TW201901291A - Apparatus and method for detecting a photomask - Google Patents

Abstract

Disclosed are methods and apparatus for qualifying a photolithographic reticle. A reticle inspection tool is used to acquire a plurality of images at different imaging configurations from each of a plurality of pattern areas of a test reticle. A reticle near field is recovered for each of the pattern areas of the test reticle based on the acquired images from each pattern area of the test reticle. The recovered reticle near field is then used to determine whether the test reticle or another reticle will likely result in unstable wafer pattern or a defective wafer.

Description

Equipment and method for detecting photomask

The present invention relates generally to the field of photomask inspection. More specifically, the present invention relates to pattern qualification.

In general, the semiconductor manufacturing industry involves highly sophisticated technologies for making integrated circuits using semiconductor materials (such as silicon) that are layered and patterned onto a substrate. Due to the large-scale integrated circuitization and reduced size of semiconductor devices, the devices made have become increasingly sensitive to defects. That is, defects that cause malfunctions in the device become smaller and smaller. The device is trouble-free before being shipped to the end user or customer. An integrated circuit is usually made from a plurality of photomasks. First, a circuit designer provides circuit pattern data describing a specific integrated circuit (IC) design to a mask production system or a mask writer. The circuit pattern data is usually in the form of a representative layout of the physical layers of the IC device being fabricated. The representative layout includes a representative layer (e.g., gate oxide, polycrystalline silicon, metallization, etc.) of each physical layer of the IC device, where each representative layer is composed of a plurality of patterned polygons defining a layer of a specific IC device . The mask writer uses circuit pattern data to write (eg, an electron beam writer or laser scanner is typically used to expose a mask pattern) which will later be used to make a number of masks for a specific IC design. Some reticlees or photomasks have a pattern containing at least transparent and opaque regions, translucent and phase-shifted regions, or absorbers and reflective regions (which together define a pattern of coplanar features in an electronic device such as an integrated circuit) The form of an optical element. A photomask is used during photolithography to define a designated area of a semiconductor wafer for etching, ion implantation, or other fabrication processes. After making each reticle or reticle group, each new reticle is usually qualified for use in wafer fabrication. For example, the mask pattern needs to be free of printable defects. In addition, any wafer made with a photomask needs to be defect free. Therefore, there is a continuing need for improved photomask and wafer inspection and qualification techniques.

A simplified overview of the invention is presented below to provide a basic understanding of one particular embodiment of the invention. This summary is not an extensive overview of the invention, and it does not identify essential / critical elements of the invention or describe the scope of the invention. Its sole purpose is to present some concepts disclosed herein in a simplified form as a prelude to the more detailed description that is presented later. In one embodiment, a method for qualifying a lithographic reticle is disclosed. An imaging tool is used to obtain a plurality of images from each of the plurality of pattern areas of a test mask according to different lighting configurations and / or different imaging configurations. Each of the pattern areas for the test mask restores a mask near field based on the images obtained from the pattern areas of the test mask. Next, the restored photomask near field is used to determine whether the test photomask or another photomask may cause an unstable wafer pattern or a defective wafer. In one embodiment, the photomask near field is directly analyzed to determine whether the test photomask or another photomask will likely result in an unstable wafer pattern or a defective wafer. In another aspect, the restored mask near field is used to detect defects in the test mask or simulated wafer images simulated from the restored mask near field, wherein the defect detection includes: comparing different The strength of one of the same grains, adjacent grains, one grain and its corresponding golden die, or one grain and one corresponding grain from a mask replica with the same design as the test mask And / or phase. In one aspect, the images are acquired at a field plane or a pupil plane. In a specific embodiment, the near field of the mask is restored without using a design database used to make the mask. In another aspect, the acquired images include at least three reflection / transmission images acquired under different imaging conditions selected to result in a near field of the same mask. In this aspect, the different imaging conditions include different focus settings and different pupil shapes, and different lighting conditions include different light source intensity distributions and / or polarized light settings. In an alternative embodiment, the method includes: (i) applying a lithographic model to the near field of the mask of the test mask to simulate a plurality of test wafer images; and (ii) analyzing the simulated test crystals Circle the image to determine if the test mask will cause an unstable or defective wafer. In this aspect, the lithographic model is configured to simulate a photolithographic process. In another aspect, the lithography model simulates an illumination source having a shape different from an illumination shape of a detection tool used to acquire an image of the test mask or another mask or wafer . In another aspect, the lithographic model is calibrated using an image generated from a design database for a calibration mask. In another example, the lithographic model is calibrated using images acquired from a calibration mask. In yet another aspect, the lithographic model is applied to the near-field of the reticle restored for the test reticle under a plurality of different lithographic process conditions, and analyzing the simulated test wafer images includes: by comparison The portions of the simulated test images associated with different process conditions and an identical mask area determine whether the test mask will likely result in an unstable wafer under the different lithographic process conditions. In an alternative embodiment, the invention relates to a detection system for identifying the qualification of a light lithographic mask. The system includes: a light source for generating an incident light beam; and an illumination optical module for guiding the incident light beam to a photomask. The system also includes: a collection optical module for directing an output beam from each of the pattern areas of the mask to at least one sensor, the at least one sensor is used to detect the output beam and is based on the The output beam produces an image or signal. The system further includes a controller configured to perform operations similar to one or more of the above method operations. These and other aspects of the invention are described further below with reference to the drawings.

