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

Abstract

Provided in the present disclosure are a wafer and a roughness measurement method and apparatus therefor, and a device and a medium. The measurement method comprises: for each sampling point on the surface of a wafer to be measured, acquiring, by means of a single-point measurement scheme, original measurement data at each sampling point that is about the height of the surface of said wafer; on the basis of original measurement data of all sampling points on the surface of said wafer, for each sampling point, acquiring, by means of a filter corresponding to a target wavelength range, a wave signal of each sampling point in the target wavelength range; and on the basis of amplitude statistical values of wave signals of all sampling points in the target wavelength range, determining the roughness of said wafer in the target wavelength range.

Description

Wafer and roughness measurement method, device, equipment and medium thereof

[0001] Cross-reference to Related Applications

[0002] This application claims priority to Chinese Patent Application No. 202411101473.0, filed on August 12, 2024, the contents of which are incorporated herein by reference in its entirety. TECHNICAL FIELD

[0003] The present disclosure relates to the technical field of semiconductor manufacturing, and in particular to a wafer and a roughness measurement method, device, equipment and medium thereof. BACKGROUND

[0004] As a substrate required by a chip manufacturing process, the roughness (uniformity) of the surface morphology of a silicon wafer is related to the uniformity of the trench width of a semiconductor device prepared in the chip manufacturing process and the stability of a multi-layer stacked structure.

[0005] As the line width of a semiconductor device is continuously reduced and the device structure is continuously developed to a multi-layer stacked structure, the requirement for the roughness of the surface morphology of a silicon wafer is becoming increasingly strict, such as strict requirements for the roughness of a more microscopic area. Therefore, a roughness measurement method needs to be proposed based on more strict roughness requirements. SUMMARY

[0006] The present disclosure provides a wafer and a roughness measurement method, device, equipment and medium thereof; a roughness evaluation scheme is provided for more strict roughness requirements, which can more accurately evaluate the roughness of a wafer.

[0007] In a first aspect, the present disclosure provides a wafer roughness measurement method, the measurement method comprising:

[0008] For each sampling point of the surface of the wafer to be measured, the original measurement data of each sampling point about the wafer surface height is obtained through a single-point measurement scheme;

[0009] Based on the original measurement data of all sampling points of the surface of the wafer to be measured, the wave signal of each sampling point in the target wavelength range is obtained for each sampling point through a filter corresponding to the target wavelength range;

[0010] The roughness of the wafer to be measured in the target wavelength range is determined based on the amplitude statistical value of the wave signal of all sampling points in the target wavelength range.

[0011] In a second aspect, the present disclosure provides a wafer roughness measurement device, the measurement device comprising: an acquisition unit, a filtering unit and a determination unit; wherein,

[0012] The acquisition unit is configured to acquire, for each sampling point of the surface of the wafer to be measured, original measurement data about the height of the wafer surface at each sampling point obtained by a single-point measurement scheme.

[0013] The filtering unit is configured to acquire, for each sampling point, an amplitude statistical value of a wave signal of each sampling point in the target wavelength range by a filter corresponding to the target wavelength range, based on the original measurement data of all sampling points of the surface of the wafer to be measured.

[0014] The determination unit is configured to determine the roughness of the wafer to be measured in the target wavelength range according to the amplitude statistical values of the wave signals of all sampling points in the target wavelength range.

[0015] In a third aspect, the present disclosure provides a computing device, comprising a processor and a memory; the processor is configured to execute instructions stored in the memory to implement the wafer roughness measurement method according to the first aspect.

[0016] In a fourth aspect, the present disclosure provides a computer-readable storage medium, which stores at least one instruction for being executed by a processor to implement the wafer roughness measurement method according to the first aspect.

[0017] In a fifth aspect, the present disclosure provides a wafer, which, after obtaining original measurement data of the surface height by a single-point measurement scheme, acquires a wave signal of each sampling point in a target wavelength range by a filter corresponding to the target wavelength range, and determines that the roughness of the wafer to be measured in the target wavelength range is within a set index threshold range based on amplitude statistical values of the wave signals of all sampling points in the target wavelength range.

