CN118280868B - Method, device, terminal, medium and program product for measuring edge roughness of curve pattern line - Google Patents
Method, device, terminal, medium and program product for measuring edge roughness of curve pattern line Download PDFInfo
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Abstract
The application provides a method, a device, a terminal, a medium and a program product for measuring edge roughness of a curve pattern line, wherein the method comprises the following steps: acquiring scanning electron microscope images of a plurality of exposure fields of a target wafer; performing alignment processing on the scanning electron microscope image of each exposure field to obtain an average image of each exposure field, and further obtaining the actual contour of the curve pattern of the exposure field to be measured by a contour extraction mode; contour extraction is carried out on an average image of the wafer obtained based on the average image of each exposure field, and an ideal contour of a curve pattern of the exposure field to be measured is obtained; the line edge roughness of the curve pattern of the exposure field to be measured is obtained by calculating the average deviation value of the actual contour of the curve pattern of the exposure field to be measured from the ideal contour. The method of the application realizes the measurement of the line edge roughness of arbitrary curve patterns. The actual contour and the ideal contour of the curve pattern extracted by the method have higher precision.
Description
Technical Field
The present application relates to the field of semiconductor manufacturing technology, and in particular, to a method, an apparatus, a terminal, a medium, and a program product for measuring edge roughness of a curved pattern line.
Background
Line edge roughness (Line Edge Roughness, LER), which refers to the deviation between the edge of a pattern and a theoretically perfect smooth edge, is widely used in the characterization of large scale integrated circuit manufacturing processes. Line edge roughness has an important impact on chip performance and chip manufacturing yield. On the one hand, larger line edge roughness can bring about larger random edge placement errors (EDGE PLACEMENT Error, i.e. EPE), so as to cause physical defects such as bridging, breaking points and the like, and on the other hand, larger line edge roughness can also influence the electrical performance of the chip. For the transistor Gate (Gate), a larger line edge roughness may cause negative effects such as increased leakage current; for metal lines, a larger line edge roughness results in a decrease in the actual area of the metal line, thereby increasing its resistance and RC delay. Therefore, measurement of line edge roughness is very important.
Since the design layout of integrated circuits is usually composed of straight line segments in both horizontal and vertical directions, current line edge roughness measurements are also usually made for one-dimensional straight lines. The actual edge position of the one-dimensional pattern is typically obtained by scanning electron microscopy, and the edge roughness is calculated from the deviation between the actual edge position and the ideal edge position on each sampling line. However, with the rise of new semiconductor devices such as silicon light in recent years, the shape of the device pattern is not only a straight line but also a curve of an arbitrary shape. For curved patterns, the measurement of line edge roughness based on prior art methods introduces large errors, since its corresponding ideal profile cannot be described by some known function.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, it is an object of the present application to provide a method, an apparatus, a terminal, a medium and a program product for measuring line edge roughness of a curved pattern, for solving the problem of a large error in measuring line edge roughness based on the prior art method.
To achieve the above and other related objects, a first aspect of the present application provides a method of measuring edge roughness of a curved pattern line, comprising: acquiring scanning electron microscope images of a plurality of exposure fields of a target wafer, and performing alignment processing on the scanning electron microscope images of each exposure field to acquire an average image of each exposure field; contour extraction is carried out on average images of the exposure fields to be measured in the plurality of exposure fields, and the actual contour of the curve pattern of the exposure fields to be measured is obtained; contour extraction is carried out on an average image of a wafer obtained based on the average image of each exposure field, and an ideal contour of a curve pattern of the exposure field to be measured is obtained; and obtaining the line edge roughness of the curve pattern of the exposure field to be measured by calculating the average deviation value of the actual contour of the curve pattern of the exposure field to be measured from the ideal contour.
In some embodiments of the first aspect of the present application, the scanning electron microscope image of each exposure field comprises: scanning electron microscope images obtained after scanning in a plurality of scanning directions, respectively.
In some embodiments of the first aspect of the present application, the scanning electron microscope image of each exposure field is subjected to an alignment process to obtain an average image of each exposure field, which process comprises: moving the scanning electron microscope image in each scanning direction of each exposure field to obtain an image aligned with the target layout in each scanning direction of each exposure field; determining an up-sampling multiple based on a minimum step length during movement and a pixel pitch of a scanning electron microscope image; up-sampling the image aligned with the target layout in each scanning direction of each exposure field according to the determined up-sampling multiple to obtain an up-sampled image in each scanning direction of each exposure field; based on the upsampled images in the respective scanning directions of each exposure field, an average image of each exposure field is obtained.
