Wafer scanning data acquisition method and verification method of semiconductor inspection system

Abstract

This invention provides a method for acquiring wafer scanning data and a verification method for a semiconductor inspection system. The wafer scanning data acquisition method includes: acquiring scanning simulation parameters and descriptive data of wafer scanning features; and generating wafer scanning data based on the scanning simulation parameters and the descriptive data of wafer scanning features. This invention uses scanning simulation parameters to simulate scanning the descriptive data describing wafer scanning features to obtain wafer scanning data, thereby eliminating the need for actual scanning equipment to scan a real wafer and reducing the cost of acquiring wafer scanning data.

Description

Technical Field

[0001] This invention relates to the field of semiconductor testing technology, and more specifically to a method for acquiring wafer scanning data and a method for verifying a semiconductor testing system. Background Technology

[0002] Semiconductor testing and measurement equipment requires a large amount of wafer scanning data in the early stages to verify the algorithm and system operation. Related technologies use wafer scanning equipment to scan wafers to obtain wafer scanning data. However, to obtain a large amount of wafer scanning data, the equipment needs to be started to scan a large number of wafers, which makes the wafer scanning data acquisition costly. Summary of the Invention

[0003] In view of this, the present invention aims to provide a wafer scanning data acquisition method and a semiconductor inspection system verification method to solve the problem of high cost of wafer scanning data acquisition in the prior art.

[0004] This invention provides a method for acquiring wafer scanning data, the method comprising:

[0005] Obtain description data of scanning simulation parameters and wafer scanning characteristics;

[0006] The wafer scan data is generated based on the scan simulation parameters and the descriptive data of the wafer scan features.

[0007] In one embodiment, the descriptive data of the wafer scanning features includes descriptive data of wafer defect features and descriptive data of wafer surface response features. The wafer scanning data is generated based on the scanning simulation parameters and the descriptive data of the wafer scanning features, including:

[0008] Based on the scanning simulation parameters and the descriptive data of the wafer surface response characteristics, wafer surface response data in the corresponding scanning data format is generated;

[0009] Based on the scanning simulation parameters and the description data of the wafer defect characteristics, wafer defect data corresponding to the scanning data format is generated;

[0010] The wafer scan data is generated based on the wafer surface response data corresponding to the scan data format and the wafer defect data.

[0011] In one embodiment, the descriptive data of the wafer surface response characteristics includes a simulation expression of the wafer surface response characteristics and variable value data of the parameter variables in the simulation expression. Generating wafer surface response data in a corresponding scan data format based on the scan simulation parameters and the descriptive data of the wafer surface response characteristics includes:

[0012] The simulation expression is solved using the variable value data to obtain the wafer surface response data corresponding to the first coordinate system;

[0013] Based on the scanning simulation parameters, the wafer surface response data corresponding to the first coordinate system is scanned and mapped to obtain wafer surface response data corresponding to the scanning data format.

[0014] In one embodiment, the simulation expression is a Fourier series expression.

[0015] In one embodiment, the descriptive data of the wafer defect features includes the positional distribution information of the wafer defects in a second coordinate system and the first defect signal value corresponding to the wafer defects. Generating wafer defect data corresponding to the scan data format based on the scan simulation parameters and the descriptive data of the wafer defect features includes:

[0016] Based on the scanning simulation parameters, the location distribution information of the wafer defects is scanned and mapped to obtain the wafer defect location corresponding to the scanning data format;

[0017] Based on the scanning simulation parameters, the first defect signal value corresponding to the wafer defect is processed to obtain the second defect signal value corresponding to the scanning data format of the wafer defect;

[0018] Based on the wafer defect location corresponding to the scan data format and the second defect signal value, wafer defect data corresponding to the scan data format is obtained.

[0019] In one embodiment, the method further includes:

[0020] Obtain the distribution data of system noise;

[0021] The wafer scan data is subjected to noise addition processing based on the system noise distribution data to obtain wafer scan data with added noise.

[0022] In one embodiment, acquiring the distribution data of system noise includes:

[0023] Obtain descriptive data of noise characteristics;

[0024] Based on the description data of the noise characteristics, the distribution data of the system noise is generated.