[0018] The present disclosure provides a wafer and a measurement method, device, equipment and medium for the roughness thereof; the original measurement data of a wafer to be measured is filtered by a filter corresponding to a target wavelength range, and the roughness of the wafer to be measured is represented according to amplitude statistical values of wave signals in the target wavelength range after filtering. Since the target wavelength range corresponds to the size of a small detection area, compared with related solutions, the technical solution of the present disclosure can evaluate or measure the roughness of a smaller area, and can more accurately evaluate the roughness of the wafer. BRIEF DESCRIPTION OF DRAWINGS

[0019] FIG. 1 is a flowchart of a wafer roughness measurement method according to the present disclosure;

[0020] FIG. 2 is a schematic diagram of a filter sliding on a wafer surface according to the present disclosure;

[0021] FIG. 3 is a schematic diagram of a circular Gaussian filter provided by the present disclosure;

[0022] FIG. 4 is a schematic diagram of a divided analysis region provided by the present disclosure;

[0023] FIG. 5 is a schematic diagram of a wafer roughness measurement device provided by the present disclosure;

[0024] FIG. 6 is a schematic diagram of a computing device provided by the present disclosure. DETAILED DESCRIPTION

[0025] The technical solutions in the present disclosure will be described in detail below with reference to the accompanying drawings in the present disclosure.

[0026] For the uniformity of the wafer surface topography, the height difference between each point on the wafer surface generally reflects the fluctuation of the height values of each point on the wafer surface. Based on this understanding, the present disclosure regards this fluctuation phenomenon as being caused by the superposition of wave signals of different wavelengths from the perspective of waves. The smaller the wavelength of the wave signal, the smaller the size of the region representing the fluctuation of the height values; the larger the wavelength of the wave signal, the larger the size of the region representing the fluctuation of the height values.

[0027] Based on the above description, in order to evaluate or measure the roughness of a smaller region, the present disclosure filters the above fluctuation phenomenon based on the size of the region for which the roughness is desired to be measured, thereby obtaining the wave signal data within the wavelength range corresponding to the region for which the roughness is desired to be measured, and calculating the roughness of the wafer under the size standard of the region according to the wave signal data.

[0028] Based on this, referring to FIG. 1, a wafer roughness measurement method provided by the present disclosure is shown, which includes steps S101 to S103.

[0029] In step S101, for each sampling point on the surface of the wafer to be measured, the original measurement data of the height of the wafer surface at each sampling point is obtained through a single-point measurement scheme.

[0030] It should be noted that the original measurement data is the data basis for filtering and wave signal amplitude statistics in subsequent steps S102 and S103. In the present disclosure, the single-point measurement scheme is used to measure the original data of the surface height of the sampling points on the surface of the wafer to be measured to obtain the original measurement data.

[0031] A single-point measurement scheme is a scheme in which only one sampling point can be measured in one measurement process. In some examples, a contact measurement scheme can be used, such as using a probe to contact a wafer surface to be measured and move horizontally on the wafer surface. As the probe moves horizontally, the height difference of the wafer surface to be measured causes the probe to move vertically, and the vertical displacement is sensed by a displacement sensor and converted into height data of the wafer surface to be measured, i.e., raw measurement data about the height of the wafer surface. In other examples, a non-contact measurement scheme such as a capacitance measurement, a laser focus measurement, etc. can also be used.

[0032] After each sampling point of the wafer surface to be measured is measured by the single-point measurement scheme described above, the raw measurement data of all sampling points can reflect the height difference between each sampling point, and the entire wafer surface can be regarded as a three-dimensional fluctuation phenomenon.

[0033] In step S102, based on the raw measurement data of all sampling points of the wafer surface to be measured, a wave signal of each sampling point in a target wavelength range is obtained for each sampling point by using a filter corresponding to the target wavelength range.

[0034] In the present disclosure, the raw measurement data of all sampling points is regarded as a three-dimensional fluctuation phenomenon, and the amplitudes of wave signals of different wavelengths superimposed to form the fluctuation phenomenon can be used to represent the height difference in a region corresponding to the wavelength. Based on this, the present disclosure uses a filter to filter out a wave signal of a target wavelength corresponding to a target size from the fluctuation phenomenon.

[0035] In some examples, the target wavelength range includes at least one of a 0-1.8 micron wavelength range, a 1.8-22 micron wavelength range, and a 22 micron wavelength to 20 millimeter wavelength range, and for any of the above target wavelength ranges, it includes an upper wavelength limit and a lower wavelength limit. Specifically, first, a low-pass filter function is used to filter out wave signals with a wavelength higher than the upper wavelength limit from the fluctuation phenomenon, and then a high-pass filter function is used to filter out wave signals with a wavelength lower than the lower wavelength limit, and finally the wave signals in the target wavelength range are obtained.

