Wafer, roughness improvement method and apparatus therefor, device, and medium

Abstract

The present disclosure provides a wafer, a roughness improvement method and apparatus therefor, a device, and a medium. The method comprises: detecting a roughness of a bare wafer in a target wavelength range after a line cutting process is completed; when the roughness is greater than or equal to a set roughness threshold, then, based on priorities of multiple cutting process parameters and cutting process parameters indicated by a fitting function between the multiple cutting process parameters and the roughness in the target wavelength range, selecting cutting process parameters that need to be adjusted so as to reduce the roughness of the bare wafer in the target wavelength range obtained during a subsequent line cutting process.

Description

Methods, apparatus, equipment and media for improving wafer and its roughness

[0001] Cross-reference to related applications

[0002] This application claims priority to Chinese Patent Application No. 202411435849.1, filed in China on October 15, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] 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

[0004] 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, polishing, 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.

[0005] 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.

[0006] However, there is currently no solution to optimize the wire cutting process based on the surface roughness of the bare wafer obtained from the wire cutting process. Summary of the Invention

[0007] This disclosure provides a wafer and a method, apparatus, device, and medium for improving its roughness; using the roughness of the bare wafer obtained by wire cutting within a target wavelength range as an evaluation index, and adjusting the process parameters in the wire cutting process through this index to reduce the surface roughness of the wafer.

[0008] In a first aspect, this disclosure provides a method for improving wafer roughness, the method comprising:

[0009] The roughness of a bare wafer after wire cutting is measured within the target wavelength range.

[0010] When the roughness is greater than or equal to a set roughness threshold, the cutting process parameters that need to be adjusted are selected based on 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, so as to reduce the roughness of the bare wafer obtained by the subsequent wire cutting process in the target wavelength range.

[0011] Secondly, this disclosure provides a wafer roughness improvement apparatus, the apparatus comprising: a detection section, a comparison section, and a process improvement section; wherein,

[0012] The detection section is configured to detect the roughness of a bare wafer that has undergone wire cutting in the target wavelength range.

[0013] The comparison section is configured to compare the roughness with a set roughness threshold, and to trigger the process improvement section when the roughness is greater than or equal to the set roughness threshold.

[0014] The process improvement section is configured to select the cutting process parameters that need to be adjusted to reduce the roughness of the bare wafer obtained from subsequent wire dicing processes in the target wavelength range, based on 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.

[0015] 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.

[0016] 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.

[0017] 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:

[0018] When the target wavelength range is 0 to 1.8 micrometers, the roughness is 0.01 to 1 nm;

[0019] When the target wavelength range is 1.8 to 22 micrometers, the roughness is 1 to 3 nm;

[0020] When the target wavelength range is 22 micrometers to 20 millimeters, the roughness is 3 to 30 nm.

[0021] This disclosure provides a wafer and a method, apparatus, device, and medium for improving its roughness. Using the roughness of a bare wafer obtained by wire dicing within a target wavelength range as an evaluation index, when the roughness of the bare wafer after wire dicing is greater than or equal to a set roughness threshold within the target wavelength range, the method selects the dicing process parameters that need adjustment based on the priority indicated by the fitting function between multiple dicing process parameters and the roughness within the target wavelength range. The roughness of the bare wafer obtained in subsequent wire dicing processes within the target wavelength range is reduced by adjusting the selected dicing process parameters. Attached Figure Description

[0022] Figure 1 is a schematic diagram of an exemplary multi-wire cutting device provided in this disclosure.

[0023] Figure 2 is a schematic diagram of the cutting area during the wire EDM process provided in this disclosure.

[0024] Figure 3 is a schematic flowchart of a method for improving wafer roughness provided in this disclosure.

[0025] Figure 4 is a schematic diagram of the process for detecting roughness in the target wavelength range provided in this disclosure.

[0026] Figure 5 is a schematic diagram of a filter sliding on a wafer surface provided in this disclosure.

[0027] Figure 6 is a schematic diagram of an analysis region obtained by dividing the data according to this disclosure.

[0028] Figure 7 is a schematic diagram of the components of a wafer roughness improvement device provided in this disclosure.

[0029] Figure 8 is a schematic diagram of another wafer roughness improvement device provided in this disclosure.

[0030] Figure 9 is a schematic diagram of the structure of a computing device provided in this disclosure. Detailed Implementation

[0031] The technical solutions in this disclosure will now be clearly and completely described with reference to the accompanying drawings.