In some embodiments of the first aspect of the present application, an average image for each exposure field is obtained based on the upsampled image for the respective scanning direction of each exposure field, which process comprises: determining a maximum rectangular overlap region between the upsampled images in the respective scanning directions for each exposure field; based on the up-sampled image in the respective scanning directions of each exposure field, an average value of the intensities of each pixel point within the maximum rectangular overlap region is calculated to obtain an average image of each exposure field.
In some embodiments of the first aspect of the present application, the means for calculating the average deviation value of the actual profile of the curve pattern of the exposure field to be measured from the ideal profile comprises: dividing the ideal contour of the curve pattern of the exposure field to be measured to obtain a plurality of sampling curve segments; and carrying out average value calculation on the calculated average deviation value between the actual contour and each sampling curve segment of the ideal contour to obtain the average deviation value of the actual contour of the curve pattern of the exposure field to be measured to the ideal contour.
In some embodiments of the first aspect of the present application, the means for calculating an average deviation value between the actual profile and each sampled curve segment of the ideal profile comprises: dividing each sampling curve segment of the ideal contour to generate a plurality of sampling points of each sampling curve segment of the ideal contour; obtaining the intersection point of each sampling curve segment and the actual contour according to the normal direction of each sampling curve segment of the ideal contour; calculating a deviation value of each sampling point of each sampling curve segment based on each sampling point of each sampling curve segment and an intersection point of each sampling point and the actual contour; and carrying out average value calculation on the deviation value of each sampling point of each sampling curve segment to obtain the average deviation value between the actual contour and each sampling curve segment of the ideal contour.
To achieve the above and other related objects, a second aspect of the present application provides an apparatus for measuring edge roughness of a curved pattern line, comprising: an image acquisition module for acquiring scanning electron microscope images of a plurality of exposure fields of a target wafer; the alignment processing module is connected with the image acquisition module and is used for performing alignment processing on the scanning electron microscope image of each exposure field to obtain an average image of each exposure field; the actual contour extraction module is connected with the alignment processing module and is used for extracting the contour of the average image of the exposure field to be measured in the plurality of exposure fields to obtain the actual contour of the curve pattern of the exposure field to be measured; an ideal contour extraction module, connected with the alignment processing module, for extracting the contour of the average image of the wafer obtained based on the average image of each exposure field, to obtain the ideal contour of the curve pattern of the exposure field to be measured; and the roughness calculation module is respectively connected with the actual contour extraction module and the ideal contour extraction module, and obtains the line edge roughness of the curve pattern of the exposure field to be measured by calculating the average deviation value of the actual contour of the curve pattern of the exposure field to be measured to the ideal contour.
To achieve the above and other related objects, a third aspect of the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of measuring curve pattern line edge roughness.
To achieve the above and other related objects, a fourth aspect of the present application provides a computer program product comprising computer program code for causing a computer to implement the method of measuring edge roughness of a curve pattern line, when the computer program code is run on the computer.
To achieve the above and other related objects, a fifth aspect of the present application provides an electronic terminal including a memory, a processor, and a computer program stored on the memory; the processor executes the computer program to implement the method of measuring curve pattern line edge roughness.
As described above, the method, apparatus, terminal, medium and program product for measuring edge roughness of curved pattern lines of the present application have the following beneficial effects:
the method of the application realizes the measurement of the line edge degree of any curve pattern; the ideal contour extracted from the average wafer image obtained by the alignment process has high precision; the error of the actual contour extracted from the average image of the exposure field to be measured is small.
Drawings
FIG. 1 is a flow chart of a method for measuring edge roughness of a curved pattern line according to an embodiment of the application.
Fig. 2 is a schematic diagram showing the positional relationship of images before alignment according to an embodiment of the application.
Fig. 3 is a schematic diagram showing the aligned image position relationship in an embodiment of the application.
Fig. 4 is a schematic diagram of a sampled image according to an embodiment of the application.
FIG. 5 is a schematic diagram showing a method for measuring deviation between an actual profile and an ideal profile according to an embodiment of the application.
FIG. 6 is a schematic diagram of a method for calculating the deviation of an actual profile from a sampled curve segment in accordance with an embodiment of the present application.
FIG. 7 is a schematic diagram showing an apparatus for measuring edge roughness of a curved pattern line according to an embodiment of the application.
Fig. 8 is a schematic structural diagram of an electronic terminal according to an embodiment of the application.