[0036] For the above examples, for example, the filter is a circular filter, and the circular filter is composed of a double Gaussian filter function, where a first Gaussian filter function G LP1 may be a Gaussian low-pass filter function with a low-pass filter range covering the upper limit of the target wavelength range; and a second Gaussian filter function G LP2 may be a Gaussian low-pass filter function with a low-pass filter range covering the lower limit of the target wavelength range, and a high-pass filter function is obtained by (1-G LP2 ). Based on the first Gaussian filter function and the second Gaussian filter function, the circular filter GDHP may be expressed as G DHP = G LP1 (1 - G LP2 ).

[0037] In the present disclosure, taking the circular filter in the above example as an example, as shown in FIG. 2, the circular filter indicated by the arrow can be slid on the surface of the wafer to be measured according to the sampling points, and the wave signal of each sampling point in the target wavelength range can be obtained by filtering the original measurement data of the sampling point at the center of the circular filter and other sampling points covered by the action range of the circular filter through the circular filter.

[0038] In step S103, the roughness of the wafer to be measured in the target wavelength range is determined based on the amplitude statistical value of the wave signal of all sampling points in the target wavelength range.

[0039] In the present disclosure, specifically, after obtaining the wave signal of all sampling points in the target wavelength range, the wafer to be measured can be divided into multiple analysis regions. For each analysis region, the amplitudes of the wave signals of all sampling points in the target wavelength range are counted to obtain the amplitude statistical value of the wave signal of each analysis region in the target wavelength range, such as the mean value, the extreme value, the extreme value under a certain size area ratio, the range, the variance, the standard deviation, the median, the mode, etc.

[0040] Taking the range as an example in the present disclosure, after obtaining the range of the amplitude values of the wave signals of all analysis regions in the target wavelength range, the mean value of the range of the amplitude values of all analysis regions is calculated and taken as the index value of the roughness of the wafer to be measured in the target wavelength range.

[0041] After taking the mean value of the range of the amplitude values of all analysis regions as the index value of the roughness of the wafer to be measured in the target wavelength range, the roughness of the wafer to be measured can be determined based on the judgment result of whether the index value is in the index threshold range corresponding to the target wavelength range. Specifically, when the target wavelength range is 0 to 1.8 microns, the index threshold range is 0.01 to 1 nm. When the target wavelength range is 1.8 to 22 microns, the index threshold range is 1 to 3 nm. When the target wavelength range is 22 microns to 20 millimeters, the index threshold range is 3 to 30 nm.

[0042] The technical solution shown in the foregoing figure 1 filters the original measurement data of the wafer to be measured by using the filter corresponding to the target wavelength range, and represents the roughness of the wafer to be measured according to the amplitude statistical value of the wave signal in the target wavelength range after filtering. Since the target wavelength range corresponds to the size of a small detection area, compared with related solutions, the technical solution of the present disclosure can evaluate or measure the roughness of a smaller area and can more accurately evaluate the roughness of the wafer.

[0043] For the technical solution shown in the foregoing figure 1, it needs to be explained that when the number of sampling points is large, the single-point measurement solution takes a long time to complete the measurement process of a wafer, which may cause low production capacity in actual production process. When the number of sampling points is small, it is difficult to accurately evaluate the roughness of the wafer due to too small data volume. Based on this, the present disclosure adaptively adjusts the sampling strategy according to the target wavelength range, not only improves the measurement capacity of the present solution in actual production process, but also meets the evaluation accuracy of the wafer roughness. In some possible implementation manners, the method further includes: determining the number of sampling points according to the upper limit of the target wavelength range and the position where the surface morphology is poor under the current process condition.

[0044] For the foregoing implementation manner, in some examples, the determination of the number of sampling points according to the upper limit of the target wavelength range and the position where the surface morphology is poor under the current process condition includes:

[0045] determining the number of diametric directions for sampling on the wafer to be measured according to the position where the surface morphology is poor under the current process condition and the periodic distance of the steel wire twisted after the wire cutting process of the wire cutting process;

[0046] taking a value smaller than the upper limit of the target wavelength range as the sampling interval in each diametric direction;

[0047] determining the number of sampling points according to the number of diametric directions for sampling on the wafer to be measured and the sampling interval in each diametric direction.

[0048] For the above implementation and its examples, it needs to be explained that the wafer is usually sampled based on polar coordinates to obtain sampling points. The sampling strategy includes the number n of sampling directions through the diameter of the wafer surface and the sampling interval m in each sampling direction. In related solutions, sampling is usually performed according to a fixed number of sampling directions and a sampling interval. This fixed sampling solution is not flexible enough, and for wafers that do not require high-density sampling requirements, it will cause a waste of production capacity. The technical solution of the foregoing FIG. 1 can be seen: the roughness index is obtained by calculating and processing the wave signals in the target wavelength range, therefore, the present disclosure adaptively determines the sampling strategy for the target wavelength range, thereby avoiding the phenomenon of waste of production capacity.