Cross-References to Related Applications This application claims the priority right of U.S. Patent Application No. 15 / 641,150 filed by Rui-fang Shi et al. On July 3, 2017, and is a part of its continuation application. The U.S. Patent Application No. 15 / 641,150 claims the priority right of PCT Application No. PCT / US2016 / 045749 filed by Abdurrahman Sezginer et al. On August 5, 2016 under 35 USC § 120, which is PCT / US2016 / 045749 claims the priority of the previous application filed by Abdurrahman Sezginer and others on August 10, 2015, U.S. Application No. 14 / 822,571 (now U.S. Application No. 9,547,892, issued on January 17, 2017) right. This application also claims the priority of US Provisional Application No. 62 / 508,369, filed on May 18, 2017. The entire contents of these applications and patents are incorporated herein by reference for all purposes. In the following description, numerous specific details are set forth to provide a thorough understanding of the present invention. The invention may be practiced without some or all of these specific details. In other instances, well-known process operations or equipment components have not been described in detail so as not to unnecessarily obscure the present invention. Although the invention will be described in conjunction with specific embodiments, it will be understood that it is not intended to limit the invention to those embodiments. Before masks are shipped to a production facility, defects of each mask are detected and other features of the mask are otherwise characterized (e.g., pattern stability, CD, CD uniformity) before wafers are fabricated using this mask (Properties) It would be advantageous to make and / or periodically requalify this mask after it has been used in the production process for a certain period of time. One embodiment of the present invention includes a technique for restoring a near-field image of a mask based on a mask image obtained from a detection tool under a plurality of different imaging parameters. This mask near-field image can then be used in many mask qualification applications. In one example, a mask near-field image can be input to a lithographic model to predict a wafer image or various wafer pattern characteristics related to how the resulting pattern will be printed on the wafer. The predicted wafer image and / or various wafer characteristics can then be analyzed for defect detection, mask qualification or requalification, and / or any other suitable measurement or inspection application. The mask near-field image itself can also be analyzed for various purposes as described further herein. The terms "mask", "mask", and "light mask" are used interchangeably herein and each may generally include a transparent substrate, such as glass, borosilicate glass, Quartz or fused silica. Opaque (or substantially opaque) materials can include any suitable material that completely or partially blocks light lithographic light (eg, deep UV or extreme UV). Exemplary materials include chromium, molybdenum silicide (MoSi), tantalum silicide, tungsten silicide, opaque MoSi on glass (OMOG), and the like. A polycrystalline silicon film can also be added between the opaque layer and the transparent substrate to improve adhesion. A low-reflection film such as molybdenum oxide (MoO ₂ ), Tungsten oxide (WO ₂ ), Titanium nitride (TiO ₂ ) Or chromium oxide (CrO ₂ ). In a specific example, an EUV mask may include multiple layers having alternating layers with different refractive indices and low absorption characteristics, such as molybdenum (Mo) and silicon (Si), and an absorber material such as Anti-reflective oxide capped tantalum boron nitride film). The term photomask refers to different types of photomasks, including but not limited to a clear-field photomask, a dark-field photomask, a binary photomask, a phase shift mask (PSM), and an alternate PSM , An attenuation or halftone PSM, a ternary attenuation PSM, a chromium-free phase lithography PSM, and a chromium-free phase lithography (CPL). A clear field mask has a transparent field or background area, and a dark field mask has an opaque field or background area. A binary mask is a mask having patterned areas that are transparent or opaque. For example, a light mask made from a transparent fused silica blank having a pattern defined by a chrome metal adsorption film may be used. Binary masks are different from phase-shift masks (PSM). One type of phase-shift mask (PSM) can include a film that only partially transmits light, and these masks are often referred to as halftone or embedded phase-shift masks. Masks (EPSM), such as ArF and KrF masks. If a phase shift material is placed on the alternate clear space of a reticle, the reticle is called an alternate PSM, an ALT PSM, or a Levenson PSM. One type of phase-shifting material applied to any layout pattern is called an attenuating or halftone PSM, which can be made by replacing an opaque material with a part of a transmissive or "halftone" film. A ternary attenuation PSM system also includes one of the completely opaque features of the attenuation PSM. The next generation of lithography has introduced the use of extreme ultraviolet radiation (EUV, wavelength 13.5 nm), which is absorbed in the normal atmosphere and glass. For this reason, the lithography EUV process takes place under vacuum, and the optical reflection lens / mirror is used to focus to an EUV light mask that will have a reflective and absorber pattern instead of a translucent and opaque pattern. FIG. 1 is a flowchart of a mask near-field recovery program 100 according to an embodiment of the present invention. The following mask recovery process 100 can be performed for a particular mask or set of masks at any suitable time in the life cycle of a mask, as described further below in various use cases of the restored mask near field. By way of example, a mask near-field can be restored before any wafers are made with this (etc.) mask, before starting a large number of wafer fabrications, or during requalification of this (etc.) mask eligibility. First, in operation 102, a mask detection tool is used to obtain at least three images of a mask according to different imaging configurations. Alternatively, two images can be used, but it has been found to work well with three images. Acquisition using different imaging configurations can be simultaneous or sequential. The acquired image need not be at the field plane. By way of example, two or more images can be acquired at a pupil plane with direct access to the diffraction intensity. Various suitable combinations of lighting and / or collection configurations may be utilized to acquire two or more images. Generally, different imaging configurations are selected to provide an image from which the near field of the mask can be calculated. Any suitable imaging or optical configuration can be selected so that the mask near field remains the same under different operating conditions. Examples include different focus settings, different illumination shapes (e.g., different directions or patterns), different polarized light for the entire illumination pupil or different parts of the illumination pupil, different apodization settings that obscure different parts of the collected beam, etc . In one embodiment, different focus settings (over focus and defocus (such as 0 focus, ± 800 or ± 1600 defocus, etc.) can be used to acquire different images. In another example, different quadrants of the illumination pupil may have different polarization settings. In another example, the imaging configuration may include high-resolution images, such as transmission images with different pupil shapes and / or different focus conditions (eg, for ArF masks). In another embodiment, three or more reflected images having different pupil shapes and / or different focus conditions may be obtained (e.g., for an EUV mask). A relatively low NA (eg, less than 0.5) can be used to image the mask with a "substantially low resolution". In contrast, a "substantially high-resolution image" generally refers to a feature in which a feature printed on a reticle appears substantially as it is formed on the reticle (in the optics of the reticle detection system used to produce the image). (Within limits), one mask, one image. A "substantially high-resolution image" of a mask is obtained by imaging a physical mask at the plane of the mask with a substantially high-resolution mask detection system (e.g., a numerical aperture (NA) greater than 0.8). Generate an image. The "substantially low NA" used to generate a reticle image can be used essentially on the reticle side by an exposure / lithography system to project an image of the reticle onto a wafer to thereby characterize the reticle. The NA transferred to the wafer is the same. In a substantially low NA image (or LNI), the mask feature may have an appearance that is substantially different from the actual mask feature. For example, a mask feature may appear to have more rounded corners in an LNI, one of the features, than an actual feature formed on the mask. In general, any suitable imaging tool can be used to mask the near-field recovery process. In the specific embodiment described herein, the results of an initial recovery process can later be used for pattern stability or defect detection evaluations of the same or other masks based on additional mask images from a particular inspection tool . For consistency in these use cases, a photomask detection system detector that will be used for subsequent inspections of the same or other photomasks or a similarly configured photomask detection system (e.g., The same method and model of the photomask detection system (a different photomask detection system) is a similarly configured detector to obtain the image of the photomask used for mask near-field recovery. In other words, images that can be used for mask recovery can be acquired under the same optical conditions as would be used during subsequent mask testing or qualification processes. In this way, the interaction between the photomask and the illumination electromagnetic waves of the detection system can be measured as directly as possible. In alternative embodiments, the means for mask near-field recovery may be different from a mask detection system. For example, the imaging tool may utilize the same wavelength (eg, wavelength (DUV-based 193.3 nm or EUV-based 13.5 nm) as the lithography system in which the reticle will be used for wafer manufacturing). In fact, any suitable electromagnetic wavelength can be used to mask near-field recovery. Referring again to the illustrated example, then, in operation 104, three or more images may be aligned with each other or each image may be aligned with a post-OPC database. For example, acquired images may be aligned via a spatial or frequency domain method. The alignment adjustment may depend on the specific geometry of the imaging system used. If different images are obtained using different collection paths, an adjustment of the images can be made to compensate for the differences in optical paths. In imaging tools, a mask having one of various patterns is illuminated by electromagnetic (EM) waves incident from many directions. This incident light is diffracted from different points of the mask pattern according to different electromagnetic field phases which interfere with each other. The near field of the mask is an electromagnetic field at a distance close to one of the wavelengths of the mask. The collection optics generally directs a diffraction-restricted portion of the light from the mask toward a detector (or wafer) to form an image. The detector detects the intensity as a result of interference due to the near field of the mask, but does not detect the phase. Although the far-field intensity is obtained in the detected signal, it is desirable to recover the mask near-field including amplitude and phase. In the illustrated embodiment, the near-field of the mask is restored and stored based on these acquired mask images, as illustrated in operation 106. Multiple images (or signals) are generally used to recover a masked near field that contains both phase and amplitude components. The near field data can be determined by a regression technique based on the images acquired from the photomask. For example, a quasi-Newton or conjugate gradient technique can be used to recover (regress) a selected portion of a reticle from an optical image or intensity of the reticle recorded at a detector plane Near field. In addition, any other suitable regression method and / or algorithm can be used to determine near-field data from one or more actual images. Masking near-field recovery can usually be achieved by solving an optimization problem, which seeks to minimize the difference between the observed intensity image and the image obtained from the assumed masked optical field. In particular, restoring the near field of a mask from the intensity image of a mask is an inverse calculation problem or a regression problem. The near field can be restored iteratively by minimizing a cost function (eg, energy or penalty function). The minimized number may be the sum of the squares of the differences between the acquired image and the intensity image calculated from the near field of the mask at the detector. In other words, the intensity images can be calculated from the final mask near field for various optical system property groups, and when the mask near field is found, these calculated images will most closely match the acquired images. Various mask near field recovery methodologies and system embodiments are further described in U.S. Patent No. 9,478,019 issued by Abdurrahman Sezginer et al. On October 25, 2016, the entirety of which is incorporated herein by reference for all purposes. in. In the case where multiple images are acquired under various optical conditions, a restored near-field mask carrying phase and amplitude information m Can be determined by the following equation: Equation 1 In Equation 1 above, Is the measured image for imaging condition α, Is a set of feature vectors describing detection imaging systems, A set of corresponding eigenvalues of the imaging system, and A non-negative weighting factor between 0 and 1. The above equations can be