CN119515984A

CN119515984A - A method and device for locating reference points in a measurement area

Info

Publication number: CN119515984A
Application number: CN202510087936.0A
Authority: CN
Inventors: 李景峰; 谢宇梁
Original assignee: Yixin Technology Hangzhou Co ltd
Current assignee: Yixin Technology Hangzhou Co ltd
Priority date: 2025-01-20
Filing date: 2025-01-20
Publication date: 2025-02-25
Anticipated expiration: 2045-01-20
Also published as: CN119515984B

Abstract

The application discloses a method and a device for positioning a reference point of a measurement area, which directly operate geometric data through a geometric method, extract characteristic values, gradually screen out points suitable for serving as the reference point of the measurement area, such as AP and/or AFP, shorten time consumption, improve efficiency, and more effectively realize measuring Critical Dimension (CD) and positioning a target area, such as an EP area. Meanwhile, the problem that the operation time is increased along with the increasing amplitude of the image size is avoided.

Description

Method and device for positioning reference point of measurement area

Technical Field

The present application relates to, but is not limited to, semiconductor integrated circuit technology, and more particularly to a method and apparatus for locating a reference point of a measurement area.

Background

In order to meet the demands for higher speed and higher integration of semiconductor devices, circuit patterns are becoming finer and finer. In order to ensure accuracy of the fabrication process, a resolution enhancement function (RET) and Optical Proximity Correction (OPC) are introduced. However, these finer masks add complexity to the fabrication, making it more difficult to predict the transmission shape by simulation. Consequently, critical dimension scanning electron microscope (CD-SEM, critical Dimension Scanning Electron Microscopy) metrology requirements have also become more complex and diverse, particularly when characterizing critical OPC models, the number of measurement area points (EP, evaluation Points) required has increased dramatically.

In semiconductor manufacturing processes, engineers use images obtained from wafers as reference templates in order to measure critical dimensions (e.g., the width or pitch of micro-circuits) on the wafer. These images are typically taken by optical microscopy or Scanning Electron Microscopy (SEM). In order to make measurements using a CD-SEM, the operator needs to align the Field of View (FOV) of the microscope with the target area. This alignment is done manually, requiring the operator to adjust the position of the sample under the microscope so that the designated measurement area is exactly centered in the field of view of the microscope. Since the operator needs to manually align the CD-SEM to specify the FOV of a location, it typically takes several minutes to collect an image template each time. Thus, creating a CD-SEM image template containing a large number of policies typically takes several hours.

To cope with this time-consuming manual operation, technical approaches based on automation are gradually introduced in the industry. These methods identify image features mainly by image matching and pixel traversal, in particular based on image features of auto focus (AFP, autofocus Point) and addressing points (AP, ADDRESSING POINT), automatically find the corresponding points in the vicinity of the EP, that is, by AFP and AP features in the image, and quickly determine the position of the measurement region EP using automated techniques. However, the temporal complexity of image conversion increases exponentially with increasing image size, and the time required for computation can be far from expected when processing larger images, resulting in inefficiency.

To ensure reliable measurements, engineers typically choose the appropriate AP and AFP to ensure accurate correction of the imaging position and focusing of the electron beam. Traditionally, the selection of these points has been largely dependent on the experience of the engineer, and has been time consuming, inefficient, and greatly increased in computation time with increasing image size.

Disclosure of Invention

The application provides a method and a device for positioning a reference point of a measurement area, which can shorten the time consumption, improve the efficiency and simultaneously avoid the problem of increasing the operation time along with the increase of the image size.

The embodiment of the application provides a method for positioning a reference point of a measurement area, which comprises the following steps:

setting a search range by taking a measurement area point EP as a center, extracting a geometric line segment and a division point thereof in the search range, wherein the division point is a plurality of candidate points obtained by dividing the geometric line segment at equal distance;

Extracting basic geometric features of each candidate point;

Calculating the characteristic value of each candidate point according to the extracted basic geometric characteristics;

acquiring a screening weighted value according to the obtained characteristic value of each candidate point;

and after sorting according to the screening weighted characteristic values, screening the candidate points according to screening conditions to obtain the reference points of the positioning measurement areas.

In one illustrative example, the base geometric features include:

Width, representing the shortest distance of the candidate point to the inside geometry;

a space representing the shortest distance of the candidate point to the outside geometry;

length represents the total length of the geometric line segment where the candidate point is located;

Where width=width× (-1/length), space=space× (-1/length).

