Non-uniform ion implantation process monitoring method based on template matching image recognition

Abstract

The invention provides a non-uniform ion implantation process monitoring method based on template matching image recognition, and the method comprises the steps: 1, carrying out the to-be-monitored non-uniform ion implantation of a wafer, carrying out the modeling according to the measurement data of the wafer, and obtaining a template used for monitoring the dose / resistance distribution of the non-uniform ion implantation; step 2, carrying out resistance measurement on the batch of wafers after the non-uniform ion implantation, and drawing a resistance distribution diagram according to the coordinates and the resistance values of the measurement point positions; and 3, carrying out image identification comparison operation on the template obtained in the step 1 and the resistance distribution diagram obtained in the step 2 to obtain a similarity score, and carrying out statistical process control and control on the similarity score. Abnormalities such as deviation and rotation of dose distribution patterns of the non-uniform ion implantation process are effectively captured, and monitoring of the non-uniform ion implantation process is achieved.

Description

Technical Field

[0001] This application relates to the field of semiconductor technology, and specifically to a method for monitoring non-uniform ion implantation processes based on template matching image recognition. Background Technology

[0002] In semiconductor manufacturing, reactive gases are typically non-uniformly distributed radially across the wafer. The reactive gases are consumed at the wafer edges before flowing towards the center, resulting in less reactive gas at the center than at the edges. This causes variations in critical dimensions (CD), film thickness, and other parameters along the wafer's radial direction. While minor variations can be optimized to some extent by fine-tuning process parameters, they cannot be completely eliminated.

[0003] The continuous shrinking of semiconductor device dimensions and the increasing number of patterns per unit area exacerbate the non-uniform distribution of reactive gases in the wafer's radial direction. Gas is rapidly consumed by the patterns at the edges, leading to a severe shortage of reactive gas in the center. Consequently, differences in critical dimensions (CD) and film thickness in the wafer's radial direction become even more difficult to reduce, posing a significant challenge to controlling the within-wafer uniformity of the final device performance. For example, the inability to further reduce the difference between the gate CD at the edge and the center makes it difficult to solve the problem of the edge's Idsat being significantly lower than that of the center; the inability to further reduce the difference between the gate CD and the spacer thickness at the edge and the center results in a significant difference in Vt between the edge and the center, which is difficult to optimize.

[0004] To address this issue, existing technologies employ non-uniform ion implantation, adjusting the ion implantation dose distribution within the wafer from a uniform to a non-uniform state. This specifically reduces the performance differences of devices at different locations on the wafer, optimizing the wafer-wide uniformity of device performance. For example, the difference between the gate CD at the edge and the center cannot be further reduced. To address this, non-uniform ion implantation creates differences in implantation dose at each location, effectively compensating for the Idsat at the edge to the level of the center.

[0005] Current ion implantation process monitoring methods involve ion implantation and rapid thermal annealing of the wafer, followed by measurement of resistance at multiple points within the wafer. The average and standard deviation of the resistance at all points are then calculated, and statistical process control (SPC) is applied. However, non-uniform ion implantation dose distributions can exhibit elliptical or off-center shapes; therefore, current ion implantation process monitoring methods are not suitable for non-uniform ion implantation processes. Figure 1 For example, although the difference between the two resistance distributions is that the positions of the two high points have shifted, the average value and standard deviation of the two resistance distributions are the same, and the existing methods cannot capture anomalies such as graph shift and rotation. Summary of the Invention

[0006] In view of the shortcomings of the prior art described above, the purpose of this application is to provide a non-uniform ion implantation process monitoring method based on template matching image recognition, so as to solve the problem that the prior art cannot effectively monitor the non-uniform ion implantation process.

[0007] To achieve the above and other related objectives, this application provides a method for monitoring non-uniform ion implantation processes based on template matching image recognition, comprising:

[0008] Step 1: Perform non-uniform ion implantation to be monitored on a wafer, and model it based on the measurement data of the wafer to obtain a template for monitoring the dose / resistance distribution of the non-uniform ion implantation.

[0009] Step 2: Perform resistance measurements on the batch of wafers after the non-uniform ion implantation, and plot the resistance distribution map based on the coordinates and resistance values ​​of each measurement point.

[0010] Step 3: Perform image recognition comparison between the template obtained in Step 1 and the resistance distribution map obtained in Step 2 to obtain a similarity score, and then perform statistical process control on the similarity score.

[0011] Preferably, after non-uniform ion implantation is performed on the wafer, the wafer is subjected to rapid thermal treatment to activate the doped ions.

[0012] Preferably, the cosine similarity evaluation method is used to obtain the similarity score, and the formula for calculating the similarity score is: Where A is the feature vector obtained by template transformation, and B is the feature vector obtained by resistance distribution diagram transformation.

[0013] Preferably, the resistance measuring device is equipped with a software module that obtains a template, resistance distribution diagram and similarity score through the resistance measuring device, uploads the similarity score to the monitoring system, and performs statistical process control and management on the similarity score through the monitoring system.

[0014] Preferably, the monitoring system includes a software module that receives the resistance values ​​and coordinates uploaded by the resistance measuring device, obtains templates, resistance distribution maps and similarity scores through the monitoring system, and then performs statistical process control and management on the similarity scores.