Detailed Description
Other advantages and effects of the present application will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present application with reference to specific examples. The application may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
In embodiments of the present application, the words "first," "second," and the like are used to distinguish between identical or similar items that have substantially the same function and effect. It will be appreciated by those of skill in the art that the words "first," "second," and the like do not limit the amount and order of execution, and that the words "first," "second," and the like do not necessarily differ.
In the embodiments of the present application, words such as "exemplary" or "such as" denote examples, illustrations, or descriptions. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.
In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a alone, a and B together, and B alone, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, a-b, a-c, b-c or a-b-c, wherein a, b, c can be single or multiple.
Before explaining the present invention in further detail, terms and terminology involved in the embodiments of the present invention will be explained, and the terms and terminology involved in the embodiments of the present invention are applicable to the following explanation:
<1> exposure field: refers to the area of the wafer surface that can be covered by a single exposure of the lithography machine during the lithography process. The size of this area determines the size of the chip pattern that can be processed during each lithography process. In the photolithography process, a wafer is divided into a plurality of exposure fields, and each exposure field is subjected to steps such as smearing, exposing, developing, and the like of photoresist, so as to obtain the same exposed pattern.
<2> Scanning electron microscope (Scanning Electron Microscope, SEM): the image produced by a scanning electron microscope is generated by the interaction of an electron beam with the sample, which can provide high resolution details of the surface topography of the sample.
The application provides a method, a device, a terminal, a medium and a program product for measuring edge roughness of a curve pattern line, wherein the method comprises the following steps: acquiring scanning electron microscope images of a plurality of exposure fields of a target wafer; performing alignment processing on the scanning electron microscope image of each exposure field to obtain an average image of each exposure field, and further obtaining the actual contour of the curve pattern of the exposure field to be measured by a contour extraction mode; contour extraction is carried out on an average image of the wafer obtained based on the average image of each exposure field, and an ideal contour of a curve pattern of the exposure field to be measured is obtained; the line edge roughness of the curve pattern of the exposure field to be measured is obtained by calculating the average deviation value of the actual contour of the curve pattern of the exposure field to be measured from the ideal contour. The method of the application realizes the measurement of the line edge roughness of arbitrary curve patterns. The actual contour and the ideal contour of the curve pattern extracted by the method have higher precision.
To facilitate an understanding of embodiments of the present application, a detailed description is first provided with reference to fig. 1. FIG. 1 is a flow chart of a method for measuring edge roughness of a curved pattern line in an embodiment of the application. The method for measuring the edge roughness of the curve pattern line in the embodiment mainly comprises the following steps:
step S101: scanning electron microscope images of a plurality of exposure fields of a target wafer are acquired.
The target wafer is a wafer after lithography or etching.
It should be noted that, the type of the scanning electron microscope may be selected by those skilled in the art according to actual needs, which is not limited in the present invention.
In one embodiment, the scanning electron microscope image of each exposure field includes: scanning electron microscope images obtained after scanning in a plurality of scanning directions, respectively.
When measured by an electron microscope, the contrast of the image was related to the scanning direction of the electron beam. The image contrast along the electron beam scanning direction is the best and the image contrast in the direction perpendicular to the scanning direction is the worst. For arbitrary curve patterns, because the line segment direction is continuously changed along the pattern contour, a single electron beam scanning direction must cause poor contrast of corresponding images of curve segments in certain directions, thereby causing larger edge measurement errors. Therefore, the present embodiment compensates for differences in image contrast in different directions caused by a single electron beam scanning direction by scanning in a plurality of scanning directions.
In one embodiment, for each exposure field, four scanning electron microscope images of the scanning directions 0 °, 45 °, 90 °, and 135 ° are acquired.
Step S102: the scanning electron microscope image of each exposure field is subjected to an alignment process to obtain an average image of each exposure field.
In one embodiment, the scanning electron microscope image of each exposure field is aligned to obtain an average image of each exposure field, which includes: moving the scanning electron microscope image in each scanning direction of each exposure field to obtain an image aligned with the target layout in each scanning direction of each exposure field; determining an up-sampling multiple based on a minimum step length during movement and a pixel pitch of a scanning electron microscope image; up-sampling the image aligned with the target layout in each scanning direction of each exposure field according to the determined up-sampling multiple to obtain an up-sampled image in each scanning direction of each exposure field; based on the upsampled images in the respective scanning directions of each exposure field, an average image of each exposure field is obtained.
The target pattern is an etched target pattern or an optical proximity correction target pattern obtained in the process of generating a mask pattern for the design pattern.
