Wafer, wafer roughness improvement method, wafer roughness improvement device, wafer roughness improvement equipment and medium

Abstract

The invention provides a wafer, a wafer roughness improving method, a wafer roughness improving device, wafer roughness improving equipment and a medium. The method comprises the following steps: detecting the roughness of a bare wafer subjected to a wire cutting process in a target wavelength range; when the roughness is larger than or equal to a set roughness threshold value, according to the priority of the cutting process parameters indicated by a fitting function between the multiple cutting process parameters and the roughness in the target wavelength range, the roughness in the target wavelength range is obtained; and selecting the cutting process parameters needing to be adjusted to reduce the roughness of the bare wafer obtained in the subsequent wire cutting process in the target wavelength range.

Description

Technical Field

[0001] The present disclosure relates to the field of semiconductor manufacturing technology, and in particular to a method, device, equipment and medium for improving a wafer and its roughness. Background Art

[0002] In the wafer manufacturing process, after the single crystal silicon rod is prepared by the Czochralski method, the single crystal silicon rod is sequentially subjected to wire cutting, grinding, etching, grinding, chemical mechanical polishing (CMP, Chemical Mechanical Polishing) and cleaning processes to finally obtain a single crystal silicon wafer. For a single crystal silicon wafer, its surface morphology is a key parameter to measure its quality. Surface roughness is an important performance parameter among the wafer surface morphology parameters.

[0003] According to the various processing steps in the wafer manufacturing process described above, after the single crystal silicon rod is cut into a bare wafer by the wire cutting equipment, the bare wafer already has an initial surface state, and the subsequent grinding, etching, grinding, CMP and cleaning processes only gradually repair the surface damage based on the initial surface state. Based on this, if you want to obtain a single crystal silicon wafer with better surface roughness index, then you need to start process optimization at the stage of the wire cutting process to improve the surface roughness of the bare wafer obtained by the wire cutting process, thereby improving the surface roughness index of the final single crystal silicon wafer.

[0004] However, there is currently no solution for optimizing the process at the wire cutting process stage based on the surface roughness of the bare wafer obtained during the wire cutting process. Summary of the invention

[0005] The present invention provides a method, device, equipment and medium for improving a wafer and its roughness; the roughness of a bare wafer obtained by wire cutting within a target wavelength range is used as an evaluation index, and the process parameters in the wire cutting process are adjusted by the index, thereby reducing the roughness of the wafer surface.

[0006] The technical solution of the present disclosure is achieved as follows: In a first aspect, the present disclosure provides a method for improving wafer roughness, the method comprising: Detect the roughness of bare wafers that have completed the wire-cutting process within the target wavelength range; When the roughness is greater than or equal to a set roughness threshold, the cutting process parameters that need to be adjusted are selected according to the priority of the cutting process parameters indicated by a fitting function between multiple cutting process parameters and the roughness in the target wavelength range to reduce the roughness of the bare wafer obtained in the subsequent wire cutting process in the target wavelength range.

[0007] In a second aspect, the present disclosure provides a device for improving wafer roughness, the device comprising: a detection part, a comparison part and a process improvement part; wherein: The detection part is configured to detect the roughness of the bare wafer that has completed the wire cutting process in the target wavelength range; The comparison part is configured to compare the roughness with a set roughness threshold, and trigger the process improvement part when the roughness is greater than or equal to the set roughness threshold; The process improvement part is configured to select the cutting process parameters that need to be adjusted to reduce the roughness of the bare wafer obtained by the subsequent wire cutting process in the target wavelength range according to the priority of the cutting process parameters indicated by the fitting function between multiple cutting process parameters and the roughness in the target wavelength range.

[0008] In a third aspect, the present disclosure provides a computing device, comprising: a processor and a memory; the processor is used to execute instructions stored in the memory to implement the method for improving wafer roughness as described in the first aspect.

[0009] In a fourth aspect, the present disclosure provides a computer-readable storage medium storing at least one instruction, wherein the at least one instruction is used to be executed by a processor to implement the method for improving wafer roughness as described in the first aspect.

[0010] In a fifth aspect, the present disclosure provides a wafer, which is obtained by a wire cutting process improved by the wafer roughness improvement method according to the first aspect, and has a roughness in a target wavelength range of at least one of the following: When the target wavelength ranges from 0 to 1.8 micrometers, the roughness is from 0.01 to 1 nm; When the target wavelength ranges from 1.8 to 22 micrometers, the roughness is 1 to 3 nm; When the target wavelength ranges from 22 micrometers to 20 millimeters, the roughness is 3 to 30 nm.

