Method and system for detecting sharp corner position in ion beam uniformity image

Abstract

The invention discloses a method and system for detecting a sharp corner position in an ion beam uniformity image, and the method comprises the steps: S1, obtaining beam current intensity data in a terminal target chamber, and drawing a uniformity image of an ion beam according to the beam current intensity data; s2, based on the beam current intensity data, calculating a current intensity mean value and a uniformity value of the uniformity image in a preset wafer injection range; s3, positioning a local maximum value point of the flow intensity value in the uniformity image; s4, for each local maximum value point, judging whether the flow intensity values of the local maximum value point and a plurality of continuous data points adjacent to the local maximum value point exceed a preset threshold value or not; if yes, judging that the local maximum value point is a sharp corner, and recording the horizontal abscissa of the local maximum value point; and S5, comparing the recorded horizontal abscissa of the sharp corner with left and right boundary abscissa of a preset wafer injection range to judge whether the sharp corner enters the wafer injection range or not. The method has the advantages of rapid and accurate sharp corner detection and the like.

Description

Technical Field

[0001] This invention relates primarily to the field of semiconductor fabrication technology, and specifically to a method and system for detecting sharp corner positions in ion beam uniformity images. Background Technology

[0002] In existing high-current beamforming equipment, the ribbon beam undergoes expansion, focusing, and deflection processes. Upon reaching the terminal, the beam often concentrates at both ends, manifesting as sharp corners in a one-dimensional uniformity image. If sharp corners exist and their influence extends into the wafer implantation area, failure to identify and address them can lead to difficulties in beam uniformity adjustment, causing the equipment's automatic adjustment function to malfunction and impacting production efficiency.

[0003] Currently, whether the beam is adjusted manually or automatically, there is no detection of sharp corner positions before adjustment, and visual observation alone is not accurate enough. If the sharp corner position enters the wafer implantation range, it will seriously affect the success rate of beam adjustment. Even if the uniformity is successfully adjusted by force, the beam will be greatly deformed, and the angle and beam density will be difficult to meet the implantation requirements.

[0004] Current technologies lack sufficient understanding of the impact on other parameters after forcibly adjusting sharp angles, and neglect the identification of sharp angle positions; secondly, there is a lack of simple and effective means to determine what kind of shape is a sharp angle and where it is located, and similar image recognition methods are not applicable to the actual use of ion implantation machines. Summary of the Invention

[0005] To address the technical problems existing in the prior art, the present invention provides a method and system for automatically, rapidly, and accurately identifying the location of sharp corners in an ion beam uniformity image.

[0006] To solve the above-mentioned technical problems, the technical solution proposed by this invention is as follows: A method for detecting sharp corner positions in an ion beam uniformity image, comprising the following steps: S1. Acquire beam current intensity data in the terminal target chamber, and draw a uniformity image of the ion beam based on the beam current intensity data; S2. Based on the beam current intensity data, calculate the mean current intensity (Mean) and uniformity value (U) of the uniformity image within the preset wafer implantation range; S3. Locate the local maximum point of the flow intensity value within the uniformity image; S4. For each local maximum point located in step S3, determine whether the current intensity value of itself and its adjacent multiple consecutive data points all exceed a preset threshold; if so, determine that the local maximum point is a sharp corner and record its horizontal coordinate; wherein the preset threshold is determined by the average current intensity Mean and the uniformity value U obtained in step S2. S5. Compare the horizontal coordinate of the sharp corner recorded in step S4 with the horizontal coordinates of the left and right boundaries of the preset wafer implantation range to determine whether the sharp corner has entered the wafer implantation range.

[0007] Preferably, in step S1, the specific process of drawing the uniformity image is as follows: continuously acquiring the beam current intensity of the wafer scanning plane in the target chamber; associating the scanning position coordinates with the corresponding current intensity data to draw the original ion beam current intensity distribution curve, i.e., the uniformity image.

