Patent Grant
7962863
1. Field of the Invention
The present invention generally relates to computer-implemented methods, systems, and computer-readable media for determining a model for predicting printability of reticle features on a wafer. Certain embodiments relate to selecting a model for predicting printability of reticle features on a wafer by comparing one or more characteristics of reticle features of simulated images generated using different models for a set of different values of exposure conditions and one or more characteristics of reticle features printed on the wafer.
2. Description of the Related Art
The following descriptions and examples are not admitted to be prior art by virtue of their inclusion within this section.
Fabricating semiconductor devices such as logic and memory devices typically includes processing a substrate such as a semiconductor wafer using a number of semiconductor fabrication processes to form various features and multiple levels of the semiconductor devices. For example, lithography is a semiconductor fabrication process that involves transferring a pattern from a reticle to a resist arranged on a semiconductor wafer. Additional examples of semiconductor fabrication processes include, but are not limited to, chemical-mechanical polishing, etch, deposition, and ion implantation. Multiple semiconductor devices may be fabricated in an arrangement on a semiconductor wafer and then separated into individual semiconductor devices.
Lithography is typically one of the most important processes in integrated circuit (IC) manufacturing since a pattern printed in a resist by lithography is utilized as a masking layer to transfer the pattern to additional layers on a wafer in subsequent processing steps. Therefore, the pattern that is formed on the wafer during lithography directly affects the features of the ICs that are formed on the wafer. Consequently, defects that are formed on a wafer during lithography may be particularly problematic for the IC manufacturing process. One of the many ways in which defects may be formed on the patterned wafer during lithography is by transfer of defects that are present on the reticle to the wafer. Therefore, detection and correction of defects on the reticle such as unwanted particulate or other matter is performed rather stringently to prevent as many defects on the reticle from being transferred to the wafer during lithography.
However, as the dimensions of ICs decrease and the patterns being transferred from the reticle to the wafer become more complex, marginalities in the features formed on the reticle become increasingly important. Therefore, significant efforts have been devoted to developing methods and systems that can be used to detect problems in the pattern on the reticle or in the design that will cause problems on the wafer. These efforts are relatively complex and difficult due, at least in part, to the fact that not all discrepancies or marginalities in the pattern formed on the reticle will cause errors on the wafer that will adversely affect the IC. In other words, some marginalities in the pattern formed on the reticle may not produce defects on the wafer at all or may produce defects on the wafer that will not reduce the performance characteristics of the IC. Therefore, one challenge of many in developing adequate methods and systems for qualifying a reticle pattern is to discriminate between pattern defects or marginalities that “matter” and those that do not.
One way to check a reticle pattern before the reticle is fabricated is design rule checking (DRC). However, conventional DRC operates only at the nominal process conditions or, at most, at a limited number of process conditions and/or at a limited number of points within the device. Other software-based methods for detecting design pattern defects prior to fabrication of the reticle have been proposed, and one such method is described in U.S. Patent Application Publication No. 2003/0119216A1 by Weed, which is incorporated by reference as if fully set forth herein. However, this method is designed to determine only the best focus and exposure settings and not to explore the full range of the process window conditions available for each design.
Such software methods, therefore, have several disadvantages. In particular, these software methods do not examine the full range of process window conditions thereby failing to detect process window marginalities and missing potential defects. In addition, these methods do not determine the exact focus and exposure conditions under which defects will occur thereby preventing the complete optimization of the design. The lack of complete process window information also limits the ability to implement advanced process control techniques for critical dimension control across all critical features on the device.
If the layout of a reticle design passes verification, reticle enhancement technique (RET) features may be added to the circuit layout. This step is commonly referred to as “decorating” the circuit layout. Adding the RET features to the circuit layout may be performed in a number of different ways. The RET features may include a number of different RET features such as optical proximity correction (OPC) features. The decoration may also be verified prior to reticle fabrication. Verifying the decoration may include optical rule checking (ORC). If the decorated design fails verification, the RET features in the decorated design may be altered, and the decorated design may be re-verified.