solved iteratively, for example, by methods such as quasi-Newton or conjugate gradients. Another example is the Gerchberg-Saxton algorithm, in which one of a field plane image and a pupil plane diffraction level can be used to solve both the amplitude and phase of an object. In one embodiment, the near field of the mask may be determined based on the acquired image via a Hopkins approximation. In another embodiment, the regression does not include a thin mask approximation. For example, the near field of a mask is calculated as an electromagnetic field that appears near the surface of the mask when illuminated by a normal incident plane wave. In lithography and inspection, a photomask is illuminated by plane waves incident from many directions. When the direction of incidence changes, according to the Hopkins approximation, the direction of the diffraction order changes but its constant amplitude and phase remain approximately unchanged. The embodiments described herein may use the Hopkins phase approximation but not the so-called thin mask or Kirchhoff approximation. The recovery formula can also vary with different norms or a regular term. R Adding and changing, this is not conducive to oscillations in the near field, as follows: The regular term R may have previous information about the near field or an expectation based on a physical understanding of the mask substrate / material. In addition, the norm used for image differences can be an l-norm and can be adjusted based on the specific needs of the optimization function. It is interesting to note that due to the wider range of incident angles of light of a higher NA and associated interference electric field components, the interference of the masked electromagnetic field vector caused by a higher NA will be larger (greater than a Low NA detection system). The actual mask can be attributed to the mask writing process and changes with the intended design pattern. Obtaining a near-field mask from the masked image means that this near-field mask is obtained from the actual physical mask rather than the design database. That is, the near field of the mask can be restored without using a design database. Masked near-field results can then be used in various applications. In one embodiment, masked near-field results can be used to predict wafer patterns using one or more models. That is, the restored mask near field can be used to simulate a lithographic image. Any suitable technique can be used to simulate a lithographic image based on a masked near-field image. One embodiment includes computing a lithographic image through a partial homology model: Equation 2 where λ _i Represents the characteristic value of lithography TCC (transfer cross coefficient); Feature vector (core) representing TCC; s Wafer stack, which contains the refractive index of the film; f Focus; and z The vertical position of the lithographic plane in the resist material. The cross-transfer coefficient (TCC) of Equation 2 may include the vector propagation of a field through a lithographic projector (including a film stack on a wafer). Before using a model to predict wafer results, the model can be calibrated to produce the most accurate results possible. The model can be calibrated using any suitable technique. A specific embodiment of the present invention provides a technique for calibrating a lithography model based on a near-field result of a mask recovered from a calibration mask. In an alternative embodiment, a design library is used to calibrate the model. For example, calibration mask images can be generated from a design library. A calibration reticle will typically be designed to have properties (s) that are substantially similar to the reticle to be inspected for defect detection or to be measured for metrology purposes. For example, the calibration mask and the test mask are preferably formed of substantially the same material having substantially the same thickness and composition. Alternatively, two photomasks may have been formed using the same process. The two reticles may not necessarily have the same pattern printed thereon, as long as the patterns on the reticle can be broken down into substantially the same segments (eg, lines with similar widths, etc.). In addition, the photomask to be detected and the photomask used to obtain an image may be the same photomask. FIG. 2 is a flowchart illustrating a model calibration process 200 according to a specific embodiment of the present invention. As shown, in operation 208, a set of initial model parameters may be used to model the photolithography process and photoresist as applied to the mask near-field image (201) recovered from a calibration mask. Alternatively, the calibration process 200 may use a simulated calibration mask image (202) simulated from a design database. The mask image can be generated from the database by simulating the mask making and imaging process on the design database. Any suitable model can be used to generate optical images for the characteristics of the design database. By way of example, this simulation may include using the coherent system summation (SOCS) or Abbe methodology described herein. There are several software packages that can simulate intensity images of an optical system from a known design database. An example was developed by Dr. Fraunhofer IISB in Erlangen, Germany. LiTHO. In the case of simulating an image 202 from the design database, the near field can be simulated first. This can be achieved by using the software package cited above and several other packages (including Prolith by KLA-Tencor, HyperLith by Panoramic Technologies, etc.) carry out. The model used to generate the wafer image based on the near field image of the mask may include only the effects of a photolithography scanner, and it may also include the effects of resist, etching, CMP, or any other wafer process. An exemplary process simulation model tool is available from Prolith of KLA-Tencor, Inc. of Milpitas, California. Resist and etching processes can be closely or approximately modeled. In a specific embodiment, the model may be in the form of a compact resist model, which includes a 3D acid diffusion inside a particular resist material and a configuration that imposes boundary conditions therein, and is applied to form one of the latent images Single threshold. It should be noted that the modeled lithography tool may have a lighting shape or light source different from the mask detection tool used to obtain the actual image of the mask. In a particular embodiment, the modeled lithography tool may have a light source that is the same as or similar to a mask detector tool. Other simulation methods can be used, such as SOCS or Abbe. An algorithm commonly referred to as coherent system summation (SOCS) attempts to transform an imaging system into a bank of linear systems whose output is squared, scaled, and summed. The SOCS approach has been described elsewhere, including Nicolas Cobb's PhD thesis "Fast Optical and Process Proximity Correction Algorithms for Integrated Circuit Manufacturing" (University of California, Berkeley, Spring 1998). The Abbe algorithm involves calculating object images one at a time for each point source, and then summing the intensity images together taking into account the relative intensity of each source point. The input of the model and its modeling parameters includes a set of process conditions applied to the restored near-field mask. That is, the model is configured to simulate different sets of process conditions on the reconstructed near-field mask (or simulated mask image). Each set of process conditions generally corresponds to a set of wafer process parameters that are characterised or partially characterised as a wafer process for forming a wafer pattern from a mask. For example, a specific focus and exposure setting can be entered into the model. Other adjustable model parameters can also include one or more of the following parameters: a projection lens wavefront parameter, an apodization parameter, a chromatic aberration focus error parameter, a vibration parameter, a resist profile index, and a resist float Slag measurement, top loss measurement, etc. Using this model with different sets of process conditions can result in a set of simulated wafer or resist pattern images formed by the reconstructed near-field mask under different processing conditions, and these simulated wafer images can be used for pattern stability and Defect detection evaluation, as described further herein. In operation 216, a calibration mask may also be used to fabricate one of the calibration wafers from which the actual image was obtained. In one example, a critical dimension (CD) scanning electron microscope (SEM) is used to acquire actual images. Other imaging tools can be used, but a high-resolution tool is preferred. In general, a calibration wafer will contain any number of known structures, which can vary widely. The structure may be in the form of a grating that is usually periodic. Each grating can be periodic in one direction (X or Y) (for example, a linear spatial grating), or it can be periodic in two directions (X and Y) (for example, a linear grating) Raster space raster). An example of a grid space grating may include a line array in the Y direction, where each line is segmented in the X direction. Another example of grid space is a one-point structure array. That is, each structure can take the form of a one-line space grating, a grid space grating, a checkerboard pattern structure, and the like. Structural design characteristics can each include line width (width at a specific height), line space width, line length, shape, sidewall angle, height, pitch, grating orientation, top profile (top rounded or T-top level ), Bottom contour (footing), etc. The calibration wafer may contain structures with different combinations of these characteristics. As should be understood, different structural characteristics (such as different widths, pitches, shapes, pitches, etc.) exhibit different responses to the focal point, and therefore the calibration mask preferably includes different structures with different characteristics. In a specific embodiment, the calibration wafer may take the form of a "design-of-experience (DOE)" wafer having one of different measurement points subjected to different processing conditions. In a more general embodiment, process parameter variations are organized in a pattern on the surface of a semiconductor wafer (referred to as a DOE wafer). In this way, the measurement points correspond to different locations on the surface of the wafer with different associated process parameter values. In one example, the DOE pattern is a focus / exposure matrix (FEM) pattern. Generally, a DOE wafer exhibiting a FEM pattern includes a grid pattern of measurement points. In one grid direction (for example, the x direction), the exposure dose changes while the depth of focus remains constant. In an orthogonal grid direction (for example, the y direction), the depth of focus changes while the exposure dose remains constant. In this way, the measurement data collected from the FEM wafer includes data associated with known changes in focus and dosage process parameters. FEM measurement points are generally positioned across the focal-exposure matrix wafer. In fact, there can generally be one or more measurement points per field. Each field may be formed using a different combination of focus and exposure combinations (or may be just focus or exposure). For example, a first field may be generated using a first combination, and a second field may be generated using a second combination different from the first combination. Multiple combinations can be generated using changing focus and changing exposure, changing focus-constant exposure, constant focus-changing exposure, and the like. The number of measurement points can also be different. The number of dots per field is usually smaller on the production wafer because the real estate on the production wafer is extremely precious. Furthermore, measurements performed on a production wafer are less due to time constraints in production than measurements performed on a focus exposure matrix wafer. In one embodiment, a single point is measured per field. In another embodiment, multiple points are measured per field. In most FEM cases, the measurement point structure is formed from the same designed pattern using different processing parameters. It should be noted, however, that different focus exposure matrices may have different structures. For example, a first matrix may be performed using a first raster type, and a second matrix may be performed using a second raster type different from the first raster type. In an alternative embodiment, a simulated calibration image (202) generated from a design database for a calibration mask can be used as input to the model. That is, the model can be calibrated without recovering the near field from a physical calibration mask. Instead, the lithographic image is simulated by simulating (non-recovering) the near field from the design database and applying the lithography imaging model to the simulated near field to achieve a lithographic result comparable to the actual result from the wafer (216) . In general, optical signal data associated with known changes in process parameters, structural parameters, or both of any group can be envisaged. Regardless of the form, the calibration wafer structure can be printed on many different wafer layers. In particular, a standard lithography process is generally used (e.g., a circuit image is projected through a photomask and onto a silicon wafer coated with a photoresist) to print a printed structure onto a photoresist Layer. The wafer may be one of the calibration wafers having a layer of material corresponding to the material normally present on the product wafer at this step in the testing process. The printed structure can be printed over other structures in the lower layer. The calibration wafer can be one of the product wafers with the potential to produce a working device. The calibration wafer may be one of the simple wafers used for calibration models only. The calibration wafer may be the same wafer used to calibrate the OPC design model. More