Wafer and method, apparatus, device and medium for improving roughness thereof

Abstract

The present disclosure provides a wafer and a method, device, equipment and medium for improving roughness thereof; the method comprises: when the roughness of a bare wafer completed by a wire sawing process in a target wavelength range is greater than or equal to a set roughness threshold value, determining an index value for characterizing the cutting capacity of the currently used cutting slurry based on the geometric similarity of abrasive particles for the wire sawing process in the currently used cutting slurry and a regular polyhedron; when the index value is less than or equal to a set performance threshold value, supplementing new cutting slurry to the equipment performing the wire sawing process.

Description

Technical Field

[0001] This disclosure relates to the field of semiconductor manufacturing technology, and in particular to a method, apparatus, device and medium for improving the roughness of a wafer. Background Technology

[0002] In wafer manufacturing, after a single-crystal silicon rod is prepared using the Czochralski method, it undergoes a series of processing steps including wire cutting, grinding, etching, milling, chemical mechanical polishing (CMP), and cleaning to ultimately obtain a single-crystal silicon wafer. For single-crystal silicon wafers, surface morphology is a key parameter for evaluating their quality. Surface roughness is an important performance parameter among the surface morphology parameters of wafers.

[0003] Based on the various processing steps in the wafer manufacturing process described above, after the single-crystal silicon rod is cut into bare wafers using wire cutting equipment, the bare wafer already possesses an initial surface state. Subsequent processing steps such as grinding, etching, polishing, CMP, and cleaning merely serve to gradually repair surface damage based on this initial surface state. Therefore, if a single-crystal silicon wafer with better surface roughness is desired, process optimization needs to begin at the wire cutting stage to improve the surface roughness of the bare wafer obtained from the wire cutting process, thereby enhancing the final surface roughness index of the single-crystal silicon wafer.

[0004] In the wire EDM process, the uniformity of abrasive particle size is a process parameter characterizing cutting capability. Specifically, it involves sampling abrasive particles, statistically analyzing their sizes, and using the statistical values ​​from this sample to estimate the overall cutting capability of the abrasive particles. However, the sampling method and the accuracy of the statistical results in estimating the true overall cutting capability of the abrasive particles in the process described above are unverifiable. Summary of the Invention

[0005] This disclosure provides a method, apparatus, device, and medium for improving the surface roughness of a wafer. The shape of the abrasive particles and their geometric similarity to regular polyhedra are used as an evaluation index for cutting capability. This index is then used to optimize the wire cutting process, thereby reducing the surface roughness of the wafer.

[0006] The technical solution disclosed herein is implemented as follows:

[0007] In a first aspect, this disclosure provides a method for improving wafer roughness, the method comprising:

[0008] When the roughness of the bare wafer after wire cutting is greater than or equal to the set roughness threshold in the target wavelength range, an index value for characterizing the cutting capability of the currently used cutting slurry is determined based on the geometric similarity between the abrasive particles used in the wire cutting process and the regular polyhedron in the currently used cutting slurry.

[0009] When the index value is less than or equal to the set performance threshold, new cutting slurry is added to the equipment performing the wire cutting process.

[0010] Secondly, this disclosure provides a wafer roughness improvement apparatus, the apparatus comprising: a determining part, a comparing part, and a process improvement part; wherein,

[0011] The determining part is configured to determine an index value to characterize the cutting capability of the currently used cutting slurry when the roughness of the bare wafer that has completed the wire cutting process is greater than or equal to a set roughness threshold in the target wavelength range. This index value is based on the geometric similarity between the abrasive particles used in the wire cutting process and the regular polyhedron in the currently used cutting slurry.

[0012] The comparison section is configured to compare the indicator value with a set performance threshold, and to trigger the process improvement section when the indicator value is less than or equal to the set performance threshold.

[0013] The process improvement section is configured to add new cutting slurry to the equipment performing the wire cutting process.

[0014] Thirdly, this disclosure provides a computing device comprising: a processor and a memory; the processor being configured to execute instructions stored in the memory to implement the wafer roughness improvement method as described in the first aspect.

[0015] Fourthly, this disclosure provides a computer-readable storage medium storing at least one instruction that is executed by a processor to implement the wafer roughness improvement method as described in the first aspect.

[0016] Fifthly, this disclosure provides a wafer obtained by a wire dicing process improved by the wafer roughness improvement method described in the first aspect, wherein the roughness in the target wavelength range is at least one of the following:

[0017] When the target wavelength range is 0 to 1.8 micrometers, the roughness is 0.01 to 1 nm;

[0018] When the target wavelength range is 1.8 to 22 micrometers, the roughness is 1 to 3 nm;

[0019] When the target wavelength range is 22 micrometers to 20 millimeters, the roughness is 3 to 30 nm.

[0020] This disclosure provides a wafer and a method, apparatus, device, and medium for improving its surface roughness. When the roughness of a bare wafer after a wire dicing process is greater than or equal to a set roughness threshold in the target wavelength range, an index value characterizing the cutting capability of the currently used dicing slurry is determined based on the geometric similarity between the abrasive particles used in the wire dicing process and regular polyhedra in the slurry. If this index value is less than or equal to a set performance threshold, new dicing slurry is added to the equipment performing the wire dicing process. This not only allows for accurate evaluation of the cutting performance of the abrasive particles but also timely replenishment of new dicing slurry when cutting performance deteriorates, maintaining the cutting performance of the dicing slurry at a good level and reducing the surface roughness of the wafer. Attached Figure Description

[0021] Figure 1 This is a schematic diagram illustrating the composition of an exemplary multi-wire cutting device provided in this disclosure.

[0022] Figure 2 This is a schematic diagram of a method for improving wafer roughness provided in this disclosure.

[0023] Figure 3 This is a schematic diagram of a microscopic image of the abrasive particles provided in this disclosure.