[0049] In the specific implementation process, taking the target wavelength range of 22 microns to 20 millimeters as an example, the upper limit of the theoretical value of the sampling interval should be no more than 20 millimeters, otherwise the information of the corresponding waveband cannot be completely collected. Based on this, the present disclosure determines the upper limit value of the sampling interval according to the upper limit of the wavelength of the target wavelength range, such as m < 20 millimeters.

[0050] In addition, the distance L between two sampling points (adjacent sampling points) with the same distance from the center of the wafer but in adjacent sampling directions can be calculated by the arc length formula L = r x θ, where r represents the distance from the center of the wafer, i.e. the radius of the position of the sampling point, and θ represents the included angle between the adjacent sampling directions. It can be seen from the arc length formula that as the distance of the sampling point from the center of the wafer increases, the distance between the two sampling points is increasing, which indicates that this polar coordinate-based sampling solution has a natural defect, i.e. the sampling density at the periphery of the wafer is lower than that at the inner periphery, thereby causing the possibility of loss of surface height information at the periphery of the wafer. The statistical parameters of the wafer surface height are anisotropic, i.e. the surface height information weight of the inner periphery of the wafer is higher. On the other hand, because the surface height is not a data that will have a sudden change in a short distance under normal manufacturing process of the wafer, it indicates that even under relatively sparse sampling conditions, the true surface height information can still be simulated through interpolation between numerical values. Under the above two effects that antagonize each other, the present disclosure sets the number n of sampling directions as follows: n = Rπ / d

[0051] Where R is the characteristic radius, representing the position where the surface morphology is poor under the current process condition, and d is the periodic distance of the steel wire after the online cutting process.

[0052] For the production capacity of the above-mentioned embodiment of the implementation process in the actual production process, the present disclosure takes the sampling strategy of n=144 and m=0.2 mm as a comparative example for comparison. The embodiment and the comparative example are respectively sampled on one lot (i.e. 25 pieces) of wafers, and both are detected after sampling according to the scheme shown in the foregoing FIG. 1 to detect the roughness index of the target wavelength range of 22 microns to 20 millimeters. For the embodiment, different n is set by setting different R and d. Finally, the technical effect of the embodiment is represented according to the Pearson correlation coefficient P of the roughness index of the embodiment and the comparative example. The detailed comparison results are shown in Table 1.

[0053] Table 1

[0054] In the above Table 1, No. 1 represents the sampling strategy of the comparative example, i.e. n=144 and m=0.2 mm, the Pearson correlation coefficient is set to 1, and the relative capacity is also set to 1.

[0055] From No. 2 to No. 7, n is determined according to different R and d, and m is determined in the range less than 20 mm. It can be seen that the Pearson correlation coefficients of No. 2, No. 3 and No. 5 exceed 0.7, and even reach 0.87. Moreover, since n is reduced and m is increased relative to the comparative example, the number of sampling points is also reduced, and the relative capacity is also correspondingly improved. As can be seen from Table 1, the sampling strategy described in the foregoing implementation and examples can not only achieve similar roughness evaluation accuracy, but also significantly improve the production capacity compared with the comparative example.

[0056] Based on the filter shown in FIG. 1, in some possible implementation manners, for all sampling points, the radius of the action range of the filter is determined by the upper limit of the target wavelength range.

[0057] For the above-mentioned implementation, specifically, the target wavelength range is set to 22 microns to 20 millimeters, and the radius of the action range of the circular filter is only related to the upper limit w of the target wavelength range, i.e. 20 millimeters. For example, for each of all sampling points on the wafer surface, the radius of the action range of the circular filter when filtering can be set to 0.5*w. In the present disclosure, the manner of setting the radius of the action range of the filter in the present implementation can be referred to as constant filter radius.

[0058] However, it should be noted that the closer the wafer surface edge is, the more dramatic the topography changes. In order to accurately capture the dramatic topography changes, when the sampling point is close to the wafer surface edge, the effective range of the corresponding circular filter should be smaller than that of the sampling point close to the wafer surface center, that is, as the sampling point gradually moves away from the wafer center, the effective range of the corresponding filter should decrease, or be called shrinkage.

[0059] Based on this, in some implementations, when the distance between the sampling point and the center of the wafer to be measured is less than or equal to the critical distance, the radius of the effective range of the filter is the first radius; when the distance between the sampling point and the center of the wafer to be measured is greater than the critical distance, the radius of the effective range of the filter 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.