than one calibration wafer can be used to calibrate the lithographic model. When using multiple calibration wafers, the same or different calibration masks can be used. Different calibration masks can have patterns with different sizes to generate a wider range of image data. The process parameters used to form the calibration structure are generally configured to maintain the characteristics of the pattern within the desired specifications. For example, the calibration structure may be printed on a calibration wafer as part of a calibration procedure, or they may be printed on a production wafer during production. During production, calibration structures are typically printed in scribe lines between device regions (eg, the dies defining an IC) placed on a production wafer. The measurement point may be a dedicated calibration structure disposed around the device structure, or it may be part of the device structure (eg, a periodic portion). As should be understood, it may be more difficult to use part of the device structure, but it tends to be more accurate because it is part of the device structure. In another embodiment, the alignment structure may be printed across an entire alignment wafer. Referring again to FIG. 2, in operation 210, a corresponding modeling result and a calibration result (eg, an image) may be compared. Then, in operation 212, it may be determined whether the model parameters will be adjusted. If the model parameters are to be adjusted, the model parameters are adjusted in operation 214 and the process 200 repeats operation 208 to model the lithography process (and the resist) using the adjusted parameters. The model parameters can be adjusted until one of the differences between the model image and the calibration image has reached a minimum value that is also below a predefined threshold. The minimized number may be the sum of the squares of the differences between the acquired calibration image and the simulated image. The output of this process 200 is a lithography / resist model and its final model parameters. This set of model parameters overcomes the technical obstacles associated with mask process modeling and mask 3D diffraction calculations by using the nature of the mask near field. The simulated wafer pattern based on the recovered mask near-field results can be used for many mask inspection, measurement, and / or qualification purposes. In one embodiment, a mask qualification is performed by assessing whether the restored mask near-field will likely cause wafer pattern defects under a range of simulated wafer fabrication conditions. For defect detection, the printability of a mask defect on a wafer is important, and the printability of a mask defect directly depends on the near field of the mask and the lithography system. After obtaining a final calibrated lithography / resist / etching model for one of a specific process (regardless of how the model is obtained), this model can be used to produce accurate masks from this mask before wafer fabrication using a mask Wafer planar resist images (for example, after development or etching) or used to requalify this mask eligibility. These resist images will allow us to evaluate wafer images of any inspection pattern with high fidelity and through different focus and exposure settings or other lithographic parameters. Because this evaluation process can occur before wafer fabrication, the cycle of qualification and defect detection can be significantly reduced. The simulated wafer image also enables the source of different patterning problems to be separated by comparing simulated wafer images after lithography, after application of the resist model, and after etching. FIG. 3 is a flowchart illustrating a mask qualification process 300 according to an embodiment of the present invention. In operation 302, for example, a mask near-field image is restored for a specific mask based on an image acquired from the specific mask. This operation may include the mask near-field recovery operation of FIG. 1. After obtaining a near field of the mask, in operation 303, the lithographic process (and the resist) may also be modeled using the final model parameters regarding the restored near field of the mask. For example, a final model is used to simulate a wafer image using a masked near-field image. Next, in operation 322, the simulated wafer pattern may be evaluated to determine pattern stability and / or positioning defects. In general, it can be determined whether the corresponding photomask may cause unstable or defective wafer patterns. In one embodiment, a plurality of different process conditions (such as focus and dose) are used to apply a model to a mask near-field image or result to evaluate the mask design stability under varying process conditions. FIG. 4A is a flowchart illustrating a process 400 for determining the stability of a wafer pattern according to an exemplary application of the present invention. First, in operation 402, each test image may be aligned with its corresponding reference image, and these images are also generated by the model under different sets of process conditions. The model calculates different test images and reference images under different processing conditions / parameters. In operation 404, each pair of aligned images may be compared to each other to obtain one or more wafer pattern differences. Then, in operation 406, the threshold value may be associated with each wafer pattern difference. Wafer pattern differences and their associated thresholds can be used together to characterize pattern stability. That is, the amount of deviation (pattern difference) of a particular pattern under different simulation process conditions and whether this deviation crosses an associated threshold value together characterize the pattern stability. A process window of a manufacturing process specifies an expected or defined process deviation amount under which the resulting patterns are evaluated to ensure that they will remain stable or within certain specified deviation tolerances (eg, threshold values). Different thresholds for assessing pattern stability can be assigned to different areas of the mask and thereby correspond to the wafer pattern. Thresholds can all be the same or different based on various factors (such as pattern design background, pattern MEEF (or mask error enhancement factor as described further below) level, or sensitivity of device performance to wafer pattern variations). For example, compared to a semi-dense area of the mask, we can choose a closer threshold for the pattern in a dense area. Optionally, a set of initial hot spots or pattern weakness areas can be identified in both the reference mask pattern and the test mask pattern. For example, a designer may provide a list of one of the design hotspots that is critical to the function of the device. For example, an area defined as a hot spot may be assigned a detection threshold, and a non-hot spot area may be assigned a higher threshold (for defect detection). This difference can be used to optimize detection resources. This pattern stability assessment can be used to facilitate mask qualification, thereby overcoming many challenges in this area. As the density and complexity of integrated circuits (ICs) continue to increase, detecting photolithographic mask patterns becomes increasingly challenging. Each new-generation IC has denser and more complex patterns that currently meet and exceed the optical limits of lithography systems. To overcome these optical limitations, various resolution enhancement techniques (RET), such as optical proximity correction (OPC), have been introduced. For example, OPC helps overcome some diffraction restrictions by modifying the light mask pattern so that the resulting printed pattern corresponds to the original desired pattern. Such modifications may include disturbances in the size and edges of the main IC features (ie, printable features). Other modifications involve adding serifs to the corners of the pattern and / or providing nearby sub-resolution assistance features (SRAF), which is not expected to result in printed features and therefore are referred to as non-printable features. It is expected that these non-printable features cancel out pattern disturbances that would otherwise occur during the printing process. However, OPC makes the mask pattern even more complicated and often very different from the resulting wafer image. In addition, OPC defects are usually not converted into printable defects. The increased complexity of light mask patterns and the fact that all pattern elements are not expected to directly affect the printed pattern make the task of detecting meaningful pattern defects of light masks much more difficult. As the semiconductor industry moves toward even smaller features, cutting-edge manufacturers are starting to use even more exotic OPCs, such as inverse lithography (ILT), which results in highly complex patterns on the mask. Therefore, it is highly desirable to know the mask write fidelity and its wafer print quality before physically manufacturing the wafer. A measure of the importance of a defect is its MEEF or mask error enhancement factor. This factor correlates the size of the defect in the mask plane with the magnitude of the defect it will affect the printed image. High MEEF defects have a high effect on printed patterns; low MEEF defects have little or no effect on printed patterns. A pattern that is too small in a dense thin line portion of a pattern is an example of a defect with a high MEEF, where a small mask plane size error can cause one of the printed patterns to completely collapse. An isolated small pinhole is one example of a defect with a low MEEF, where the defect itself is too small to print and is far enough from the nearest major pattern edge to not affect how the edge is printed. Such examples show that the MEEF of a defect is a slightly more complex function of the defect type and the pattern background in which the defect is located. In addition to higher MEEF mask defects that cause more significant wafer defects, specific design patterns and corresponding mask patterns can also be more robust to process variations than other designs and mask patterns. When the manufacturing process starts to deviate from optimal process conditions, certain mask patterns can cause more significant wafer pattern disturbances and defects. FIG. 4B is a flowchart of a defect detection program 450 according to another embodiment of the present invention. In operation 452, each modeled test wafer image may be aligned with its corresponding reference image. In one embodiment, a die-to-die or cell-to-cell alignment can be accomplished. In another embodiment, the modeled test wafer image is aligned with a reference image generated from the corresponding OPC design. For example, a post-OPC design is processed to simulate the mask making process for this design. For example, the corners are rounded. Generally, a reference image can be derived from the same die as an earlier test image, from an adjacent identical die, or generated from a design database. In a specific example, a reference image is obtained from one of the "gold" grains that has been proven to be defect-free (eg, immediately after manufacturing the mask and qualifying the mask). The gold mask image obtained from the mask when the known mask is free of defects can be stored and used later to calculate the gold mask near-field image and wafer image when needed. Alternatively, the near-field image of the golden mask can be stored for future access without the need to calculate the near-field during future inspections. In operation 454, the pairs of aligned test images and reference images are compared based on an associated threshold value to locate mask defects. Any suitable mechanism can be used to associate a threshold with a particular mask area, as described further above. Any suitable metric can be compared between the test image and the reference image. For example, the profile of the test and reference wafer images can be compared as a measure of edge placement error (EPE). Then, in operation 456, the corresponding simulated wafer defect area and its corresponding reference pre-OPC area may be compared for each mask defect. That is, the simulated wafer pattern is evaluated to determine whether a mask defect causes a wafer defect with an expected design change. Referring again to FIG. 3, in operation 324, it can then be determined whether the design is defective based on the simulated mask image. In one embodiment, it is determined whether the design pattern under an specified range (or process window) of one of the process conditions results in unacceptable wafer pattern variations. Determine if there is a significant difference due to process variability. If the difference between different processed wafer patterns is higher than a corresponding threshold, then these wafer patterns can be considered defective. These system defects are called hot spots. It can also be determined whether any difference between an analog wafer pattern from a photomask and its corresponding pre-OPC pattern is higher than a predefined threshold. If it is determined that the design is defective, the design may be modified in operation 332. Once a reticle design is verified, the reticle may still contain hot spots that should be monitored. The following operations are described as being performed on a mask that has at least some identified hot spots. Of course, if the mask does not contain any identified hotspots, the following operations in FIG. 3 can be skipped and the masks are used without hotspot monitoring during production and inspection. In the illustrated example, if the design is not considered defective, a determination can be made in operation 326 as to whether any hot spots can be monitored. If the hotspot is determined to be monitorable, the hotspot may be monitored during the wafer process in operation 334. For example, a hot pattern can be monitored during wafer fabrication to determine whether the process has deviated from specifications and has caused the corresponding wafer pattern to have key parameters that change to unacceptable values. One embodiment may involve setting a relatively high MEEF