Currently, many methods for calibrating OPC feature models and OPC feature verification models involve generating a number of models and choosing the one that best simulates the wafer data. The calibration is typically performed based on data at a single focus and exposure condition or on data at focus and exposure conditions concentrated near the best focus and exposure condition. This approach has the disadvantage that the simulations may not be accurate across the entire process window and at other arbitrary focus and exposure conditions. In addition, the data is typically collected and interpreted manually in the currently used methods, which increases the probability of error in the calibration.
Accordingly, it would be desirable to develop computer-implemented methods, systems, and computer-readable media for determining a model for predicting printability of reticle features on a wafer for a set of different values of exposure conditions automatically.
The following description of various embodiments of computer-implemented methods, systems, and computer-readable media is not to be construed in any way as limiting the subject matter of the appended claims.
One embodiment relates to a computer-implemented method for determining a model for predicting printability of reticle features on a wafer. The method includes generating simulated images of the reticle features printed on the wafer using different generated models for a set of different values of exposure conditions. The method also includes determining one or more characteristics of the reticle features of the simulated images. In addition, the method includes comparing the one or more characteristics of the reticle features of the simulated images to one or more characteristics of the reticle features printed on the wafer using a lithography process. The method further includes selecting one of the different generated models as the model to be used for predicting the printability of the reticle features based on results of the comparing step.
In one embodiment, all steps of the computer-implemented method are performed automatically upon receipt of an instruction to perform the computer-implemented method. In another embodiment, predicting the printability of the reticle features includes verifying optical proximity correction features of the reticle features.
In one embodiment, the method includes generating the different generated models. In another embodiment, the method includes generating the different generated models such that each of the different generated models has one or more different parameters, different values for one or more parameters of the different generated models, or some combination thereof. In an additional embodiment, the method includes generating the different generated models such that differences in values of one or more parameters of the different generated models are greater than predetermined criteria.
In one embodiment, the different values of the exposure conditions are located in four quadrants of focus and exposure matrix space. In another embodiment, the different values of the exposure conditions are located in only a subset of four quadrants of focus and exposure matrix space. In an additional embodiment, the set of the different values of the exposure conditions includes values proximate extremes of a process window for the lithography process and best values for the exposure conditions.
In one embodiment, the method includes determining features of interest in the reticle features based on the simulated images. In another embodiment, the method includes acquiring images of the reticle features printed on the wafer at the different values of the exposure conditions and determining the one or more characteristics of the reticle features printed on the wafer at the different values of the exposure conditions using the acquired images. In an additional embodiment, the method includes determining features of interest in the reticle features based on the simulated images, determining locations on the wafer at which the features of interest are printed at the different values of the exposure conditions, and acquiring images of the reticle features printed on the wafer at the locations. In a further embodiment, the method includes acquiring images of the reticle features printed on the wafer at the different values of the exposure conditions from a metrology tool coupled to a computer system configured to perform the computer-implemented method.
In one embodiment, the method includes contouring the simulated images and images of the reticle features printed on the wafer for edge definition and determining the one or more characteristics of the reticle features of the simulated images and the reticle features printed on the wafer using the contoured images. In another embodiment, the one or more characteristics of the reticle features of the simulated images and the reticle features printed on the wafer include critical dimension.
In one embodiment, the selecting step includes determining a figure of merit for each of the different generated models based on the results of the comparing step. In another embodiment, the selecting step includes determining a composite figure of merit for each of the different generated models based on the results of the comparing step performed for two or more of the reticle features in the simulated images and in images of the reticle features printed on the wafer. In an additional embodiment, the selecting step includes determining a figure of merit for each of the different generated models and selecting the different generated model having the best figure of merit as the model to be used for predicting the printability of the reticle features.
Each of the steps of each of the embodiments of the method described above may be performed as described further herein. In addition, each of the embodiments of the method described above may include any other step(s) of any other method(s) described herein. Furthermore, each of the embodiments of the method described above may be performed by any of the systems described herein.
Another embodiment relates to a system configured to determine a model for predicting printability of reticle features on a wafer. The system includes a simulation engine configured to generate simulated images of the reticle features printed on the wafer using different generated models for a set of different values of exposure conditions. The system also includes a computer system configured to determine one or more characteristics of the reticle features of the simulated images. The computer system is also configured to compare the one or more characteristics of the reticle features of the simulated images to one or more characteristics of the reticle features printed on the wafer using a lithography process. The computer system is further configured to select one of the different generated models as the model to be used for predicting the printability of the reticle features based on results of the comparison. The system described above may be further configured as described herein.