[0011] The present disclosure provides a method, device, equipment and medium for improving a wafer and its roughness; the roughness of a bare wafer obtained by wire cutting within a target wavelength range is used as an evaluation index; when the roughness of a bare wafer that has completed a wire cutting process within the target wavelength range is greater than or equal to a set roughness threshold, the cutting process parameters that need to be adjusted are selected according to the priority of the cutting process parameters indicated by a fitting function between multiple cutting process parameters and the roughness within the target wavelength range; and the roughness of the bare wafer obtained by a subsequent wire cutting process within the target wavelength range is reduced by adjusting the selected cutting process parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A schematic diagram of an exemplary multi-wire cutting device provided in the present disclosure.

[0013] Figure 2 A schematic diagram of the cutting area during the wire cutting process provided in the present disclosure.

[0014] Figure 3 A schematic flow chart of a method for improving wafer roughness provided in the present disclosure.

[0015] Figure 4 A schematic diagram of a process for detecting roughness within a target wavelength range provided by the present disclosure.

[0016] Figure 5 A schematic diagram of a filter provided in the present disclosure sliding on a wafer surface.

[0017] Figure 6 A schematic diagram of a divided analysis area provided in the present disclosure.

[0018] Figure 7 A schematic diagram of the composition of a wafer roughness improvement device provided by the present invention.

[0019] Figure 8 A schematic diagram of another device for improving wafer roughness provided by the present invention.

[0020] Fig. 9 A schematic diagram of the structure of a computing device provided by the present disclosure. DETAILED DESCRIPTION

[0021] The technical solutions in the present disclosure will be described clearly and completely below in conjunction with the accompanying drawings in the present disclosure.

[0022] See also Figure 1 , which shows an exemplary multi-wire cutting device 1 applicable to the technical solution of the present disclosure, and the device 1 may include a wire cutting unit 11 and a carrying unit 12. In some embodiments of the present disclosure, the wire cutting unit 11 may be located below the carrying unit 12 in the vertical direction. In embodiments not shown in the present disclosure, the wire cutting unit 11 may also be located above the carrying unit 12 in the vertical direction, which will not be described in detail here.

[0023] The wire cutting unit 11 may include a plurality of wire spools 111, cutting wires 112 and a cutting liquid supply unit 113. The cutting wires 112 are wound around the wire spools 111 to form an array of cutting wire segments parallel to each other. Figure 1The number of the bobbins 111 is two as an example for explanation. The two bobbins 111 are arranged opposite to each other with their axes parallel to each other. Two cutting liquid supply units 113 are respectively located directly above the two bobbins 111 and are used to spray cutting liquid to the two bobbins 111 and the cutting wire 112. The cutting liquid can be a liquid medium in which abrasive particles are suspended.

[0024] The reciprocating direction of the spool 111 and the cutting wire 112 toward and away from the carrier unit 12 is as follows: Figure 1 As shown by the solid arrow in the figure, the reciprocating speed can be 5 m / s to 18 m / s, for example. The carrying unit 12 is used to load and fix the silicon rod S to be processed, and can 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, the silicon rod to be processed can be bonded to the lower surface of the base 121 through its circumferential surface, thereby being fixed to the base 121.

[0025] for Figure 1 The wire cutting device 1 shown in the figure can move the bearing unit 12 in the vertical direction toward the cutting wire segment array so that the silicon rod to be processed is close to the cutting wire segment array. After the cutting wire segment array and the silicon rod S to be processed are in contact with each other, the cutting of the silicon rod S to be processed is achieved by utilizing the movement of each cutting wire segment array in the cutting wire segment array along its extension direction and the feeding movement of the bearing unit 12 in the vertical direction toward the cutting wire segment array. It should be noted that the present disclosure realizes the movement of the wire bearing unit 12 through a lifting device (not shown in the figure). It can be understood that those skilled in the art can also realize the movement of the bearing unit 12 through other methods according to actual needs and implementation scenarios, and the present disclosure does not elaborate on this.

[0026] A plurality of wire grooves 111A are provided on the circumferential surface of the bobbin 111 to guide and fix the cutting wire 112 to ensure that the cutting wire 112 maintains a stable tension and position during the cutting process. Typically, the wire grooves 111A are evenly distributed on the circumferential surface of the bobbin 111 .

[0027] In the process of wire cutting based on the above-mentioned multi-wire cutting equipment 1, the cutting liquid cannot be sprayed to the middle part of the silicon rod S to be processed, and the cutting liquid for cutting this part can only be obtained by carrying and transporting the cutting wire. Since the cutting wire can only run in a limited space, and there is no strong adhesion between the cutting liquid and the cutting wire material, the cutting liquid attached to the cutting wire is very easy to be scraped off during the transportation of the cutting wire, so that when cutting the middle part of the silicon rod S to be processed, the content of the cutting liquid is less than the edge part of the silicon rod S to be processed, and the insufficient content of the cutting liquid will cause the cutting force along the cutting direction to change. Specifically, due to the lack of convective heat transfer and heat dissipation path for the cutting liquid, more heat will accumulate and cannot be dissipated when cutting the middle part of the silicon rod S to be processed, which will cause thermal stress differences throughout the wafer, thereby causing deformation of the wafer.