level to detect masks and / or wafer patterns corresponding to hot spots. As conditions move further away from the nominal process conditions, the CD or EPE can grow larger and endanger the integrity of the wafer process. Hotspot patterns can be identified only when a test mask pattern changes by a predefined amount, regardless of how this change is compared to the original intended design (e.g., pre-OPC data). In other words, a significant change in one of the physical mask patterns under different process conditions may indicate a problem with the expected design pattern. The difference between the corresponding modeled image portions indicates the difference in the effects of the process conditions on the designed pattern and the manufactured mask. The differences associated with a particular design pattern are often referred to as "design hotspots" or simply "hot spots" and represent weaknesses in the design regarding specific process conditions that have been checked (and possibly also on manufactured masks). Examples of the types of differences that can be found between modeled images under different process conditions are CD (critical size) or EPE (edge placement error). In another embodiment, if the model is applied to a post-OPC design database, the resulting wafer pattern may correspond to a pattern that the designer intends to print on the wafer. Optionally, the results of applying the model to a post-OPC database can be used with modeled images to improve hotspot detection. For example, one of the models of the post-OPC database only considers design effects, and thus can be used to separate the effects of wafer processing on design and the effects of wafer processing on manufactured masks. The modeled pattern from the near field of the mask can be compared with the modeled wafer image from the corresponding post OPC pattern. For example, when a group of modeled wafer patterns of different process changes match the corresponding modeled OPC wafer pattern of the same process change, the source of the change in the wafer pattern (or resist pattern) due to the process change can be determined Design patterns that can be redesigned or monitored rather than derived from a defect in the mask pattern. However, if a change on a wafer due to a process change from a post-OPC database is different from a change on a wafer due to the same process change from a recovered mask (or mask near field), then this The hot spot is considered to originate from a hot spot that can be repaired or monitored from the actual mask. The simulated wafer image differences can also be analyzed to determine wafer CD uniformity (CDU) metrics across the die or over time (when mask changes occur during exposure during the manufacturing process). For example, if the resolution is high enough, the CD of each target of each image can be measured by analyzing and measuring the distance between the edges of the targets. Alternatively, the intensity difference between the reference image and the test image can be calibrated and transformed into a CD variation, such as by Carl E. Hess et al., U.S. Patent Application No. 14 / 664,565, filed on March 20, 2015, and U.S. Patent Application No. 14 / 390,834, filed by Rui-fang Shi et al. On October 6, 2014 The entire text of these applications is incorporated herein by reference for all purposes. In operation 328, it may also be determined whether the photomask should be repaired. It can be determined that the expected wafer pattern change exceeds the specifications of the process window expected to be used during the lithography process. In certain cases, the reticle may contain one of the defects repaired in operation 336. Then, the mask eligibility can be re-qualified. Otherwise, in operation 330, if the photomask cannot be repaired, the photomask may be discarded. Then, a new photomask can be manufactured and requalified. In addition to using a restored mask near-field image to simulate a wafer image during a qualification process, or instead of using a restored mask near-field image to simulate a wafer image during a qualification process, you can also directly A mask near-field image or result is evaluated during mask qualification. FIG. 5 is a flowchart illustrating a mask qualification process 500 applied to a restored near-field image or result according to an alternative embodiment of the present invention. First, in operation 502, a mask near-field result is restored from a mask. The near-field image of the mask can be restored for a specific mask based on the image acquired from the specific mask. This operation may be practiced similar to the mask near-field recovery operation of FIG. 1. In addition, some operations of FIG. 5 may be implemented in a manner similar to that of FIG. 3, but for the restored mask near-field image, the intensity and / or phase components of the image are included. As shown, then, in operation 522, the mask near-field results may be evaluated to characterize and / or locate defects. Generally, it can be determined whether the corresponding photomask is defective or has hot spots that need to be monitored. More specifically, some of the techniques described herein for evaluating simulated wafer images can be implemented on masked near-field images. During a defect detection process, any suitable measure of the test mask near-field image and the reference mask near-field image can be compared. For example, the intensity and / or phase can be compared. Different defect types will have different effects on intensity and / or phase values. These discrepancies can be judged to be true defects that may cause a defective wafer or identify hot spots or areas that can be repaired or monitored (as opposed to non-impacting defects). For example, then, in operation 524, it may be determined whether the design is defective. If the design is determined to be defective, the design may be modified in operation 532. For example, it can be determined whether any difference between a mask near-field image and its corresponding post-OPC-based near field is higher than a predefined threshold for detecting defects. The process 500 may continue to determine whether to monitor wafer hot spots, repair the mask, or redesign the mask, as described above. If the design is not considered to be defective, a determination can be made in operation 526 as to whether any hot spots can be monitored. For example, it can be determined that any intensity and / or phase difference between a test mask near-field image and a reference mask near-field image is close to an associated threshold. For example, if it is determined that a hot spot can be monitored, the hot spot can be monitored during the wafer process in operation 534. For example, a hot pattern can be monitored during wafer fabrication to determine whether the process has deviated from specifications and has caused the corresponding wafer pattern to have key parameters that change to unacceptable values. One embodiment may involve setting a relatively high sensitivity level to detect masks and / or wafer patterns corresponding to hot spots. As conditions move further away from the nominal process conditions, CD errors or EPEs can become large and endanger the integrity of the wafer process. In operation 528, it may also be determined whether the photomask will be repaired. In certain cases, the reticle may contain one of the defects repaired in operation 536. Then, the mask eligibility can be re-qualified. Otherwise, in operation 530, if the photomask cannot be repaired, the photomask may be discarded. Then, a new photomask can be manufactured and requalified. The specific technology of the present invention provides mask pattern qualification and early detection of weak patterns or hot spots on a physical mask before starting wafer fabrication. In addition to providing a mask-based image recovery mask near field, wafer process effects (including many settings for focus and exposure, and effects of wafer resist, etching, CMP, and any other wafer process) How a full range affects the wafer pattern. Since only the mask image is used to restore the near field of the mask without using the mask design data, prior knowledge of the mask is not required. Since the mask pattern is roughly four times larger than the wafer pattern, it can be determined that the pattern is more accurately positioned relative to the design database. The above-mentioned technology can also be extended to any suitable type of mask, such as the pattern qualification of EUV masks. The techniques of this invention may be implemented in any suitable combination of hardware and / or software. FIG. 6 is a graphical representation of an exemplary detection system 600 in which the techniques of the present invention can be implemented. The detection system 600 may receive input 602 from a high NA detection tool or a low NA detector that mimics a scanner (not shown). The detection system may also include: a data distribution system (for example, 604a and 604b) for distributing the received input 602; an intensity signal (or patch) processing system (for example, a block processor and a photomask) Qualification system (e.g., 612)) for masking near-field and wafer recovery, process modeling, etc .; a network (e.g., switched network 608) that allows communication between inspection system components ; A mass storage device 616 is selected; and one or more detection control and / or inspection stations (for example, 610) for inspecting the near field intensity and phase (value, image or difference) of the mask, the mask / crystal Circle image, identified hot spots, CD, CDU map, process parameters, etc. Each processor of the detection system 600 may typically include one or more microprocessor integrated circuits and may also include interfaces and / or memory volume circuits, and may additionally be coupled to one or more shared and / or global memory devices. . The detector or data acquisition system (not shown) used to generate the input data 602 may take the form of any suitable instrument (for example, as described further herein) for obtaining the intensity signal or image of a photomask. For example, a low NA detector may construct an optical image or generate intensity values for a portion of a mask based on a portion of the detected light that is reflected, transmitted, or otherwise directed to one or more light sensors. The low NA detector can then output an intensity value or image. The low NA detection tool is operable to detect and collect reflected and / or transmitted light as an incident beam is scanned across blocks of a mask. As described above, the incident light beam can be scanned across the mask scanning strips each including a plurality of blocks. Light is collected in response to this incident beam from a plurality of points or sub-regions of each block. The low NA detection tool is generally operable to convert this detected light into a detected signal corresponding to an intensity value. The detected signal may take the form of an electromagnetic waveform having an amplitude value corresponding to different intensity values at different positions of the mask. The detected signal can also take the form of a simple list of intensity values and one of the associated mask point coordinates. The detected signal may also take the form of an image having different intensity values corresponding to different positions or scanning points on the mask. Two or more images of the mask can be generated after the entire position of the mask is scanned and converted into a detected signal, or two can be generated when each part of the mask is scanned with the final two or more images Parts of one or more images to complete the mask after scanning the entire mask. The detected signals can also take the form of aerial images. That is, an aerial imaging technique can be used to simulate the optical effects of the photolithography system to generate an aerial image of a photoresist pattern exposed on the wafer. Generally, the optics of a photolithography tool are simulated to generate an aerial image based on a detected signal from a photomask. The aerial image corresponds to a pattern generated by light that enters the photoresist layer of a wafer through the photolithography optics and the photomask. In addition, a photoresist exposure process for a specific type of photoresist material can be simulated. Incident or detected light may pass through any suitable spatial aperture to produce any incident or detected light profile at any suitable incident angle. For example, a specific beam profile such as dipole, quadrupole, quasar, ring, etc. can be generated using programmable illumination or detection aperture. In a particular example, light source mask optimization (SMO) or any pixelated lighting technique may be implemented. Incident light may also travel through a linear polarizer to linearly polarize all or a portion of the illumination pupil in one or more polarized light. The detected light can pass through the apodization component to block a specific area of the collected light beam. The intensity or image data 602 may be received via a network 608 by a data distribution system. The data distribution system may be associated with one or more memory devices (such as a RAM buffer) for holding at least a portion of the received data 602. Preferably, the total memory is large enough to hold one entire sample of data. For example, a gigabyte of memory works well for a sample of 1 million by 1000 pixels or points. Data distribution systems (e.g., 604a and 604b) may also control the distribution of portions of the input data 602 received to processors (e.g., 606a and 606b). For example, the data distribution system may post data of a first block to a first block processor 606a, and may post data of a second block to a block processor 606b. Multiple sets of data from multiple blocks can also be delivered to each block processor. The block processor may receive an intensity value or an image corresponding to at least a portion of the mask or the block. The block processors may also be individually coupled to or integrated with one or more memory devices (such as providing local memory functions, such as a DRAM device holding a received data portion) (not shown). Preferably, the