In one embodiment, the specific process of determining the upsampling multiple includes: the pixel pitch of the scanning electron microscope image in the respective scanning directions of each exposure field is s. When alignment is performed, the distance of the image movement is an integer multiple of the minimum step length s/M (M is a positive integer) when the image movement is performed, and the alignment error of the image is within s/M. Since the pixel pitch is s, the minimum step length during movement is s/M, and the up-sampling multiple is M.
In one embodiment, the upsampling may be performed using a standard interpolation method such as a third order polynomial.
In one embodiment, the pixels of the upsampled image in the respective scanning directions of each exposure field are aligned.
The specific procedure of the alignment process will be explained below, by way of example, with reference to the accompanying drawings:
Taking the following scanning electron microscope image of the exposure field as an example:
The scanning electron microscope image of the exposure field includes: scanning electron microscope images obtained by scanning in four scanning directions of 0 °,45 °, 90 °, and 135 °, respectively.
Before alignment, as shown in FIG. 2, the center coordinates of the scanning electron microscope images in the four scanning directions of the exposure field are the same.
After aligning the scanning electron microscope images in the four scanning directions of the exposure field with the target layout, respectively, an image aligned with the target layout in the four scanning directions of the exposure field as shown in fig. 3 is obtained. As can be seen from fig. 3, the center coordinates of the images aligned with the target layout in the four scanning directions of the exposure field are different. As can be seen from fig. 3, the scanning electron microscope images in three scanning directions among the scanning electron microscope images in four scanning directions of the exposure field are shifted by an integer multiple of 1/2 pixel pitch. From this, it can be determined that the up-sampling multiple is 2.
The image aligned with the target layout in each scanning direction of each exposure field is up-sampled by a factor of 2, resulting in an up-sampled image in each scanning direction of the exposure field as shown in FIG. 4. After upsampling, the pixels of the upsampled image in the four scanning directions of the exposure field are aligned.
In one embodiment, an average image for each exposure field is obtained based on the upsampled image for the respective scanning direction of each exposure field, which process comprises: determining a maximum rectangular overlap region between the upsampled images in the respective scanning directions for each exposure field; based on the up-sampled image in the respective scanning directions of each exposure field, an average value of the intensities of each pixel point within the maximum rectangular overlap region is calculated to obtain an average image of each exposure field.
The specific procedure for obtaining an average image of each exposure field will be explained below with reference to the accompanying drawings:
first, the maximum rectangular overlap area between the upsampled images in the respective scanning directions for each exposure field is determined. The size of the largest rectangular overlap region is the size of the average image of the exposure field.
For example, the largest rectangular overlap region between the upsampled images in the various scanning directions of the exposure field shown in FIG. 4 is the shaded region in FIG. 4. The size of this shadow region is the size of the average image of the exposure field corresponding to FIG. 4.
Second, for a pixel point (x, y) on the target layout, which belongs to the largest rectangular overlapping region corresponding to the exposure field, calculating the intensity of the average image of the exposure field at the point according to the following formula 1 to obtain the average image of the exposure field:
; (equation 1)
Wherein,、、AndRepresented as intensities of the upsampled image of the exposure field in four directions at the pixel point, respectively.
Step S103: and carrying out contour extraction on the average image of the exposure field to be measured in the plurality of exposure fields, and obtaining the actual contour of the curve pattern of the exposure field to be measured.
In one embodiment, the contour extraction is performed on the average image of the exposure field to be measured by adopting a local gradient maximum method based on the image intensity, so as to obtain the actual contour of the curve pattern of the exposure field to be measured.
Step S104: contour extraction is performed on the wafer average image obtained based on the average image of each exposure field to obtain an ideal contour of the curve pattern of the exposure field to be measured.
In one embodiment, the contour extraction is performed on the wafer average image by using a local gradient maximum method based on the image intensity to obtain the ideal contour of the curve pattern of the exposure field to be measured.
It should be noted that since the curved pattern of each exposure field on the target wafer is exposed by the same mask pattern and subjected to the same lithography and etching process, the average of the images of all exposure fields of the target wafer can be approximated as a perfect smooth pattern (ideal contour) of the curved pattern of all exposure fields.
In one embodiment, the manner in which the average image of the wafer is obtained based on the average image of each exposure field includes: determining a maximum rectangular overlap region between the average images of the exposure fields; based on the average image of each exposure field, an intensity average value of each pixel point in the maximum rectangular overlap region is calculated to obtain a wafer average image.
Step S105: and obtaining the line edge roughness of the curve pattern of the exposure field to be measured by calculating the average deviation value of the actual contour of the curve pattern of the exposure field to be measured from the ideal contour.