[0032] Referring to Figure 1, an exemplary multi-wire cutting device 1 applicable to the technical solutions of this disclosure is shown. 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.

[0033] The wire cutting unit 11 may include multiple spools 111, cutting wires 112, and cutting fluid supply units 113. The cutting wires 112 are wound around the spools 111 to form an array of parallel cutting segments. Referring to Figure 1, an example with two spools 111 will be used below. The two spools 111 are arranged opposite each other with their axes parallel to each other. Two cutting fluid supply units 113 are located directly above the two spools 111, respectively, and are used to spray cutting fluid onto the two spools 111 and the cutting wires 112. This cutting fluid can be a liquid medium in which abrasive particles are suspended.

[0034] The reciprocating motion directions of the spool 111 and the cutting wire 112 toward and away from the support unit 12 are shown by the solid arrows in Figure 1. The reciprocating motion speed can, for example, be from 5 m / s to 18 m / s. The support unit 12 is used to load and fix the silicon rod S to be processed, and 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, the silicon rod to be processed can be fixed to the base 121 by bonding its circumferential surface to the lower surface of the base 121.

[0035] For the wire cutting device 1 shown in Figure 1, the silicon rod to be processed can be brought closer to the cutting segment array by moving the carrier unit 12 vertically toward the cutting segment array. After the cutting segment 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 segment in the cutting segment array along its extension direction and the continued feed movement of the carrier unit 12 vertically toward the cutting segment array. It should be noted that the present disclosure uses a lifting device (not shown in the figure) to move the wire carrier unit 12. It is understood that those skilled in the art can also move the carrier unit 12 in other ways according to actual needs and implementation scenarios, which will not be described in detail in this disclosure.

[0036] 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.

[0037] During wire cutting using the aforementioned multi-wire cutting equipment 1, the cutting fluid cannot be sprayed onto the middle portion of the silicon ingot S to be processed. The cutting fluid for this portion can only be obtained through the cutting wire. Since the cutting wire can only operate within a limited space, and there is no strong adhesion between the cutting fluid and the wire material, the cutting fluid adhering to the wire is easily scraped off during the wire's transport. This results in a lower cutting fluid content in the middle portion of the silicon ingot S compared to its edges, leading to insufficient cutting force along the cutting direction. Specifically, due to the lack of a convection heat transfer pathway provided by the cutting fluid, more heat accumulates in the middle portion of the silicon ingot S and cannot dissipate, causing thermal stress differences across the entire wafer and resulting in wafer deformation.

[0038] Furthermore, as the silicon ingot S is fed downwards, the cutting area during the wire dicing process undergoes an increasing-decreasing process. Taking the cross-section of the silicon ingot shown in Figure 2 as an example, as the silicon ingot S is fed downwards as indicated by the arrow, the cutting area gradually increases from a chord (dashed line) to a diameter and then decreases back to a chord (dotted line). Based on Figure 2, when the cutting area is a diameter, more heat accumulates inside the bare wafer, resulting in a higher risk of thermal stress deformation.

[0039] Based on the above, the inventors discovered 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 enable more adequate heat dissipation inside the silicon rod S to be processed, thereby improving the roughness of the bare wafer.

[0040] Based on this, referring to Figure 3, it illustrates a method for improving wafer roughness provided in this disclosure, the method including steps S301 to S302.

[0041] In step S301, the roughness of the bare wafer after the wire cutting process is detected in the target wavelength range.

[0042] 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.

[0043] Based on the above description, in order to evaluate or measure the roughness of even smaller regions, this disclosure can filter the aforementioned 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 wafer roughness under that region size standard based on the wave signal data. In this disclosure, a target wavelength range of 22 micrometers to 20 millimeters is used as an example.

[0044] In step S302, 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 the fitting function between multiple cutting process parameters and the roughness in the target wavelength range, so as to reduce the roughness of the bare wafer obtained by the subsequent wire cutting process in the target wavelength range.

[0045] In this disclosure, after detecting the roughness of the bare wafer after the wire dicing process within the target wavelength range, 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, in some examples, this roughness threshold can be set to 25 nm. That is, when the roughness value of the bare wafer within the target wavelength range is greater than or equal to 25 nm, it indicates that the dicing capability of the multi-wire dicing equipment 1 is severely degraded.

[0046] Specifically, the bare wafers obtained from the wire dicing process exhibit obvious periodic lines on a macroscopic scale. These lines can be considered as the overall roughness of the wafer surface. Based on this understanding, it can be inferred that these lines, like the roughness mentioned in the previous steps, can manifest as a wave phenomenon with amplitude, and this wave phenomenon is also caused by the superposition of wave signals of different wavelengths.