memory is large enough to hold data corresponding to a block of the mask. For example, 8 megabytes of memory works well for an intensity value or an image corresponding to a block of 512 by 1024 pixels. Alternatively, the block processors may share memory. Each set of input data 602 may correspond to one scanning band of the photomask. One or more sets of data can be stored in the memory of the data distribution system. The memory can be controlled by one or more processors in the data distribution system, and the memory can be divided into a plurality of partitions. For example, the data distribution system may receive data corresponding to a portion of a scan zone into a first memory partition (not shown), and the data distribution system may receive another data corresponding to another scan zone to a first zone. Two memory partitions (not shown). Preferably, each of the memory partitions of the data distribution system maintains only the portion of data that will be delivered to a processor associated with this memory partition. For example, the first memory partition of the data distribution system may hold the first data and post the first data to the block processor 606a, and the second memory partition may hold the second data and post the second data to the block Block processor 606b. The data distribution system can define and allocate groups of data based on any suitable parameters of the data. For example, data may be defined and assigned based on the corresponding positions of the blocks on the reticle. In one embodiment, each scan band is associated with a range of row positions corresponding to the horizontal position of pixels within the scan band. For example, rows 0 to 256 of the scanning zone may correspond to a first block, and the pixels in these rows will include a first image or a first set of intensity values that are delivered to one or more block processors. Similarly, the rows 257 to 512 of the scanning zone may correspond to a second block, and the pixels in these rows will include a second image or a second set of intensity values that are delivered to different block processors (s). Inspection equipment can be adapted to inspect semiconductor devices or wafers and optical masks as well as EUV masks or masks. Examples of suitable detection tools are Teron ™ operating at 193 nm or TeraScan ™ DUV photomask inspection tools available from KLA-Tencor, Milpitas, California. Other types of samples that can be detected or imaged using the detection device of the present invention include any surface, such as a flat panel display. A detection tool may include: at least one light source for generating an incident beam; illumination optics for directing the incident beam onto a sample; collection optics for directing emission from the sample in response to the incident beam An output beam; a sensor for detecting the output beam and generating an image or signal of the output beam; and a controller / processor for controlling the components of the detection tool and promoting the generation of a mask near field And analysis techniques, as described further herein. In the following exemplary detection system, the incident beam may be in any suitable form of co-dimming. In addition, any suitable lens configuration can be used to direct the incident beam toward the sample and the output beam originating from the sample toward a detector. The output beam can be reflected or scattered from the sample or transmitted through the sample. For EUV mask inspection, the output beam is usually reflected from the sample. Likewise, any suitable detector type or any suitable number of detection elements may be used to receive the output beam and provide an image or a signal based on the characteristics (eg, intensity) of the received output beam. A generalized photolithography tool will be described first, but an EUV light lithography tool will typically have only reflective optics. FIG. 7A is a simplified schematic representation of one of a typical lithographic system 700 that can be used to transfer a mask pattern from a light mask M to a wafer W according to a particular embodiment. Examples of such systems include scanners and steppers, and more specifically TWINSCAN NXT: 1970Ci stepping and scanning systems available from ASML, Veldhoven, Netherlands. Generally, an illumination source 703 directs a light beam through an illumination optical device 707 (eg, a lens 705) to a light mask M positioned in a mask plane 702. The illumination lens 705 has a numerical aperture 701 at the plane 702. The value of the numerical aperture 701 affects which defects on the light mask are significant lithographic defects and which defects are not significant lithographic defects. A portion of the light beam traveling through the light mask M forms a patterned optical signal that is guided through the imaging optics 713 and transferred onto a wafer W in an initial pattern. In a reflection system (not shown), the illumination beam is reflected from a specific portion of the mask M (and thereby absorbed by other portions of the mask M) and forms one of the reflective imaging optics guided through a wafer W Patterned signal. The detection tool may utilize similar components or be configured similarly to the light lithography tool described above, for example, LNI capabilities. However, detection tools may be alternatively or additionally configured to produce high-resolution images. FIG. 7B provides a schematic representation of an exemplary detection system 750 having illumination optics 751a and including an imaging lens with a relatively large numerical aperture 751b at a mask plane 752 according to a particular embodiment. For example, the numerical aperture 751b at the mask plane 752 of the inspection system may be much larger than the numerical aperture 701 at the mask plane 702 of the lithography system 700, which will cause a difference between the test image and the actual printed image. The detection techniques described herein can be implemented on a variety of specially configured detection systems, such as the detection system shown schematically in Figure 7B. The illustrated system 750 includes an illumination source 760 that generates a light beam that is guided through the illumination optics 751 a to a light mask M in a mask plane 752. Examples of the light source include a laser light source (eg, a deep UV or gas laser generator), a filter lamp, an LED light source, and the like. In certain embodiments, a light source can generally provide high pulse repetition rate, low noise, high power, stability, reliability, and scalability. It should be noted that although an EUV scanner is at 13. It operates at a wavelength of 5 nm, but one of the detection tools for an EUV mask need not operate at the same wavelength (although it can). In one example, the light source is a 193 nm laser. Illumination optics 751a may include a beam steering device for precise beam positioning and a beam adjustment device that may provide light level control, speckle noise reduction, and high beam uniformity. The beam steering and / or beam adjusting device may be a physical device separate from, for example, a laser. The illumination optics 751a may also include optics for controlling polarization, focus, magnification, illumination intensity distribution, and the like. As described above, the detection system 750 may have a numerical aperture 751b at the mask plane 752 that may be equal to or larger than a numerical aperture of a mask plane of the corresponding lithography system (eg, the element 701 in FIG. 7A). The to-be-detected light mask M is placed on a mask stage at a mask plane 752 and is exposed to a light source. The depicted detection system 750 may include detection optics 753a and 753b, and these detection optics 753a and 753b may also include microscope magnification optics that are designed to provide, for example, 60x to 200x or greater magnification for enhanced detection Device. The collection optics 753a and 753b may include any suitable optics for adjusting the output light / beam. For example, the collection optics 753a and 753b may include optics for controlling focus, pupil shape, polarization analyzer settings, and the like. In a transmission mode, the patterned image from the mask M can be guided through a collection of optical elements 753a, which project the patterned image onto a sensor 754a. In a reflection mode, a collection element (eg, beam splitter 776 and detection lens 778) directs and captures the reflected light from the mask M onto the sensor 754b. Although two sensors are shown, a single sensor can be used to detect reflected light and transmitted light during different scans of the same mask area. Suitable sensors include charge-coupled devices (CCD), CCD arrays, time delay integration (TDI) sensors, TDI sensor arrays, photomultiplier tubes (PMT), and other sensors. The row of illumination optics can be moved relative to the mask stage and / or by any suitable mechanism relative to a stage moved by a detector or camera to scan a block of the mask. For example, a motor mechanism can be used to move the stage. For example, the motor mechanism can be formed by a screw driver and a stepper motor, a linear driver with a feedback position, or an actuator and a stepper motor. The system 700 may utilize one or more motor mechanisms to move any of the system components relative to the illumination or collection optical path. The signals captured by each sensor (e.g., 754a and / or 754b) can be processed by a computer system 773 or more generally by one or more signal processing devices, which can be individually Contains an analog-to-digital converter configured to convert analog signals from each sensor into digital signals for processing. Computer system 773 typically has one or more processors coupled to input / output ports and one or more memories via appropriate buses or other communication mechanisms. The computer system 773 may also include one or more input devices (eg, a keyboard, mouse, joystick) to provide user input, such as changing focus and other test recipe parameters. The computer system 773 may also be connected to a stage to control, for example, the same position (eg, focus and scan), and to other detection system components to control other detection parameters and configurations of these detection system components. The computer system 773 may be configured (e.g., with programmed instructions) to provide a user interface (e.g., a computer screen) to display mask near-field intensity and phase (value, image, or difference), mask / crystal Circle image, identified hot spots, CD, CDU map, process parameters, etc. The computer system 773 may be configured to analyze reflected and / or transmitted detected and / or analog signals or images, the intensity, phase, and / or other characteristics of the near-field results of the recovered reticle. Computer system 773 may be configured (e.g., with programmed instructions) to provide a user interface (e.g., on a computer screen) to display the resulting intensity and / or phase values, images, and other detection characteristics. In a particular embodiment, the computer system 773 is configured to implement the detection techniques detailed above. Because such information and program instructions can be implemented on a specially configured computer system, this system contains program instructions / computer code that can be stored on a computer-readable medium for performing the various operations described herein. . Examples of machine-readable media include, but are not limited to: magnetic media such as hard disks, floppy disks, and magnetic tapes; optical media such as CD-ROM disks; magneto-optical media such as optical disks; and specially configured to store and execute program instructions Hardware devices, such as read-only memory (ROM) and random access memory (RAM). Examples of program instructions include both machine code generated by a compiler and files containing higher-level code executable by a computer using an interpreter. FIG. 7B shows an example in which an illumination beam is directed toward the sample surface at a substantially normal angle relative to the surface being detected. In other embodiments, an illumination beam can be directed at an oblique angle, which allows separation of the illumination beam from the reflected beam. In these embodiments, an attenuator may be positioned on the reflected beam path to attenuate a zeroth order component of the reflected beam before the reflected beam reaches a detector. In addition, an imaging aperture can be positioned on the reflected beam path to shift the phase of the zeroth order component of the reflected beam. It should be noted that the above description and drawings should not be construed as limiting specific components of the system and that the system may be embodied in many other forms. For example, the intended inspection or measurement tool may have any suitable feature from any number of known imaging or metrology tools configured to detect defects and / or resolve key features of a mask or wafer. For example, a detection or measurement tool may be adjusted for bright field imaging microscopy, dark field imaging microscopy, all-sky imaging microscopy, phase contrast microscopy, polarized contrast microscopy, and homogeneous detection microscopy. Surgery. It is also expected that single-image and multi-image methods can be used to capture the image of the target. These methods include, for example, single-grip, double-grip, single-grip coherent detection microscopy (CPM), and dual-grip CPM methods. It is also contemplated that non-imaging optical methods, such as scatterometry, form part of the detection or metrology equipment. Although the foregoing invention has been described in considerable detail for purposes of clarity of understanding, it will be understood that certain changes and modifications may be practiced within the scope of the accompanying patent application. It should be noted that there are many alternative ways of implementing the processes, systems, and devices of the present invention. Therefore, this embodiment is to be considered as illustrative and not restrictive, and the invention is not limited to the details given herein.