In one embodiment, the way to calculate the average deviation value of the actual profile of the curve pattern of the exposure field to be measured from the ideal profile comprises: dividing the ideal contour of the curve pattern of the exposure field to be measured to obtain a plurality of sampling curve segments; and carrying out average value calculation on the calculated average deviation value between the actual contour and each sampling curve segment of the ideal contour to obtain the average deviation value of the actual contour of the curve pattern of the exposure field to be measured to the ideal contour.
In one embodiment, the means for calculating the average deviation value between the actual profile and each sampled curve segment of the ideal profile comprises: dividing each sampling curve segment of the ideal contour to generate a plurality of sampling points of each sampling curve segment of the ideal contour; obtaining the intersection point of each sampling curve segment and the actual contour according to the normal direction of each sampling curve segment of the ideal contour; calculating a deviation value of each sampling point of each sampling curve segment based on each sampling point of each sampling curve segment and an intersection point of each sampling point and the actual contour; and carrying out average value calculation on the deviation value of each sampling point of each sampling curve segment to obtain the average deviation value between the actual contour and each sampling curve segment of the ideal contour.
The process of calculating the average deviation value of the actual profile versus the ideal profile of the curve pattern of the exposure field to be measured will be explained below with reference to the accompanying drawings:
And dividing the ideal contour of the curve pattern of the exposure field to be measured to obtain a plurality of sampling curve segments. The divided ideal profile is shown in fig. 5 (curve segment AB in fig. 5 is a sampled curve segment in the ideal profile).
Since the average deviation value between each sampled curve segment of the actual profile and the ideal profile is calculated in the same manner, the sampled curve segment AB is described below as an example:
As shown in fig. 6, the sampling curve segment AB is divided to generate a plurality of sampling points. The normal direction of the sampled curve segment AB is the normal direction of the connecting line of the curve segment starting point A and the curve segment ending point B. For each sampling point on the sampling curve segment, the intersection point of the sampling point and the actual contour is obtained along the normal direction of the sampling curve segment AB. The distance from the sampling point to the intersection point of the sampling point and the actual contour is the absolute value of the deviation value of the sampling point.
For example, as shown in fig. 6, for a sampling point a on the sampling curve segment AB, its intersection with the actual contour is b, and the distance between the sampling point a and the intersection b is the absolute value of the deviation value of the sampling point a.
The deviation value is positive or negative, and the manner of determining the deviation value to be positive or negative includes: if the line segment direction from a certain sampling point to the intersection point of the sampling point and the actual contour points to the outer side of the ideal contour, the deviation value of the sampling point is a positive value; if the line segment direction from the sampling point to the intersection point of the sampling point and the actual contour points to the inner side of the ideal contour, the deviation value of the sampling point is a negative value.
And after obtaining the deviation values of the sampling points of each sampling curve segment, carrying out average value calculation on the deviation values of the sampling points of each sampling curve segment to obtain the average deviation value between the actual contour and each sampling curve segment of the ideal contour. Then, the average deviation value of the actual profile of the curve pattern of the exposure field to be measured from the ideal profile is calculated by the following equation 2：
; (Equation 2)
Where N is the number of sampled curve segments,Is the offset value of the sampling point.
Finally, the line edge roughness of the curve pattern of the exposure field to be measured is calculated by the following equation 3：
; (Equation 3)
Where N is the number of sampled curve segments,As the deviation value of the sampling point,An average deviation value of an actual contour of the curve pattern of the exposure field to be measured from an ideal contour.
Fig. 7 is a schematic block diagram of an apparatus 7 for measuring edge roughness of a curvilinear pattern line provided by an embodiment of the present application. As shown in fig. 7, the apparatus 7 includes:
an image acquisition module 71 for acquiring scanning electron microscope images of a plurality of exposure fields of a target wafer;
An alignment processing module 72, connected to the image acquisition module 71, for performing alignment processing on the scanning electron microscope image of each exposure field to obtain an average image of each exposure field;
An actual contour extraction module 73, connected to the alignment processing module 72, for performing contour extraction on an average image of an exposure field to be measured among the plurality of exposure fields, to obtain an actual contour of a curve pattern of the exposure field to be measured;
An ideal contour extraction module 74, connected to the alignment processing module 72, for performing contour extraction on a wafer average image obtained based on the average image of each exposure field, to obtain an ideal contour of the curve pattern of the exposure field to be measured;
The roughness calculation module 75 is connected to the actual contour extraction module 73 and the ideal contour extraction module 74, respectively, and obtains the line edge roughness of the curve pattern of the exposure field to be measured by calculating the average deviation value of the actual contour of the curve pattern of the exposure field to be measured from the ideal contour.
