Abstract: A method for determining corrections to features of a mask. The method includes obtaining (i) a pattern group for a design layout, and (ii) defect inspection data of a substrate imaged using the mask used in the patterning process for the design layout; determining, based on the defect inspection data, a defect map associated with the pattern group, wherein the defect map comprises locations of assist features having a relatively higher probability of being printed on the substrate compared to other patterns of the design layout; and determining, via simulating an optical proximity correction process using data associated with the defect map, corrections to the features of the mask.

Abstract: 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.

Abstract: Disclosed herein is a method of automatically obtaining training images to train a machine learning model that improves image quality. The method may comprise analyzing a plurality of patterns of data relating to a layout of a product to identify a plurality of training locations on a sample of the product to use in relation to training the machine learning model. The method may comprise obtaining a first image having a first quality for each of the plurality of training locations, and obtaining a second image having a second quality for each of the plurality of training locations, the second quality being higher than the first quality. The method may comprise using the first image and the second image to train the machine learning model.

Abstract: A method for aligning a wafer image with a reference image, comprising: searching for a targeted reference position on the wafer image for aligning the wafer image with the reference image; and in response to a determination that the targeted reference position does not exist: defining a current lock position and an area that encloses the current lock position on the wafer image; computing an alignment score of the current lock position; comparing the alignment score of the current lock position with stored alignment scores of positions previously selected in relation to aligning the wafer image with the reference image; and aligning the wafer image with the reference image based on the comparison.

Abstract: Systems and methods for optimal electron beam metrology guidance are disclosed. According to certain embodiments, the method may include receiving an acquired image of a sample, determining a set of image parameters based on an analysis of the acquired image, determining a set of model parameters based on the set of image parameters, generating a set of simulated images based on the set of model parameters. The method may further comprise performing measurement of critical dimensions on the set of simulated images and comparing critical dimension measurements with the set of model parameters to provide a set of guidance parameters based on comparison of information from the set of simulated images and the set of model parameters. The method may further comprise receiving auxiliary information associated with target parameters including critical dimension uniformity.

Abstract: Systems and methods for image enhancement are disclosed. A method for enhancing an image may include acquiring a first scanning electron microscopy (SEM) image at a first resolution. The method may also include acquiring a second SEM image at a second resolution. The method may further include providing an enhanced image by using the first SEM image as a reference to enhance the second SEM image. The enhanced image may be provided by using one or more features extracted from the first image to enhance the second SEM image, or using the first SEM image as a reference to numerically enhance the second SEM image.

Abstract: It discloses a chemical regeneration method of oxidized coenzyme NAD(P)+ which is under an oxygen or air atmosphere condition, adding a catalytic amount of bridged flavin, and oxidizing NAD(P)H to obtain NAD(P)+. The catalyst for regeneration of cofactor is cheap and easily available small organic molecule having no noble metal; this regeneration system can regenerate NADH and NADPH; this regeneration system has a wide pH range and temperature range, being applicable to various oxidation reactions catalyzed by nicotinamide-dependent oxidoreductase.

Abstract: It discloses a chemical regeneration method of oxidized coenzyme NAD(P)+ which is under an oxygen or air atmosphere condition, adding a catalytic amount of bridged flavin, and oxidizing NAD(P)H to obtain NAD(P)+. The catalyst for regeneration of cofactor is cheap and easily available small organic molecule having no noble metal; this regeneration system can regenerate NADH and NADPH; this regeneration system has a wide pH range and temperature range, being applicable to various oxidation reactions catalyzed by nicotinamide-dependent oxidoreductase.