100‧‧‧Mask near-field recovery procedure / mask recovery process

102‧‧‧Operation

104‧‧‧Operation

106‧‧‧Operation

200‧‧‧ Model Calibration Process / Procedure

201‧‧‧Mask near-field image restored from calibration mask

202‧‧‧Simulated calibration mask image simulated from design database / Simulated image from design database / Simulated calibration image generated from design database

208‧‧‧Operation

210‧‧‧ Operation

212‧‧‧Operation

214‧‧‧Operation

216‧‧‧operation / actual results from wafer

300‧‧‧ Mask Qualification Process

302‧‧‧Operation

303‧‧‧operation

322‧‧‧ Operation

324‧‧‧ Operation

326‧‧‧operation

328‧‧‧operation

330‧‧‧ Operation

332‧‧‧Operation

334‧‧‧Operation

336‧‧‧Operation

400‧‧‧ process

402‧‧‧operation

404‧‧‧operation

406‧‧‧Operation

450‧‧‧ Defect detection procedure

452‧‧‧ Operation

454‧‧‧ Operation

456‧‧‧ Operation

500‧‧‧Photomask qualification process / procedure

502‧‧‧operation

522‧‧‧operation

524‧‧‧ Operation

526‧‧‧operation

528‧‧‧ Operation

530‧‧‧operation

532‧‧‧operation

534‧‧‧operation

536‧‧‧operation

600‧‧‧ Detection System

602‧‧‧Enter / input data / intensity or image data

604a‧‧‧Data Distribution System

604b‧‧‧Data Distribution System

606a‧‧‧The first block processor

606b‧‧‧block processor

608‧‧‧switched network

610‧‧‧Inspection control / viewing station

612‧‧‧block processor and photomask qualification system

616‧‧‧ Mass storage device

700 ‧ ‧ lithography system

701‧‧‧NA / element

702‧‧‧Mask plane

703‧‧‧light source

705‧‧‧lens

707‧‧‧lighting optics

713‧‧‧ Imaging Optics

750‧‧‧ Detection System

751a‧‧‧Lighting Optics

751b‧‧‧ NA

752‧‧‧mask plane

753a‧‧‧detection optics / collection optics / optical components

753b‧‧‧detection optics / collection optics

754a‧‧‧Sensor

754b‧‧‧Sensor

760‧‧‧light source

773‧‧‧Computer System

776‧‧‧ Beam Splitter

778‧‧‧detection lens

M‧‧‧Light Mask / Mask

W‧‧‧ Wafer

FIG. 1 is a flowchart illustrating a mask near-field recovery procedure according to an embodiment of the present invention. FIG. 2 is a flowchart illustrating a model calibration process according to a specific embodiment of the present invention. FIG. 3 is a flowchart illustrating a mask qualification process according to an embodiment of the present invention. 4A is a flowchart illustrating a process for determining the stability of a mask pattern according to an exemplary application of the present invention. 4B is a flowchart illustrating a defect detection procedure according to another embodiment of the present invention. FIG. 5 is a flowchart illustrating a mask qualification process applied to a near-field image or result of a restored mask according to an alternative embodiment of the present invention. FIG. 6 is a graphical representation of an exemplary detection system in which the techniques of the present invention can be implemented. FIG. 7A is a simplified schematic representation of a lithography system for transferring a mask pattern from a light mask to a wafer according to a particular embodiment. FIG. 7B provides a schematic representation of a light mask detection device according to a particular embodiment.

