Abstract: 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.

Abstract: A 3D image sensor based on standard Complementary Metal Oxide Semiconductor (CMOS) process is described. The conventional CMOS image sensor measures a 2D projection of the 3D world in gray-scale or color image; this new sensor can measure the third dimension on the 2D image—the depth of object on the 2D image pixels. Since the standard CMOS image sensor can only sense intensity (the number of photons) at each CMOS pixel, this new sensor creates a new mechanism to encode the depth information into an intensity distribution change that CMOS sensor can sense. The idea is based on the observation or lens imaging theory that light cone for any point (pixel) on the image plane is narrower for a near object and wider for a distant object. We then use diffraction to measure the change of incident angle, based on the theory that an oblique light goes through a finite grating producing diffraction patterns multiple times from near field to far field, the incident angle is reflected as diffraction pattern shift.

Abstract: During a calculation technique, a modification to a reflective photo-mask is calculated. In particular, using information specifying a defect associated with a recessed area on a top surface of the reflective photo-mask, the modification to the reflective photo-mask is calculated. For example, the calculation may involve an inverse optical calculation in which a difference between a pattern associated with the reflective photo-mask at an image plane in a photo-lithographic process and a reference pattern at the image plane in the photo-lithographic process is used to calculate the modification at an object plane in the photo-lithographic process. Note that the modification includes a negative feature in which one or more pairs of layers in a multilayer stack in the reflective photo-mask are removed using a subtractive fabrication process. Moreover, the modification is proximate to the recessed area.

Abstract: A technique for inspecting, qualifying and repairing photo-masks for use at extreme ultra-violet (EUV) wavelengths is described. In this technique, multiple images of a substrate and/or a blank that includes multiple layers deposited on the substrate are measured and compared to identify first potential defects. Using information associated with the first potential defects, such as locations of the first potential defects, another image of the EUV photo-mask that includes a mask pattern defined in an absorption layer, which is deposited on top of the multiple layers, is measured. Based on the other image and the first potential defects, second potential defects in the EUV photo-mask are identified. Next, a qualification condition of the EUV photo-mask is determined based on the first potential defects and the second potential defects.

Abstract: During a calculation technique, a modification to a reflective photo-mask is calculated. In particular, using information specifying a defect associated with a recessed area on a top surface of the reflective photo-mask, the modification to the reflective photo-mask is calculated. For example, the calculation may involve an inverse optical calculation in which a difference between a pattern associated with the reflective photo-mask at an image plane in a photo-lithographic process and a reference pattern at the image plane in the photo-lithographic process is used to calculate the modification at an object plane in the photo-lithographic process. Note that the modification includes a negative feature in which one or more pairs of layers in a multilayer stack in the reflective photo-mask are removed using a subtractive fabrication process. Moreover, the modification is proximate to the recessed area.

Abstract: A technique for inspecting, qualifying and repairing photo-masks for use at extreme ultra-violet (EUV) wavelengths is described. In this technique, multiple images of a substrate and/or a blank that includes multiple layers deposited on the substrate are measured and compared to identify first potential defects. Using information associated with the first potential defects, such as locations of the first potential defects, another image of the EUV photo-mask that includes a mask pattern defined in an absorption layer, which is deposited on top of the multiple layers, is measured. Based on the other image and the first potential defects, second potential defects in the EUV photo-mask are identified. Next, a qualification condition of the EUV photo-mask is determined based on the first potential defects and the second potential defects.

Abstract: Embodiments of a computer system, a process, a computer-program product (i.e., software), and a data structure or a file for use with the computer system are described. These embodiments may be used to determine or generate source patterns that define illumination patterns on photo-masks during a photolithographic process. Moreover, a given source pattern may be determined concurrently with an associated mask pattern (to which a given photo-mask corresponds) or sequentially (i.e., either the given source pattern may be determined before the associated mask pattern or vice versa.). During the determining, the given source pattern may be represented using one or more level-set functions. Additionally, the source pattern may be determined using an Inverse Lithography (ILT) calculation.