[0060] In the above implementation, the critical distance is used to determine whether the sampling point is close to the wafer surface center or close to the wafer surface edge. Compared with being close to the wafer surface center, when the sampling point is close to the wafer surface edge, the effective range of the filter should be shrunk. In some examples, when the sampling point is near the edge of the wafer, the effective range of the filter will exceed the edge range of the wafer surface, at this time, during the filtering process, the part of the effective range of the filter that exceeds the edge range of the wafer surface can be supplemented with interpolation padding method, or can not be filled. The interpolation padding method can be linear extrapolation, symmetric interpolation, cubic spline interpolation, etc., which will not be described in detail in the present disclosure.

[0061] In some examples, the shrinkage can be stepwise, that is, when the distance between the sampling point and the center of the wafer to be measured is greater than the critical distance, the second radius is fixedly set to a value smaller than the first radius; it can also be gradual, that is, the second radius gradually decreases as the sampling point moves away from the center of the wafer to be measured. Specifically, when the distance between the sampling point and the center of the wafer to be measured is greater than the critical distance, the second radius is a fixed value smaller than the first radius, or the second radius is negatively related to the distance between the sampling point and the center of the wafer to be measured.

[0062] For the above-mentioned implementation and examples of constant filter radius and shrinkage of the effective range, the present disclosure is described in detail in combination with an embodiment. In the embodiment, a wafer double-layer substrate containing an oxide layer is set and subjected to one chemical mechanical polishing (CMP) process, and the thickness removal amount of the polishing process is x, which is less than the thickness of the oxide layer. The thickness difference ΔT1 in the oxide layer is measured before the CMP process, and the thickness difference ΔT2 in the oxide layer is measured after the CMP process. The value represents the film thickness non-uniformity in the target wavelength range of 22 microns to 20 millimeters, and therefore, the calculation method shown in the following formula is used to make the roughness index in the target wavelength range of 22 microns to 20 millimeters and ΔT have a better linearity: ΔT = ΔT1 - ΔT2.

[0063] For the wafer of the embodiment, it is a 12-inch (300mm) wafer, the radius R = 150mm, the edge removal amount (EE, exclude edge) is 3mm when measuring, the filter cutoff wavelength w is 20mm when the target wavelength range is 22 microns to 20 millimeters, and therefore, the critical distance a = R - EE - 0.5*w is calculated according to the following formula. The number of sampling directions and the sampling pitch are determined as n and m based on the adaptive sampling strategy proposed in the foregoing embodiments of the present disclosure, and the filter shape is circular, that is, the effective range of the filter is circular, as shown in FIG. 3, in which the X and Y axes represent the positions covered by the effective range, and the Z axis represents the weight value at the corresponding position. When the sampling point is near the edge of the wafer and the effective range of the filter exceeds the edge range of the wafer surface, the interpolation mode of the exceeding part is symmetrical interpolation.

[0064] For the radius of the effective range of the filter, the constant radius filter, the step radius filter and the gradual radius filter are taken as examples, and the settings are shown in Table 2.

[0065] Table 2

[0066] Based on the above-mentioned three kinds of effective range filters, taking 10 wafers as examples, the roughness index in the target wavelength range of 22 microns to 20 millimeters and the results of ΔT are shown in Table 3.

[0067] Table 3

[0068] According to the above-mentioned 10 wafers, the correlation coefficients of the roughness index and ΔT obtained by filtering based on the above-mentioned three different effective range filters are shown in Table 4.

[0069] Table 4

[0070] It can be seen from the results in Table 4 that the roughness based on the step radius filter has the highest matching degree with the actual result AT, and the roughness based on the gradual radius filter has a matching degree with AT which is lower than that of the step radius filter but still has a correlation of more than 80%, and can also be applied to actual production processes.

[0071] Based on the foregoing implementation and examples thereof, after obtaining the wave signals of all sampling points in the target wavelength range, the roughness of the wafer under test in the target wavelength range can be determined based on the wave signals. In some implementations, the determination of the roughness of the wafer under test in the target wavelength range based on the amplitude statistical value of the wave signals of all sampling points in the target wavelength range comprises:

[0072] The wafer under test is divided into a plurality of analysis regions;

[0073] The amplitude statistical value of the wave signals of each analysis region in the target wavelength range is calculated according to the amplitude values of the wave signals of the sampling points in each analysis region in the target wavelength range;

[0074] The roughness index of the wafer under test in the target wavelength range is calculated according to the amplitude statistical values of the wave signals of all analysis regions in the target wavelength range.