[0047] Based on the structure and working principle of the multi-wire dicing equipment shown in Figure 1, the inventors discovered that the macroscopic appearance (i.e., the wire marks) is related to the following dicing process parameters used in the wire dicing process: the moving speed of the dicing wire reciprocating motion, the period of the dicing wire reciprocating motion, and the feed speed of the silicon rod S to be processed. The degree of influence of the above three dicing process parameters on the surface roughness of the bare wafer in the target wavelength range can be characterized by a fitting function. In this disclosure, the fitting function is represented by a power function of the above three dicing process parameters, for example, as shown in the following formula:

[0048] PV = K1 × Vs a ×Tr b ×Vf c

[0049] Where Vs represents the reciprocating speed of the cutting wire, Tr represents the period of the reciprocating motion of the cutting wire, Vf represents the feed rate, a, b, and c are empirical coefficients in the fitting function, which respectively represent the degree of influence of their corresponding cutting process parameters on the roughness, and K1 represents the fitting coefficient. To determine the empirical coefficients and fitting coefficients of the above fitting function, in some examples, the cutting process parameters collected in historical wire cutting processes and the roughness detected in the target wavelength range on the bare wafers obtained from historical wire cutting processes are substituted into the above fitting function to determine a, b, c, and K1 in the fitting function.

[0050] In this disclosure, K1 = 6.2 × 10 -3 Given the empirical coefficients a = 0.529, b = 1.445, and c = 0.873, it can be seen that the period of the cutting wire reciprocating motion (corresponding to empirical coefficient b) has the greatest impact on roughness, followed by the feed rate (corresponding to empirical coefficient c), and then the moving speed of the cutting wire reciprocating motion (corresponding to empirical coefficient a). Correspondingly, priorities are assigned to the moving speed, period, and feed rate of the cutting wire reciprocating motion, respectively, with higher priorities for greater impact. Therefore, when the roughness exceeds the set roughness threshold, the cutting process parameters are adjusted according to the above priorities to reduce the roughness of the bare wafer obtained from subsequent wire cutting processes within the target wavelength range.

[0051] The technical solution shown in Figure 3 above uses the roughness of the bare wafer obtained by wire cutting in the target wavelength range as an evaluation index. 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, 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. The roughness of the bare wafer obtained by subsequent wire cutting processes in the target wavelength range is reduced by adjusting the selected cutting process parameters.

[0052] For the technical solution shown in Figure 3, in some possible implementations, 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 from the historical wire cutting process. The specific fitting process may include:

[0053] An initial fitting function is formed by multiplying the power function of the reciprocating motion speed of the cutting line with the first empirical coefficient as the exponent, the power function of the period of the reciprocating motion of the cutting line with the second empirical coefficient as the exponent, and the power function of the feed rate with the third empirical coefficient as the exponent.

[0054] In the historical wire EDM process, historical cutting process parameters are collected, and the roughness of the bare wafers that have completed the historical wire EDM process is detected in the target wavelength range.

[0055] The historical dicing process parameters and the roughness of the bare wafers after completing the historical wire dicing 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.

[0056] For the above implementation method, exemplary specific implementation details may include:

[0057] First, a fitting function is derived by expressing the above three cutting process parameters as power functions, as shown below: PV=K1×Vs a ×Tr b ×Vf c

[0058] Where Vs represents the moving speed of the reciprocating motion of the cutting line, Tr represents the period of the reciprocating motion of the cutting line, Vf represents the feed speed, a, b, and c are empirical coefficients in the fitting function, which respectively represent the degree of influence of their corresponding cutting process parameters on the surface roughness, and K1 represents the fitting coefficient.

[0059] Next, the above fitting function is logarithmically transformed to obtain the fitting function after logarithmic transformation as shown in the following equation: log(PV)=log(K1)+alog(Vs)+blog(Tr)+clog(Vf).

[0060] Then, using the historical cutting process parameters collected in the historical wire cutting process and the roughness of the bare wafers that have completed the historical wire cutting process in the target wavelength range, the empirical coefficients and fitting coefficients of the above-mentioned logarithmically transformed fitting function are calculated by the least squares method, thereby obtaining a fitting function that can be applied to the technical solution shown in Figure 3.