[0028] In addition, as the silicon rod S to be processed is fed downward, the change of the cutting area during the online cutting process is an increase-decrease process. Figure 2 Taking the cross section of the silicon rod to be processed as an example, as the silicon rod S to be processed is fed downward as shown by the arrow, the cutting area gradually increases from the chord (dashed line) to the diameter and then decreases to the chord (dotted line). Figure 2 As shown, when the cut area is one diameter, more heat is accumulated inside the bare wafer, and there is a higher risk of thermal stress deformation.

[0029] Based on the above, the inventors found that maintaining a constant cutting rate may not be an ideal wire cutting solution. As the cutting area increases, the process parameters related to the cutting rate can be appropriately adjusted to achieve more sufficient heat dissipation inside the silicon rod S to be processed, thereby improving the roughness of the bare wafer.

[0030] Based on this, see Figure 3 , which shows a method for improving wafer roughness provided by the present disclosure, the method comprising steps S301 to S302.

[0031] In step S301 , the roughness of a bare wafer that has completed a wire sawing process is detected within a target wavelength range.

[0032] In the present disclosure, the uniformity of the wafer surface morphology is reflected in the height difference between each point on the wafer surface. This height difference will show the fluctuation phenomenon of the height value of each point on the wafer surface as a whole. Based on this understanding, the present disclosure regards this fluctuation phenomenon from the perspective of waves as caused by the superposition of wave signals of different wavelengths. The smaller the wavelength of the wave signal, the smaller the size of the area characterized by the height value fluctuation phenomenon; the larger the wavelength of the wave signal, the larger the size of the area characterized by the height value fluctuation phenomenon.

[0033] Based on the above explanation, in order to evaluate or measure the roughness of a smaller area, the present disclosure can use the area size of the desired roughness measurement to filter the above-mentioned fluctuation phenomenon, thereby obtaining the wave signal data within the wavelength range corresponding to the area of ​​the desired roughness measurement, and calculate the roughness of the wafer under the area size standard based on the wave signal data. In the present disclosure, the target wavelength range is taken as 22 microns to 20 millimeters.

[0034] In step S302, when the roughness is greater than or equal to the set roughness threshold, the cutting process parameters that need to be adjusted are selected according to the priority of the cutting process parameters indicated by the fitting function between multiple cutting process parameters and the roughness in the target wavelength range to reduce the roughness of the bare wafer obtained by the subsequent wire cutting process in the target wavelength range.

[0035] In the present disclosure, after detecting the roughness of the bare wafer that has completed the wire cutting process in the target wavelength range, the roughness can be characterized by the set roughness threshold to determine whether the roughness is good. Taking the target wavelength range of 22 microns to 20 millimeters as an example, in some examples, the roughness threshold can be set to 25nm. That is, when the roughness value of the bare wafer in the target wavelength range is greater than or equal to 25nm, it indicates that the cutting ability of the multi-wire cutting device 1 is seriously degraded.

[0036] Specifically, the bare wafer obtained by the wire cutting process shows obvious periodic line marks on the macroscopic level, and these line marks can be considered as the overall presentation of roughness on the wafer surface. Based on this understanding, it can be seen that these line marks, like the roughness mentioned in the previous steps, can be manifested as a fluctuation phenomenon with amplitude, and this fluctuation phenomenon is also caused by the superposition of wave signals of different wavelengths.

[0037] Combined with the above Figure 1 The inventors found that the macroscopic performance (i.e., line marks) is related to the following cutting process parameters used in the wire cutting process: the moving speed of the cutting line reciprocating motion, the period of the cutting line reciprocating motion, and the feed speed of the silicon rod S to be processed. The influence of the above three cutting process parameters on the roughness of the surface of the above bare wafer in the target wavelength range can be characterized by a fitting function. In the present disclosure, the fitting function is represented by a power function of the above three cutting process parameters, such as shown in the following formula:

[0038] in, Indicates the reciprocating movement speed of the cutting line, Represents the period of reciprocating motion of the cutting line, Indicates the feed speed, , b.c are empirical coefficients in the fitting function, which respectively represent the influence of the corresponding cutting process parameters on the roughness. K 1 represents the fitting coefficient. In order to determine the empirical coefficient and fitting coefficient of the above fitting function, in some examples, the cutting process parameters collected in the historical wire cutting process and the roughness of the bare wafer detected in the target wavelength range obtained in the historical wire cutting process are substituted into the above fitting function to determine , b.c as well as K 1.

[0039] In this disclosure, K 1=6.2×10 -3 , = 0.529, b =1.445, c =0.873, based on this empirical coefficient , b.c The specific value of can be seen: the empirical coefficient b The period of the corresponding cutting line reciprocating motion has the greatest influence on the roughness, followed by the empirical coefficient. c The corresponding feed rate, followed by the empirical coefficient The corresponding moving speed of the reciprocating motion of the cutting line. For the magnitude of the above-mentioned influence, the priority is set for the moving speed of the reciprocating motion of the cutting line, the period of the reciprocating motion of the cutting line, and the feed speed. Specifically, the greater the influence, the higher the priority. Therefore, when the roughness exceeds the set roughness threshold, the cutting process parameters are selected according to the above-mentioned priority for adjustment, thereby reducing the roughness of the bare wafer obtained in the subsequent wire cutting process within the target wavelength range.