[0075] Specifically, as shown in FIG. 4, after the wafer surface is removed according to the EE, the remaining region is divided into a square region with a set size, for example, 10mm*10mm, so that complete analysis regions that can present a complete square and incomplete analysis regions that are on the edge of the remaining region after the EE removal and cannot present a complete square are obtained, and the two analysis regions constitute the analysis regions in the foregoing implementation.

[0076] It should be noted that the wave signals of all sampling points of the wafer surface in the target wavelength range include all information that can characterize the surface morphology (i.e., roughness) of the wafer surface in the target wavelength range corresponding to the size of the region, which can be characterized by the statistical value of the amplitude, such as the mean value, extreme value, extreme value under a set size area ratio, range, variance, standard deviation, median, mode, etc. mentioned in the foregoing technical solutions.

[0077] In the present disclosure, taking the range as an example, the amplitude statistical value of the wave signals of each analysis region in the target wavelength range is the range of the amplitude values of the wave signals of the sampling points and the interpolation points in each analysis region in the target wavelength range; accordingly, the roughness index of the wafer under test in the target wavelength range is the mean value of the range of the amplitude values of the wave signals of all analysis regions in the target wavelength range.

[0078] Based on the same inventive concept of the foregoing technical solutions, referring to FIG. 5, a wafer roughness measurement device 50 is provided, which comprises an acquisition unit 501, a filtering unit 502, and a determination unit 503.

[0079] The acquisition unit 501 is configured to acquire, for each sampling point on the surface of the wafer to be measured, original measurement data about the wafer surface height at each sampling point obtained by a single-point measurement scheme.

[0080] The filtering unit 502 is configured to acquire, for each sampling point, an amplitude statistical value of a wave signal in a target wavelength range for each sampling point by a filter corresponding to the target wavelength range based on the original measurement data of all sampling points on the surface of the wafer to be measured.

[0081] The determination unit 503 is configured to determine the roughness of the wafer to be measured in the target wavelength range according to the amplitude statistical values of the wave signals in the target wavelength range of all sampling points.

[0082] In some examples, the target wavelength range includes at least one of a 0-1.8-micron wavelength range, a 1.8-22-micron wavelength range, and a 22-micron wavelength to 20-millimeter wavelength range.

[0083] In some examples, the filter is a circular filter and is composed of a double-Gaussian filter function; the radius of the action range of the filter is determined by the distance between the sampling point and the center of the wafer to be measured.

[0084] In some examples, when the distance between the sampling point and the center of the wafer to be measured is less than or equal to a critical distance, the radius of the action range of the filter is a first radius; when the distance between the sampling point and the center of the wafer to be measured is greater than the critical distance, the radius of the action range of the filter is a second radius; wherein the first radius and the second radius are both determined by the upper limit of the target wavelength range, and the first radius is greater than the second radius.

[0085] In some examples, when the distance between the sampling point and the center of the wafer to be measured is greater than the critical distance, the second radius is a fixed numerical value smaller than the first radius, or the second radius is in a negative correlation with the distance between the sampling point and the center of the wafer to be measured.

[0086] In some examples, the acquisition unit 501 is further configured to:

[0087] According to the upper limit of the target wavelength range and the position where the high-frequency surface morphology is poor under the current process condition, the number of sampling points is determined.

[0088] In some examples, the acquisition unit 501 is configured to:

[0089] determine the number of sampling diametric directions on the wafer under test according to the positions with poor surface morphology under high frequency under the current process condition and the periodic distance of the steel wire twisted after the wire cutting process;

[0090] take a value less than the upper limit of the target wavelength range as the sampling interval in each diametric direction;

[0091] determine the number of sampling points according to the number of sampling diametric directions on the wafer under test and the sampling interval in each diametric direction.

[0092] In some examples, the determining unit 503 is configured to:

[0093] divide the wafer under test into a plurality of analysis regions;

[0094] calculate the amplitude statistical value of the wave signal in the target wavelength range of each analysis region according to the amplitude values of the wave signal in the target wavelength range of the sampling points in each analysis region;

[0095] calculate the roughness index of the wafer under test in the target wavelength range according to the amplitude statistical values of the wave signal in the target wavelength range of all analysis regions.

[0096] In some examples, 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 the interpolation points in each analysis region; accordingly, the roughness index of the wafer under test in the target wavelength range is the average of the range of the amplitude statistical values of the wave signal in the target wavelength range of all analysis regions.