It should be understood that the specific process of each module to perform the corresponding steps is described in detail in the above method embodiments, and is not described herein for brevity.
It should also be understood that the division of the modules in the embodiment of the present application is merely a logic function division, and other division manners may be actually implemented. In addition, each functional module in the embodiments of the present application may be integrated in one processor, or may exist alone physically, or two or more modules may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules.
In one embodiment, the scanning electron microscope image of each exposure field includes: scanning electron microscope images obtained after scanning in a plurality of scanning directions, respectively.
In one embodiment, the scanning electron microscope image of each exposure field is aligned to obtain an average image of each exposure field, which includes: moving the scanning electron microscope image in each scanning direction of each exposure field to obtain an image aligned with the target layout in each scanning direction of each exposure field; determining an up-sampling multiple based on a minimum step length during movement and a pixel pitch of a scanning electron microscope image; up-sampling the image aligned with the target layout in each scanning direction of each exposure field according to the determined up-sampling multiple to obtain an up-sampled image in each scanning direction of each exposure field; based on the upsampled images in the respective scanning directions of each exposure field, an average image of each exposure field is obtained.
In one embodiment, an average image for each exposure field is obtained based on the upsampled image for the respective scanning direction of each exposure field, which process comprises: determining a maximum rectangular overlap region between the upsampled images in the respective scanning directions for each exposure field; based on the up-sampled image in the respective scanning directions of each exposure field, an average value of the intensities of each pixel point within the maximum rectangular overlap region is calculated to obtain an average image of each exposure field.
In one embodiment, the way to calculate the average deviation value of the actual profile of the curve pattern of the exposure field to be measured from the ideal profile comprises: dividing the ideal contour of the curve pattern of the exposure field to be measured to obtain a plurality of sampling curve segments; and carrying out average value calculation on the calculated average deviation value between the actual contour and each sampling curve segment of the ideal contour to obtain the average deviation value of the actual contour of the curve pattern of the exposure field to be measured to the ideal contour.
In one embodiment, the means for calculating the average deviation value between the actual profile and each sampled curve segment of the ideal profile comprises: dividing each sampling curve segment of the ideal contour to generate a plurality of sampling points of each sampling curve segment of the ideal contour; obtaining the intersection point of each sampling curve segment and the actual contour according to the normal direction of each sampling curve segment of the ideal contour; calculating a deviation value of each sampling point of each sampling curve segment based on each sampling point of each sampling curve segment and an intersection point of each sampling point and the actual contour; and carrying out average value calculation on the deviation value of each sampling point of each sampling curve segment to obtain the average deviation value between the actual contour and each sampling curve segment of the ideal contour.
Fig. 8 is a schematic block diagram of an electronic terminal provided in an embodiment of the present application. As shown in fig. 8, the electronic terminal includes: at least one processor 801, memory 802, at least one network interface 803, and a user interface 805. The various components in the device are coupled together by a bus system 804. It is to be appreciated that the bus system 804 is employed to enable connected communications between these components. The bus system 804 includes a power bus, a control bus, and a status signal bus in addition to a data bus. But for clarity of illustration the various buses are labeled as bus systems in fig. 8.
The user interface 805 may include, among other things, a display, keyboard, mouse, trackball, click gun, keys, buttons, touch pad, or touch screen, etc.
It is to be appreciated that memory 802 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read Only Memory (ROM), a programmable Read Only Memory (PROM, programmable Read-Only Memory), which serves as an external cache, among others. By way of example, and not limitation, many forms of RAM are available, such as static random Access Memory (SRAM, staticRandom Access Memory), synchronous static random Access Memory (SSRAM, synchronous Static RandomAccess Memory). The memory described by embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.
The memory 802 in the embodiment of the present invention is used to store various kinds of data to support the operation of the electronic terminal 800. Examples of such data include: any executable programs for operating on the electronic terminal 800, such as an operating system 8021 and application programs 8022; the operating system 8021 contains various system programs, such as framework layers, core library layers, driver layers, etc., for implementing various basic services and handling hardware-based tasks. The application 8022 may comprise various applications, such as a media player (MEDIA PLAYER), browser (Browser), etc., for implementing various application services. The method for measuring the edge roughness of the curve pattern line provided by the embodiment of the invention can be contained in the application program 8022.