[0040] Above Figure 3 The technical scheme shown takes the roughness of the bare wafer obtained by wire cutting within the target wavelength range as an evaluation indicator. When the roughness of the bare wafer that has completed the wire cutting process within the target wavelength range is greater than or equal to the set roughness threshold, the cutting process parameters that need to be adjusted are selected according to the priority of the cutting process parameters indicated by the fitting function between multiple cutting process parameters and the roughness within the target wavelength range. The roughness of the bare wafer obtained by the subsequent wire cutting process within the target wavelength range is reduced by adjusting the selected cutting process parameters.

[0041] for Figure 3 In some possible implementations of the technical solution shown, the fitting function can be obtained by fitting the cutting process parameters collected in the historical wire cutting process and the roughness detected in the target wavelength range of the bare wafer obtained in the historical wire cutting process. The specific fitting process may include: Initializing a fitting function according to the product of a power function of the moving speed of the cutting line reciprocating motion with a first empirical coefficient as an exponent, a power function of the period of the cutting line reciprocating motion with a second empirical coefficient as an exponent, and a power function of the feeding speed with a third empirical coefficient as an exponent; In the historical wire cutting process, historical cutting process parameters are collected, and the roughness of the bare wafer that has completed the historical wire cutting process in the target wavelength range is detected; The historical cutting process parameters and the roughness of the bare wafer that has completed the historical wire cutting process in the target wavelength range are substituted into the fitting function to obtain the first empirical coefficient, the second empirical coefficient and the third empirical coefficient in the fitting function.

[0042] For the above implementation, exemplary specific implementation details may include: First, a fitting function is expressed by a power function of the above three cutting process parameters as follows:

[0043] in, Vs Indicates the reciprocating movement speed of the cutting line, Tr Represents the period of reciprocating motion of the cutting line, V Indicates the feed speed, , b.c are empirical coefficients in the fitting function, which respectively represent the influence of the corresponding cutting process parameters on the roughness. K 1 indicates the fitting coefficient.

[0044] Next, the above fitting function is logarithmically transformed, so that the fitting function after logarithmic transformation is as shown in the following formula: .

[0045] Then, using the historical cutting process parameters collected in the historical wire cutting process and the roughness of the bare wafer in the target wavelength range after the historical wire cutting process, the empirical coefficients and fitting coefficients of the above-mentioned logarithmically transformed fitting function are calculated by the least squares method, so as to obtain the coefficients applicable to the target wavelength range. Figure 3 Fitting function of the technical solution shown.

[0046] Through the above fitting function acquisition process, we can finally get K 1=6.2×10 -3 , = 0.529, b =1.445, c=0.873. According to the above empirical coefficients, it can be known that the period of the reciprocating motion of the cutting line has the greatest impact on the roughness, followed by the feed speed, and then the moving speed of the reciprocating motion of the cutting line.

[0047] In the present disclosure, some historical cutting process parameters and the corresponding roughness of bare wafers that have completed the historical wire sawing process in the range of 22 micron wavelength to 20 mm wavelength are shown in Table 1 below.

[0048]

[0049] Table 1 In the present disclosure, when the target wavelength range is 1.8 to 22 microns, based on the acquisition process of the above fitting function, it can be obtained: K 1=4.4×10 -3 , = 0.659, b =1.217, c =0.887. According to the above empirical coefficients, it can also be known that the period of the reciprocating motion of the cutting line has the greatest impact on the roughness, followed by the feed speed, and then the moving speed of the reciprocating motion of the cutting line. In the present disclosure, some historical cutting process parameters and the corresponding roughness of bare wafers that have completed the historical line cutting process in the range of 1.8 to 22 microns are shown in Table 2 below.

[0050]

[0051] Table 2 In the present disclosure, when the target wavelength range is 0 to 1.8 microns, based on the acquisition process of the above fitting function, it can be obtained: K 1=6.7×10 -3 , = 0.813, b =1.105, c =0.971. According to the above empirical coefficients, it can also be known that the period of the reciprocating motion of the cutting line has the greatest impact on the roughness, followed by the feed speed, and then the moving speed of the reciprocating motion of the cutting line. In the present disclosure, some historical cutting process parameters and the corresponding roughness of bare wafers that have completed the historical line cutting process in the range of 0 to 1.8 microns are shown in Table 3 below.

[0052]

[0053] Table 3 In the above Tables 1, 2 and 3, the roughness increases with V , Vs as well as TrThe situation that changes with the change of can also verify the above conclusion about the influence of the cutting line reciprocating motion period, feed speed and moving speed of the cutting line reciprocating motion on the roughness.