[0097] Referring to FIG. 6, a structural block diagram of a computing device provided by an example embodiment of the present disclosure is shown. In some examples, the computing device 60 can be at least one of a smartphone, a smart watch, a desktop computer, a laptop computer, a virtual reality terminal, an augmented reality terminal, a wireless terminal, and a laptop computer. The computing device 60 has a communication function and can access a wired network or a wireless network. The computing device 60 can be referred to as one of a plurality of terminals, and a person skilled in the art can know that the number of terminals can be more or less. In some examples, the computing device 60 can receive data based on the accessed wired network or wireless network. It can be understood that the computing device 60 undertakes the calculation and processing work of the technical solutions of the present disclosure, which are not limited by the present disclosure.

[0098] As shown in FIG. 6, the computing device in the present disclosure can include one or more of the following components: a processor 610 and a memory 620.

[0099] Optionally, the processor 610 utilizes various interfaces and lines to connect various parts within the entire computing device, to perform various functions of the computing device and process data by running or executing instructions, programs, code sets or instruction sets stored in the memory 620, and calling data stored in the memory 620. Optionally, the processor 610 can be implemented in at least one of a hardware form of a digital signal processing (DSP), a field-programmable gate array (FPGA), a programmable logic array (PLA). The processor 610 can be integrated with a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), a neural-network processing unit (NPU), and a baseband chip. Among them, the CPU is mainly used to process operating systems, user interfaces, and application programs; the GPU is used to render and draw the content to be displayed on the touch display screen; the NPU is used to implement artificial intelligence (AI) functions; and the baseband chip is used to process wireless communication. It can be understood that the above baseband chip can also not be integrated into the processor 610, but be implemented by a separate chip.

[0100] The memory 620 can include a random access memory (RAM) and can also include a read-only memory (ROM). Optionally, the memory 620 includes a non-transitory computer-readable storage medium. The memory 620 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 620 can include a program storage area and a data storage area, wherein the program storage area can store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above various method embodiments, etc.; and the data storage area can store data created according to the use of the computing device, etc.

[0101] In addition, those skilled in the art can understand that the structure of the computing device shown in the above figure does not constitute a limitation on the computing device, and the computing device can include more or fewer components than the figure, or combine certain components, or different component arrangements. 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 wireless fidelity (WiFi) module, a power supply, a Bluetooth module, and the like. Components are not described here.

[0102] The present disclosure also provides a computer readable storage medium storing at least one instruction for being executed by a processor to implement the wafer roughness measurement method according to any of the above embodiments.

[0103] The present 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 the processor executes the computer instructions to cause the computing device to perform the wafer roughness measurement method according to any of the above embodiments.

[0104] The present disclosure also provides a wafer whose roughness index obtained by the wafer roughness measurement method according to any of the above embodiments is within a set index threshold range. It is determined that there is no metal aggregation defect.

[0105] Specifically, for the above wafer, after obtaining the original measurement data of the surface height by sampling through a single-point measurement scheme, a filter corresponding to a target wavelength range is used to obtain the wave signal of each sampling point in the target wavelength range, and based on the amplitude statistical value of the wave signal of all sampling points in the target wavelength range, it is determined that the roughness of the wafer to be measured in the target wavelength range is within a set index threshold range.

[0106] In some examples, when the target wavelength range is 0 to 1.8 microns, the index threshold range is 0.01 to 1 nm; when the target wavelength range is 1.8 to 22 microns, the index threshold range is 1 to 3 nm; and when the target wavelength range is 22 microns to 20 millimeters, the index threshold range is 3 to 30 nm.

[0107] Those skilled in the art should be aware that, in the above one or more examples, the functions described in the present disclosure can be implemented in hardware, software, firmware or any combination thereof. When implemented in software, the functions can be stored in a computer readable medium or transmitted as one or more instructions or code on a computer readable medium. The computer readable medium includes computer storage medium and communication medium, and the communication medium includes any medium that facilitates transfer of a computer program from one place to another.

[0108] It should be noted that the technical solutions described in the present disclosure can be combined arbitrarily without conflict.

[0109] The above is merely specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present disclosure, which should be covered within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

Claims

1. A wafer roughness measurement method, comprising: obtaining, for each sampling point on a surface of a wafer to be measured, original measurement data about wafer surface height at each sampling point by a single-point measurement scheme; obtaining, for each sampling point, a wave signal of each sampling point in a target wavelength range by a filter corresponding to the target wavelength range based on the original measurement data of all sampling points on the surface of the wafer to be measured; determining a roughness of the wafer to be measured in the target wavelength range based on amplitude statistical values of the wave signals of all sampling points in the target wavelength range.

