An improved methods and systems for detecting defect(s) on a mask are disclosed. An improved method comprises inspecting an exposed wafer after the wafer was exposed, by a lithography system using a mask, with a selected process condition that is determined based on a mask defect printability under the selected process condition; and identifying, based on the inspection, a wafer defect that is caused by a defect on the mask to enable identification of the defect on the mask.

Methods include generating a scanner aerial image using a neural network, where the scanner aerial image is generated using a mask inspection image that has been generated by a mask inspection machine. Embodiments also include training the neural network with a set of images, such as with a simulated scanner aerial image and another image selected from a simulated mask inspection image, a simulated Critical Dimension Scanning Electron Microscope (CD-SEM) image, a simulated scanner emulator image and a simulated actinic mask inspection image.

A method to improve a lithographic process of imaging a portion of a design layout onto a substrate using a lithographic projection apparatus, the method including: computing a multi-variable cost function, the multi-variable cost function being a function of a stochastic variation of a characteristic of an aerial image or a resist image, or a function of a variable that is a function of the stochastic variation or that affects the stochastic variation, the stochastic variation being a function of a plurality of design variables that represent characteristics of the lithographic process; and reconfiguring one or more of the characteristics of the lithographic process by adjusting one or more of the design variables until a certain termination condition is satisfied.

There are provided a manufacturing method for a substrate having a conductive pattern, a manufacturing method for an electronic device, and a substrate having a conductive pattern, which are excellent in the dimensional stability of the conductive pattern after applying an electric current, as well as a protective film for a metal nanobody.

Provided are the manufacturing method for a substrate having a conductive pattern, comprising a step 1a of forming a conductive layer a containing a metal nanobody and a resin 1 on a substrate; a step 1b of forming a resin layer b containing a resin 2 on the conductive layer a; a step 2a of forming a photosensitive resin layer c on the resin layer b; a step 3 of obtaining a resin pattern c′ of the photosensitive resin layer by exposure and development treatment on the photosensitive resin layer c; a step 4 of removing the metal nanobody in the conductive layer a by etching to form a conductive pattern d; and a step 5a of softening or swelling at least one of the resin 1 or the resin 2, the manufacturing method for an electronic device, the substrate having a conductive pattern, and the protective film for a metal nanobody.

To determine an imaging quality of an optical system when illuminated by illumination light within an entrance pupil or exit pupil, a test structure is initially arranged in an object plane of the optical system and an illumination angle distribution for illuminating the test structure with the illumination light is specified. The test structure is illuminated at different distance positions relative to the object plane. An intensity of the illumination light is measured in an image plane of the optical system, the illumination light having been guided by the optical system when imaging the test structure at each distance position. An aerial image measured in this way is compared with a simulated aerial image and fit parameters of a function set for describing the simulated aerial image are adapted and a wavefront of the optical system is determined on the basis of the result of a minimized difference.

A method for determining process window limiting patterns based on aberration sensitivity associated with a patterning apparatus. The method includes obtaining (i) a first set of kernels and a second set of kernels associated with an aberration wavefront of the patterning apparatus and (ii) a design layout to be printed on a substrate via the patterning apparatus; and determining, via a process simulation using the design layout, the first set of kernels, and the second set of kernels, an aberration sensitivity map associated with the aberration wavefront, the aberration sensitivity map indicating how sensitive one or more portions of the design layout are to an individual aberrations and an interaction between different aberrations; determining, based on the aberration sensitivity map, the process window limiting pattern associated with the design layout having relatively high sensitivity compared to other portions of the design layout.

An optical measuring system is used to reproduce a target wavefront of an imaging optical production system when an object is illuminated with illumination light. The optical measuring system comprises an object holder displaceable by actuator means and at least one optical component displaceable by actuator means. Within the scope of the target wavefront reproduction, a starting actuator position set (X.sub.0), in which each actuator is assigned a starting actuator position, is initially specified. An expected design wavefront (W.sub.D) which approximates the target wavefront and which the optical measuring system produces as a set wavefront is determined. A coarse measurement of a starting wavefront (W.sub.0) which the optical measuring system produces as actual wavefront after actually setting the starting actuator position set (X.sub.0) is carried out. Then, the object holder is adjusted by actuator means until a coarse target wavefront (W.sub.1) is obtained for a coarse actuator position set (X.sub.1) in the case of a minimum wavefront deviation between the actual wavefront and the design wavefront (W.sub.D). Said coarse target wavefront is then subjected to a fine measurement and the at least one optical component is displaced until a fine target wavefront (W.sub.2) is obtained for a fine actuator position set (X.sub.2) in the case of a minimum deviation between the actual wavefront setting-in in that case and the design wavefront (W.sub.D). This reproduction method allows wavefront deviations of the optical measuring system generated by way of targeted misalignment to provide a good approximation of corresponding deviations of the optical production system.

A system of measuring an image of a pattern in a high NA scanning-type extreme ultra-violet (EUV) mask is disclosed. The system may include a light source generating an EUV light; an toroidal mirror; an flat mirror allowing light, which is reflected by the toroidal mirror, to be incident into the mask; an beam splitter; a light detection part; an anamorphic zone-plate lens focusing a transmitted portion of a light emitted from the beam splitter on the mask; a stage; and an anamorphic photo sensor, which is configured to measure an energy of a reflected portion of the coherent EUV light, is composed of a detector array, and has different sizes from each other in horizontal and vertical directions of an incidence surface of the detector array.

Methods and systems for configuring a metrology tool are described. A processor can receive a height map of a sample from an apparatus configured to generate wafer height maps. The received height map can indicate height information of a plurality of features on a surface of the sample. The plurality of features can be located on a plurality of focal planes. The processor can generate settings for the metrology tool based on the height map of the sample.

Methods and systems for determining information for a specimen are provided. Certain embodiments relate to bump height 3D inspection and metrology using deep learning artificial intelligence. For example, one embodiment includes a deep learning (DL) model configured for predicting height of one or more 3D structures formed on a specimen based on one or more images of the specimen generated by an imaging subsystem. One or more computer systems are configured for determining information for the specimen based on the predicted height. Determining the information may include, for example, determining if any of the 3D structures are defective based on the predicted height. In another example, the information determined for the specimen may include an average height metric for the one or more 3D structures.