[0024] Figure 4 This is a schematic diagram of a filter sliding on a wafer surface, as provided in this disclosure.

[0025] Figure 5 This is a schematic diagram of an analysis region obtained by dividing the data as provided in this disclosure.

[0026] Figure 6 This is a schematic diagram of a wafer roughness improvement device provided in this disclosure.

[0027] Figure 7 This is a schematic diagram of the structure of a computing device provided in this disclosure. Detailed Implementation

[0028] The technical solutions in this disclosure will now be clearly and completely described with reference to the accompanying drawings.

[0029] See Figure 1The illustration shows an exemplary multi-wire cutting device 1 applicable to the technical solutions of this disclosure. The device 1 may include a wire cutting unit 11 and a support unit 12. In some embodiments of this disclosure, the wire cutting unit 11 may be located below the support unit 12 in the vertical direction. In embodiments not shown in this disclosure, the wire cutting unit 11 may also be located above the support unit 12 in the vertical direction, which will not be elaborated here.

[0030] The wire cutting unit 11 may include multiple spools 111, cutting wires 112, and a cutting slurry supply unit 113. The cutting wires 112 are wound around the spools 111 to form an array of mutually parallel cutting segments. (Refer to below) Figure 1 The following description uses two spools 111 as an example. The two spools 111 are arranged opposite each other with their axes parallel to each other. Two cutting slurry supply units 113 are located directly above the two spools 111, respectively, and are used to spray cutting slurry onto the two spools 111 and the cutting wire 112. The cutting slurry can be a liquid medium in which abrasive particles are suspended.

[0031] The reciprocating motion directions of the spool 111 and the cutting line 112 toward and away from the bearing unit 12 are as follows: Figure 1 As indicated by the solid arrows, the reciprocating speed can be, for example, 10 m / s to 15 m / s. The support unit 12, used to load and fix the silicon rod S to be processed, may include a base 121 and an intermediate member 122. The silicon rod S to be processed is fixed to the base 121 via the intermediate member 122, for example, by bonding its circumferential surface to the lower surface of the base 121, thereby fixing it to the base 121.

[0032] for Figure 1 The wire cutting device 1 shown can bring the silicon rod to be processed closer to the cutting line array by moving the support unit 12 vertically toward the cutting line array. After the cutting line array comes into contact with the silicon rod to be processed, the silicon rod to be processed is cut by the movement of each cutting line array along its extension direction and the continued feed movement of the support unit 12 vertically toward the cutting line array. It should be noted that the present disclosure uses a lifting device (not shown in the figure) to move the wire support unit 12. It is understood that those skilled in the art can also move the support unit 12 in other ways according to actual needs and implementation scenarios, which will not be described in detail in this disclosure.

[0033] Multiple grooves 111A are formed on the circumferential surface of the spool 111 to guide and fix the cutting wire 112, ensuring that it maintains stable tension and position during the cutting process. Typically, the grooves 111A are evenly distributed on the circumferential surface of the spool 111.

[0034] Based on the above Figure 1 The multi-wire cutting device 1 shown uses a cutting wire 112 made of tungsten steel or similar material. During its reciprocating motion, the microscopic interaction mechanism between the abrasive particles in the cutting slurry and the silicon rod S to be processed can be called the "rolling-indentation" model. That is, after the abrasive particles are pressed by the cutting wire and the cutting slurry fluid, they are embedded into the surface of the silicon rod S to be processed. Then, through the displacement of the cutting wire and the cutting slurry fluid, the non-embedded part of the embedded abrasive particles acts as a lever to pry open a local area of ​​the surface of the silicon rod S to be processed, thus removing the material from the local area of ​​the silicon rod S.

[0035] Based on the above microscopic mechanism, it can be concluded that the removal of material from the silicon rod S depends on the ability of abrasive particles to embed into the material surface. Since silicon is a brittle material at room temperature, abrasive particles should not be embedded too deeply into the surface of the silicon rod S; otherwise, large-area damage can easily be caused by levering. Although this increases the material removal rate, it will result in a very poor surface condition.

[0036] It should be noted that, since the ease of lever action depends on the length of the lever arm, the inventors found that the ideal abrasive particle shape should have a suitable edge length. Furthermore, the inventors also found that increasing the number of angles helps increase the probability of the abrasive particle embedding into the surface of the silicon rod S material being processed. Therefore, the inventors concluded that, in addition to having a suitable edge length, the ideal abrasive particle should also have as many solid angles (i.e., edges) as possible.

[0037] For a solid geometric body, if it is necessary to simultaneously satisfy the requirements of having as many edges as possible and each edge having a large edge length, then only a regular polyhedron can meet these requirements. However, in the actual production of abrasive particles, due to the limitations of kinetic and thermodynamic control conditions during industrial processing, it is difficult to produce abrasive particles with shapes that conform to regular polyhedra. In practice, the shapes of abrasive particles are irregular.

[0038] Based on this, this disclosure aims to describe the cutting capability of abrasive particles by the degree to which their shape deviates from a regular polyhedral structure, in order to accurately evaluate their cutting performance and improve the wire EDM process based on this cutting capability, thereby improving wafer roughness. Figure 2 As shown, it illustrates a method for improving wafer roughness provided in this disclosure, the method comprising steps S210 to S220.

[0039] In step S210, when the roughness of the bare wafer that has completed the wire cutting process is greater than or equal to the set roughness threshold in the target wavelength range, an index value for characterizing the cutting capability of the currently used cutting slurry is determined based on the geometric similarity between the abrasive particles used in the wire cutting process and the regular polyhedron in the currently used cutting slurry.