[0008] Preferably, the specific process in step S2 is as follows: Within the preset wafer injection range, specifically corresponding to the actual lateral width of the wafer to receive injection in the process requirements, it has a clear left boundary coordinate X_left_wafer and right boundary coordinate X_right_wafer on the X-axis; Calculate the mean (Mean) of all current intensity data within this preset wafer implantation range; The uniformity value U within the preset wafer implantation range is calculated based on the mean (Mean).

[0009] Preferably, the formula for calculating the uniformity value U is: U = (σ / Mean) × 100%; Where σ is the standard deviation of all current intensity data within the preset wafer implantation range.

[0010] Preferably, in step S3, a local maximum point of the flux intensity value is located in a predetermined region within the uniformity image; wherein the predetermined region is the region near both ends of the boundary of a preset wafer injection range; specifically, the preset wafer injection range has a left boundary coordinate X_left_wafer and a right boundary coordinate X_right_wafer; the predetermined region is X_left_wafer±M and X_right_wafer±M, where M is a preset value.

[0011] Preferably, the range of values ​​for the multiple data points in step S4 is 5-10.

[0012] Preferably, the formula for calculating the preset threshold in step S4 is: Preset threshold = Mean × (1 + k × U); Where k is an adjustable sensitivity coefficient.

[0013] Preferably, in step S1, the Faraday is moved to scan on a horizontal axis perpendicular to the ion beam band direction, and its main dose cup is used to continuously acquire the beam current intensity of the target chamber wafer scanning plane.

[0014] The present invention also discloses a computer-readable storage medium having a computer program stored thereon, the computer program performing the steps of the method described above when run by a processor.

[0015] The present invention further discloses a detection system for sharp corner positions in an ion beam uniformity image, comprising a memory and a processor connected to each other, wherein the memory stores a computer program, and the computer program executes the steps of the method described above when run by the processor.

[0016] Compared with the prior art, the advantages of the present invention are as follows: This invention designs a detection algorithm based on moving Faraday measurement and statistical criteria, which can automatically, quickly and accurately identify the abnormal sharp corner positions at both ends of the ion beam uniformity image and determine whether they have invaded the wafer implantation range. This effectively solves the problem of automatic beam uniformity adjustment failure caused by sharp corners, and significantly improves the process debugging success rate and production efficiency of ion implanters. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the measurement component of the ion implanter of the present invention.

[0018] Figure 2 This is a schematic diagram of the uniformity image of the present invention (the left side is a sharp corner).

[0019] Figure 3 This is a schematic diagram of the uniformity image of the present invention (uniformity = 3.2).

[0020] Figure 4 This is a schematic diagram of the uniformity image of the present invention (uniformity = 0.88).

[0021] Figure 5 This is a flowchart of the detection method of the present invention in an embodiment.

[0022] Legend: 1. Moving Faraday; 2. Main dose cup. Detailed Implementation

[0023] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0024] The method for detecting sharp corner positions in an ion beam uniformity image provided in this invention relies on the measurement components of the ion implanter. For example... Figure 1As shown, the measurement component is a moving Faraday 1, which contains a main dose cup 2. This main dose cup 2 is made of graphite and connected to a corresponding signal acquisition circuit. When the ion beam bombards the graphite cup, a corresponding current signal is generated. By recording the beam current intensity data acquired by the moving Faraday 1 during scanning in the terminal target chamber, the obtained current intensity data is saved and plotted as a uniformity image. Parameters such as the ion beam current intensity, uniformity, band beam width, and horizontal center are calculated for subsequent analysis.

[0025] like Figure 5 As shown, the method for detecting sharp corner positions in an ion beam uniformity image according to an embodiment of the present invention includes the following steps: S1. Control the moving Faraday 1 to scan along the horizontal axis perpendicular to the ion beam band direction, and use its master dose cup 2 to continuously acquire the beam current intensity (unit: mA) at the corresponding position in the target chamber (usually the wafer scanning plane); correlate the scanning position coordinates (X-axis) with the corresponding current intensity data (Y-axis) to plot the original ion beam current intensity distribution curve, i.e., the uniformity image, such as... Figure 2 As shown.