In an exemplary embodiment, the positioning measurement region reference point is an addressing point AP;

The characteristic value of each candidate point comprises a distance characteristic value and a symmetry characteristic value of each candidate point and the EP.

In one illustrative example, a gaussian function is used to calculate the distance feature value of each of the candidate points from the EP and ensure that the preset distance requirement is met.

In one illustrative example, the computing symmetry features includes, for example:

Calculating a first symmetry feature value of the length direction;

Calculating a second symmetry characteristic value of the width/space direction;

And combining the first symmetry characteristic value and the second symmetry characteristic value to obtain the symmetry characteristic.

In one illustrative example, the location measurement area reference point is an auto-focus AFP;

the feature value of each candidate point further comprises a geometric complexity feature.

In one illustrative example, computing the geometric complexity feature includes:

calculating the number of connected components of the line segment where the candidate point is located;

calculating the number of holes in the geometry, wherein the holes are closed geometric shapes formed by line segments or polygon boundaries;

And calculating the geometric complexity characteristic value according to the calculated number of the communicating components and the calculated number of the holes.

In one illustrative example, the screening condition is that the weighted feature value is the largest;

after sorting according to the screening weighted feature values, screening the candidate points according to screening conditions to obtain positioning measurement area reference points, wherein the method comprises the following steps:

and taking the point with the largest weighted characteristic value as the reference point of the positioning measurement area from the rest candidate points.

In an exemplary embodiment, the screening condition further includes that the connection angle between the candidate point and the EP is reasonable;

Further comprises:

Finding out a candidate point with the minimum weighted characteristic value, taking the candidate point as a datum point, and defining the connecting line direction of the datum point and the EP as 0 degree;

for each candidate point, calculating the connection angle of the connection line of the candidate point and the EP relative to a reference point;

and taking the point with the largest weighted characteristic value and reasonable connecting line angle of the candidate point and the EP as the reference point of the positioning measurement area.

Embodiments of the present application also provide a computer-readable storage medium storing computer-executable instructions for performing the method of locating a measurement region reference point as set forth in any one of the above.

An embodiment of the present application further provides a computer device, including a memory and a processor, where the memory stores instructions executable by the processor for performing the steps of the method for locating a measurement area reference point as described in any one of the above.

The embodiment of the application also provides a device for positioning the reference point of the measurement area, which comprises a first extraction module, a second extraction module, a calculation module, an acquisition module and a determination module, wherein,

The first extraction module is used for setting a search range by taking the EP as a center, extracting geometric line segments and division points thereof in the search range, wherein the division points are a plurality of candidate points obtained by dividing the geometric line segments at equal distances;

The second extraction module is used for extracting the basic geometric characteristics of each candidate point;

The calculation module is used for calculating the characteristic value of each candidate point according to the extracted basic geometric characteristics;

The acquisition module is used for acquiring screening weighted values according to the acquired characteristic values of each candidate point;

and the determining module is used for screening the candidate points according to screening conditions after sorting according to the screening weighted characteristic values so as to obtain the reference points of the positioning measurement areas.

According to the method for positioning the reference point of the measurement area, provided by the embodiment of the application, the geometric data is directly operated through a geometric method, the characteristic value is extracted, the points suitable for being used as the reference point of the measurement area, such as AP and/or AFP, are gradually screened out, the time consumption is shortened, the efficiency is improved, and the measurement of the Critical Dimension (CD) and the positioning of the target area, such as an EP area, are more efficiently realized. Meanwhile, the problem that the operation time is increased along with the increasing amplitude of the image size is avoided.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Drawings

The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate and do not limit the application.

FIG. 1 is a flow chart of a method for locating a reference point of a measurement area according to an embodiment of the application;

fig. 2 is a schematic structural diagram of an apparatus for locating a reference point of a measurement area according to an embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the present application more apparent, embodiments of the present application will be described in detail hereinafter with reference to the accompanying drawings. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be arbitrarily combined with each other.

In one typical configuration of the application, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer readable media, as defined herein, does not include non-transitory computer readable media (transmission media), such as modulated data signals and carrier waves.

The steps illustrated in the flowchart of the figures may be performed in a computer system, such as a set of computer-executable instructions. Also, while a logical order is depicted in the flowchart, in some cases, the steps depicted or described may be performed in a different order than presented herein.

