Charged particle beam image processing device and charged particle beam device provided with it

Abstract

The present application provides a charged particle beam image processing apparatus and a charged particle beam device provided with the same. A charged particle beam image processing apparatus capable of setting an appropriate inspection area for an observation image including edges of a line pattern is provided. The charged particle beam image processing apparatus performs image processing on an observation image generated by a charged particle beam device, characterized by comprising: an extraction section that extracts edges of a line pattern from an inspection area of the observation image; a division section that divides the inspection area into divisions having a plurality of measurement point numbers; a measurement section that measures line edge roughness in each of the divisions, generating distribution data of the line edge roughness for each division; a calculation section that calculates line edge roughness in the entire inspection area, and calculates a theoretical curve of the line edge roughness for each division; and a determination section that determines whether the inspection area is appropriate based on a comparison of the distribution data and the theoretical curve.

Description

Technical Field

[0001] The present invention relates to a charged particle beam image processing apparatus for performing image processing on an observation image generated by a charged particle beam apparatus in line pattern inspection for semiconductors. Background Technology

[0002] Charged particle beam devices are used to generate images for observing the fine structure of a sample by irradiating it with charged particle beams such as electron beams. They are used in processes such as semiconductor manufacturing. In semiconductor manufacturing, the measurement of LER (Line Edge Roughness), which measures the unevenness of the edges of the semiconductor's line patterns, is crucial.

[0003] Patent Document 1 discloses a method for measuring the swing of LER based on theoretical grounds. Specifically, it discloses: calculating the spatial frequency distribution of LER at multiple edges measured within a measurement region shorter than the inspection area of ​​the observed image of the line pattern, and calculating the LER of the inspection area based on the calculated spatial frequency distribution.

[0004] Existing technical documents

[0005] Patent documents

[0006] Patent Document 1: JP 2008-116472

[0007] However, in Patent Document 1, the evaluation only focuses on the periodicity of edge groups and does not yet reach the evaluation of the continuity of edge groups. That is, due to the excessively wide inspection area, if the intervals between edges in the edge group become thicker, the continuity of the edge group cannot be maintained, and the measurement accuracy of line edge roughness will decrease. Summary of the Invention

[0008] Therefore, the object of the present invention is to provide a charged particle beam image processing apparatus capable of setting an appropriate inspection area for an observation image containing edges of line patterns.

[0009] To achieve the above objectives, the present invention provides a charged particle beam image processing apparatus for image processing of an observation image generated by a charged particle beam apparatus. The charged particle beam image processing apparatus is characterized by comprising: an extraction unit that extracts the edges of a line pattern from an inspection area of ​​the observation image; a segmentation unit that segments the inspection area into regions having a plurality of measurement points; a measurement unit that measures the line edge roughness in each of the regions and generates distribution data of the line edge roughness for each region; a calculation unit that calculates the line edge roughness over the entire inspection area and calculates a theoretical curve of the line edge roughness for each region; and a determination unit that determines whether the inspection area is appropriate based on a comparison between the distribution data and the theoretical curve.

[0010] The effects of the invention

[0011] According to the present invention, a charged particle beam image processing apparatus is provided that can set an appropriate inspection area for an observation image containing edges of line patterns. Attached Figure Description

[0012] Figure 1 This is a diagram illustrating an example of the overall structure of the charged particle beam image processing apparatus of Embodiment 1.

[0013] Figure 2 This is a diagram illustrating an example of the overall structure of a charged particle beam device.

[0014] Figure 3 This is a diagram illustrating the appropriate inspection area and sampling interval.

[0015] Figure 4 This is a diagram illustrating an example of the process flow involved in Embodiment 1.

[0016] Figure 5 It is a graph that illustrates the comparison between the distributed data and the theoretical curve.

[0017] Figure 6 This is an example of a warning screen indicating an inappropriate sampling interval.

[0018] Explanation of reference numerals in the attached figures

[0019] 1: Charged particle beam image processing device; 2: Computation unit; 3: Memory; 4: Storage device; 5: Network adapter; 6: System bus; 7: Display device; 8: Input device; 10: Charged particle beam device; 11: Charged particle beam image database; 101: Electron beam source; 102: Primary electron beam; 103: Objective lens; 104: Deflector; 105: Sample; 106: Movable stage; 108: Secondary electron beam; 112: Detector; 115: Image processing unit; 116: Input / output unit; 117: Storage unit; 119: Control unit; 121: Optical axis Detailed Implementation

[0020] Embodiments of the charged particle beam image processing apparatus according to the present invention will be described below with reference to the accompanying drawings. Furthermore, in the following description and drawings, components having the same functional structure are labeled with the same reference numerals, thereby omitting repeated descriptions.