[0026] S2. After obtaining complete flow intensity data, determine the wafer injection range; the wafer injection range usually corresponds to the actual lateral width of the wafer to receive injection in the process requirements, and has a clear left boundary coordinate X_left_wafer and right boundary coordinate X_right_wafer on the X-axis; Next, the mean of all current intensity data within the wafer implantation range is calculated. Then, the uniformity within this range is calculated based on the mean. In this embodiment, uniformity is represented by the coefficient of variation, which is the ratio of the standard deviation σ of the flow intensity data within this range to the mean. It is usually presented as a percentage, specifically: uniformity value U = (standard deviation / mean) × 100%.

[0027] S3. On the uniformity image, focus on the vicinity of the left-hand region (e.g., near the left boundary coordinate X_left_wafer) and the right-hand region (e.g., near the right boundary coordinate X_right_wafer); sharp-angle features typically appear at both ends of the beam distribution curve. Within the left-hand and right-hand regions, find local maxima of flux intensity (i.e., for a data point, its flux intensity is greater than the flux intensity of its preceding and following adjacent data points), and record the horizontal coordinates (X_potential_peak) of these local maxima and their corresponding flux intensity values ​​(I_potential_peak).

[0028] S4. For each local maximum point found in S3, perform the following processing: not only check the local maximum point itself, but also check its adjacent N consecutive data points (N is a positive integer, N is between 5 and 10, and the number of points can be increased or decreased to achieve a more refined or coarser judgment). Check whether the current intensity values ​​of these points (including the maximum point itself, a total of N+1 points) all exceed the preset threshold. If the current intensity values ​​of the maximum point and its adjacent N points are all greater than the preset threshold, it is determined that there is a sharp corner at this position, and the x-coordinate X_horn of the sharp corner is officially recorded. Otherwise, it is considered that the maximum value is just a normal fluctuation and not a harmful sharp corner.

[0029] The preset threshold (dynamic threshold) is calculated based on the uniformity value U and the mean value Mean calculated by S2, specifically as follows: Preset threshold = Mean × (1 + k × U); Where k is an adjustable sensitivity coefficient; in this preferred embodiment, k=3. That is, the preset threshold is set to the mean plus the fluctuation represented by 3 times the uniformity.

[0030] For example: if the calculated mean is 10mA and the uniformity is 1%, then the threshold is 10 × (1 + 3 × 0.01) = 10.3mA.

[0031] By using this statistical probability principle, we can effectively distinguish between genuine concentrated sharp angles that affect uniformity adjustment and ordinary random noise fluctuations.

[0032] S5. For each sharp corner identified in S4 (x-coordinate X_horn), compare it with the boundary of the wafer implantation range; if X_horn≤X_left_wafer (left-end sharp corner enters the left boundary) or X_horn≥X_right_wafer (right-end sharp corner enters the right boundary), then determine that the sharp corner has invaded the wafer implantation range; otherwise, determine that the sharp corner is outside the wafer implantation range.

[0033] like Figure 3 and Figure 4 The figures shown are comparative diagrams of different homogeneity states (homogeneity values ​​of 3.2 and 0.88, from poor to good).

[0034] This invention, through the design of a detection algorithm based on moving Faraday measurement and statistical criteria, can automatically, quickly, and accurately identify abnormal sharp corner positions at both ends of the ion beam uniformity image and determine whether they intrude into the wafer implantation range. This effectively solves the problem of automatic beam uniformity adjustment failure caused by sharp corners, significantly improving the process debugging success rate and production efficiency of the ion implanter. Of course, more sophisticated methods such as image recognition can also identify sharp corners, but these are too complex, and the time and computational costs are not suitable for the ion implantation scenario.

[0035] The present invention also discloses a computer-readable storage medium having a computer program stored thereon, the computer program performing the steps of the method described above when run by a processor.

[0036] The present invention further discloses a detection system for sharp corner positions in an ion beam uniformity image, comprising a memory and a processor connected to each other, wherein the memory stores a computer program, and the computer program executes the steps of the method described above when run by the processor.

[0037] The medium and system of the present invention, corresponding to the methods described above, also have the advantages described above.