In order to increase the efficiency of the measurement, certain specific feature points (such as AFP and AP) in the image are used as references, through which the image features of these points, specific positions near the EP are automatically located. AFP is a specific point for adjusting and optimizing the focal length of the electron beam, and image features (such as brightness change, edge definition, etc.) of AFP are extracted to guide the instrument to focus so as to ensure imaging definition and measurement accuracy. The AP is a reference point for alignment and positioning. By identifying features of these points (such as geometry or texture information), the location of the measurement region can be precisely located. That is, EP is a critical area to be measured, and AFP and AP are reference points to assist in positioning. By analyzing the image features of the AFP and the AP, the position relation between the datum points and the templates is automatically matched, so that the accurate position of the EP is quickly found.

The inventors believe that finding the AP and AFP near the EP is essentially the most characteristic finding point. The method of using the image is also to find the feature vector by the image. While the meaning of the feature vector is in fact that it represents the geometry around the point. In order to shorten the time consumption, improve the efficiency and avoid the problem of increasing the operation time along with the increase of the image size, the embodiment of the application avoids the problem of overlarge calculation amount caused by the image by avoiding the image without using the image, and adopts a graph method to process, because the graph is simpler and more convenient for calculating the geometric shape. Moreover, the geometry is composed of a topological structure, the data structure is simple, and the time complexity change is smaller along with the increase of the image size.

Fig. 1 is a flowchart of a method for locating a reference point of a measurement area according to an embodiment of the present application, as shown in fig. 1, may include:

And 100, setting a search range by taking the EP as a center, and extracting geometric line segments and division points thereof in the search range, wherein the division points are a plurality of candidate points obtained by dividing the geometric line segments at equal distances.

In the embodiment of the application, EP is a known target point and is the core position of the examination. The AP is an addressing point for uniquely locating the EP and AFP. AFP is an auto-focus for ensuring a clear focus position.

In the case that the reference point of the positioning measurement area is an AP, the distance between the AP and the EP point needs to meet the distance requirement, for example, about 4-8 micrometers (mum), the distance between the AP and the EP is taken as a characteristic value, and the points meeting the distance requirement can be screened through the distance. The AP is an addressing point in the drawing, is used as an index to find the position index of the EP and the AFP, and is used as an index of a unique address, and uniqueness are required.

In the case of locating the measurement area reference point as AFP, the distance of AFP from AP and EP needs to meet the distance requirement, i.e. the distance needs to be far enough to avoid overlapping or too close. In one embodiment, the AFP may be a little closer to the EP, e.g., around 4 μm, and the AFP may be a little further from the EP, e.g., around 8-10 μm.

In one illustrative example, the search range may be set to a range centered on, for example, 10 μm radius, EP.

It should be noted that, extracting the geometric line segments within the search range is a well-known technique for those skilled in the art, and the specific implementation is not intended to limit the protection scope of the present application.

And 101, extracting basic geometric characteristics of each candidate point.

In one illustrative example, the underlying geometric features may include, but are not limited to, a width (width) representing the shortest distance of the candidate point to the inside geometry, a space (space) representing the shortest distance of the candidate point to the outside geometry, a length (length) representing the total length of the geometric line segment in which the candidate point is located, and so forth.

In one embodiment, width=width× (-1/length).

In one embodiment, space = space× (-1/length).

And 102, calculating the characteristic value of each candidate point according to the extracted basic geometric characteristics.

In one illustrative example, the feature value of each candidate point may include a distance feature value, a symmetry feature value, of each candidate point from the EP.

In one illustrative example, a gaussian function may be used to calculate the distance feature value of each candidate point from the EP and ensure that the preset distance requirement is met.

In one embodiment, the distance feature value is calculated as shown in equation (1):

(1)

In the formula (1), μ represents an optimal distance, that is, an ideal distance between the candidate point and the EP, μ is a central value of the gaussian function, and corresponds to a position where a peak of the gaussian distribution is located. Sigma represents standard deviation, determines the width or the diffusion degree of the Gaussian function, and the larger the sigma is, the wider the Gaussian distribution is, and the smaller the sigma is, the narrower the Gaussian distribution is.

In an illustrative example, σ may be selected depending on the actual requirements, e.g., smaller σ (e.g., 1 μm) may be selected if a tight limitation of the distance range of the candidate points is desired, and larger σ (e.g., 2-3 μm) may be selected if a more relaxed screening range is desired.

