A method and a device for correcting a placement error of a photomask are provided. The method includes: acquiring an exposure offset during a wafer exposure after photomask manufacture is completed, wherein the wafer exposure is a process of forming a circuit pattern on a wafer surface by exposure; and determining a compensation offset for subsequent photomask manufacture according to the exposure offset, to correct a placement error of a photomask, wherein the compensation offset and the exposure offset are vector values that are equal in value and opposite in direction. The method and device for correcting the placement error of the photomask provided in the embodiments of the present disclosure can reduce an overlay error existing in a photolithography process of a semiconductor device by correcting a placement error of a photomask.

A method and a device for correcting a placement error of a photomask are provided. The method includes: acquiring an exposure offset during a wafer exposure after photomask manufacture is completed, wherein the wafer exposure is a process of forming a circuit pattern on a wafer surface by exposure; and determining a compensation offset for subsequent photomask manufacture according to the exposure offset, to correct a placement error of a photomask, wherein the compensation offset and the exposure offset are vector values that are equal in value and opposite in direction. The method and device for correcting the placement error of the photomask provided in the embodiments of the present disclosure can reduce an overlay error existing in a photolithography process of a semiconductor device by correcting a placement error of a photomask.

One or more embodiments of the present disclosure describe an artificial intelligence assisted substrate defect repair apparatus and method. The AI assisted defect repair apparatus employs an object detection algorithm. Based on the plurality of images taken by detectors located at different respective positions, the detectors capture various views of an object including a defect. The composition information as well as the morphology information (e.g., shape, size, location, height, depth, width, length, or the like) of the defect and the object are obtained based on the plurality of images. The object detection algorithm analyzes the images and determines the type of defect and the recommends a material (e.g., etching gas) and the associated information (e.g., supply time of the etching gas, flow rate of the etching gas, etc.) for fixing the defect.

One or more embodiments of the present disclosure describe an artificial intelligence assisted substrate defect repair apparatus and method. The AI assisted defect repair apparatus employs an object detection algorithm. Based on the plurality of images taken by detectors located at different respective positions, the detectors capture various views of an object including a defect. The composition information as well as the morphology information (e.g., shape, size, location, height, depth, width, length, or the like) of the defect and the object are obtained based on the plurality of images. The object detection algorithm analyzes the images and determines the type of defect and the recommends a material (e.g., etching gas) and the associated information (e.g., supply time of the etching gas, flow rate of the etching gas, etc.) for fixing the defect.

Methods and devices for producing substrates with variable height features are provided. In one example, a proximity mask may include a plate positioned over a substrate, wherein at least a portion of the plate is separated from the substrate by a distance. The plate may include a first opening and a second opening, wherein the first opening is defined by a first perimeter having a first shape, wherein the second opening is defined by a second perimeter having a second shape, and wherein the first shape is different than the second shape.

Methods and devices for producing substrates with variable height features are provided. In one example, a proximity mask may include a plate positioned over a substrate, wherein at least a portion of the plate is separated from the substrate by a distance. The plate may include a first opening and a second opening, wherein the first opening is defined by a first perimeter having a first shape, wherein the second opening is defined by a second perimeter having a second shape, and wherein the first shape is different than the second shape.

The present invention relates to a method for ascertaining a repair shape for processing at least one defect of a photolithographic mask including the following steps: (a) determining at least one correction value for the repair shape of the at least one defect, wherein the correction value takes account of a position of at least one pattern element of the photolithographic mask, said at least one pattern element not contacting the at least one defect; and (b) correcting the repair shape by applying the at least one correction value.

The present invention relates to a method for ascertaining a repair shape for processing at least one defect of a photolithographic mask including the following steps: (a) determining at least one correction value for the repair shape of the at least one defect, wherein the correction value takes account of a position of at least one pattern element of the photolithographic mask, said at least one pattern element not contacting the at least one defect; and (b) correcting the repair shape by applying the at least one correction value.

In order to compensate for undesired effects of varying elevation of a target with respect to a nominal target plane, during writing a desired pattern on the target in a charged-particle beam apparatus, the pattern is re-calculated in each of a number of segments of the target plane by: determining an elevation of the target in the segment from the nominal target plane; determining a local blur value which represents the actual value of blur corresponding to the elevation, with regard to a dependence of the blur upon the elevation of the target; calculating a convolution kernel which represents a point spreading function realizing a local blur value; and re-calculating a nominal exposure pattern by applying the kernel to the pattern. The convolution kernel corresponds to introducing an additional blur into the pattern in the segment, increasing the blur to a given target blur value which is uniform to all segments.

In order to compensate for undesired effects of varying elevation of a target with respect to a nominal target plane, during writing a desired pattern on the target in a charged-particle beam apparatus, the pattern is re-calculated in each of a number of segments of the target plane by: determining an elevation of the target in the segment from the nominal target plane; determining a local blur value which represents the actual value of blur corresponding to the elevation, with regard to a dependence of the blur upon the elevation of the target; calculating a convolution kernel which represents a point spreading function realizing a local blur value; and re-calculating a nominal exposure pattern by applying the kernel to the pattern. The convolution kernel corresponds to introducing an additional blur into the pattern in the segment, increasing the blur to a given target blur value which is uniform to all segments.