[0021]

Example 1

[0022] Figure 1This diagram illustrates the hardware structure of the charged particle beam image processing apparatus 1. The charged particle beam image processing apparatus 1 is configured to be connected to the arithmetic unit 2, memory 3, storage device 4, and network adapter 5 via a system bus 6. Furthermore, the charged particle beam image processing apparatus 1 is connected to the charged particle beam device 10 and the charged particle beam image database 11 via a network 9. A display device 7 and an input device 8 are also connected to the charged particle beam image processing apparatus 1. Here, "enabled to transmit and receive signals" refers to a state where signals can be transmitted and received between electrical and optical grounds, regardless of whether they are wired or wireless.

[0023] The arithmetic unit 2 is a device that controls the operation of each component, specifically a CPU (Central Processing Unit) or MPU (Micro Processor Unit). The arithmetic unit 2 loads the program stored in the storage device 4 and the data required for program execution into the memory 3 and executes it to perform various image processing operations on the charged particle beam image. The memory 3 stores the program executed by the arithmetic unit 2 and the intermediate processing steps. The storage device 4 is a device that stores the program executed by the arithmetic unit 2 and the data required for program execution, specifically an HDD (Hard Disk Drive) or SSD (Solid State Drive). The network adapter 5 is used to connect the charged particle beam image processing device 1 to a network 9 such as a LAN, telephone line, or the Internet. Various data processed by the arithmetic unit 2 can be transmitted and received from the outside of the charged particle beam image processing device 1 via the network 9 such as a LAN (Local Area Network).

[0024] Display device 7 is a device for displaying the processing results of charged particle beam image processing device 1, specifically a liquid crystal display, touch panel, etc. Input device 8 is an operating device for the operator to give operating instructions to charged particle beam image processing device 1, specifically a keyboard, mouse, touch panel, etc. The mouse can also be a trackpad, trackball, or other pointing device.

[0025] The charged particle beam device 10 is an apparatus that generates an image of a sample for observation by irradiating it with a charged particle beam, such as a scanning electron microscope (SEM) that generates an image by scanning the sample with an electron beam. The charged particle beam image database 11 is a database system that stores the images generated by the charged particle beam device 10, corrected images obtained by image processing of the images, etc.

[0026] use Figure 2To illustrate the overall structure of a scanning electron microscope, which is an example of a charged particle beam device 10. Furthermore, in Figure 2 In this design, the direction perpendicular to the paper is defined as the X-axis, the vertical direction as the Y-axis, and the horizontal direction as the Z-axis. The scanning electron microscope includes an electron beam source 101, an objective lens 103, a deflector 104, a movable stage 106, a detector 112, an image processing unit 115, an input / output unit 116, a storage unit 117, and a control unit 119. Each part is described below.

[0027] Electron beam source 101 is a radiation source that irradiates sample 105 with a primary electron beam 102 accelerated by a given accelerating voltage.

[0028] Objective lens 103 is a converging lens used to focus the primary electron beam 102 onto the surface of sample 105. In many cases, objective lens 103 uses a magnetic pole lens with a coil and magnetic poles.

[0029] Deflector 104 is a coil or electrode that generates a magnetic field and an electric field to deflect the primary electron beam 102. By deflecting the primary electron beam 102, the surface of the sample 105 is scanned with the primary electron beam 102. In addition, the straight line connecting the center of the electron beam source 101 and the objective lens 103 is called the optical axis 121, and the primary electron beam 102, which is not deflected by deflector 104, irradiates the sample 105 along the optical axis 121.

[0030] The movable stage 106 holds the sample 105 and moves the sample 105 in the X and Y directions.

[0031] Detector 112 is a detector that detects secondary electrons 108 emitted from a sample 105 irradiated by a primary electron beam 102. Detector 112 uses an ET detector or semiconductor detector composed of a scintillator / photoconductor / photoelectron multiplier tube. The detection signal output from detector 112 is sent to image processing unit 115 via control unit 119.

[0032] The image processing unit 115 is an arithmetic unit that generates an observed image based on the detection signal output from the detector 112. It may be, for example, an MPU (Micro Processing Unit) or a GPU (Graphics Processing Unit). The image processing unit 115 can perform various image processing operations on the generated observed image. Furthermore, using... Figure 1 The charged particle beam image processing device 1 described herein may be an image processing unit 115.

[0033] The input / output unit 116 is a device that receives input conditions for observing the sample 105, i.e., observation conditions, or displays an image generated by the image processing unit 115, such as a keyboard, mouse, touch panel, liquid crystal display, etc.

[0034] Storage unit 117 is a device for storing various data and programs, such as HDD (Hard Disk Drive) and SSD (Solid State Drive). Storage unit 117 stores programs executed by control unit 119, observation conditions input from input / output unit 116, images generated by image processing unit 115, etc.