Claims (30)

A method for identifying the eligibility of a light lithography mask, the method includes: using an imaging tool to obtain a plurality of images from each of a plurality of pattern areas of a test mask according to different lighting configurations and / or different imaging configurations ; Each of the pattern areas of the test mask restores a near field of the mask based on the images obtained from each pattern area of the test mask; and analyzes the near field of the restored mask to characterize the test Mask or determine if this test mask is defective. The method of claim 1, wherein the plurality of images are acquired at a pupil plane. The method of claim 1, wherein the near field of the restored photomask is analyzed to detect defects in the test photomask, wherein the defect detection includes: comparing an identical crystal grain, an adjacent crystal grain, and a crystal grain at different times. The intensity and / or phase of the corresponding gold crystal grain or a crystal grain and a corresponding crystal grain from a photomask replica having the same design as the test photomask. The method of claim 1, wherein the near field of the photomask is restored without using a design database used to make the test photomask. The method of claim 1, wherein the acquired images include at least three reflection images acquired under different imaging conditions selected to result in a near field of the same mask, and wherein the different imaging conditions include different focus settings, Different pupil shapes and / or polarization analyzer settings, where different lighting conditions include different light source intensity distributions and / or polarization settings. The method of claim 1, wherein the acquired images include at least three transmission images acquired under different imaging conditions selected to result in a near field of the same mask, and wherein the different imaging conditions include different focus settings, Different pupil shapes or polarization analyzer settings, where the different lighting conditions include different light source intensity distributions and / or polarization settings. The method of claim 1, further comprising: applying a lithography model to the near field of the mask of the test mask to simulate a plurality of test wafer images, and analyzing the simulated test wafer images to determine the test Whether the photomask will cause an unstable or defective wafer, wherein the lithographic model is configured to simulate a photolithographic process. The method of claim 7, wherein the lithography model simulates an illumination source having a different illumination shape from one of a detection tool used to acquire an image of the test mask or another mask or wafer shape. The method of claim 7, wherein the lithographic model is calibrated using an image generated from a design database for a calibration mask. The method of claim 7, wherein the lithographic model is calibrated using an image obtained from a calibration mask. The method of claim 7, wherein the lithographic model comprises a compact resist model. The method of claim 7, wherein the lithographic model is applied to the photomask near-field recovered for the test photomask under a plurality of different photolithography process conditions, and wherein analyzing the simulated test wafer images includes: borrowing By comparing portions of the simulated test images associated with different process conditions and the same mask area, it is determined whether the test mask may cause an unstable wafer under the different lithography process conditions. The method of claim 7, further comprising repeating the following operations: acquiring an image, restoring, applying the lithographic model, and analyzing the obtained after applying each of photolithographic modeling, resist modeling, and etching modeling. These simulation test wafer images to isolate the root cause of any mask defects. The method of claim 7, wherein the imaging tool utilizes a wavelength range that is the same as a photolithography system in which the test mask is to be used in wafer manufacturing. The method of claim 7, wherein the imaging tool uses a wavelength range different from a photolithography system in which the test mask is to be used for wafer manufacturing, and wherein the simulated test wafer images are analyzed to The test wafer images perform defect detection to determine whether the test mask may cause a defective wafer. An imaging system for identifying the eligibility of a light lithographic mask, the system includes: a light source for generating an incident light beam; an illumination optical module for guiding the incident light beam to a mask A collection optical module for guiding an output beam from each of the pattern areas of the mask to at least one sensor; at least one sensor for detecting the output beam and based on the output beam Generating an image or signal; and a controller configured to perform the following operations: cause a plurality of images to be obtained from each of a plurality of pattern areas of a test mask according to different lighting configurations and / or different imaging configurations ; Each of the pattern areas of the test mask is restored a mask near field based on the images obtained from the pattern areas of the test mask; and the restored mask near field is analyzed to determine the test light Whether a mask or another mask will cause an unstable wafer pattern or a defective wafer. The system of claim 16, wherein the plurality of images are acquired at a pupil plane. If the system of claim 16, wherein the near field of the restored photomask is analyzed to detect defects in the test photomask, the defect detection includes: comparing an identical grain, an adjacent grain, and a grain at different times. The intensity and / or phase of the corresponding gold crystal grain or a crystal grain and a corresponding crystal grain from a photomask replica having the same design as the test photomask. The system of claim 16, wherein the near field of the photomask is restored without using a design database used to make the test photomask. If the system of claim 16, wherein the acquired images include at least three reflection images acquired under different imaging conditions selected to result in a near field of the same mask, and wherein the different imaging conditions include different focus settings, Different pupil shapes and / or polarization analyzer settings, where different lighting conditions include different light source intensity distributions and / or polarization settings. The system of claim 16, wherein the acquired images include at least three transmission images acquired under different imaging conditions selected to result in a near field of the same mask, and wherein the different imaging conditions include different focus settings, Different pupil shapes and / or polarization analyzer settings, where the different lighting conditions include different light source intensity distributions and / or polarization settings. The system of claim 16, wherein the controller is further configured to: apply a lithographic model to the mask near field of the test mask to simulate a plurality of test wafer images, and analyze the simulated test crystals A circle image is used to determine whether the test mask may cause an unstable or defective wafer, wherein the lithography model is configured to simulate a photolithography process. The system of claim 22, wherein the lithographic model simulates an illumination source having an illumination shape different from that of one of a detection system for acquiring an image of the test mask or another mask or wafer shape. The system of claim 22, wherein the lithographic model is calibrated using an image generated from a design database for a calibration mask. The system of claim 22, wherein the lithographic model is calibrated using an image acquired from a calibration mask. The system of claim 22, wherein the lithographic model comprises a compact resist model. The system of claim 22, wherein the lithographic model is applied to the photomask near-field restored for the test photomask under a plurality of different photolithographic process conditions, and wherein analyzing the simulated test wafer images includes: borrowing By comparing portions of the simulated test images associated with different process conditions and the same mask area, it is determined whether the test mask may cause an unstable wafer under the different lithography process conditions. The system of claim 22, wherein the controller is further configured to repeat the following operations: acquiring an image, restoring, applying the lithographic model, and analyzing the application of photolithographic modeling, resist modeling, and etching modeling These simulated test wafer images obtained after each of them to isolate the source of any mask defects. The system of claim 22, wherein the imaging system utilizes a wavelength range that is the same as a photolithography system in which the test mask is to be used in wafer manufacturing. The system of claim 22, wherein the imaging system uses a wavelength range different from a photolithography system in which the test mask is to be used for wafer manufacturing, and wherein the simulated test wafer images are analyzed to The test wafer images perform defect detection to determine whether the test mask may cause a defective wafer. Drawing translation Figure 1 102 Use a mask detection tool to obtain at least three images of a mask according to different imaging configurations 104 Align the images with each other or align the images with the rear OPC DB 106 Image restoration based on the acquired mask And save Mask Near Field (NF) Recovery Mask Near-Field Mask Near Field End End Figure 2 201 Mask near-field image recovered from self-aligning mask 202 Self-design database Simulated Calibration Mask Image 208 Models using a set of initial or adjusted model parameters, such as lithography (and resist) applied to mask near-field (or simulated mask) images 210 Modeled by comparison Results and Calibration Results Calibrate the lithographic model 212 Do you adjust model parameters? 214 Adjusting the model parameters 216 Calibration image of the calibration wafer produced Model Calibration Wafer Images Adjusted Model parameters Calibrated model parameters Calibrated model parameters Y Yes N No End End Figure 3 302 Recovery Mask near-field results 303 Use final model parameters for the mask near-field to model the lithographic process (and resist) 322 Evaluate the simulated wafer pattern to determine pattern stability and / or locate defects 324 Is the design defective? 326 Can hot spots be monitored? 328 Is the photomask repaired? 330 Discard photomask 332 Modify design 334 Monitor hot spots during wafer process 336 Repair photomask (repeated photomask qualification) Reticle Qualification Use I Simulated Wafer Images Simulated wafer image Y Yes N No End Figure 4A 402 Align each test image relative to its corresponding reference image. These images are simulated by the model under different sets of process conditions. 404 Compare each pair of aligned images to obtain one or more wafer pattern differences. 406 Associate the threshold with the wafer pattern difference Pattern stability End End Figure 4B 452 Align each test mask image with its corresponding reference image 454 Compare each pair of aligned test images based on the associated threshold Masking defect with reference image 456 For each mask defect, compare the simulated wafer defect with the corresponding reference pre-OPC Defect Inspection Defect Inspection End End Figure 5 502 Restore mask near field results 522 Evaluate mask near field results to characterize Mask quality and / or positioning defects 524 Is there a defect in the design? Can 526 hot spots be monitored? 528 Is the photomask repaired? 530 Discard photomask 532 Modify design 534 Monitor hot spots during wafer process 536 Repair photomask (repeated photomask qualification) Reticle Qualification Use II Photomask qualification use II Y Yes N No End End Figure 6 602 From Inspection Tool Input 604a Distributor Processor & Memory 604b Distributor Processor & Memory 606a Block Processor & Memory 606b Block Processor & Memory 608 Switched Network 612 Photomask Qualification Processor & Memory 616 Data Defect Review Keyboard Mouse