Abstract: A technique for reconstructing an electron-beam (EB) image, which can be a scanning-electron-microscope (SEM) image or an EB-inspection image, is described. This reconstruction technique may involve an inverse electro-optical calculation that corrects for the influence of an electro-optical transfer function associated with an EB system on the EB image. In particular, in the inverse calculation a multi-valued representation of an initial EB image is at an image plane in the model of the electro-optical transfer function and a resulting EB image is at an object plane in the model of the electro-optical transfer function. Furthermore, the model of the electro-optical transfer function may have an analytical derivative and/or may be represented by a closed-form expression.

Abstract: During a calculation technique, a modification to a reflective photo-mask is calculated. In particular, using information associated with different types of analysis techniques a group of one or more potential defects in the reflective photo-mask is determined. Then, the modification to the reflective photo-mask is calculated based on at least a subset of the group of potential defects using an inverse optical calculation. In particular, during the inverse optical calculation, a cost function at an image plane in a model of the photolithographic process is used to determine the modification to the reflective photo-mask at an object plane in the model of the photolithographic process.

Abstract: A technique for determining a full-field Mask Error Enhancement Function (MEEF) associated with a mask pattern for use in a photo-lithographic process is described. In this technique, simulated wafer patterns corresponding to the mask pattern are generated at an image plane in an optical path associated with the photo-lithographic process. Then, the full-field MEEF is determined. This full-field MEEF includes MEEF values in multiple directions at positions along one or more contours that define boundaries of one or more features in the one or more simulated wafer patterns. Moreover, at least one of the MEEF values is at a position on a contour where a critical dimension for a feature associated with the contour is undefined.

Abstract: A technique for determining photo-mask defect disposition is described. In this technique, a target mask pattern is used to expand an initial region in a photo-mask that is included in an initial mask-inspection image. In particular, a revised mask-inspection image that includes the initial region and a region surrounding the initial region is generated based on the initial mask-inspection image and the target mask pattern. Then a corresponding simulated mask pattern is calculated in an inverse optical calculation using the revised mask-inspection image and an optical model of the mask-inspection system. This simulated mask pattern is used to simulate a wafer pattern in a photo-lithographic process, and disposition of a possible defect in the initial region is subsequently determined based on the simulated wafer pattern and a target wafer pattern.

Abstract: A technique for calculating a second aerial image associated with a photo-mask that can be used to determine whether or not the photo-mask (which may include defects) is acceptable for use in a photolithographic process is described. In particular, using a first aerial image produced by the photo-mask when illuminated using a source pattern and an inspection image of the photo-mask, a mask pattern corresponding to the photo-mask is determined. For example, the first aerial image may be obtained using an aerial image measurement system, and the inspection image may be a critical-dimension scanning-electron-microscope image of the photo-mask. This image, which has a higher resolution than the first aerial image, may indicate spatial-variations of a magnitude of the transmittance of the photo-mask. Then, the second aerial image may be calculated based on the determined mask pattern using a different source pattern than the source pattern.

Abstract: A technique for reconstructing a mask pattern corresponding to a photo-mask using a target mask pattern (which excludes defects) and an image of at least a portion of the photo-mask is described. This image may be an optical inspection image of the photo-mask that is determined using inspection optics which includes an optical path, and the reconstructed mask pattern may include additional spatial frequencies than the image. Furthermore, the reconstructed mask pattern may be reconstructed based on a characteristic of the optical path (such as an optical bandwidth of the optical path) using a constrained inverse optical calculation in which there are a finite number of discrete feature widths allowed in the reconstructed mask pattern, and where a given feature has a constant feature width. Consequently, the features in the reconstructed mask pattern may each have the constant feature width, such as an average critical dimension of the reconstructed mask pattern.