[0035] The control unit 119 is an arithmetic unit that controls each unit and processes or sends data generated in each unit, such as a CPU (Central Processing Unit), MPU, etc.

[0036] The charged particle beam device described above generates an observation image for observing the line pattern of a semiconductor. This observation image is then used to measure the unevenness of the edges of the line pattern, i.e., line edge roughness (LER). For high-precision measurement of line edge roughness, it is important to define an appropriate inspection area for the observation image.

[0037] use Figure 3 To indicate the appropriate inspection area. Figure 3 Examples (a), (b), and (c) illustrate cases where the size of the examination area set for the observed image is small, medium, and large. Additionally, the examination area is... Figure 3 In (a), (b), and (c), each is shown as a vertically elongated rectangle. Furthermore, the location of the edges extracted from the inspection area is... Figure 3 The results of (a), (b), and (c) are shown in line graphs.

[0038] exist Figure 3 In cases where the inspection area is relatively small, as shown in (a), the sampling intervals of the extracted edges become denser. Therefore, although the continuity of the edge group is maintained, the evaluation of the periodicity of the edge group becomes insufficient. Furthermore, in Figure 3 In cases where the inspection area is relatively large, as shown in (c), the sampling interval of the extracted edges becomes sparser. Therefore, although periodic evaluation of edge groups is possible, the continuity of edge groups cannot be maintained. Thus, it is necessary to set... Figure 3 (b) refers to an appropriate inspection area that allows for periodic evaluation of edge groups while maintaining their continuity. In Example 1, the appropriate inspection area is set through the processing flow described later.

[0039] use Figure 4 An example of the processing flow of Example 1 will be described step by step.

[0040] (S401)

[0041] An inspection area is set for the observation image generated by the charged particle beam device 10. The inspection area can be set by the calculation unit 2 or by an operator using the input device 8. In addition, the calculation unit 2 sets the sampling interval of the edges corresponding to the set inspection area.

[0042] (S402)

[0043] The arithmetic unit 2 extracts the edges of the line pattern within the inspection area set in S401. For example, in the profile of brightness values ​​arranged horizontally within the inspection area, the position where the difference between adjacent brightness values ​​is greatest is extracted as the edge. Edge extraction is performed at a sampling interval set for the inspection area.

[0044] (S403)

[0045] The arithmetic unit 2 divides the inspection area set in S401 into multiple zones. Each zone has a number of measurement points.

[0046] (S404)

[0047] The calculation unit 2 measures the line edge roughness in each of the regions divided in S403. The line edge roughness is, for example, set as the standard deviation σ of the distance from the reference line to each edge, as shown in the following formula. In addition, the reference line is an approximate straight line calculated from the edge group in the entire inspection area, and a straight line set in the longitudinal direction in the observed image.

[0048]

Mathematical Formula 1

[0049]

[0050] Here, k is the number of measurement points in the zoning, i is an integer from 1 to k, and x i x is the distance from the baseline to each edge. k_ave It is x in each district i The average value.

[0051] (S405)

[0052] The computation unit 2 generates distribution data of the line edge roughness for each zone measured in S404. The distribution data is generated, for example, as a histogram where the horizontal axis is the interval of line edge roughness and the vertical axis is the frequency in each interval.

[0053] (S406)

[0054] The arithmetic unit 2 calculates the line edge roughness across the entire inspection area set in S401. The line edge roughness σ across the entire inspection area... true For example, it can be calculated using the following formula.

[0055]

Mathematical Formula 2

[0056]

[0057] Here, n is the number of edges in the entire region being examined, i is an integer from 1 to n, and x... i x is the distance from the baseline to each edge. ave It is x i The average value.

[0058] (S407)

[0059] The computation unit 2 calculates the theoretical curve of the line edge roughness of each zone measured in S404. The theoretical curve is, for example, the probability density f(σ;k) of the line edge roughness σ of each zone with the number of measurement points k, and is calculated by the following formula.

[0060]

Mathematical Expression 3

[0061]

[0062] Here, Γ(k / 2) is the gamma function characterized by the following formula.

[0063]

Mathematical Expression 4

[0064]

[0065] (S408)

[0066] The arithmetic unit 2 compares the distribution data generated in S405 with the theoretical curve calculated in S407 to determine whether the check area set in S401 is appropriate. If the check area is appropriate, the processing flow ends; if it is inappropriate, it returns to the processing in S401 and sets the check area again.

[0067] use Figure 5 This is used to illustrate the comparison between the distributed data and the theoretical curve. Figure 5 Example in Figure 3 The example shows three histograms and theoretical curves of the distribution data generated in each inspection area. Figure 5 The horizontal axis represents the line edge roughness (3σ) of each region with k measurement points, the vertical axis of the distributed data represents the frequency on the left, and the vertical axis of the theoretical curve represents the probability density on the right.