In one illustrative example, the computing symmetry features in step 102 may include, for example:

calculating a first symmetry characteristic value of the length direction, wherein the symmetry of the length direction represents the distribution uniformity of the geometric line segments in the length direction. For example, the symmetry is higher when the candidate point is positioned in the middle of the collection line segment, and the symmetry is lower when the candidate point is close to one end of the collection line segment;

And calculating a second symmetry characteristic value of the width/space directions, wherein the symmetry of the width and space directions shows whether the distance distribution (the width on the inner side and the space on the outer side) around the candidate point is balanced or not. For example, if the difference between the inner and outer distances is smaller, the symmetry is high, and if the difference is larger, the symmetry is low;

and combining the first symmetry characteristic value in the length direction and the second symmetry characteristic value in the width/space direction to obtain symmetry characteristics.

In one embodiment, the first symmetry-feature value =Where d1 represents the distance from the candidate point to the start point of the geometric line segment and d2 represents the distance from the candidate point to the end point of the geometric line segment. When d1=d2 (candidate point is located right in the middle of the geometric line segment), the symmetry-feature value is at most 1. When d1 or d2 approaches 0, the symmetry-feature value approaches 0.

In one embodiment, the second symmetry-feature value =When width=space (inside and outside distribution balance of candidate points), the symmetry feature value is maximum, which is 1. When width or space is significantly larger than the other, the symmetry feature value approaches 0.

In one embodiment, combining the first symmetry feature value of the length direction and the second symmetry feature value of the width/space direction to obtain the symmetry feature may include symmetry feature value=α1·first symmetry feature value+β1·second symmetry feature value, where the sum is a weight coefficient for adjusting the contribution of the two directions to the overall symmetry. In the step, two symmetry characteristic values are combined into a comprehensive value to be used as quantized expression of candidate point symmetry for subsequent sorting and screening.

In one illustrative example, for the case where the location measurement area reference point is AFP, it is preferable to select points that are simpler in geometry and have a flat edge, as these points are more easily recognized and processed by the program during the auto-focus process. While a larger space value for a point (i.e., the shortest distance of the point to the outside geometry) generally indicates that the space around this point is relatively open, farther from other geometric elements, indicating that the edge may be flatter. In this scenario, the feature value of each candidate point in step 102 also includes a geometric complexity feature. In one embodiment, the geometric complexity feature may include analyzing topology information of the geometric line segment in which the candidate point is located, specifically as follows:

and calculating the number of connected components of the line segment where the candidate point is located, wherein in the geometric shape, one group of connected line segments form one connected component. If a line segment can be connected to another point by a series of other line segments, the line segments belong to the same connected component.

The number of holes (closed areas) in the geometry, which are closed geometries formed by line segments or polygonal boundaries, is calculated.

The higher the geometric complexity characteristic value is, the more complex the representation shape is, and the lower the geometric complexity characteristic value is, the simpler the representation shape is. In one embodiment, calculating the geometric complexity characteristic may include geometric complexity = α2-number of connected components + β2-number of holes, where α2 and β2 are weight coefficients, which may be adjusted according to actual requirements. In one embodiment, the number of bus segments representing the total number of segments in the connected component to which the candidate point belongs and the average segment length representing the total length of segments in the connected component divided by the number of segments may be further considered, and the calculation of the geometric complexity characteristic value may include geometric complexity characteristic value=α3·connected component number+β3·hole number+γ1·bus segment number+δ1·average segment length, where α3, β3, γ1, and δ1 are weight coefficients, and may be adjusted according to actual requirements.

It should be noted that how to calculate the number of connected components of the line segment where the candidate point is located and the number of holes (closed areas) in geometry are well known to those skilled in the art, and the specific implementation is not intended to limit the scope of the present application.

And 103, acquiring screening weighted values according to the obtained characteristic values of each candidate point.

In one illustrative example, for the case where the reference point of the positioning measurement area is AP, the screening weight is as follows, screening weight = α4-width + β4-space + γ2-distance feature + δ2-symmetry feature, where α4, β4, γ2 and δ2 are weight coefficients, which can be adjusted according to actual needs.

In an illustrative example, for the case where the reference point of the positioning measurement area is AFP, the screening weight is such that the screening weight = α5-width + β5-space + γ3-distance feature + δ3-symmetry feature + epsilon-geometry complexity feature, where α5, β5, γ3, δ3 and epsilon are weight coefficients, which can be adjusted according to the actual requirements.

And 104, after sorting according to the screening weighted characteristic values, screening the candidate points according to screening conditions to obtain positioning measurement area reference points.

In an exemplary embodiment, the filtering condition is that the weighted feature value is the largest, and step 104 may include:

The candidate points in the EP range are eliminated, a certain protection range (such as 0.5 mu m radius) around the EP is set, all the candidate points in the range are eliminated so as to avoid selecting the point too close to the EP, the candidate point with the largest weighted characteristic value is selected, and the point with the largest weighted characteristic value is taken as a positioning measurement area reference point from the rest candidate points.