[0054] for Figure 3 The technical solution shown in the figure may be implemented in some possible ways, such as Figure 4 As shown, the process of detecting the roughness of the bare wafer that has completed the wire sawing process in the target wavelength range in step S301 may include steps S3011 to S3013.

[0055] In step S3011, for each sampling point on the surface of the bare wafer, original measurement data on the height of the wafer surface at each sampling point is obtained through a single-point measurement solution.

[0056] For this implementation, specifically, a single-point measurement scheme is a scheme in which only measurement data at one sampling point can be measured during one measurement process. 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 on the wafer surface. With this horizontal movement, the height difference on the bare wafer surface will cause the probe to produce a longitudinal displacement, which is sensed by a displacement sensor and the sensed longitudinal displacement value is converted into the height data of the bare wafer surface, that is, the original measurement data on the wafer surface height. In other examples, non-contact measurement schemes such as capacitance measurement and laser focusing measurement can also be used.

[0057] In step S3012, based on the original measurement data of all sampling points on the surface of the bare wafer, a wave signal of each sampling point in the target wavelength range is obtained through a filter corresponding to the target wavelength range for each sampling point.

[0058] In this implementation, after measuring each sampling point on the surface of the bare wafer through the above-mentioned single-point measurement scheme, the original measurement data of all sampling points can reflect the height difference between the sampling points, which can be seen as a three-dimensional fluctuation phenomenon from the entire wafer surface. For this fluctuation phenomenon, the amplitude of the wave signals of different wavelengths superimposed to form the fluctuation phenomenon can be used to represent the height difference in the area corresponding to the wavelength size. Taking the target wavelength range of 22 microns to 20 millimeters as an example, the upper limit of the wavelength is 20mm and the lower limit of the wavelength is 22μm. Taking the target wavelength range of 0 to 1.8 microns as an example, the upper limit of the wavelength is 1.8μm and the lower limit of the wavelength is 0. Taking the target wavelength range of 1.8 to 22 microns as an example, the upper limit of the wavelength is 22μm and the lower limit of the wavelength is 1.8μm.

[0059] In some examples, in order to obtain the wave signal of each sampling point within the target wavelength range, in the specific implementation process of step S3012, the wave signal with a wavelength higher than the upper wavelength limit is first filtered out from the wave phenomenon by a low-pass filter function, and then the wave signal with a wavelength lower than the lower wavelength limit is filtered out by a high-pass filter function, and finally the wave signal within the target wavelength range is obtained.

[0060] Specifically, take the above filter as an example, which is a circular filter, and the circular filter is composed of a double Gaussian filter function. LP1 It can be a Gaussian low-pass filter function whose low-pass filter range covers the upper limit of the target wavelength range; the second Gaussian filter function G LP2 It can be a Gaussian low-pass filter function whose low-pass filter range covers the lower limit of the target wavelength range and passes (1- G LP2 ) to obtain a high-pass filter function. Based on the first Gaussian filter function and the second Gaussian filter function, the circular filter G DHP It can be expressed as G DHP = G LP1 (1-G LP2 ). In the present disclosure, taking the circular filter in the above example as an example, Figure 5 As shown, the circular filter indicated by the arrow can be slid on the surface of the bare wafer according to the sampling points, and the original measurement data of the sampling point at the center of the circular filter and other sampling points covered by the range of action of the circular filter are filtered through the circular filter to obtain the wave signal of each sampling point in the target wavelength range.

[0061] It should be noted that, since the closer the wafer surface is to the edge, the more dramatic the morphological changes are, in order to accurately capture dramatic morphological changes, when the sampling point is close to the edge of the wafer surface, the corresponding circular filter's range of action should be smaller than the circular filter's range of action corresponding to the sampling point close to the center of the wafer surface, that is, as the sampling point gradually moves away from the wafer center, the corresponding filter's range of action should decrease, or shrink. Therefore, the radius of the filter's range of action is determined by the distance between the sampling point and the center of the bare wafer.

[0062] In the present disclosure, a critical distance is set to determine whether the 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 filter's range of action is the 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 filter's range of action is the 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.

[0063] Based on the above example, specifically, the shrinking method can be a step-wise method, that is, when the distance between the sampling point and the center of the bare wafer is greater than a critical distance, the second radius is fixedly set to a value smaller than the first radius; or it can be a gradual method, that is, the second radius gradually decreases as the sampling point moves 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 a 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.

[0064] In step S3013, the roughness of the bare wafer within the target wavelength range is determined based on the amplitude statistics of the wave signals of all sampling points within the target wavelength range.