[0025] In one embodiment, the noise feature description data includes noise boundary values, a noise generation coefficient sequence, and the number of samples in the noise space. Generating the system noise distribution data based on the noise feature description data includes:

[0026] Based on each noise generation coefficient in the noise generation coefficient sequence and the number of samples in the noise space, the number of noises distributed within the noise interval corresponding to each noise generation coefficient is obtained.

[0027] The span of each noise interval is obtained based on the boundary value of the noise and the number of noise generation coefficients in the noise generation coefficient sequence.

[0028] Based on the boundary values ​​of the noise and the span of each noise interval, the range of each noise interval is obtained;

[0029] For any noise interval, generate noise within the interval corresponding to the amount of noise distributed within that noise interval.

[0030] Based on the noise generated in each noise interval, the distribution data of the system noise is obtained.

[0031] In one embodiment, the scan simulation parameters include a scan start point, a scan end point, and a scan motion equation. Generating the wafer scan data based on the scan simulation parameters and the descriptive data of the wafer scan features includes:

[0032] Using the scanning start point and the scanning end point as scanning position constraints, the wafer scanning feature description data is simulated and scanned using the scanning motion equation to obtain the wafer scanning data.

[0033] Another aspect of the present invention provides a verification method for a semiconductor testing system, the method comprising:

[0034] The semiconductor inspection system is verified based on wafer scan data, wherein the wafer scan data is acquired based on the wafer scan data acquisition method described in any one of the first aspects.

[0035] Compared with related technologies, the wafer scanning data acquisition method provided by the present invention has the following advantages:

[0036] The wafer scanning data acquisition method provided by this invention includes: acquiring scanning simulation parameters and descriptive data of wafer scanning features; and generating wafer scanning data based on the scanning simulation parameters and the descriptive data of wafer scanning features. This invention uses scanning simulation parameters to simulate scanning the descriptive data describing wafer scanning features to obtain wafer scanning data, thereby eliminating the need for a real scanning device to scan a real wafer and reducing the cost of acquiring wafer scanning data. Attached Figure Description

[0037] Figure 1The diagram shows a flowchart of a wafer scanning data acquisition method according to an embodiment of the present invention.

[0038] Figure 2 The diagram shown is a structural schematic of a descriptor provided in an embodiment of the present invention.

[0039] Figure 3 The diagram shown is a structural schematic of a description table provided in an embodiment of the present invention.

[0040] Figure 4 The diagram shows a flowchart of a verification method for a semiconductor testing system provided in an embodiment of the present invention.

[0041] Figure 5 The diagram shown is a block diagram of a wafer scanning data acquisition device according to an embodiment of the present invention.

[0042] Figure 6 The diagram shown is a block diagram of a verification device for a semiconductor testing system according to an embodiment of the present invention.

[0043] Figure 7 The diagram shown is a block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] In related technologies, obtaining a large amount of wafer scanning data requires continuous collection and accumulation during the wafer testing process, increasing the cost of wafer scanning data acquisition. Furthermore, because certain types of scanning data, such as various types of wafer defect data, occur with low frequency, obtaining a sufficient number of wafer defect data requires scanning a larger number of wafers, further increasing the cost of wafer scanning data acquisition.

[0046] In view of the above problems, this application aims to provide a wafer scanning data acquisition method and a semiconductor inspection system verification method. This method uses scanning simulation parameters to simulate scanning descriptive data describing wafer scanning characteristics to obtain wafer scanning data, thereby eliminating the need for actual scanning equipment to scan a real wafer and reducing the cost of acquiring wafer scanning data. Detailed descriptions are provided in the following embodiments.

[0047] Figure 1This is a flowchart of a wafer scan data acquisition method according to an embodiment of the present invention. The method can be executed by a computer device. Figure 1 As shown, the wafer scan data acquisition method may include:

[0048] S110. Obtain the scanning simulation parameters and the descriptive data of the wafer scanning characteristics.

[0049] Among them, the scanning simulation parameters refer to the parameters used to simulate the process of an optical inspection device scanning a wafer.