[0068] In distribution data with sparse sampling intervals that do not maintain the continuity of edge groups, there are relatively large line edge roughnesses with 3σ > 5 nm. Conversely, in distribution data with dense sampling intervals where periodicity is insufficient for evaluation, there are only relatively small line edge roughnesses with 3σ < 2.5 nm. That is, if the maximum value of the line edge roughness in the distribution data is within a given range, for example, between the upper and lower limits obtained from a theoretical curve, the inspection area can be determined to be appropriate. Furthermore, if the maximum value of the line edge roughness in the distribution data is above the upper limit, the inspection area can be determined to be too wide due to a sparse sampling interval; if it is below the lower limit, the inspection area can be determined to be too narrow due to a dense sampling interval.

[0069] The upper and lower limits can be set based on the area enclosed by the theoretical curve and the horizontal axis. When the theoretical curve is calculated as a probability density f(σ;k), the area enclosed by the theoretical curve and the horizontal axis, i.e., the probability density f(σ;k), is integrated from σ = 0 to σ = ∞ to obtain a value of 1. Therefore, an area enclosed by the theoretical curve and the horizontal axis of, for example, 0.99, is set as the upper limit for line edge roughness, and an area of ​​0.5 is set as the lower limit.

[0070] Furthermore, the judgment in S408 is not limited to the maximum value of the line edge roughness using the distributed data. For example, if the correlation coefficient between the distributed data and the theoretical curve is within a given range, the inspection area is deemed appropriate. Additionally, before calculating the correlation coefficient between the distributed data and the theoretical curve, standardization is performed so that the area of ​​the entire histogram of the distributed data becomes 1. That is, the correlation coefficient between the standardized data obtained by standardizing the distributed data and the theoretical curve is calculated, and if the calculated correlation coefficient is within a given range, the inspection area is deemed appropriate.

[0071] Additionally, when S408 determines that the inspection area is inappropriate, it can be... Figure 6 An example warning screen is displayed on display device 7. Figure 6 (a) shows the warning screen when the sampling interval is sparse, and (b) shows the warning screen when the sampling interval is dense. The extracted edges are indicated by an × symbol. The operator can appropriately reset the inspection area by displaying whether the sampling interval is sparse or dense.

[0072] The processing flow described above is used to determine whether the set inspection area is appropriate for the observed image containing the edge of the line pattern. If it is not appropriate, the inspection area is set again. That is, according to Embodiment 1, a charged particle beam image processing apparatus that can set an appropriate inspection area can be provided.

[0073] The embodiments of the present invention have been described above. The present invention is not limited to the above embodiments and can be embodied by modifying the constituent elements without departing from the spirit of the invention. Furthermore, the multiple constituent elements disclosed in the above embodiments can be appropriately combined. Moreover, several constituent elements can be deleted from all the constituent elements shown in the above embodiments.

Claims

1. A charged particle beam image processing device, for processing observation images generated by a charged particle beam device, characterized in that, have: The extraction unit extracts the edges of a line pattern from the inspection area of ​​the observed image at a sampling interval set for the inspection area; A segmentation section that divides the inspection area into zones with multiple measurement points; The measurement unit measures the line edge roughness in each of the zones and generates distribution data of the line edge roughness for each zone. The calculation unit calculates the line edge roughness across the entire inspection area and calculates the theoretical curve of the line edge roughness for each zone. The determination unit determines whether the inspection area is appropriate based on a comparison between the distribution data and the theoretical curve. and The display unit, when determining that the inspection area is inappropriate, displays whether the sampling interval is too sparse or too dense, so as to reset the inspection area. The determination unit determines that the inspection area is appropriate when the maximum value of the line edge roughness of the distributed data is between the upper and lower limits obtained from the theoretical curve, or when the correlation coefficient between the standardized data (where the area of ​​the distributed data becomes 1) and the theoretical curve is within a given range.

2. The charged particle beam image processing apparatus according to claim 1, characterized in that, The calculation unit calculates the theoretical curve based on the line edge roughness across the entire inspection area and the number of measurement points.

3. The charged particle beam image processing apparatus according to claim 1, characterized in that, When the maximum value of the roughness of the line edge is not between the upper and lower limits obtained according to the theoretical curve, the determination unit determines that the inspection area is inappropriate.

4. The charged particle beam image processing apparatus according to claim 3, characterized in that, When the maximum value of the roughness of the line edge is above the upper limit value, the determination unit determines that the inspection area is too wide.

5. The charged particle beam image processing apparatus according to claim 3, characterized in that, When the maximum value of the roughness of the line edge is below the lower limit value, the determination unit determines that the inspection area is too narrow.

6. A charged particle beam device, characterized in that, have: The charged particle beam image processing apparatus according to claim 1.

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