[0065] For the above implementation, after obtaining the wave signals of all sampling points in the target wavelength range by filtering, in some examples, determining the roughness of the bare wafer in the target wavelength range based on the amplitude statistics of the wave signals of all sampling points in the target wavelength range includes: Divide the bare wafer into multiple analysis areas; Calculate the range of the amplitude of the wave signal of each analysis area in the target wavelength range according to the amplitude value of the wave signal of the sampling point in each analysis area in the target wavelength range; The range mean of the amplitude of the wave signal of all analysis areas in the target wavelength range is determined as the roughness index of the bare wafer in the target wavelength range.

[0066] For the above example, Figure 6 As shown, after the edge area of ​​the bare wafer surface is removed according to EE, the remaining area is divided according to a set size, such as a square area of ​​10mm×10mm, so that 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 area according to EE and cannot present a complete square can be obtained. These two analysis areas constitute the analysis area in the above implementation method.

[0067] It should be noted that the wave signals of all sampling points on the wafer surface within the target wavelength range include all information that can characterize the surface morphology (i.e., roughness) of the wafer surface within the size area corresponding to the target wavelength range. This information can be characterized by the statistical values ​​of the amplitude, such as the mean, extreme value, extreme value under a set size area ratio, range, variance, standard deviation, median, mode, etc. of the amplitude mentioned in the aforementioned technical solution.

[0068] In the present disclosure, taking the range as an example, the amplitude statistic of the wave signal of each analysis area in the target wavelength range is the range of the amplitude values ​​of the wave signal of the sampling points and interpolation points in each analysis area in the target wavelength range; accordingly, the roughness index of the bare wafer in the target wavelength range is the average of the ranges of the amplitude values ​​of the wave signals of all analysis areas in the target wavelength range.

[0069] Based on the above technical solutions and specific embodiments, the roughness of the wafer obtained by the wire cutting process improved by the above wafer roughness improvement method in the target wavelength range is at least one of the following: When the target wavelength ranges from 0 to 1.8 micrometers, the roughness is from 0.01 to 1 nm; When the target wavelength ranges from 1.8 to 22 micrometers, the roughness is 1 to 3 nm; When the target wavelength ranges from 22 micrometers to 20 millimeters, the roughness is 3 to 30 nm.

[0070] Based on the same inventive concept as the above technical solution, see Figure 7 , which shows a wafer roughness improvement device 70, the device 70 includes: a detection part 701, a comparison part 702 and a process improvement part 703; wherein, The detection part 701 is configured to detect the roughness of the bare wafer that has completed the wire sawing process within the target wavelength range; The comparison part 702 is configured to compare the roughness with a set roughness threshold, and when the roughness is greater than or equal to the set roughness threshold, trigger the process improvement part 703; The process improvement part 703 is configured to select the cutting process parameters that need to be adjusted to reduce the roughness of the bare wafer obtained by the subsequent wire cutting process in the target wavelength range according to the priority of the cutting process parameters indicated by the fitting function between multiple cutting process parameters and the roughness in the target wavelength range.

[0071] In some examples, the plurality of cutting process parameters include: a moving speed of the cutting line reciprocating motion, a period of the cutting line reciprocating motion, and a feed speed; Accordingly, the fitting function is represented by the product of power functions respectively related to the moving speed of the cutting wire reciprocating motion, the period of the cutting wire reciprocating motion and the feed speed.

[0072] For some examples, see Figure 8 The device 70 further comprises a fitting portion 704 configured to: Initializing a fitting function according to the product of a power function of the moving speed of the cutting line reciprocating motion with a first empirical coefficient as an exponent, a power function of the period of the cutting line reciprocating motion with a second empirical coefficient as an exponent, and a power function of the feeding speed with a third empirical coefficient as an exponent; In the historical wire cutting process, historical cutting process parameters are collected, and the roughness of the bare wafer that has completed the historical wire cutting process in the target wavelength range is detected; The historical cutting process parameters and the roughness of the bare wafer that has completed the historical wire cutting process in the target wavelength range are substituted into the fitting function to obtain the first empirical coefficient, the second empirical coefficient and the third empirical coefficient in the fitting function.

[0073] In some examples, the fitting portion 704 is configured to: Performing logarithmic transformation on the fitting function to obtain a logarithmic transformed fitting function; Using the historical cutting process parameters and the roughness of the bare wafer that has completed the historical wire cutting process in the target wavelength range, the first empirical coefficient, the second empirical coefficient and the third empirical coefficient in the fitting function after logarithmic transformation are calculated by the least squares method.

[0074] In some examples, the detection portion 701 is configured to: For each sampling point on the surface of the bare wafer, obtaining original measurement data about the height of the wafer surface at each sampling point through a single-point measurement scheme; Based on the original measurement data of all sampling points on the surface of the bare wafer, for each sampling point, a wave signal of each sampling point in the target wavelength range is obtained through a filter corresponding to the target wavelength range; The roughness of the bare wafer within the target wavelength range is determined based on amplitude statistics of wave signals of all sampling points within the target wavelength range.