[0038] The present invention can implement all or part of the processes in the methods of the above embodiments, or it can be implemented by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium includes: any entity or device capable of carrying computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. The memory is used to store computer programs and / or modules. The processor implements various functions by running or executing the computer programs and / or modules stored in the memory, and by calling data stored in the memory. The memory may include high-speed random access memory, as well as non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital (SD) cards, flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0039] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principle of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A method for detecting sharp corner positions in an ion beam uniformity image, characterized in that, Includes the following steps: S1. Acquire beam current intensity data in the terminal target chamber, and draw a uniformity image of the ion beam based on the beam current intensity data; S2. Based on the beam current intensity data, calculate the mean current intensity (Mean) and uniformity value (U) of the uniformity image within the preset wafer implantation range; S3. Locate the local maximum point of the flow intensity value within the uniformity image; S4. For each local maximum point located in step S3, determine whether the current intensity value of itself and its adjacent multiple consecutive data points all exceed a preset threshold; if so, determine that the local maximum point is a sharp corner and record its horizontal coordinate. The preset threshold is determined by the mean flow intensity Mean and the uniformity value U obtained in step S2. S5. Compare the horizontal coordinate of the sharp corner recorded in step S4 with the horizontal coordinates of the left and right boundaries of the preset wafer implantation range to determine whether the sharp corner has entered the wafer implantation range.

2. The method for detecting sharp corner positions in an ion beam uniformity image according to claim 1, characterized in that, In step S1, the specific process of drawing the uniformity image is as follows: continuously acquire the beam current intensity of the wafer scanning plane in the target chamber; correlate the scanning position coordinates with the corresponding current intensity data to draw the original ion beam current intensity distribution curve, i.e., the uniformity image.

3. The method for detecting sharp corner positions in an ion beam uniformity image according to claim 1 or 2, characterized in that, The specific process in step S2 is as follows: Within the preset wafer injection range, specifically corresponding to the actual lateral width of the wafer to receive injection in the process requirements, it has a clear left boundary coordinate X_left_wafer and right boundary coordinate X_right_wafer on the X-axis; Calculate the mean (Mean) of all current intensity data within this preset wafer implantation range; The uniformity value U within the preset wafer implantation range is calculated based on the mean (Mean).

4. The method for detecting sharp corner positions in an ion beam uniformity image according to claim 3, characterized in that, The formula for calculating the uniformity value U is: U = (σ / Mean) × 100%; Where σ is the standard deviation of all current intensity data within the preset wafer implantation range.

5. The method for detecting sharp corner positions in an ion beam uniformity image according to claim 1 or 2, characterized in that, In step S3, local maxima of the flux intensity value are located in a predetermined region within the uniformity image; wherein the predetermined region is the region near both ends of the boundary of a preset wafer implantation range; specifically, the preset wafer implantation range has left boundary coordinates X_left_wafer and right boundary coordinates X_right_wafer; the predetermined region is X_left_wafer±M and X_right_wafer±M, where M is a preset value.

6. The method for detecting sharp corner positions in an ion beam uniformity image according to claim 1 or 2, characterized in that, The range of values ​​for multiple data points in step S4 is 5-10.

7. The method for detecting sharp corner positions in an ion beam uniformity image according to claim 1 or 2, characterized in that, The formula for calculating the preset threshold in step S4 is: Preset threshold = Mean × (1 + k × U); Where k is an adjustable sensitivity coefficient.

8. The method for detecting sharp corner positions in an ion beam uniformity image according to claim 1 or 2, characterized in that, In step S1, the Faraday (1) is moved to scan on the horizontal axis perpendicular to the ion beam band direction, and its main dose cup (2) is used to continuously collect the beam current intensity of the target chamber wafer scanning plane.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program, when run by a processor, performs the steps of the method as described in any one of claims 1-8.

10. A system for detecting sharp corner positions in an ion beam uniformity image, comprising a memory and a processor interconnected, wherein the memory stores a computer program, characterized in that... The computer program, when run by a processor, performs the steps of the method as described in any one of claims 1-8.

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