[0040] In this disclosure, the uniformity of the wafer surface morphology is reflected in the height difference between points on the wafer surface. This height difference manifests as a fluctuation in the height value of each point on the wafer surface as a whole. Based on this understanding, this disclosure considers this fluctuation phenomenon from a wave perspective as being caused by the superposition of wave signals of different wavelengths. The smaller the wavelength of the wave signal, the smaller the area representing the height value fluctuation phenomenon; the larger the wavelength of the wave signal, the larger the area representing the height value fluctuation phenomenon.

[0041] Based on the above description, in order to evaluate or measure the roughness of a smaller region, this disclosure can filter the above-mentioned fluctuation phenomenon using the size of the region where the roughness is to be measured, thereby obtaining wave signal data within the wavelength range corresponding to the region where the roughness is to be measured, and calculating the roughness of the wafer under the size standard of that region based on the wave signal data.

[0042] After obtaining the roughness of the bare wafer in the target wavelength range after the wire dicing process, a set roughness threshold can be used to characterize whether the roughness is good or not. Taking a target wavelength range of 22 micrometers to 20 millimeters as an example, this roughness threshold can be set to 30 nm. That is, when the roughness value of the bare wafer in the target wavelength range is greater than or equal to 30 nm, it indicates that the dicing capability of the multi-wire dicing equipment 1 is severely degraded. The degraded dicing capability of the multi-wire dicing equipment 1 may be caused by the degraded dicing capability of the dicing slurry, or by other components in the multi-wire dicing equipment 1 or other process parameters in the wire dicing process. Therefore, in the case of severe degraded dicing capability of the multi-wire dicing equipment 1, this disclosure evaluates the dicing capability of the dicing slurry, so that after determining that the dicing capability of the dicing slurry has degraded, step S220 is executed to improve the dicing capability of the dicing slurry to improve the dicing capability of the multi-wire dicing equipment 1, thereby improving the wafer roughness.

[0043] It should be noted that the cutting ability of the cutting slurry comes from the abrasive particles within it. When the cutting ability of the abrasive particles decreases, the cutting ability of the cutting slurry also decreases accordingly. Based on the inventors' understanding of the ideal shape requirements for abrasive particles, and the fact that a regular polyhedral structure meets these requirements, in this disclosure, the cutting ability of the abrasive particles can be described by the degree to which their shape deviates from the regular polyhedral structure. That is, the greater the deviation of the abrasive particles from the regular polyhedral structure, the lower the cutting ability of the cutting slurry; conversely, the smaller the deviation, the higher the cutting ability. In some examples, for the abrasive particles in the currently used cutting slurry, their geometric similarity to a regular polyhedron can be used as an index value to characterize the cutting ability of the cutting slurry.

[0044] In step S220, when the index value is less than or equal to the set performance threshold, new cutting slurry is added to the equipment performing the wire cutting process.

[0045] In this disclosure, a set performance threshold is used to evaluate the degree of degradation of the cutting ability of the cutting slurry. For example, when the index value obtained in step S210, which characterizes the cutting ability of the currently used cutting slurry, is less than or equal to the performance threshold, it indicates that the cutting ability of the abrasive particles in the cutting slurry has been severely degraded. If continued use occurs, it will lead to an increase in the roughness of the bare wafer obtained by wire cutting in the target wavelength range. Therefore, it is necessary to improve the abrasive particles with degraded cutting ability. During wire cutting, the cutting slurry is usually recycled. When the abrasive particles in the cutting slurry are severely degraded, new cutting slurry needs to be added. In some examples, the multi-wire cutting equipment performing the wire cutting process can be shut down, and then all the cutting slurry in the container used to store the cutting slurry in the multi-wire cutting equipment can be drained before replacing it with new cutting slurry. In some examples, to avoid the adverse effects of frequent downtime on the equipment and reduce production efficiency, the replenishment method may also be to add new cutting slurry to the container used to store the cutting slurry, so that the newly added cutting slurry is fully mixed with the existing cutting slurry in the container, thereby improving the severely degraded cutting ability to meet the cutting ability requirements corresponding to the performance threshold.

[0046] for Figure 2The technical solution described above involves determining an index value characterizing the cutting capability of a wire-cutting slurry when the roughness of the bare wafer after wire cutting is greater than or equal to a set roughness threshold within the target wavelength range. This index value is based on the geometric similarity between the abrasive particles in the wire-cutting slurry and regular polyhedra. Furthermore, if this index value is less than or equal to a set performance threshold, new slurry is added to the equipment performing the wire cutting process. This not only accurately assesses the cutting performance of the abrasive particles but also allows for timely replenishment of slurry when cutting performance deteriorates, maintaining the cutting performance of the slurry at a good level and reducing wafer surface roughness.

[0047] against Figure 2 In some implementations of the technical solution shown, the process of obtaining the geometric similarity between the abrasive particles used in the wire EDM process in the currently used cutting slurry and the regular polyhedron may include:

[0048] The cutting slurry currently in use is scanned using a scanning electron microscope to acquire microscopic images of multiple abrasive particles in the cutting slurry currently in use;

[0049] By performing image analysis on the microscopic images of each abrasive particle, the length of each side, the maximum diagonal length, and the number of solid angles of each abrasive particle are obtained.

[0050] The geometric similarity between each abrasive particle and a regular polyhedron is determined based on the length of each side of each abrasive particle and the number of solid angles collected.

[0051] Specifically, during the wire cutting process, the cutting slurry is uniformly mixed by mechanical stirring and then evenly dispersed on the cutting line. This disclosure utilizes a scanning electron microscope (SEM) at a set magnification (scale) and according to a set step to scan the currently used cutting slurry, thereby obtaining multiple microscopic images of the abrasive particles, such as... Figure 3 As shown, Figure 3 The image prominently displays microscopic images of three acquired abrasive particles. For each acquired microscopic image of an abrasive particle, a well-trained deep learning model for image instance segmentation, such as mask-RCNN, can be used to analyze the microscopic image to obtain three shape parameters of each acquired abrasive particle, such as the length of all sides of each acquired abrasive particle, the maximum diagonal length, and the number of solid angles (edges) contained in each abrasive particle.