In one embodiment, in order to ensure that the selected reference point of the positioning measurement area has the optimal characteristic, the screening condition further includes that the connection angle between the candidate point and the EP is reasonable, and step 104 may further include:

sorting from small to large according to the weighted characteristic value of each candidate point;

finding out a candidate point with the smallest weighted characteristic value, taking the candidate point as a reference point, and defining the connecting line direction of the reference point and the EP as 0 degree (the direction of a reference coordinate system);

For each candidate point, a line angle of a line connecting the candidate point and the EP is calculated with respect to the reference point. The angle can be normalized to a [0, 360] degree range and converted to a floating point type value by dividing it by 360;

if the weighted eigenvalues of the two candidate points are very close in the remaining candidate points, in order to ensure that the connection angle between the final positioning measurement area reference point and the EP has a certain directional advantage (such as avoiding too concentrated or repeated directions), the point with the largest weighted eigenvalue and reasonable connection angle between the candidate point and the EP is used as the positioning measurement area reference point.

It should be noted that reasonable means that the direction of the reference point of the positioning measurement area is associated with the geometric feature of the EP (such as the directivity or symmetry of the overall graph), so that candidate points that are too close to or repeat in direction with the EP are avoided, and that the finally selected reference point of the positioning measurement area is unique in geometric sense.

According to the method for positioning the reference points of the measurement area, provided by the embodiment of the application, the reference points of the measurement area such as AP and AFP are effectively identified based on the geometric features under the condition that image calculation is not used, so that the time consumption is shortened, the efficiency is improved, the calculation complexity is reduced, and the problem that the calculation time is prolonged along with the increase of the image size is avoided.

The application also provides a computer readable storage medium storing computer executable instructions for performing the method of locating a measurement region reference point as described in any one of the preceding claims.

The application further provides a computer device comprising a memory and a processor, wherein the memory has stored therein instructions executable by the processor for performing the steps of the method of locating a measurement area reference point as described in any of the above.

Fig. 2 is a schematic diagram of a composition structure of an apparatus for locating a reference point of a measurement area according to an embodiment of the present application, as shown in fig. 2, including a first extraction module, a second extraction module, a calculation module, an acquisition module, and a determination module, where,

According to the device for positioning the reference point of the measurement area, provided by the embodiment of the application, the geometric data is directly operated through a geometric method, the characteristic value is extracted, the points suitable for being used as the reference point of the measurement area, such as AP and/or AFP, are gradually screened out, the time consumption is shortened, the efficiency is improved, and the measurement of the Critical Dimension (CD) and the positioning of the target area, such as an EP area, are more efficiently realized. Meanwhile, the problem that the operation time is increased along with the increasing amplitude of the image size is avoided.

Although the embodiments of the present application are described above, the embodiments are only used for facilitating understanding of the present application, and are not intended to limit the present application. Any person skilled in the art can make any modification and variation in form and detail without departing from the spirit and scope of the present disclosure, but the scope of the present disclosure is to be determined by the appended claims.

Claims

1. A method of locating a reference point of a measurement area, comprising:

Extracting basic geometric features of each candidate point;

2. The method of claim 1, wherein the base geometric feature comprises:

Where width=width× (-1/length), space=space× (-1/length).

3. The method of claim 1, wherein the positioning measurement region reference point is an addressing point, AP;

4. A method according to claim 3, wherein a gaussian function is used to calculate a distance characteristic value for each of the candidate points from the EP and ensure that a preset distance requirement is met.

5. A method according to claim 3, wherein said calculating symmetry features comprises, for example:

Calculating a first symmetry feature value of the length direction;

6. A method according to claim 3, wherein the positioning measurement region reference point is an auto-focus AFP;

7. The method of claim 6, wherein computing the geometric complexity feature comprises:

8. A method according to claim 3, wherein the screening condition is that the weighted feature value is maximum;

9. The method of claim 8, the screening criteria further comprising a reasonable angle of connection of the candidate points to the EP;

Further comprises:

10. A computer readable storage medium storing computer executable instructions for performing the method of locating a measurement region reference point of any one of claims 1-9.

11. A computer device comprising a memory and a processor, wherein the memory has stored therein instructions executable by the processor for performing the steps of the method of locating a measurement area reference point as set forth in any one of claims 1-9.

12. The device for positioning the reference point of the measurement area is characterized by comprising a first extraction module, a second extraction module, a calculation module, an acquisition module and a determination module, wherein,