An additional embodiment relates to a computer-readable medium that includes program instructions executable on a computer system for performing a computer-implemented method for determining a model for predicting printability of reticle features on a wafer. The computer-implemented method includes generating simulated images of the reticle features printed on the wafer using different generated models for a set of different values of exposure conditions. The method also includes determining one or more characteristics of the reticle features of the simulated images. In addition, the method includes comparing the one or more characteristics of the reticle features of the simulated images to one or more characteristics of the reticle features printed on the wafer using a lithography process. The method further includes selecting one of the different generated models as the model to be used for predicting the printability of the reticle features based on results of the comparing step.
The computer-readable medium described above may be further configured as described herein. The steps of the computer-implemented method may be further performed as described herein. In addition, the computer-implemented method for which the program instructions are executable may include any other step(s) of any other method(s) described herein.
Further advantages of the present invention may become apparent to those skilled in the art with the benefit of the following detailed description of the preferred embodiments and upon reference to the accompanying drawings in which:
While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and may herein be described in detail. The drawings may not be to scale. It should be understood, however, that the drawings and detailed description thereto are not intended to limit the invention to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope of the present invention as defined by the appended claims.
As used herein, the term “wafer” generally refers to substrates formed of a semiconductor or non-semiconductor material. Examples of such a semiconductor or non-semiconductor material include, but are not limited to, monocrystalline silicon, gallium arsenide, and indium phosphide. Such substrates may be commonly found and/or processed in semiconductor fabrication facilities.
A wafer may include one or more layers formed upon a substrate. For example, such layers may include, but are not limited to, a resist, a dielectric material, a conductive material, and a semiconductive material. Many different types of such layers are known in the art, and the term wafer as used herein is intended to encompass a wafer including all types of such layers.
One or more layers formed on a wafer may be patterned or unpatterned. For example, a wafer may include a plurality of dies, each having repeatable patterned features. Formation and processing of such layers of material may ultimately result in completed devices. Many different types of devices such as integrated circuits (ICs) may be formed on a wafer, and the term wafer as used herein is intended to encompass a wafer on which any type of device known in the art is being fabricated.
The terms “reticle” and “mask” are used interchangeably herein. A reticle generally includes a transparent substrate such as glass, borosilicate glass, and fused silica having opaque regions formed thereon in a pattern. The opaque regions may be replaced by regions etched into the transparent substrate. Many different types of reticles are known in the art, and the term reticle as used herein is intended to encompass all types of reticles.
Turning now to the drawings, it is noted that the figures are not drawn to scale. In particular, the scale of some of the elements of the figures is greatly exaggerated to emphasize characteristics of the elements. It is also noted that the figures are not drawn to the same scale. Elements shown in more than one figure that may be similarly configured have been indicated using the same reference numerals.
The embodiments described herein generally relate to lithography process condition selection and automation of modeling flow. For example, one embodiment relates to a computer-implemented method for determining a model for predicting printability of reticle features on a wafer. In some embodiments, predicting the printability of the reticle features on the wafer includes verifying optical proximity correction (OPC) features of the reticle features. For example, the model may be configured for predicting the printability of reticle features that are “decorated” or modified by reticle enhancement technique (RET) features such as OPC features or any other RET features known in the art. In this manner, the model may be configured and used for verifying that reticle features decorated with RET features such as OPC features will print correctly on the wafer. However, the method may be used for determining a model for predicting the printability of any reticle features known in the art and reticle features of any type of reticle known in the art. In addition, as described further herein, the embodiments described herein may use more than one reticle feature for model determination.