[0050] Here, wafer scan features refer to the feature data obtained by scanning a wafer using an optical inspection device. In this embodiment of the invention, the scan features existing in the wafer are simulated using descriptive data of wafer scan features.

[0051] In some implementations, computer devices can acquire scanning simulation parameters and wafer scanning feature description data through methods such as interface input, network reception, configuration file acquisition, database acquisition, and acquisition from other media.

[0052] S120. Generate wafer scan data based on the scan simulation parameters and the description data of the wafer scan characteristics.

[0053] In this embodiment of the invention, after obtaining the scanning simulation parameters and the descriptive data of the wafer scanning features, the scanning simulation parameters can be used to simulate a scan of the descriptive data describing the wafer scanning features to obtain wafer scanning data. This eliminates the need for a real scanning device to scan a real wafer, reducing the cost of acquiring wafer scanning data. Furthermore, since the descriptive data of the wafer scanning features can be freely constructed to simulate the scanning features present in the wafer as needed, even feature types with low actual occurrence frequency can have a high acquisition frequency, further reducing the cost of acquiring wafer scanning data.

[0054] In some implementations, the scan simulation parameters include a scan start point, a scan end point, and a scan motion equation. In this case, generating wafer scan data based on the scan simulation parameters and descriptive data of the wafer scan features may include the following steps:

[0055] Using the scanning start point and scanning end point as scanning position constraints, the wafer scanning feature description data is simulated using the scanning motion equation to obtain wafer scanning data.

[0056] In this embodiment of the invention, starting from the scanning start point, the description data of the wafer scanning features is continuously solved by the scanning motion equation, thereby realizing the simulated scanning process of the wafer, and thus obtaining the simulated scanning data of each sampling point in the wafer, until the scanning ends at the scanning endpoint, and the wafer scanning data is obtained.

[0057] In some implementations, the scanning simulation parameters may also include information such as the scanning mode, the intensity of the system laser, and the system gain, which are used to further configure the simulated scanning process.

[0058] In some implementations, the descriptive data for wafer scan features includes descriptive data for wafer defect features and descriptive data for wafer surface response features. The descriptive data for wafer defect features describes what type of defect exists at what location on the wafer. The descriptive data for wafer surface response features describes data from other parts of the wafer besides defects, which constitute the vast majority of the wafer scan data.

[0059] In some implementations, when the description data of wafer scanning features includes description data of wafer defect features and description data of wafer surface response features, generating wafer scanning data based on scanning simulation parameters and the description data of wafer scanning features may include the following steps:

[0060] Based on the scanning simulation parameters and the descriptive data of the wafer surface response characteristics, wafer surface response data in the corresponding scanning data format is generated; based on the scanning simulation parameters and the descriptive data of the wafer defect characteristics, wafer defect data in the corresponding scanning data format is generated; and based on the wafer surface response data and wafer defect data in the corresponding scanning data format, wafer scanning data is generated.

[0061] In this embodiment of the invention, by processing the descriptive data of wafer surface response features using scanning simulation parameters, a simulated scan of the wafer surface response features can be achieved, thereby generating wafer surface response data in a corresponding scan data format. Furthermore, by processing the descriptive data of wafer defect features using scanning simulation parameters, a simulated scan of wafer defect features can be achieved, thereby generating wafer defect data in a corresponding scan data format. Subsequently, wafer scan data can be further obtained from the wafer surface response data and wafer defect data in the corresponding scan data format obtained through simulated scanning.

[0062] In this embodiment of the invention, to simplify the construction process of the descriptive data for wafer scanning features, the descriptive data is typically constructed based on a wafer coordinate system or other coordinate systems. After the simulated scanning process, data in the corresponding scan data format can be obtained. For example, the data in the corresponding scan data format can be serialized binary data arranged in the scanning order.

[0063] In some implementations, after obtaining wafer surface response data and wafer defect data in the corresponding scanning data format, the wafer defect data can be traversed, and the corresponding positions in the wafer surface response data can be replaced with the wafer defect data to generate wafer scanning data.