The method disclosed in the above embodiment of the present invention may be applied to the processor 801 or implemented by the processor 801. The processor 801 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware in the processor 801 or by instructions in software. The Processor 801 may be a general purpose Processor, a digital signal Processor (DSP, digital Signal Processor), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The processor 801 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. The general purpose processor 801 may be a microprocessor or any conventional processor or the like. The steps of the accessory optimization method provided by the embodiment of the invention can be directly embodied as the execution completion of the hardware decoding processor or the execution completion of the hardware and software module combination execution in the decoding processor. The software modules may be located in a storage medium having memory and a processor reading information from the memory and performing the steps of the method in combination with hardware.
In an exemplary embodiment, the electronic terminal 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, programmable logic devices (PLDs, programmable Logic Device), complex programmable logic devices (CPLDs, complex Programmable Logic Device) for performing the aforementioned method of measuring curve pattern line edge roughness.
According to a method provided by an embodiment of the present application, the present application also provides a computer program product, including: computer program code which, when run on a computer, causes the computer to perform the method of measuring edge roughness of a curved pattern line in the embodiment shown in fig. 1.
According to the method provided by the embodiment of the application, the application further provides a computer readable storage medium, wherein the computer readable storage medium stores a program code, and when the program code runs on a computer, the computer is caused to execute the method for measuring the edge roughness of the curve pattern line in the embodiment of fig. 1.
As used in this specification, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a computing device and the computing device can be a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between 2 or more computers. Furthermore, these components can execute from various computer readable media having various data structures stored thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from two components interacting with one another in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).
Those of ordinary skill in the art will appreciate that the various illustrative logical blocks (illustrative logical block) and steps (steps) described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
In the above-described embodiments, the functions of the respective functional units may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions (programs). When the computer program instructions (program) are loaded and executed on a computer, the processes or functions in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by a wired (e.g., coaxial cable, fiber optic, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). Computer readable storage media can be any available media that can be accessed by a computer or data storage devices, such as servers, data centers, etc., that contain an integration of one or more available media. Usable media may be magnetic media (e.g., floppy disks, hard disks, magnetic tape), optical media (e.g., high density digital video discs (digital video disc, DVD), or semiconductor media (e.g., solid State Drives (SSDs)), etc.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
In summary, the present application provides a method, apparatus, terminal, medium and program product for measuring edge roughness of a curved pattern line, where the method includes: acquiring scanning electron microscope images of a plurality of exposure fields of a target wafer; performing alignment processing on the scanning electron microscope image of each exposure field to obtain an average image of each exposure field, and further obtaining the actual contour of the curve pattern of the exposure field to be measured by a contour extraction mode; contour extraction is carried out on an average image of the wafer obtained based on the average image of each exposure field, and an ideal contour of a curve pattern of the exposure field to be measured is obtained; the line edge roughness of the curve pattern of the exposure field to be measured is obtained by calculating the average deviation value of the actual contour of the curve pattern of the exposure field to be measured from the ideal contour. The method of the application realizes the measurement of the line edge roughness of arbitrary curve patterns. The actual contour and the ideal contour of the curve pattern extracted by the method have higher precision. Therefore, the application effectively overcomes various defects in the prior art and has high industrial utilization value.
The above embodiments are merely illustrative of the principles of the present application and its effectiveness, and are not intended to limit the application. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the application. Accordingly, it is intended that all equivalent modifications and variations of the application be covered by the claims, which are within the ordinary skill of the art, be within the spirit and scope of the present disclosure.
Claims (7)
1.A method of measuring line edge roughness of a curvilinear pattern, comprising:
Acquiring scanning electron microscope images of a plurality of exposure fields of a target wafer; wherein the scanning electron microscope image of each exposure field comprises: scanning electron microscope images respectively obtained after scanning in a plurality of scanning directions;
Performing alignment processing on the scanning electron microscope image of each exposure field to obtain an average image of each exposure field; wherein, the process comprises the following steps:
Moving the scanning electron microscope image in each scanning direction of each exposure field to obtain an image aligned with the target layout in each scanning direction of each exposure field; determining an up-sampling multiple based on a minimum step length during movement and a pixel pitch of a scanning electron microscope image; up-sampling the image aligned with the target layout in each scanning direction of each exposure field according to the determined up-sampling multiple to obtain an up-sampled image in each scanning direction of each exposure field;
obtaining an average image for each exposure field based on the upsampled images in the respective scanning directions of each exposure field;
And wherein an average image for each exposure field is obtained based on the upsampled images for the respective scanning directions of each exposure field, the process comprising: determining a maximum rectangular overlap region between the upsampled images in the respective scanning directions for each exposure field; calculating an average value of intensities of each pixel point in the maximum rectangular overlapping region based on the up-sampled image in the respective scanning directions of each exposure field to obtain an average image of each exposure field;
Contour extraction is carried out on average images of the exposure fields to be measured in the plurality of exposure fields, and the actual contour of the curve pattern of the exposure fields to be measured is obtained;
Contour extraction is carried out on an average image of a wafer obtained based on the average image of each exposure field, and an ideal contour of a curve pattern of the exposure field to be measured is obtained;
And obtaining the line edge roughness of the curve pattern of the exposure field to be measured by calculating the average deviation value of the actual contour of the curve pattern of the exposure field to be measured from the ideal contour.