The methods described herein may also be configured and used for creating a brand new (not pre-existing) model, for refining (e.g., calibrating) a pre-existing model, and/or for calibrating a new model. Furthermore, the models determined according to embodiments described herein may include OPC models (e.g., models used to create OPC features) and models used for OPC feature verification. For example, OPC models are typically used to create OPC features by using the nominal process conditions (e.g., nominal focus and exposure conditions). The created OPC features are then verified using another model (i.e., the OPC verification model). Verification models typically verify OPC features at nominal focus and exposure conditions. However, as described herein, the verification model may be configured to check the OPC features at different values of exposure conditions to determine if the OPC features provide a reasonable process window for the lithography process.
In some embodiments, all steps of the computer-implemented method are performed automatically upon receipt of an instruction to perform the computer-implemented method. The instruction may include, for example, an instruction from a user indicating that the computer-implemented method is to be performed. The instruction may include any suitable instruction expressed in any suitable manner. In addition, the computer-implemented method may be configured to receive (and detect receipt) of the instruction in any suitable manner. Upon detection of receipt of the instruction, the computer-implemented method may automatically perform all steps of any of the embodiments described herein. In this manner, the embodiments described herein may automatically determine models for predicting wafer printability.
One embodiment of such a method is shown in
In some embodiments, as shown in step 10 of
Each of the different generated models may include a resist model (e.g., a model of the resist that will be printed with the reticle features on the wafer) and a lithography model (e.g., a model of the optical parameters of an exposure tool that will be used to print the reticle on the wafer or a “scanner model” and a model of other process steps involved in the lithography process such as develop and post exposure bake). The different generated models may also include models for any other material or process involved in printing the reticle features on a wafer (e.g., a reticle manufacturing model).
As shown in step 12 of
The exposure conditions may include focus and dose. For example, in one embodiment, the different values of the exposure conditions are located in four quadrants of focus and exposure matrix space.
As further shown in
In another embodiment, the different values of the exposure conditions are located in only a subset of four quadrants 16 of focus and exposure matrix space 14. For example, the different values may be located in two or more of the four quadrants of the focus and exposure matrix space. In particular, although a subset or superset of the conditions in the four quadrants described above can be used, consideration may be given to the fact that focus is not a symmetric operation. In other words, a focus of 100 nm on the positive side of the best focus condition does not produce the same aerial image and wafer pattern as 100 nm on the negative side of the best focus condition. However, if the models differ more than the asymmetry in focus, then different values in a subset of the four quadrants may be used to produce sufficient information for determining a model for predicting printability of reticle features on a wafer.
In an additional embodiment, the set of the different values of the exposure conditions includes values proximate extremes of a process window for the lithography process and best values for the exposure conditions. For instance, focus and exposure matrix space 14 may define the process window for a lithography process. The extremes of the process window may include at least the four quadrant conditions of the focus and exposure matrix space. In this manner, different values 18 of the exposure conditions may include values proximate the extremes of the process window, and values 20 may be the best values (e.g., nominal or reference values) for the exposure conditions. As such, the expected printable pattern on the wafer may be simulated in the embodiments described herein using each model and focus and exposure conditions that are near the extremes of the process window as well as at best focus and exposure. In this manner, data may be collected at the best focus and exposure conditions and near the extremes of the process window in the four quadrants surrounding the best focus and exposure conditions. Moreover, the different values of the exposure conditions may, in some instances, exceed the process window to any suitable degree. The degree to which the different values exceed the process window may be selected by a user or selected by the embodiments described herein (e.g., automatically). Furthermore, although the exposure conditions may preferably include focus and exposure, the exposure conditions may also include any other conditions of the lithography process such as the type of illumination (e.g., annular, quadrapole, etc.) that may be used to print the reticle features.
In some embodiments, as shown in step 22 of
In one embodiment, the method includes acquiring images of the reticle features printed on the wafer, as shown in step 24 of
In some embodiments, the images of the reticle features printed on the wafer may be acquired at locations on the wafer at which features of interest in the reticle features are printed. For example, as shown in step 22 of
As shown in step 26 of
The one or more characteristics of the reticle features of the simulated images and the acquired images may be determined in any suitable manner using any suitable algorithm and/or method. For example, in one embodiment, the method includes contouring the simulated images and images of the reticle features printed on the wafer for edge definition and determining the one or more characteristics of the reticle features of the simulated images and the reticle features printed on the wafer using the contoured images. In this manner, extracting the relevant data from the images may include contouring the images with well-defined algorithm(s) for edge definition.