[0064] In some implementations, the descriptive data of the wafer surface response characteristics includes a simulation expression of the wafer surface response characteristics and variable values ​​of the parameter variables in the simulation expression. In this case, generating wafer surface response data in a corresponding scan data format based on the scan simulation parameters and the descriptive data of the wafer surface response characteristics may include the following steps:

[0065] The simulation expression is solved using the variable value data to obtain the wafer surface response data corresponding to the first coordinate system; the wafer surface response data corresponding to the first coordinate system is scanned and mapped based on the scan simulation parameters to obtain the wafer surface response data in the corresponding scan data format.

[0066] In this embodiment of the invention, considering the very large amount of wafer surface response data, in order to simplify the construction difficulty of the descriptive data of wafer surface response features, simulation expressions and variable value data of parameter variables in the simulation expressions can be used to express the descriptive data of wafer surface response features. By configuring different variable value data for parameter variables, a large amount of descriptive data of wafer surface response features can be easily constructed.

[0067] After obtaining the simulation expression for the wafer surface response characteristics and the variable values ​​of the parameters in the simulation expression, the simulation expression can be solved using the variable values ​​to obtain the wafer surface response data corresponding to the first coordinate system. Furthermore, the wafer surface response data corresponding to the first coordinate system can be scanned and mapped using the simulation parameters to obtain the wafer surface response data in the corresponding scan data format. Here, the first coordinate system can be the wafer coordinate system or other coordinate systems.

[0068] Furthermore, considering the large amount of wafer surface response data but the low frequency of change between adjacent data, the wafer surface response data obtained by scanning the wafer using a wafer scanning device has a certain periodicity according to probability. Therefore, in some implementations, Fourier series expressions can be used to simulate the wafer surface response data obtained by scanning.

[0069] In some implementations, the simulation expression for the wafer surface response characteristics can be expressed using the following Fourier series expression:

[0070]

[0071] in, , K, N, k, , For parameter variables, This is the calculated value of the Fourier series expression.

[0072] Furthermore, in one example, the descriptive data of the wafer surface response characteristics can be constructed using the various parameter variables in the above formula, and the descriptive data of the wafer surface response characteristics is as follows:

[0073] =v?, K=m, N=v?

[0074] =1, =v? , =v?

[0075] =2, =v? , =v?

[0076] ...

[0077] ...

[0078] =m, =v? , =v?

[0079] The description data of the wafer surface response characteristics shown above presents the Fourier coefficients of a total of m harmonics, and v? indicates that the value of this item can be set.

[0080] In one example, the descriptive data of the above wafer surface response characteristics can also be simplified to the following representation:

[0081] v? , m, v?

[0082] 1, v? , v?

[0083] 2, v? , v?

[0084] ...

[0085] ...

[0086] m, v? , v?

[0087] In some implementations, the scanning start point and scanning end point can be used as scanning position constraints, and the scanning motion equation can be used to simulate scanning the descriptive data of the above wafer surface response characteristics to obtain wafer surface response data in the corresponding scanning data format.

[0088] In some implementations, the descriptive data of wafer defect features includes the positional distribution information of wafer defects in a second coordinate system and the first defect signal value corresponding to the wafer defects. In this case, generating wafer defect data in a corresponding scan data format based on the scan simulation parameters and the descriptive data of wafer defect features may include the following steps:

[0089] Based on the scanning simulation parameters, the location distribution information of wafer defects is scanned and mapped to obtain the wafer defect location in the corresponding scan data format. Based on the scanning simulation parameters, the first defect signal value corresponding to the wafer defect is processed to obtain the second defect signal value in the corresponding scan data format. Based on the wafer defect location and the second defect signal value in the corresponding scan data format, the wafer defect data in the corresponding scan data format is obtained.

[0090] The wafer defect described in the wafer defect feature description data can be one or more defects. The second coordinate system and the first coordinate system can be the same coordinate system, for example, both being wafer coordinate systems. The first defect signal value is the defect signal value recorded in the constructed wafer defect feature description data, and the second defect signal value is the defect signal value corresponding to the defect in the scan data format after simulated scanning.