[0052] Among the three shape parameters mentioned above, the lengths of all sides and the number of solid angles can be used to characterize the shape similarity between the abrasive particle and the regular polyhedron. Based on this, in this disclosure, the geometric similarity between each abrasive particle and the regular polyhedron can be calculated based on the difference between the number of solid angles of each abrasive particle and the variance of the lengths of all sides. Specifically, the geometric similarity index between the abrasive particle and the regular polyhedron is defined as LR, which is used to characterize the magnitude of the similarity between the geometric shape of the abrasive particle and the regular polyhedron. For any abrasive particle, its LR index can be calculated by the following formula:

[0053]

[0054] In the above formula, Indicates the number of solid angles of abrasive particles. This indicates the number of edges of the abrasive particles. This represents the variance of the side lengths of all sides of the abrasive particle, which can be understood as... The larger, The smaller the value, the larger the LR value, indicating a higher geometric similarity between the abrasive particles and the regular polyhedron.

[0055] Based on the above implementation, in some examples, after obtaining the geometric similarity between the abrasive particles and the regular polyhedron, step S210, which determines the index value characterizing the cutting capability of the currently used cutting slurry based on the geometric similarity between the abrasive particles used in the wire EDM process and the regular polyhedron, includes:

[0056] Obtain the median value of the geometric similarity between all collected abrasive particles and regular polyhedra;

[0057] Obtain the variance of the maximum diagonal length of all collected abrasive particles;

[0058] The index value used to characterize the cutting ability of the currently used cutting slurry is obtained based on the median value of the geometric similarity between all collected abrasive particles and regular polyhedra, and the variance of the maximum diagonal length of all collected abrasive particles.

[0059] In the above example, specifically, after obtaining the LR value of each abrasive particle, the LR values ​​of abrasive particles in all microscopic images can be statistically analyzed to obtain the geometric similarity (LRS) between all abrasive particles and regular polyhedra. For example, after normalizing the LR values ​​of all abrasive particles, the median can be taken as the LRS. This LRS also represents the regular polyhedral similarity of the currently applicable cutting slurry and can be used as a characterization parameter of the cutting ability of the cutting slurry.

[0060] Furthermore, in this disclosure, for each abrasive particle, the farthest distance of a pixel in the microscopic image is determined as the maximum diagonal length (DL) value of that abrasive particle. Next, after statistically analyzing the DL values ​​of all abrasive particles in all microscopic images, normalization is performed, and the variance of the normalized values ​​is used as another parameter characterizing the cutting ability of the cutting slurry, for example, this parameter is defined as DLS (dialog length statistic). Specifically, DLS can be calculated using the following formula:

[0061]

[0062] In the above formula, This represents the normalized DL values ​​of all collected abrasive particles. This represents the variance of the normalized DL values ​​for all collected abrasive particles.

[0063] Based on the LRS and DLS mentioned above, the index value SP, which characterizes the cutting capability of the currently used cutting slurry, can be calculated using the following formula:

[0064] SP = LRS / DLS.

[0065] As shown in the above formula, when the geometry of the abrasive particles is very close to that of a regular polyhedron, the value of LRS will increase; when the size of the abrasive particles is very uniform, the value of DLS will decrease. Combining these two parameters characterizing the cutting ability of the cutting slurry, in the above two cases, the index value SP, which can reflect or characterize the cutting ability of the cutting slurry, will be larger.

[0066] against Figure 2 In some implementations of the technical solution shown, the method further includes:

[0067] For each sampling point on the surface of the bare wafer, the raw measurement data of the wafer surface height at each sampling point is obtained through a single-point measurement scheme;

[0068] Based on the raw measurement data of all sampling points on the surface of the bare wafer, the wave signal of each sampling point in the target wavelength range is obtained by using a filter corresponding to the target wavelength range for each sampling point;

[0069] The roughness of the bare wafer in the target wavelength range is determined based on the amplitude statistics of the wave signal at all sampling points in the target wavelength range.

[0070] Specifically, the single-point measurement scheme described above means that a single measurement process can only measure data at one sampling point. In some examples, a contact measurement scheme can be used, such as using a probe to contact the surface of a bare wafer and move horizontally across the wafer surface. As this horizontal movement occurs, the height difference on the wafer surface causes a longitudinal displacement of the probe. This longitudinal displacement is sensed by a displacement sensor and converted into the height data of the wafer surface, i.e., the raw measurement data regarding the wafer surface height. In other examples, non-contact measurement schemes such as capacitance measurement or laser focusing measurement can also be used.

[0071] After measuring each sampling point on the bare wafer surface using the above single-point measurement scheme, the raw measurement data of all sampling points can reflect the height difference between each sampling point, which can be viewed as a three-dimensional wave phenomenon on the entire wafer surface. For this wave phenomenon, the amplitude of wave signals of different wavelengths superimposed to form this wave phenomenon can be used to represent the height difference within a region corresponding to the wavelength.

[0072] In some instances, the target wavelength range includes at least one of the following: 0 to 1.8 micrometer wavelengths, 1.8 to 22 micrometer wavelengths, and 22 micrometer to 20 millimeter wavelengths. Taking a target wavelength range of 22 micrometer to 20 millimeter wavelengths as an example, it includes an upper wavelength limit and a lower wavelength limit.