The one or more characteristics of the reticle features of the simulated images and the acquired images may include any suitable characteristic(s) of the reticle features. For example, in one embodiment, the one or more characteristics of the reticle features of the simulated images and the reticle features printed on the wafer include critical dimension (CD). In addition, the method may include extracting the relevant data from the images using CD measurements of 1.5D features or 2D features. (1D features may include reticle features such as lines or spaces, while 2D features may include reticle features having a closed boundary (e.g., such that the entire boundary can be traced from one point on the boundary and back to the same point). In contrast, 1.5D features may include features such as LES or features typically used to measure overlay. In this manner, 1.5D features may include a positional relationship between two different features). In one embodiment, therefore, the method may include using 2D data from the entire process window for model determination.
As shown in step 30 of
In one example, characteristic(s) of the images may be compared on a point-by-point basis across the images, and differences between the characteristic(s) may be identified using, for example, algorithms. The algorithms that are used for the comparing step may include algorithms that are the same as, or substantially similar to, those used in inspection. Therefore, difference detection may be performed by comparing characteristic(s) of the images. Any region in the simulated images that varies from the corresponding region in the acquired image by more than a threshold value may be flagged as a difference. All of the algorithmic tools used in physical inspection systems can be used in this comparing step including applying multiple algorithmic detectors based on different smoothing filters applied to varying numbers of nearest neighbor pixels and detecting single edge misplacements (CD errors) and/or dual edge misplacements (registration errors).
The comparing step may have the same tuning capability as defect detection algorithms used for physical inspection tools. In particular, the algorithms that are used for the comparing step described herein may be configured such that the sensitivity of the algorithms can be optimized to detect differences for some reticle features that will impact device performance and yield. In one such example, the sensitivity of the algorithms may be altered from feature-to-feature based on one or more as-designed characteristics of the features (e.g., dimensions, criticality, etc.). Therefore, the model selected as described further herein may be more accurate for predicting the printability of reticle features that are more relevant to device performance and yield than other reticle features.
The characteristics of the reticle features are preferably compared for the simulated images and the acquired images generated for the same values of the exposure conditions. In other words, the comparison may be performed on an exposure condition-to-exposure condition basis. In this manner, the method may include using multiple values of exposure conditions for model determination. In addition, the method may include using multiple reticle features as described above and multiple values of exposure conditions for model determination. Output of the comparing step may include coordinates of the differences between the simulated and acquired images, portions of the simulated images (and possibly acquired images) corresponding to the positions of the differences, a database clip of the as-designed reticle features, the severity (e.g., the magnitude) of the differences detected between the different images, or some combination thereof.
The method shown in
In addition, since more than one reticle feature and more than one value of exposure conditions are used to select the model to be used for predicting the printability of the reticle features, different generated models may have different minimum differences depending on the reticle feature and exposure condition. In other words, local minimum differences (for different features and different exposure conditions) may be exhibited by different models. However, the model that is selected for use as the model for predicting the printability of the reticle features may be the model that is determined to have a global minimum across reticle features and across exposure conditions. In this manner, the model that is selected for use as the model for predicting the printability of the reticle features may not necessarily be the “best fit” model, but may be the model that provides the most accurate results across a range of reticle features and exposure conditions.
In some embodiments, the method includes determining a figure of merit for each of the different models, as shown in step 34 of
In one option, the figure of merit may be constructed based on the difference in area between simulated and actual features. In another option, the figure of merit may be constructed by combining multiple CD measurements and analyzing the multiple CD measurements either by minimizing the chi-square difference or the maximum CD difference between many points on the simulation and actual data. For example, the chi-square difference for 1D data may include the root mean squared (rms) for the data. In contrast, the chi-square difference for 2D data may be the edge placement error (EPE). In addition, for 2D data, the points on the simulated and actual data at which the maximum CD or other difference is determined may include many different slices across the data (e.g., the CD error can be determined in one dimension of the feature at various points across the orthogonal dimension of the feature).