2. The method for measuring line edge roughness of a curve pattern according to claim 1, wherein the way of calculating the average deviation value of the actual profile of the curve pattern of the exposure field to be measured from the ideal profile comprises:
Dividing the ideal contour of the curve pattern of the exposure field to be measured to obtain a plurality of sampling curve segments;
and carrying out average value calculation on the calculated average deviation value between the actual contour and each sampling curve segment of the ideal contour to obtain the average deviation value of the actual contour of the curve pattern of the exposure field to be measured to the ideal contour.
3. The method of measuring line edge roughness of a curve pattern as claimed in claim 2, wherein the way of calculating an average deviation value between said actual profile and each sampled curve segment of said ideal profile comprises:
dividing each sampling curve segment of the ideal contour to generate a plurality of sampling points of each sampling curve segment of the ideal contour;
Obtaining the intersection point of each sampling curve segment and the actual contour according to the normal direction of each sampling curve segment of the ideal contour;
Calculating a deviation value of each sampling point of each sampling curve segment based on each sampling point of each sampling curve segment and an intersection point of each sampling point and the actual contour;
and carrying out average value calculation on the deviation value of each sampling point of each sampling curve segment to obtain the average deviation value between the actual contour and each sampling curve segment of the ideal contour.
4. An apparatus for measuring edge roughness of a curvilinear pattern line, comprising:
An image acquisition module for acquiring scanning electron microscope images of a plurality of exposure fields of a target wafer; wherein the scanning electron microscope image of each exposure field comprises: scanning electron microscope images respectively obtained after scanning in a plurality of scanning directions;
The alignment processing module is connected with the image acquisition module and is used for performing alignment processing on the scanning electron microscope image of each exposure field to obtain an average image of each exposure field; wherein, the process comprises the following steps:
Moving the scanning electron microscope image in each scanning direction of each exposure field to obtain an image aligned with the target layout in each scanning direction of each exposure field; determining an up-sampling multiple based on a minimum step length during movement and a pixel pitch of a scanning electron microscope image; up-sampling the image aligned with the target layout in each scanning direction of each exposure field according to the determined up-sampling multiple to obtain an up-sampled image in each scanning direction of each exposure field; obtaining an average image for each exposure field based on the upsampled images in the respective scanning directions of each exposure field;
Based on the upsampled image of each exposure field in the respective scanning direction, an average image of each exposure field is obtained, which process comprises: determining a maximum rectangular overlap region between the upsampled images in the respective scanning directions for each exposure field; calculating an average value of intensities of each pixel point in the maximum rectangular overlapping region based on the up-sampled image in the respective scanning directions of each exposure field to obtain an average image of each exposure field;
The actual contour extraction module is connected with the alignment processing module and is used for extracting the contour of the average image of the exposure field to be measured in the plurality of exposure fields to obtain the actual contour of the curve pattern of the exposure field to be measured;
an ideal contour extraction module, connected with the alignment processing module, for extracting the contour of the average image of the wafer obtained based on the average image of each exposure field, to obtain the ideal contour of the curve pattern of the exposure field to be measured;
And the roughness calculation module is respectively connected with the actual contour extraction module and the ideal contour extraction module, and obtains the line edge roughness of the curve pattern of the exposure field to be measured by calculating the average deviation value of the actual contour of the curve pattern of the exposure field to be measured to the ideal contour.
5. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the method of any one of claims 1 to 3.
6. A computer program product comprising computer program code means for causing a computer to carry out the method as claimed in any one of claims 1 to 3 when said computer program code means are run on the computer.
7. An electronic terminal comprising a memory, a processor and a computer program stored on the memory, characterized in that the processor executes the computer program to implement the method of any one of claims 1 to 3.
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