[0061] Through the above process of obtaining the fitting function, we can finally obtain K1 = 6.2 × 10 -3 a = 0.529, b = 1.445, c = 0.873. Based on the above empirical coefficients, it can be concluded that the period of the reciprocating motion of the cutting line has the greatest impact on the surface roughness, followed by the feed rate, and then the moving speed of the reciprocating motion of the cutting line.

[0062] In this disclosure, some historical dicing process parameters and the corresponding roughness of bare wafers that have completed historical wire dicing processes in the range of 22 micrometer wavelength to 20 millimeter wavelength are shown in Table 1 below.

[0063] Table 1

[0064] In this disclosure, when the target wavelength range is 1.8 to 22 micrometers, based on the above-described fitting function acquisition process, K1 = 4.4 × 10⁻⁶ can be obtained. -3 a = 0.659, b = 1.217, c = 0.887. Based on the above empirical coefficients, it can also be seen that the period of the reciprocating motion of the cutting wire has the greatest impact on the roughness, followed by the feed rate, and then the moving speed of the reciprocating motion of the cutting wire. In this disclosure, some historical cutting process parameters and the corresponding roughness of bare wafers that have completed historical wire cutting processes in the wavelength range of 1.8 to 22 micrometers are shown in Table 2 below.

[0065] Table 2

[0066] In this disclosure, when the target wavelength range is 0 to 1.8 micrometers, based on the above-described fitting function acquisition process, K1 = 6.7 × 10⁻⁶ can be obtained. -3 a = 0.813, b = 1.105, c = 0.971. Based on the above empirical coefficients, it can also be seen that the cycle of the reciprocating motion of the cutting wire has the greatest impact on the roughness, followed by the feed rate, and then the moving speed of the reciprocating motion of the cutting wire. In this disclosure, some historical cutting process parameters and the corresponding roughness of bare wafers that have completed historical wire cutting processes in the wavelength range of 0 to 1.8 micrometers are shown in Table 3 below.

[0067] Table 3

[0068] The changes in roughness with variations in Vf, Vs, and Tr in Tables 1, 2, and 3 above also verify the conclusions regarding the influence of the cutting line reciprocating motion period, feed rate, and moving speed on roughness.

[0069] For the technical solution shown in Figure 3, in some possible implementations, as shown in Figure 4, the process of detecting the roughness of the bare wafer after the wire cutting process in the target wavelength range in step S301 may include steps S3011 to S3013.

[0070] In step S3011, 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.

[0071] Specifically, in this implementation, a single-point measurement scheme means that only one sampling point can be measured in a single 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 across the wafer surface. As this horizontal movement occurs, the height difference on the wafer surface causes the probe to undergo longitudinal displacement. 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.

[0072] In step S3012, based on the original 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.

[0073] In this implementation, after measuring each sampling point on the bare wafer surface using the aforementioned 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 the wave signals of different wavelengths superimposed to form the wave phenomenon can be used to represent the height difference within a region corresponding to the wavelength. For example, with a target wavelength range of 22 micrometers to 20 millimeters, the upper wavelength limit is 20 mm, and the lower wavelength limit is 22 μm. Similarly, with a target wavelength range of 0 to 1.8 micrometers, the upper wavelength limit is 1.8 μm, and the lower wavelength limit is 0. And again, with a target wavelength range of 1.8 to 22 micrometers, the upper wavelength limit is 22 μm, and the lower wavelength limit is 1.8 μm.

[0074] In some examples, in order to obtain the wave signal of each sampling point within the target wavelength range, in the specific implementation of step S3012, firstly, a low-pass filter function is used to filter out wave signals with wavelengths higher than the upper wavelength limit from the wave phenomenon, and then a high-pass filter function is used to filter out wave signals with wavelengths lower than the lower wavelength limit, finally obtaining the wave signal within the target wavelength range.

[0075] Specifically, taking the aforementioned filter as an example, and this circular filter is composed of two Gaussian filter functions. 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, taking the circular filter of the above example as an example, as shown in Figure 5, 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.

[0076] 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.

[0077] 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.

[0078] 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.

[0079] In step S3013, 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.

[0080] 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:

[0081] The bare wafer is divided into multiple analysis regions;

[0082] 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.

[0083] The mean range of amplitude differences of wave signals in all analysis regions within the target wavelength range is determined as the roughness index of the bare wafer within the target wavelength range.

[0084] For the example above, as shown in Figure 6, after the edge region is removed according to EE, the remaining region on the bare wafer surface is divided into square regions of a set size, such as 10mm×10mm. This results in a complete analysis region that can present a complete square and a non-complete analysis region that is at the edge of the remaining region after the edge region is removed according to Edge Exclusion (EE) and cannot present a complete square. These two analysis regions constitute the analysis region in the above implementation.

