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.

According to one embodiment, a method for displaying an index value in generation of a mask pattern verification model includes: calculating a first index value using a plurality of images; estimating a model on the basis of the first index value and pattern information; calculating a second index value using the model; and displaying at least one of the first index value and the second index value.

A high harmonic radiation source and associated method of generating high harmonic radiation is disclosed. The high harmonic radiation source is configured to condition a gas medium by irradiating the gas medium with a pre-pulse of radiation, thereby generating a plasma comprising a pre-pulse plasma distribution; and irradiate the gas medium with a main pulse of radiation to generate said high harmonic radiation. The conditioning step is such that the plasma comprising a pre-pulse plasma distribution acts to configure a wavefront of said main pulse to improve one or both of: the efficiency of the high harmonic generation process and the beam quality of the high harmonic radiation. The high harmonic radiation source further may comprise a beam shaping device configured to shape said customized pre-pulse prior to said conditioning.

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 image analysis method for identifying features in an image of a part of an array of features formed by a multi-step process, the method comprising: analyzing variations in features visible in the image; and associating features of the image with steps of the multi-step process based at least in part on results of the analyzing.

Disclosed is an illumination source comprising a gas delivery system comprising a gas nozzle. The gas nozzle comprises an opening in an exit plane of the gas nozzle. The gas delivery system is configured to provide a gas flow from the opening for generating an emitted radiation at an interaction region. The illumination source is configured to receive a pump radiation having a propagation direction and to provide the pump radiation in the gas flow. A geometry shape of the gas nozzle is adapted to shape a profile of the gas flow such that gas density of the gas flow first increases to a maximum value and subsequently falls sharply in a cut-off region along the propagation direction.

Embodiments of the present disclosure relate to a system, a software application, and a method of a lithography process to update one or more of a mask pattern, maskless lithography device parameters, lithography process parameters utilizing a file readable by each of the components of a lithography environment. The file readable by each of the components of a lithography environment stores and shares textual data and facilitates communication between of the components of a lithography environment such that the mask pattern corresponds to a pattern to be written is updated, the maskless lithography device of the lithography environment is calibrated, and process parameters of the lithography process are corrected for accurate writing of the mask pattern on successive substrates.

A system and method for generating predictive images for wafer inspection using machine learning are provided. Some embodiments of the system and method include acquiring the wafer after a photoresist applied to the wafer has been developed; imaging a portion of a segment of the developed wafer; acquiring the wafer after the wafer has been etched; imaging the segment of the etched wafer; training a machine learning model using the imaged portion of the developed wafer and the imaged segment of the etched wafer; and applying the trained machine learning model using the imaged segment of the etched wafer to generate predictive images of a developed wafer. Some embodiments include imaging a segment of the developed wafer; imaging a portion of the segment of the etched wafer; training a machine learning model; and applying the trained machine learning model to generate predictive after-etch images of the developed wafer.

A method of determining a correction for a process parameter related to a lithographic process, wherein the lithographic process includes a plurality of runs during each one of which a pattern is applied to one or more substrates. The method of determining includes obtaining pre-exposure metrology data describing a property of a substrate; obtaining post-exposure metrology data comprising one or more measurements of the process parameter having been performed on one or more previously exposed substrates; assigning, based on the pre-exposure metrology data, a group membership status from one or more groups to the substrate; and determining the correction for the process parameter based on the group membership status and the post-exposure metrology data.