of electrons stimulated by the photon conversion event. In some embodiments, the detector resolves one or more x-ray photon energies in addition to location of incidence.

Methods and systems for improving a measurement recipe describing a sequence of measurements employed to characterize semiconductor structures are described herein. A measurement recipe is repeatedly updated before a queue of measurements defined by the previous measurement recipe is fully executed. In some examples, an improved measurement recipe identifies a minimum set of measurement options that increases wafer throughput while meeting measurement uncertainty requirements. In some examples, measurement recipe optimization is controlled to trade off measurement robustness and measurement time. This enables flexibility in the case of outliers and process excursions. In some examples, measurement recipe optimization is controlled to minimize any combination of measurement uncertainty, measurement time, move time, and target dose. In some examples, a measurement recipe is updated while measurement data is being collected. In some examples, a measurement recipe is updated at a site while data is collected at another site.

An overlay mark includes a first, a second, a third, and a fourth component. The first component is located in a first region of the first overlay mark and includes a plurality of gratings that extend in a first direction. The second component is located in a second region of the first overlay mark and includes a plurality of gratings that extend in the first direction. The third component is located in a third region of the first overlay mark and includes a plurality of gratings that extend in a second direction different from the first direction. The fourth component is located in a fourth region of the first overlay mark and includes a plurality of gratings that extend in the second direction. The first region is aligned with the second region. The third region is aligned with the fourth region.

Some devices, systems, and methods obtain a material map of a region; divide the region into a plurality of subregions; perform, for each of one or more subregions of the plurality of subregions, a first drop-pattern-generation process, wherein the first drop-pattern-generation process generates a respective initial drop pattern for the subregion based on the material map; and perform, for each of the one or more subregions of the plurality of subregions, a second drop-pattern-generation process, wherein the second drop-pattern-generation process generates a respective revised drop pattern for the subregion based on the material map and on the respective initial drop pattern for the subregion.

A method for determining a metric of a feature on a substrate obtained by a semiconductor manufacturing process involving a lithographic process, the method including: obtaining an image of at least part of the substrate, wherein the image includes at least the feature; determining a contour of the feature from the image; determining a plurality of segments of the contour; determining respective weights for each of the plurality of segments; determining, for each of the segments, an image-related metric; and determining the metric of the feature in dependence on the weights and the calculated image-related metric of each of the segments.