[0085] 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.

[0086] 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.

[0087] 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 in the target wavelength range of at least one of the following:

[0088] When the target wavelength range is 0 to 1.8 micrometers, the roughness is 0.01 to 1 nm;

[0089] When the target wavelength range is 1.8 to 22 micrometers, the roughness is 1 to 3 nm;

[0090] When the target wavelength range is 22 micrometers to 20 millimeters, the roughness is 3 to 30 nm.

[0091] Based on the same inventive concept as the aforementioned technical solution, referring to Figure 7, a wafer roughness improvement device 70 is shown. The device 70 includes: a detection section 701, a comparison section 702, and a process improvement section 703; wherein,

[0092] The detection section 701 is configured to detect the roughness of a bare wafer that has completed the wire cutting process within a target wavelength range.

[0093] The comparison section 702 is configured to compare the roughness with a set roughness threshold, and to trigger the process improvement section 703 when the roughness is greater than or equal to the set roughness threshold.

[0094] The process improvement section 703 is configured to select the cutting process parameters that need to be adjusted to reduce the roughness of the bare wafer obtained from subsequent wire dicing processes in the target wavelength range, based on 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.

[0095] In some examples, the plurality of cutting process parameters include: the moving speed of the cutting wire reciprocating motion, the cycle of the cutting wire reciprocating motion, and the feed rate;

[0096] Accordingly, the fitting function is represented by the product of power functions of the moving speed of the cutting line reciprocating motion, the period of the cutting line reciprocating motion, and the feed speed, respectively.

[0097] In some examples, referring to FIG8, the device 70 further includes a fitting portion 704, configured to:

[0098] An initial fitting function is formed by multiplying the power function of the reciprocating motion speed of the cutting line with the first empirical coefficient as the exponent, the power function of the period of the reciprocating motion of the cutting line with the second empirical coefficient as the exponent, and the power function of the feed rate with the third empirical coefficient as the exponent.

[0099] In the historical wire EDM process, historical cutting process parameters are collected, and the roughness of the bare wafers that have completed the historical wire EDM process is detected in the target wavelength range.

[0100] The historical dicing process parameters and the roughness of the bare wafers after completing the historical wire dicing 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.

[0101] In some examples, the fitting portion 704 is configured as follows:

[0102] The fitting function is then subjected to a logarithmic transformation to obtain the logarithmically transformed fitting function.

[0103] Using the historical dicing process parameters and the roughness of the bare wafer after the historical wire dicing 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.

[0104] In some examples, the detection section 701 is configured to:

[0105] 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;

[0106] 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;

[0107] 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.

[0108] In some examples, the filter is a circular filter and consists of a double Gaussian filter function;

[0109] 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.

[0110] In some examples, the detection section 701 is configured to:

[0111] The bare wafer is divided into multiple analysis regions;

[0112] 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.

[0113] The mean range of amplitude differences of wave signals in all analysis regions within the target wavelength range is determined as the roughness index of the bare wafer within the target wavelength range.

[0114] In some examples, when the target wavelength range is 0 to 1.8 micrometers, the roughness threshold is 1 nm;

[0115] When the target wavelength range is 1.8 to 22 micrometers, the roughness threshold is 3 nm;

[0116] When the target wavelength range is from 22 micrometers to 20 millimeters, the roughness threshold is 25 nm.

[0117] 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.

[0118] Please refer to Figure 9, which shows a structural block diagram of a computing device provided in an exemplary embodiment of this disclosure. In some examples, the computing device 90 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 90 has communication functions and can access wired or wireless networks. The computing device 90 can refer to one of a plurality of 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 90 can receive data based on the accessed wired or wireless network. It is understood that the computing device 90 undertakes the calculation and processing work of the technical solution of this disclosure, and this disclosure does not limit it in this respect.

[0119] As shown in Figure 9, the computing device of this disclosure may include one or more of the following components: processor 910 and memory 920.

[0120] Optionally, the processor 910 connects various parts within the computing device using various interfaces and lines, and performs various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 920, and by calling data stored in the memory 920. Optionally, the processor 910 can be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 910 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 for display on the touch screen; the NPU is used to implement Artificial Intelligence (AI) functions; and the baseband chip is used for wireless communication. It is understandable that the aforementioned baseband chip may not be integrated into the processor 910, but may be implemented using a separate chip.