Abstract: A technique for reconstructing an electron-beam (EB) image, which can be a scanning-electron-microscope (SEM) image or an EB-inspection image, is described. This reconstruction technique may involve an inverse electro-optical calculation that corrects for the influence of an electro-optical transfer function associated with an EB system on the EB image. In particular, in the inverse calculation a multi-valued representation of an initial EB image is at an image plane in the model of the electro-optical transfer function and a resulting EB image is at an object plane in the model of the electro-optical transfer function. Furthermore, the model of the electro-optical transfer function may have an analytical derivative and/or may be represented by a closed-form expression.

Abstract: A technique for reconstructing a mask pattern corresponding to a photo-mask using a target mask pattern (which excludes defects) and an image of at least a portion of the photo-mask is described. This image may be an optical inspection image of the photo-mask that is determined using inspection optics which includes an optical path, and the reconstructed mask pattern may include additional spatial frequencies than the image. Furthermore, the reconstructed mask pattern may be reconstructed based on a characteristic of the optical path (such as an optical bandwidth of the optical path) using a constrained inverse optical calculation in which there are a finite number of discrete feature widths allowed in the reconstructed mask pattern, and where a given feature has a constant feature width. Consequently, the features in the reconstructed mask pattern may each have the constant feature width, such as an average critical dimension of the reconstructed mask pattern.

Abstract: A technique for calculating a second aerial image associated with a photo-mask that can be used to determine whether or not the photo-mask (which may include defects) is acceptable for use in a photolithographic process is described. In particular, using a first aerial image produced by the photo-mask when illuminated using a source pattern and an inspection image of the photo-mask, a mask pattern corresponding to the photo-mask is determined. For example, the first aerial image may be obtained using an aerial image measurement system, and the inspection image may be a critical-dimension scanning-electron-microscope image of the photo-mask. This image, which has a higher resolution than the first aerial image, may indicate spatial-variations of a magnitude of the transmittance of the photo-mask. Then, the second aerial image may be calculated based on the determined mask pattern using a different source pattern than the source pattern.

Abstract: During a calculation technique, a modification to a reflective photo-mask is calculated. In particular, using information associated with different types of analysis techniques a group of one or more potential defects in the reflective photo-mask is determined. Then, the modification to the reflective photo-mask is calculated based on at least a subset of the group of potential defects using an inverse optical calculation. In particular, during the inverse optical calculation, a cost function at an image plane in a model of the photolithographic process is used to determine the modification to the reflective photo-mask at an object plane in the model of the photolithographic process.

Abstract: Defect printability analysis in a mask or wafer requires the accurate identification of defect images and reference (i.e. defect-free) images, in particular for a die-to-die inspection mode. A method of automatically distinguishing a reference image from a defect image is provided. In this method, multiple images can be accessed and aligned. Then, a common area of the multiple images can be defined. At this point, a complexity of each of the images, as defined by the common area, can be computed. Advantageously, by comparing the complexity of the multiple images, the reference and defect images can be quickly and accurately designated. Specifically, the most complex image is designated the defect image because the defect image must describe the defect. Complexity can be computed using various techniques.

Abstract: Embodiments of a method for determining a mask pattern to be used on a photo-mask in a lithography process are described. This method may be performed by a computer system. During operation, this computer system receives at least a portion of a first mask pattern including first regions that violate pre-determined rules associated with the photo-mask. Next, the computer system determines a second mask pattern based on at least the portion of the first mask pattern, where the second mask pattern includes second regions that are estimated to comply with the pre-determined rules. Note that the second regions correspond to the first regions, and the second mask pattern is determined using a different technique than that used to determine the first mask pattern.

Abstract: A technique for determining a full-field Mask Error Enhancement Function (MEEF) associated with a mask pattern for use in a photo-lithographic process is described. In this technique, simulated wafer patterns corresponding to the mask pattern are generated at an image plane in an optical path associated with the photo-lithographic process. Then, the full-field MEEF is determined. This full-field MEEF includes MEEF values in multiple directions at positions along one or more contours that define boundaries of one or more features in the one or more simulated wafer patterns. Moreover, at least one of the MEEF values is at a position on a contour where a critical dimension for a feature associated with the contour is undefined.