In another embodiment, selecting one of the different generated models includes determining a composite figure of merit for each of the different generated models based on the results of the comparing step (step 30 of
The method may also include performing one or more additional steps based on the results of the comparing step (step 30 of
The embodiments described herein have a number of advantages over currently used methods and systems for generating models for OPC features and OPC feature verification. For instance, as described herein, the different generated models may be evaluated across a number of different values of exposure conditions. Therefore, the model that is selected to be used for predicting printability of the reticle features on a wafer may advantageously be the best model (out of those evaluated) for predicting the printing of the reticle features across the largest possible range of values of the exposure conditions. In addition, as described herein, the different generated models may be evaluated across a number of different reticle features. As such, the model that is selected to be used for predicting the printability of the reticle features on a wafer may advantageously be the best model (out of those evaluated) for predicting the printing of a number of different reticle features.
The method may also include storing results of the selecting step (step 32 of
The embodiment of the method shown in
The method shown in
In some embodiments, the method shown in
As shown in
The system shown in
The computer system may include any suitable computer system known in the art. For example, computer system 56 may take various forms, including a personal computer system, mainframe computer system, workstation, image computer, parallel processor, or any other device known in the art. In general, the term “computer system” may be broadly defined to encompass any device having one or more processors, which executes instructions from a memory medium.
The system shown in
In some embodiments, the computer system is configured to contour the simulated images and images of the reticle features printed on the wafer for edge definition and to determine the one or more characteristics of the reticle features of the simulated images and the reticle features printed on the wafer using the contoured images. The computer system may be configured to perform such contouring and determining as described further herein. In an additional embodiment, the computer system is configured to select the model to be used for predicting the printability of the reticle features by determining a figure of merit and/or a composite figure of merit, which may be determined as described further herein. System 52, simulation engine 54, and computer system 56 may be further configured as described herein.
As described above, all steps of the computer-implemented method may be performed automatically upon receipt of an instruction to perform the computer-implemented method. In this manner, the entire process may be automated. In one particular example, a system configured to acquire images of the reticle features printed on the wafer may include a SEM or an AFM. The SEM or AFM may be configured to automatically acquire the data (e.g., take the images) and pass the images to a computer system such as that described herein. The computer system can be configured to automatically generate the simulated images for each model. The computer system can also be configured to automatically compare the SEM/AFM images with the simulated images (e.g., using an algorithm that calculates the edge differences between the digitized data of the two types of images). In this manner, the system may be configured for automation of the process flow by linking to the SEM and/or AFM with automatic data comparison. The figure of merit may be generated by combining the actual and simulated data. The computer system may be configured to then automatically decide which model is best.
Program instructions 60 implementing methods such as those described herein may be transmitted over or stored on computer-readable medium 58. The computer-readable medium may be a transmission medium such as a wire, cables, or wireless transmission link. The computer-readable medium may also be a storage medium such as a read-only memory, a random access memory, a magnetic or optical disk, or a magnetic tape.
The program instructions may be implemented in any of various ways, including procedure-based techniques, component-based techniques, and/or object-oriented techniques, among others. For example, the program instructions may be implemented using ActiveX controls, C++ objects, JavaBeans, Microsoft Foundation Classes (“MFC”), or other technologies or methodologies, as desired.
Further modifications and alternative embodiments of various aspects of the invention may be apparent to those skilled in the art in view of this description. For example, computer-implemented methods, systems, and computer-readable media for determining a model for predicting printability of reticle features on a wafer are provided. Accordingly, this description is to be construed as illustrative only and is for the purpose of teaching those skilled in the art the general manner of carrying out the invention. It is to be understood that the forms of the invention shown and described herein are to be taken as the presently preferred embodiments. Elements and materials may be substituted for those illustrated and described herein, parts and processes may be reversed, and certain features of the invention may be utilized independently, all as would be apparent to one skilled in the art after having the benefit of this description of the invention. Changes may be made in the elements described herein without departing from the spirit and scope of the invention as described in the following claims.
This application claims priority to U.S. Provisional Application No. 60/916,354 entitled “Computer-Implemented Methods, Systems, and Carrier Media for Determining a Model for Predicting Printability of Reticle Features on a Wafer,” filed May 7, 2007, which is incorporated by reference as if fully set forth herein.
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