[0075] In some examples, the filter is a circular filter and is composed of a double Gaussian filter function; The radius of the filter's range of action 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 filter's range of action 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 filter's range of action is a second radius; wherein both the first radius and the second radius are determined by an upper limit of the target wavelength range, and the first radius is greater than the second radius.

[0076] In some examples, the detection portion 701 is configured to: Divide the bare wafer into multiple analysis areas; Calculate the range of the amplitude of the wave signal of each analysis area in the target wavelength range according to the amplitude value of the wave signal of the sampling point in each analysis area in the target wavelength range; The range mean of the amplitude of the wave signal of all analysis areas in the target wavelength range is determined as the roughness index of the bare wafer in the target wavelength range.

[0077] In some examples, when the target wavelength range is 0 to 1.8 micrometers, the roughness threshold is 1 nm; When the target wavelength range is 1.8 to 22 micrometers, the roughness threshold is 3 nm; When the target wavelength ranges from 22 micrometers to 20 millimeters, the roughness threshold is 25 nm.

[0078] It should be noted that, for the specific implementation of the functions configured by each "part" in the above-mentioned device, reference can be made to the implementation methods and examples of the corresponding steps in the above-mentioned method for improving wafer roughness, which will not be repeated here.

[0079] Please refer to Fig. 9 , which shows a structural block diagram of a computing device provided by an exemplary embodiment of the present disclosure. In some examples, the computing device 90 may be at least one of a smart phone, a smart watch, a desktop computer, a laptop, a virtual reality terminal, an augmented reality terminal, a wireless terminal, and a laptop portable computer. The computing device 90 has a communication function and can access a wired network or a wireless network. The computing device 90 may generally refer to one of a plurality of terminals, and those skilled in the art may know that the number of the above terminals may be more or less. In some examples, the computing device 90 may receive data based on the wired network or wireless network to which it is connected. It can be understood that the computing device 90 undertakes the calculation and processing work of the technical solution of the present disclosure, and the present disclosure does not limit this.

[0080] like Fig. 9 As shown, the computing device in the present disclosure may include one or more of the following components: a processor 910 and a memory 920 .

[0081] Optionally, the processor 910 uses various interfaces and lines to connect various parts of the entire computing device, and executes various functions of the computing device and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 920, and calling data stored in the memory 920. Optionally, the processor 910 can be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 910 can integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), a neural network processor (NPU), and a baseband chip. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing the content that needs to be displayed on the touch display; the NPU is used to implement artificial intelligence (AI) functions; and the baseband chip is used to process wireless communications. It is understandable that the above baseband chip may not be integrated into the processor 910, but may be implemented by a separate chip.

[0082] The memory 920 may include a random access memory (RAM) or a read-only memory (ROM). Optionally, the memory 920 includes a non-transitory computer-readable storage medium. The memory 920 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 920 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 a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above various method embodiments, etc.; the data storage area may store data created according to the use of the computing device, etc.

[0083] In addition, those skilled in the art can understand that the structure of the computing device shown in the above drawings does not constitute a limitation on the computing device, and the computing device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. For example, the computing device also includes a display screen, a camera assembly, a microphone, a speaker, a radio frequency circuit, an input unit, a sensor (such as an acceleration sensor, an angular velocity sensor, a light sensor, etc.), an audio circuit, a WiFi module, a power supply, a Bluetooth module and other components, which will not be described in detail here.

[0084] The present disclosure also provides a computer-readable storage medium storing at least one instruction, wherein the at least one instruction is used to be executed by a processor to implement the method for improving wafer roughness as described in the above embodiments.

[0085] The present disclosure also provides a computer program product, which includes 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 the processor executes the computer instructions, so that the computing device executes to implement the method for improving wafer roughness described in the above-mentioned embodiments.

[0086] The present disclosure also provides a wafer, which is obtained by a wire cutting process improved by the wafer roughness improvement method described in the above technical solution, and has a roughness in a target wavelength range of at least one of the following: When the target wavelength ranges from 0 to 1.8 micrometers, the roughness is from 0.01 to 1 nm; When the target wavelength ranges from 1.8 to 22 micrometers, the roughness is 1 to 3 nm; When the target wavelength ranges from 22 micrometers to 20 millimeters, the roughness is 3 to 30 nm.

[0087] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the present disclosure can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. Storage media can be any available media that can be accessed by a general or special-purpose computer.

[0088] It should be noted that the technical solutions described in the present disclosure can be combined arbitrarily without conflict.

[0089] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for improving wafer roughness, characterized in that: The method comprises: Detect the roughness of bare wafers that have completed the wire-cutting process within the target wavelength range; When the roughness is greater than or equal to a set roughness threshold, the cutting process parameters that need to be adjusted are selected according to the priority of the cutting process parameters indicated by a fitting function between multiple cutting process parameters and the roughness in the target wavelength range to reduce the roughness of the bare wafer obtained in the subsequent wire cutting process in the target wavelength range.