[0073] In some examples, to obtain the wave signal at each sampling point within the target wavelength range, a low-pass filter is first used to filter out wave signals with wavelengths above the upper wavelength limit, followed by a high-pass filter to filter out wave signals below the lower wavelength limit, ultimately obtaining the wave signal within the target wavelength range. Specifically, the filter described above is a circular filter, and this circular filter consists of two Gaussian filter functions, wherein the first Gaussian filter function G... LP1 It can be a Gaussian low-pass filter function whose low-pass filtering range covers to the upper limit of the target wavelength range; a second Gaussian filter function G LP2 It can be a Gaussian low-pass filter function whose low-pass filtering range covers to the lower limit of the target wavelength range, and is obtained through (1-G LP2 The high-pass filter function is obtained. Based on the first and second Gaussian filter functions described above, the circular filter G... DHP It can be represented as G DHP = G LP1 (1-G) LP2 In this disclosure, the circular filter of the above example is used as an example, such as... Figure 4As shown, the circular filter indicated by the arrow can be slid on the surface of the bare wafer according to the sampling points. The original measurement data of the sampling point at the center of the circular filter and other sampling points covered by the effective range of the circular filter are filtered by the circular filter to obtain the wave signal of each sampling point in the target wavelength range.

[0074] It should be noted that, because the morphology changes more drastically closer to the edge of the wafer surface, in order to accurately capture these dramatic changes, the effective range of the circular filter corresponding to a sampling point near the wafer edge should be smaller than that of the circular filter corresponding to a sampling point closer to the wafer center. In other words, as the sampling point moves further away from the wafer center, the effective range of the corresponding filter should decrease, or shrink. Therefore, the radius of the filter's effective range is determined by the distance between the sampling point and the center of the bare wafer.

[0075] In this disclosure, a critical distance is set to determine whether a sampling point is close to the center of the wafer surface or close to the edge of the wafer surface. When the distance between the sampling point and the center of the bare wafer is less than or equal to the critical distance, the radius of the effective range of the filter is a first radius; when the distance between the sampling point and the center of the bare wafer is greater than the critical distance, the radius of the effective range of the filter is a second radius; wherein, both the first radius and the second radius are determined by the upper limit of the target wavelength range, and the first radius is greater than the second radius.

[0076] Based on the above example, the shrinkage can be implemented in a step-like manner, where the second radius is fixed at a value smaller than the first radius when the distance between the sampling point and the center of the bare wafer is greater than a critical distance; or it can be implemented gradually, where the second radius gradually decreases as the sampling point moves further away from the center of the bare wafer. Specifically, when the distance between the sampling point and the center of the bare wafer is greater than the critical distance, the second radius is a fixed value smaller than the first radius; or, the second radius is negatively correlated with the distance between the sampling point and the center of the bare wafer.

[0077] In the above implementation, after obtaining the wave signal of all sampling points in the target wavelength range through filtering, in some examples, determining the roughness of the bare wafer in the target wavelength range based on the amplitude statistics of the wave signal of all sampling points in the target wavelength range includes:

[0078] The bare wafer is divided into multiple analysis regions;

[0079] The range of the amplitude of the wave signal in the target wavelength range for each analysis region is calculated based on the amplitude values ​​of the wave signal at the sampling points in each analysis region.

[0080] The roughness index of the bare wafer in the target wavelength range is calculated based on the range of amplitudes of wave signals in all analysis regions within the target wavelength range.

[0081] For the above example, such as Figure 5 As shown, after removing the edge region according to EE, the remaining area on the bare wafer surface is divided into square areas of a set size, such as 10mm*10mm. This results in a complete analysis area that can present a complete square and an incomplete analysis area that is at the edge of the remaining area after removing the edge region according to EE and cannot present a complete square. These two analysis areas constitute the analysis area in the above implementation.

[0082] It should be noted that the wave signal of all sampling points on the wafer surface within the target wavelength range includes all information that can characterize the surface morphology (i.e. roughness) of the wafer surface within the corresponding size area of ​​the target wavelength range. This information can be characterized by statistical values ​​of amplitude, such as the mean, extreme values, extreme values ​​under the set size area ratio, range, variance, standard deviation, median, mode, etc. of the amplitude mentioned in the aforementioned technical solution.

[0083] In this disclosure, taking the range as an example, the amplitude statistical value of the wave signal in the target wavelength range of each analysis region is the range of the amplitude values ​​of the wave signal in the target wavelength range of the sampling points and interpolation points in each analysis region; correspondingly, the roughness index of the bare wafer in the target wavelength range is the average value of the range of the amplitude values ​​of the wave signal in the target wavelength range of all analysis regions.

[0084] Based on the above technical solution, this disclosure is illustrated through the following three specific embodiments.

[0085] In Example 1, taking a target wavelength range of 22 micrometers to 20 millimeters as an example, the roughness of the bare wafer obtained by wire cutting in the target wavelength range and the index value SP used to characterize the cutting ability of the currently used cutting slurry are obtained according to the above technical solution based on the duration of the cutting slurry cycle, as shown in Table 1 below.

[0086]

[0087] Table 1

[0088] As shown in Table 1, after 10 hours of cycling, the SP value of the cutting slurry decreased significantly (from 3.1 to 0.9), and correspondingly, the roughness of the target wavelength range also increased significantly (from 18.4 to 31.3). This indicates that in the wire cutting process, the new cutting slurry should be replaced after 10 hours of use.

[0089] Furthermore, in this embodiment, based on the conclusion of the aforementioned 10-hour period, new cutting slurry was added to the existing cutting slurry after 10 hours (i.e., the 15th hour) and after 20 hours (i.e., the 25th hour). The roughness and SP values ​​within the target wavelength range were obtained according to the above technical solution, as shown in Table 2.

[0090]

[0091] Table 2

[0092] As shown in Table 2, when the cutting ability of the cutting slurry deteriorates, the overall cutting ability of the cutting slurry can be improved by adding new cutting slurry.

[0093] Based on the above technical solutions and specific embodiments, the wafer obtained by the wire cutting process improved by the aforementioned wafer roughness improvement method has a roughness of 3 to 30 nm in the target wavelength range of 22 micrometer wavelength to 20 millimeter wavelength.