[0015] As described above, the non-uniform ion implantation process monitoring method based on template matching image recognition provided in this application has the following beneficial effects: effectively capturing anomalies such as dose distribution pattern shift and rotation in non-uniform ion implantation processes, thereby realizing the monitoring of non-uniform ion implantation processes. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is an example diagram showing that existing ion implantation process monitoring methods cannot effectively monitor non-uniform ion implantation processes.

[0018] Figure 2 The flowchart shown is a method for monitoring non-uniform ion implantation process based on template matching image recognition provided in an embodiment of this application. Detailed Implementation

[0019] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this invention.

[0020] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] In the description of this application, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," indicating orientation or positional relationships, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0022] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal connection of two components; and they can refer to a wireless connection or a wired connection. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0023] Furthermore, the technical features involved in the different embodiments of this application described below can be combined with each other as long as they do not conflict with each other.

[0024] Please see Figure 2 The flowchart illustrates a non-uniform ion implantation process monitoring method based on template matching image recognition provided in an embodiment of this application.

[0025] like Figure 2 As shown, the non-uniform ion implantation process monitoring method based on template matching image recognition includes the following steps:

[0026] Step 1: Perform non-uniform ion implantation to be monitored on a wafer, and model it based on the measurement data of the wafer to obtain a template for monitoring the dose / resistance distribution of the non-uniform ion implantation.

[0027] Step 2: Perform resistance measurements on the batch of wafers after the non-uniform ion implantation, and plot the resistance distribution map based on the coordinates and resistance values ​​of each measurement point.

[0028] Step 3: Perform image recognition comparison between the template obtained in Step 1 and the resistance distribution map obtained in Step 2 to obtain a similarity score, and then perform statistical process control on the similarity score.

[0029] In steps one and two, after non-uniform ion implantation is performed on the wafer, the wafer is subjected to rapid thermal treatment to activate the doped ions.

[0030] In step three, a cosine similarity evaluation method is used to obtain a similarity score. The template obtained in step one and the resistance distribution map obtained in step two are converted into feature vectors A and B. The cosine value of the angle between the vectors is used to represent the similarity. The closer to 1, the more similar the vectors are, and the closer to -1, the less similar the vectors are.

[0031] The formula for calculating the similarity score is:

[0032] Example 1

[0033] A software module is installed in the resistance measuring device to obtain templates, resistance distribution diagrams, and similarity scores. The similarity scores are then uploaded to a monitoring system, which performs statistical process control and management on the similarity scores.

[0034] Example 2

[0035] The monitoring system is equipped with a software module that receives resistance values ​​and coordinates uploaded by resistance measurement devices. The monitoring system then obtains templates, resistance distribution maps, and similarity scores, and performs statistical process control and management on the similarity scores.

[0036] It should be noted that the illustrations provided in this embodiment are only schematic representations of the basic concept of this application. Therefore, the drawings only show the components related to this invention and are not drawn according to the actual number, shape and size of the components. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0037] In summary, the non-uniform ion implantation process monitoring method based on template matching image recognition provided in this application uses template matching image recognition to evaluate the similarity between the resistance distribution map of non-uniform ion implantation and the template. This effectively captures anomalies such as dose distribution map shifts and rotations in the non-uniform ion implantation process, thus enabling monitoring of the non-uniform ion implantation process. Therefore, this application effectively overcomes the various shortcomings of the prior art and has high industrial application value.

[0038] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this invention should still be covered by the claims of this application.

Claims

1. A method for monitoring non-uniform ion implantation processes based on template matching image recognition, characterized in that, The method includes: Step 1: Perform non-uniform ion implantation to be monitored on a wafer, and model it based on the measurement data of the wafer to obtain a template for monitoring the dose / resistance distribution of the non-uniform ion implantation. Step 2: Perform resistance measurement on the batch of wafers after the non-uniform ion implantation, and draw a resistance distribution map based on the coordinates and resistance values ​​of each measurement point. Step 3: Perform image recognition comparison operation between the template obtained in Step 1 and the resistance distribution map obtained in Step 2 to obtain a similarity score, and perform statistical process control on the similarity score.

2. The method according to claim 1, characterized in that, After the non-uniform ion implantation is performed on the wafer, the wafer is subjected to rapid thermal treatment to activate the doped ions.

3. The method according to claim 1, characterized in that, The similarity score is obtained using the cosine similarity evaluation method, and the formula for calculating the similarity score is as follows: Wherein, A is the feature vector obtained by the template transformation, and B is the feature vector obtained by the resistance distribution map transformation.

4. The method according to claim 1, characterized in that, A software module is set in the resistance measuring device to obtain the template, the resistance distribution map and the similarity score through the resistance measuring device, and upload the similarity score to the monitoring system. The monitoring system performs statistical process control and management on the similarity score.

5. The method according to claim 1, characterized in that, The monitoring system is equipped with a software module that receives the resistance value and coordinates uploaded by the resistance measurement device, obtains the template, the resistance value distribution map and the similarity score through the monitoring system, and then performs statistical process control and management on the similarity score.

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