2. The method according to claim 1, characterized in that The plurality of cutting process parameters include: a moving speed of the cutting line reciprocating motion, a period of the cutting line reciprocating motion, and a feed speed; Accordingly, the fitting function is represented by the product of power functions respectively related to the moving speed of the cutting wire reciprocating motion, the period of the cutting wire reciprocating motion and the feed speed.

3. The method according to claim 1, characterized in that The method further comprises: Initializing a fitting function according to the product of a power function of the moving speed of the cutting line reciprocating motion with a first empirical coefficient as an exponent, a power function of the period of the cutting line reciprocating motion with a second empirical coefficient as an exponent, and a power function of the feeding speed with a third empirical coefficient as an exponent; In the historical wire cutting process, historical cutting process parameters are collected, and the roughness of the bare wafer that has completed the historical wire cutting process in the target wavelength range is detected; The historical cutting process parameters and the roughness of the bare wafer that has completed the historical wire cutting process in the target wavelength range are substituted into the fitting function to obtain the first empirical coefficient, the second empirical coefficient and the third empirical coefficient in the fitting function.

4. The method according to claim 3, characterized in that Substituting the historical cutting process parameters and the roughness of the bare wafer that has completed the historical wire cutting process in the target wavelength range into the fitting function to obtain the first empirical coefficient, the second empirical coefficient and the third empirical coefficient in the fitting function, comprises: Performing logarithmic transformation on the fitting function to obtain a logarithmic transformed fitting function; Using the historical cutting process parameters and the roughness of the bare wafer that has completed the historical wire cutting process in the target wavelength range, the first empirical coefficient, the second empirical coefficient and the third empirical coefficient in the fitting function after logarithmic transformation are calculated by the least squares method.

5. The method according to claim 1, characterized in that: The roughness detection of the bare wafer after the wire cutting process in the target wavelength range includes: For each sampling point on the surface of the bare wafer, obtaining original measurement data about the height of the wafer surface at each sampling point through a single-point measurement scheme; Based on the original measurement data of all sampling points on the surface of the bare wafer, for each sampling point, a wave signal of each sampling point in the target wavelength range is obtained through a filter corresponding to the target wavelength range; The roughness of the bare wafer within the target wavelength range is determined based on amplitude statistics of wave signals of all sampling points within the target wavelength range.

6. The method according to claim 1, characterized in that The filter is a circular filter and is composed of a double Gaussian filter function; The radius of the filter's range of action 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 filter's range of action 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 filter's range of action is a second radius; wherein both the first radius and the second radius are determined by an upper limit of the target wavelength range, and the first radius is greater than the second radius.

7. The method according to claim 5, characterized in that The method of determining the roughness of the bare wafer within the target wavelength range based on the amplitude statistics of the wave signals of all sampling points within the target wavelength range comprises: Divide the bare wafer into multiple analysis areas; Calculate the range of the amplitude of the wave signal of each analysis area in the target wavelength range according to the amplitude value of the wave signal of the sampling point in each analysis area in the target wavelength range; The range mean of the amplitude of the wave signal of all analysis areas in the target wavelength range is determined as the roughness index of the bare wafer in the target wavelength range.

8. The method according to any one of claims 1 to 7, characterized in that: When the target wavelength range is 0 to 1.8 micrometers, the roughness threshold is 1 nm; When the target wavelength range is 1.8 to 22 micrometers, the roughness threshold is 3 nm; When the target wavelength ranges from 22 micrometers to 20 millimeters, the roughness threshold is 25 nm.

9. A device for improving wafer roughness, characterized in that: The device comprises: a detection part, a comparison part and a process improvement part; wherein, The detection part is configured to detect the roughness of the bare wafer that has completed the wire cutting process in the target wavelength range; The comparison part is configured to compare the roughness with a set roughness threshold, and trigger the process improvement part when the roughness is greater than or equal to the set roughness threshold; The process improvement part is configured to select the cutting process parameters that need to be adjusted to reduce the roughness of the bare wafer obtained in the subsequent wire cutting process in the target wavelength range according to the priority of the cutting process parameters indicated by the fitting function between multiple cutting process parameters and the roughness in the target wavelength range.

10. A computing device, characterized in that The computing device comprises: a processor and a memory; the processor is used to execute instructions stored in the memory to implement the method for improving wafer roughness as claimed in 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 used to be executed by a processor to implement the method for improving wafer roughness according to any one of claims 1 to 8.

12. A wafer, characterized in that: The wafer is obtained by a wire cutting process improved by the wafer roughness improvement method according to claims 1 to 9, and the roughness in the target wavelength range is at least one of the following: When the target wavelength ranges from 0 to 1.8 micrometers, the roughness is from 0.01 to 1 nm; When the target wavelength ranges from 1.8 to 22 micrometers, the roughness is 1 to 3 nm; When the target wavelength ranges from 22 micrometers to 20 millimeters, the roughness is 3 to 30 nm.

Images