[0094] In Example 2, taking a target wavelength range of 1.8 micrometers to 22 micrometers as an example, the roughness of the bare wafer obtained by wire cutting in the target wavelength range and the index value SP used to characterize the cutting ability of the currently used cutting slurry are obtained according to the above technical solution based on the duration of the cutting slurry cycle, as shown in Table 3 below.

[0095]

[0096] Table 3

[0097] As shown in Table 3, after 4 hours of circulation, the SP value of the cutting slurry decreased to 4.8, and correspondingly, the roughness of the target wavelength range showed a significant improvement (from 2.9 to 5.3). This indicates that in the wire cutting process, the new cutting slurry should be replaced after 4 hours of use.

[0098] Furthermore, in this embodiment, based on the conclusion of the above 4-hour period, new cutting slurry was added to the existing cutting slurry at the 4th and 10th hours, respectively. The roughness and SP values ​​within the target wavelength range were obtained according to the above technical solution, as shown in Table 4.

[0099]

[0100] Table 4

[0101] As shown in Table 4, when the cutting ability of the cutting slurry deteriorates, the overall cutting ability of the cutting slurry can be improved by adding new cutting slurry.

[0102] Based on the above technical solutions and specific embodiments, the wafer obtained by the wire dicing process improved by the aforementioned wafer roughness improvement method has a roughness of 1 to 3 nm in the target wavelength range of 1.8 micrometer wavelength to 22 micrometer wavelength.

[0103] In Example 3, taking a target wavelength range of 0 micrometers to 1.8 micrometers as an example, the roughness of the bare wafer obtained by wire cutting in the target wavelength range and the index value SP used to characterize the cutting ability of the currently used cutting slurry are obtained according to the above technical solution based on the duration of the cutting slurry cycle, as shown in Table 5 below.

[0104]

[0105] Table 5

[0106] As can be seen from Table 3, after 4 hours of cycling, the SP value of the cutting slurry decreased to 5.7, and correspondingly, the roughness of the target wavelength range was significantly improved (to 1.8 nm). This indicates that during the wire cutting process, the new cutting slurry was updated in the 4th hour of use.

[0107] Furthermore, in this embodiment, based on the conclusion of the above 4-hour period, a new cutting slurry is added to the existing cutting slurry at the 4th hour. The roughness and SP values ​​within the target wavelength range are obtained according to the above technical solution, as shown in Table 6.

[0108]

[0109] Table 6

[0110] As shown in Table 6, when the cutting ability of the cutting slurry deteriorates, the overall cutting ability of the cutting slurry can be improved by adding new cutting slurry.

[0111] Based on the above technical solutions and specific embodiments, the wafer obtained by the wire cutting process improved by the aforementioned wafer roughness improvement method has a roughness of 0.01 to 1 nm in the target wavelength range of 1.8 micrometer wavelength to 22 micrometer wavelength.

[0112] Based on the same inventive concept as the aforementioned technical solution, see [link to inventive concept]. Figure 6 The illustration shows a wafer roughness improvement apparatus 60, which includes: a determining section 601, a comparing section 602, and a process improvement section 603; wherein,

[0113] The determining portion 601 is configured to determine an index value characterizing the cutting capability of the currently used cutting slurry based on the geometric similarity between the abrasive particles used in the wire cutting process and the regular polyhedron in the target wavelength range when the roughness of the bare wafer that has completed the wire cutting process is greater than or equal to a set roughness threshold.

[0114] The comparison section 602 is configured to compare the index value with a set performance threshold, and to trigger the process improvement section 603 when the index value is less than or equal to the set performance threshold.

[0115] The process improvement section 603 is configured to add new cutting slurry to the equipment performing the wire cutting process.

[0116] In some examples, the determining portion 601 is also configured to:

[0117] The cutting slurry currently in use is scanned using a scanning electron microscope to acquire microscopic images of multiple abrasive particles in the cutting slurry currently in use;

[0118] By performing image analysis on the microscopic images of each abrasive particle, the length of each side and the number of solid angles of each abrasive particle can be obtained.

[0119] The geometric similarity between each abrasive particle and a regular polyhedron is determined based on the length of each side of each abrasive particle and the number of solid angles.

[0120] In some examples, the determining portion 601 is also configured to:

[0121] The geometric similarity between each abrasive particle and the regular polyhedron is calculated based on the difference between the number of solid angles of each abrasive particle and the length variance of all its sides.

[0122] In some examples, the determining portion 601 is further configured to: obtain the maximum diagonal length of each abrasive particle by performing image analysis on the microscopic image of each abrasive particle acquired;

[0123] Accordingly, the determining portion 601 is configured to:

[0124] Obtain the median value of the geometric similarity between all collected abrasive particles and regular polyhedra;

[0125] Obtain the variance of the maximum diagonal length of all collected abrasive particles;

[0126] The index value used to characterize the cutting ability of the currently used cutting slurry is obtained based on the median value of the geometric similarity between all the collected abrasive particles and regular polyhedra, and the variance of the maximum diagonal length of all the collected abrasive particles.

[0127] In some examples, the determining portion 601 is configured to:

[0128] The index value used to characterize the cutting ability of the currently used cutting slurry is calculated based on the ratio of the median value of the geometric similarity between all the collected abrasive particles and regular polyhedra to the variance of the maximum diagonal length of all the collected abrasive particles.

[0129] In some examples, the determining portion 601 is also configured to:

[0130] For each sampling point on the surface of the bare wafer, the raw measurement data of the wafer surface height at each sampling point is obtained through a single-point measurement scheme;

[0131] Based on the raw measurement data of all sampling points on the surface of the bare wafer, the wave signal of each sampling point in the target wavelength range is obtained by using a filter corresponding to the target wavelength range for each sampling point;

[0132] The roughness of the bare wafer in the target wavelength range is determined based on the amplitude statistics of the wave signal at all sampling points in the target wavelength range.