[0091] In this embodiment of the invention, by scanning and mapping the location distribution information of wafer defects using scanning simulation parameters, the wafer defect location corresponding to the scanning data format can be obtained. By processing the first defect signal value corresponding to the wafer defect using scanning simulation parameters, a second defect signal value corresponding to the wafer defect in the scanning data format can be obtained. Furthermore, the wafer defect location corresponding to the wafer defect in the scanning data format and the second defect signal value can be further combined to obtain wafer defect data corresponding to the wafer defect in the scanning data format.

[0092] In some implementations, after obtaining wafer surface response data and wafer defect data in the corresponding scan data format, the wafer defect data can be traversed, and the corresponding positions in the wafer surface response data can be replaced with the second defect signal value in the wafer defect data to generate wafer scan data.

[0093] In some implementations, considering the small number of wafer defects, a descriptive table can be used to construct descriptive data for wafer defect features for ease of data construction and readability. Each row of the descriptive table represents a defect feature, and each row is called a descriptor. Each descriptor can record the positional distribution information of the wafer defect in the second coordinate system and the first defect signal value corresponding to the wafer defect. Each descriptor consists of two parts: a fixed attribute part and an extended attribute part. The fixed part is mandatory for every descriptor, while the extended part is determined according to the defect feature described by the current descriptor, and the length of the extended part is not fixed.

[0094] For example, such as Figure 2As shown, all attributes in the descriptor consist of a Type and an attribute value. Type indicates the type of the attribute within the computer device, facilitating processing by the device. There are four fixed attributes, each representing a fixed attribute in sequence: X, Y, V, and Shape. X and Y represent the coordinates of the defect feature in the wafer coordinate system, V represents the value of the defect feature during data sampling, and Shape represents the shape of the defect feature. Extended attributes are used to supplement the description when the fixed attributes are insufficient to fully describe the information of the defect feature.

[0095] For example, if there is a circular particle of size V0 at coordinates (x0, y0) with radius r0, the descriptor corresponding to the description data of this defect feature is:

[0096] [float:x0, float:y0, float:V0, str:circle, float:r0].

[0097] Among them, float:x0, float:y0, float:V0, and str:circle are fixed attributes, while float:r0 is an extended attribute. x0, y0, circle, and r0 together constitute the positional distribution information of the defect in the wafer coordinate system, and V0 is the first defect signal value corresponding to the defect.

[0098] In some implementations, such as Figure 3 As shown, a description table can be a list of descriptors, and since the length of the extended attributes of each descriptor can be different, the length of each descriptor in the description table can also be different.

[0099] In some implementations, the scanning start point and scanning end point can be used as scanning position constraints, and the scanning motion equation can be used to simulate scanning the above description data of wafer defect features to obtain wafer defect data in the corresponding scanning data format.

[0100] In one example, after simulating a scan of the above description data of wafer defect features, the wafer defect data in the corresponding scan data format is as follows:

[0101] Row1, col1, V1

[0102] Row2, col2, V2

[0103] ...

[0104] ...

[0105] Rown, coln, Vn

[0106] The aforementioned wafer defect data specifies the row and column of the scan data, indicating the magnitude of the defect signal value V. After the scan motion equation is applied, the descriptive data of the wafer defect features is decomposed into signals at individual locations and output to the wafer defect data.

[0107] Furthermore, considering the system noise present in wafer scanning equipment, noise issues can be taken into account when simulating the generation of wafer scanning data to improve the accuracy of wafer scanning data acquisition. In some embodiments, system noise distribution data can be added to represent the noise impact during data generation. In this case, the wafer scanning data acquisition method of this embodiment may further include the following steps:

[0108] Obtain the system noise distribution data; based on the system noise distribution data, perform noise addition processing on the wafer scan data to obtain the wafer scan data with added noise.

[0109] In this embodiment of the invention, noise is added to the wafer scanning data by using the distribution data of system noise, thereby obtaining wafer scanning data with added noise and improving the accuracy of the simulated wafer scanning data.