[0121] The memory 920 may include random access memory (RAM) or read-only memory (ROM). Optionally, the memory 920 may include a non-transitory computer-readable storage medium. The memory 920 may be used to store instructions, programs, code, 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 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.

[0122] 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 (Wireless Fidelity) module, power supply, Bluetooth module, etc., which will not be described in detail here.

[0123] 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.

[0124] 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.

[0125] 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:

[0126] When the target wavelength range is 0 to 1.8 micrometers, the roughness is 0.01 to 1 nm;

[0127] When the target wavelength range is 1.8 to 22 micrometers, the roughness is 1 to 3 nm;

[0128] When the target wavelength range is 22 micrometers to 20 millimeters, the roughness is 3 to 30 nm.

[0129] 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.

[0130] It should be noted that the technical solutions described in this disclosure can be combined arbitrarily as long as they do not conflict.

[0131] 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 wafer roughness, the method comprising: The roughness of a bare wafer after wire cutting is measured within the target wavelength range. When the roughness is greater than or equal to a set roughness threshold, the cutting process parameter that needs to be adjusted is selected according to the priority of the cutting process parameter indicated by the fitting function between multiple cutting process parameters and the roughness in the target wavelength range.

2. The method according to claim 1, wherein, The multiple cutting process parameters include: the moving speed of the cutting line reciprocating motion, the cycle of the cutting line reciprocating motion, and the feed speed; The fitting function is represented by the product of power functions of the moving speed of the cutting line reciprocating motion, the period of the cutting line reciprocating motion, and the feed speed, respectively.

3. The method according to claim 1, further comprising: An initial fitting function is formed by multiplying the power function of the reciprocating motion speed of the cutting line with the first empirical coefficient as the exponent, the power function of the period of the reciprocating motion of the cutting line with the second empirical coefficient as the exponent, and the power function of the feed rate with the third empirical coefficient as the exponent. In the historical wire EDM process, historical cutting process parameters are collected, and the roughness of the bare wafers that have completed the historical wire EDM process is detected in the target wavelength range. The historical dicing process parameters and the roughness of the bare wafers after completing the historical wire dicing 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, wherein, The step of substituting the historical dicing process parameters and the roughness of the bare wafer after completing 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 includes: The fitting function is then subjected to a logarithmic transformation to obtain the logarithmically transformed fitting function. Using the historical dicing process parameters and the roughness of the bare wafer after the historical wire dicing 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, wherein, The roughness of the bare wafer after wire cutting is measured within the target wavelength range, including: 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; 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; 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.

6. The method according to claim 5, wherein, The filter is a circular filter and consists of a double Gaussian filter function; 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.

7. The method according to claim 5, wherein, Determining the roughness of the bare wafer in the target wavelength range based on the amplitude statistics of the wave signal at all sampling points in the target wavelength range includes: The bare wafer is divided into multiple analysis regions; 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. The mean range of amplitude differences of wave signals in all analysis regions within the target wavelength range is determined as the roughness index of the bare wafer within the target wavelength range.

8. The method according to any one of claims 1 to 7, wherein, 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 range is from 22 micrometers to 20 millimeters, the roughness threshold is 25 nm.

9. A wafer roughness improvement apparatus, the apparatus comprising: The inspection section, the comparison section, and the process improvement section; among them, The detection section is configured to detect the roughness of a bare wafer that has undergone wire cutting in the target wavelength range. The comparison section is configured to compare the roughness with a set roughness threshold, and to trigger the process improvement section when the roughness is greater than or equal to the set roughness threshold. The process improvement section is configured to select the cutting process parameters that need to be adjusted to reduce the roughness of the bare wafer obtained from subsequent wire cutting processes in the target wavelength range, based on 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, the computing device comprising: Processor and memory; The processor is configured to execute instructions stored in the memory to implement the wafer roughness improvement method as described in any one of claims 1 to 8.

11. A computer-readable storage medium storing at least one instruction for execution by a processor to implement the method for improving wafer roughness as described in any one of claims 1 to 8.

12. A wafer obtained by a wire dicing process improved by the wafer roughness improvement method according to any one of claims 1 to 8, and having a roughness in a target wavelength range of at least one of the following: When the target wavelength range is 0 to 1.8 micrometers, the roughness is 0.01 to 1 nm; When the target wavelength range is 1.8 to 22 micrometers, the roughness is 1 to 3 nm; When the target wavelength range is 22 micrometers to 20 millimeters, the roughness is 3 to 30 nm.

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