[0133] In some examples, the filter is a circular filter and consists of a double Gaussian filter function;

[0134] The radius of the effective range of the filter is determined by the distance between the sampling point and the center of the bare wafer. When the distance between the sampling point and the center of the bare wafer is less than or equal to a critical distance, the radius of the effective range of the filter is a first radius; when the distance between the sampling point and the center of the bare wafer is greater than the critical distance, the radius of the effective range of the filter is a second radius. The first radius and the second radius are both determined by the upper limit of the target wavelength range, and the first radius is greater than the second radius.

[0135] In some examples, the determining portion 601 is also configured to:

[0136] The bare wafer is divided into multiple analysis regions;

[0137] The range of the amplitude of the wave signal in the target wavelength range for each analysis region is calculated based on the amplitude values ​​of the wave signal at the sampling points in each analysis region.

[0138] The roughness index of the bare wafer in the target wavelength range is calculated based on the range of amplitudes of wave signals in all analysis regions within the target wavelength range.

[0139] In some examples, the target wavelength range includes at least one of the following: 0 to 1.8 micrometer wavelengths, 1.8 to 22 micrometer wavelengths, and 22 micrometer wavelengths to 20 millimeter wavelengths.

[0140] It should be noted that for the specific implementation of the functions configured in each "part" of the above-mentioned device, please refer to the implementation method and examples of the corresponding steps in the aforementioned method for improving wafer roughness, which will not be repeated here.

[0141] Please refer to Figure 7 This diagram illustrates a structural block diagram of a computing device provided in an exemplary embodiment of this disclosure. In some examples, the computing device 70 can be at least one of devices such as a smartphone, smartwatch, desktop computer, laptop, virtual reality terminal, augmented reality terminal, wireless terminal, and laptop computer. The computing device 70 has communication capabilities and can access wired or wireless networks. The computing device 70 can refer to one of multiple terminals, and those skilled in the art will understand that the number of such terminals can be more or less. In some examples, the computing device 70 can receive data based on the accessed wired or wireless network. It is understood that the computing device 70 undertakes the computation and processing work of the technical solution of this disclosure, and this disclosure does not limit it in this regard.

[0142] like Figure 7 As shown, the computing device in this disclosure may include one or more of the following components: processor 710 and memory 720.

[0143] Optionally, the processor 710 connects various parts of the computing device using various interfaces and lines, and performs various functions of the computing device and processes data by running or executing instructions, programs, code sets or instruction sets stored in memory 720, and calling data stored in memory 720.

[0144] In this disclosure, the processor 710 performs the following steps by executing instructions stored in the memory:

[0145] When the roughness of the bare wafer after wire cutting is greater than or equal to the set roughness threshold in the target wavelength range, an index value for characterizing the cutting capability of the currently used cutting slurry is determined based on the geometric similarity between the abrasive particles used in the wire cutting process and the regular polyhedron in the currently used cutting slurry.

[0146] When the index value is less than or equal to the set performance threshold, an instruction is generated and sent to replenish new cutting slurry into the equipment performing the wire EDM process.

[0147] It should be noted that for the specific implementation methods and examples of the above execution steps, please refer to the implementation methods and examples of the corresponding steps in the aforementioned wafer roughness improvement method, which will not be repeated here.

[0148] Optionally, the processor 710 can be implemented using at least one hardware form selected from Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 710 can integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), Neural-network Processing Unit (NPU), and baseband chip. Specifically, the CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required to be displayed on the touch screen; the NPU is used to implement Artificial Intelligence (AI) functions; and the baseband chip is used to handle wireless communication. It is understood that the baseband chip can also be implemented as a separate chip without being integrated into the processor 710.

[0149] The memory 720 may include random access memory (RAM) or read-only memory (ROM). Optionally, the memory 720 may include a non-transitory computer-readable storage medium. The memory 720 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 720 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the various method embodiments described above, etc.; the data storage area may store data created according to the use of the computing device, etc.

[0150] In addition, those skilled in the art will understand that the structure of the computing device shown in the above figures does not constitute a limitation on the computing device. The computing device may include more or fewer components than shown, or combine certain components, or have different component arrangements. For example, the computing device may also include a display screen, camera assembly, microphone, speaker, radio frequency circuit, input unit, sensors (such as accelerometer, angular velocity sensor, light sensor, etc.), audio circuit, WiFi module, power supply, Bluetooth module, etc., which will not be described in detail here.

[0151] This disclosure also provides a computer-readable storage medium storing at least one instruction that is executed by a processor to implement the wafer roughness improvement method as described in the various embodiments above.

[0152] This disclosure also provides a computer program product including computer instructions stored in a computer-readable storage medium; a processor of a computing device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computing device to perform the wafer roughness improvement method described in the above embodiments.

[0153] This disclosure also provides a wafer obtained by a wire dicing process improved by the wafer roughness improvement method described in the foregoing technical solution, wherein the roughness in the target wavelength range is at least one of the following:

[0154] When the target wavelength range is 0 to 1.8 micrometers, the roughness is 0.01 to 1 nm;

[0155] When the target wavelength range is 1.8 to 22 micrometers, the roughness is 1 to 3 nm;

[0156] When the target wavelength range is 22 micrometers to 20 millimeters, the roughness is 3 to 30 nm.

[0157] Those skilled in the art will recognize that the functions described in this disclosure in one or more of the examples above can be implemented using hardware, software, firmware, or any combination thereof. When implemented in software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of a computer program from one place to another. Storage media can be any available medium accessible to a general-purpose or special-purpose computer.