2. The metrology method of claim 1, wherein, The target wavelength range includes at least one of a 0-1.8 micron wavelength range, a 1.8-22 micron wavelength range, and a 22 micron wavelength to 20 millimeter wavelength range.

3. The metrology method of claim 1, wherein, The filter is a circular filter and is composed of a double Gaussian filter function; a radius of an effective range of the filter is determined by a distance of the sampling point from a center of the wafer to be measured. 4.The measurement method of claim 3, wherein when the distance of the sampling point from the center of the wafer to be measured 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 of the sampling point from the center of the wafer to be measured is greater than the critical distance, the radius of the effective range of the filter is a second radius; wherein the first radius and the second radius are both determined by an upper limit of the target wavelength range, and the first radius is greater than the second radius.

5. The metrology method of claim 4, wherein, When the distance of the sampling point from the center of the wafer to be measured is greater than the critical distance, the second radius is a fixed value less than the first radius, or the second radius is in a negative correlation with the distance of the sampling point from the center of the wafer to be measured. 6.The measurement method of claim 1, further comprising: determining a number of sampling points according to an upper limit of a target wavelength range and positions where surface topography is poor under a current process condition.

7. The metrology method of claim 6, wherein, The determination of the number of sampling points according to the upper limit of the target wavelength range and the positions where surface topography is poor under the current process condition includes: determining a number of diametric directions for sampling on the wafer to be measured according to the positions where surface topography is poor under the current process condition and a period distance of a wire twisted after a wire cutting process in a wire cutting process; taking a value less than the upper limit of the target wavelength range as a sampling interval in each diametric direction; determining the number of sampling points according to the number of diametric directions for sampling on the wafer to be measured and the sampling interval in each diametric direction.

8. The method according to any one of claims 1 to 7, wherein, The determination of the roughness of the wafer to be measured in the target wavelength range based on the amplitude statistical values of the wave signals of all sampling points in the target wavelength range includes: dividing the wafer to be measured into a plurality of analysis regions; calculating an amplitude statistical value of a wave signal of each analysis region in the target wavelength range according to amplitude values of the wave signals of the sampling points in each analysis region in the target wavelength range; calculating a roughness index of the wafer to be measured in the target wavelength range according to the amplitude statistical values of the wave signals of all analysis regions in the target wavelength range.

9. The method of claim 8, wherein, The amplitude statistical value of the wave signal of each analysis region in the target wavelength range is a range of amplitude values of the wave signal of the sampling point and the interpolation point in each analysis region in the target wavelength range; Correspondingly, the roughness index of the wafer to be measured in the target wavelength range is the average of the range of amplitude values of the wave signal of all analysis regions in the target wavelength range.

10. A wafer roughness metrology device, the metrology device comprising: An acquisition unit, a filtering unit and a determination unit; wherein, The acquisition unit is configured to obtain, for each sampling point on the surface of the wafer to be measured, original measurement data about the wafer surface height at each sampling point obtained by a single-point measurement scheme; The filtering unit is configured to obtain, for each sampling point, an amplitude statistical value of the wave signal of each sampling point in the target wavelength range based on the original measurement data of all sampling points on the surface of the wafer to be measured, through a filter corresponding to the target wavelength range; The determination unit is configured to determine the roughness of the wafer to be measured in the target wavelength range according to the amplitude statistical values of the wave signals of all sampling points in the target wavelength range.

11. A computing device comprising: A processor and a memory; The processor is used to execute instructions stored in the memory to implement the wafer roughness measurement method according to any one of claims 1 to 9.

12. A computer readable storage medium, the computer readable storage medium stores at least one instruction, the at least one instruction is used to be executed by a processor to implement the wafer roughness measurement method according to any one of claims 1 to 9.

13. A wafer, after obtaining original measurement data of surface height by a single-point measurement scheme, using a filter corresponding to a target wavelength range to obtain a wave signal of each sampling point in the target wavelength range, and determining that the roughness of the wafer in the target wavelength range is within a set index threshold range based on the amplitude statistical values of the wave signals of all sampling points in the target wavelength range.

14. The wafer of claim 13, wherein, When the target wavelength range is 0 to 1.8 microns, the index threshold range is 0.01 to 1 nm; When the target wavelength range is 1.8 to 22 microns, the index threshold range is 1 to 3 nm; When the target wavelength range is 22 microns to 20 millimeters, the index threshold range is 3 to 30 nm.

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