[0158] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for improving roughness of a wafer, characterized by, The method comprises: scanning the currently used cutting slurry by a scanning electron microscope to collect micro images of a plurality of abrasive particles in the currently used cutting slurry; when the bare wafer after completing the wire sawing process has a roughness in a target wavelength range greater than or equal to a set roughness threshold, determining an index value for representing the cutting ability of the currently used cutting slurry based on the geometric similarity of the abrasive particles in the currently used cutting slurry for the wire sawing process to a regular polyhedron; when the index value is less than or equal to a set performance threshold, supplementing a new cutting slurry to the device performing the wire sawing process; wherein the determining of the index value for representing the cutting ability of the currently used cutting slurry based on the geometric similarity of the abrasive particles in the currently used cutting slurry for the wire sawing process to a regular polyhedron comprises: obtaining the maximum diagonal length of each of the collected abrasive particles by image analysis on the micro image of each of the collected abrasive particles; obtaining the median value of the geometric similarity of all the collected abrasive particles to a regular polyhedron; obtaining the variance of the maximum diagonal length of all the collected abrasive particles; obtaining the index value for representing the cutting ability of the currently used cutting slurry according to the median value of the geometric similarity of all the collected abrasive particles to a regular polyhedron and the variance of the maximum diagonal length of all the collected abrasive particles.

2. The method of claim 1, wherein, The method further comprises: obtaining the length of each edge and the number of solid angles of each of the collected abrasive particles by image analysis on the micro image of each of the collected abrasive particles; determining the geometric similarity of each of the collected abrasive particles to a regular polyhedron according to the length of each edge and the number of solid angles of each of the collected abrasive particles.

3. The method of claim 2, wherein, The determining of the geometric similarity of each of the collected abrasive particles to a regular polyhedron according to the length of each edge and the number of solid angles of each of the collected abrasive particles comprises: calculating the geometric similarity of each of the collected abrasive particles to a regular polyhedron according to the difference between the number of solid angles and the variance of the length of all edges of each of the collected abrasive particles.

4. The method of claim 1, wherein, The obtaining of the index value for representing the cutting ability of the currently used cutting slurry according to the median value of the geometric similarity of all the collected abrasive particles to a regular polyhedron and the variance of the maximum diagonal length of all the collected abrasive particles comprises: calculating the index value for representing the cutting ability of the currently used cutting slurry according to the ratio between the median value of the geometric similarity of all the collected abrasive particles to a regular polyhedron and the variance of the maximum diagonal length of all the collected abrasive particles.

5. The method of claim 1, wherein, The method further comprises: for each sampling point of the surface of the bare wafer, obtaining original measurement data about the wafer surface height at each sampling point by a single-point measurement scheme; based on the original measurement data of all the sampling points of the surface of the bare wafer, obtaining, for each sampling point, a wave signal of each sampling point in a target wavelength range by a filter corresponding to the target wavelength range; The roughness of the bare wafer in the target wavelength range is determined based on amplitude statistical values of wave signals of all sampling points in the target wavelength range.

6. The method of claim 5, wherein, The filter is a circular filter and is composed of a double Gaussian filter function; The radius of the action range of the filter is determined by the distance between the sampling point and the center of the bare wafer, and when the distance between the sampling point and the center of the bare wafer is less than or equal to a critical distance, the radius of the action range of the filter is a first radius; when the distance between the sampling point and the center of the bare wafer is greater than the critical distance, the radius of the action range of the filter is a second radius; wherein the first radius and the second radius are both determined by the upper limit of the target wavelength range, and the first radius is greater than the second radius.

7. The method of claim 5, wherein, The roughness of the bare wafer in the target wavelength range is determined based on amplitude statistical values of wave signals of all sampling points in the target wavelength range, comprising: The bare wafer is divided into a plurality of analysis regions; The range of amplitudes of wave signals of each analysis region in the target wavelength range is calculated according to the amplitude values of wave signals of sampling points in each analysis region in the target wavelength range; The roughness index of the bare wafer in the target wavelength range is calculated according to the range of amplitudes of wave signals of all analysis regions in the target wavelength range.

8. The method according to any one of claims 1 to 7, characterized in that, The target wavelength range includes at least one of the following wavelength ranges: 0-1.8 microns, 1.8-22 microns, and 22 microns to 20 millimeters.

9. A device for improving wafer roughness, characterized in that, The device comprises a determination part, a comparison part and a process improvement part; wherein, The determination part is configured to: scan the currently used cutting slurry by a scanning electron microscope to acquire micro images of a plurality of abrasive particles in the currently used cutting slurry; when the roughness of the bare wafer in the target wavelength range after completing the wire cutting process is greater than or equal to a set roughness threshold, determine an index value for characterizing the cutting ability of the currently used cutting slurry based on the geometric similarity of the abrasive particles used in the wire cutting process to the regular polyhedron in the currently used cutting slurry; The comparison part is configured to compare the index value with a set performance threshold, and when the index value is less than or equal to the set performance threshold, trigger the process improvement part; The process improvement part is configured to supplement new cutting slurry to the device performing the wire cutting process; The determination part is configured to: obtain the maximum diagonal length of each abrasive particle by image analysis of the acquired micro image of each abrasive particle; obtain the median value of the geometric similarity of all abrasive particles to the regular polyhedron; obtain the variance of the maximum diagonal length of all abrasive particles; obtain the index value for characterizing the cutting ability of the currently used cutting slurry according to the median value of the geometric similarity of all abrasive particles to the regular polyhedron and the variance of the maximum diagonal length of all abrasive particles.

10. A computing device, comprising: The computing device comprises a processor and a memory; the processor is configured to execute instructions stored in the memory to implement the method for improving wafer roughness according to any one of claims 1 to 8.

11. A computer readable storage medium, characterized in that, The computer readable storage medium stores at least one instruction, and the at least one instruction is configured to be executed by a processor to implement the method for improving wafer roughness according to any one of claims 1 to 8.

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