[0110] In some implementations, the distribution data of system noise can be directly input or generated through simulation. Compared with direct input, the distribution data of system noise generated through simulation has greater randomness and better effect.

[0111] In some implementations, acquiring system noise distribution data may include the following steps:

[0112] Obtain descriptive data of noise characteristics; based on the descriptive data of noise characteristics, generate distribution data of system noise.

[0113] In this embodiment of the invention, the noise feature description data is used to describe the noise distribution when generating wafer scan data. Therefore, the system noise distribution data can be generated based on the noise feature description data.

[0114] In some implementations, computer devices can acquire system noise distribution data or noise characteristic description data through methods such as interface input, network reception, configuration file acquisition, database acquisition, or acquisition through other media.

[0115] In some implementations, the descriptive data of noise characteristics includes noise boundary values, a sequence of noise generation coefficients, and the number of samples in the noise space. In this case, generating the distribution data of system noise based on the descriptive data of noise characteristics may include the following steps:

[0116] Based on each noise generation coefficient in the noise generation coefficient sequence and the number of samples in the noise space, the quantity of noise distributed within the noise interval corresponding to each noise generation coefficient is obtained; based on the noise boundary value and the quantity of noise generation coefficients in the noise generation coefficient sequence, the interval span of each noise interval is obtained; based on the noise boundary value and the interval span of each noise interval, the interval range of each noise interval is obtained; for any noise interval, noise corresponding to the quantity of noise distributed within that noise interval is generated within the interval range of that noise interval; based on the noise generated within each noise interval, the distribution data of system noise is obtained.

[0117] In this embodiment of the invention, a set of coefficients—noise boundary values, noise generation coefficients, and the number of noise spatial samples—can be used to simulate the noise situation of the entire system. Optionally, the noise boundary values ​​may include the maximum and minimum noise values. The noise generation coefficient sequence is an ordered list because it is generated according to a certain noise distribution or a mixture of several noise distributions.

[0118] In this embodiment of the invention, firstly, based on each noise generation coefficient in the noise generation coefficient sequence and the number of samples in the noise space, the number of noises distributed within the noise interval corresponding to each noise generation coefficient is generated. Then, based on the noise boundary value and the number of noise generation coefficients in the noise generation coefficient sequence, the interval span of each noise interval is generated. Then, based on the noise boundary value and the interval span of each noise interval, the interval range of each noise interval is obtained. After that, for any noise interval, noise corresponding to the number of noises distributed within the noise interval can be generated within the interval range of the noise interval. Finally, based on the noise generated in each noise interval, the distribution data of system noise can be obtained.

[0119] The following example illustrates the process of generating the noise distribution data mentioned above.

[0120] Assume the noise characteristics are described by the following data:

[0121] NPmax=v? NPmin=v? NC=v?

[0122] NGF=[e0,e1,e2,…,en]

[0123] Where NGF=[e0, e1, e2, ..., en] represents the noise generation coefficient sequence, n is the length of the NGF sequence, NC represents the number of samples in the noise space, NPmax represents the maximum noise value, NPmin represents the minimum noise value, and v? indicates that the value of this item can be set.

[0124] First, based on each noise generation coefficient in the noise generation coefficient sequence and the number of samples in the noise space, the noise quantity NBN distributed within the noise interval corresponding to each noise generation coefficient is generated, as follows:

[0125] NBn=NC×NGF=[NC×e0, NC×e1, NC×e2,…, NC×en]

[0126] Round NC×e0, NC×e1, NC×e2, and NC×en up to obtain the noise quantity NBN distributed within the noise interval corresponding to each noise generation coefficient.

[0127] Then, based on the noise boundary values ​​and the number of noise generation coefficients in the noise generation coefficient sequence, the span of each noise interval is obtained. ,as follows:

[0128]

[0129] Then, based on the noise boundary values ​​and the span of each noise interval, the range of each noise interval is obtained as follows:

[0130] Initialize NP_C0 = NPmin. Then, increment NP_C0 by one interval span NBS each time, letting NP_Ci = NP_C0 + i × NBS, until i = n. Then utilize... Replace NP_Cn. Thus, we obtain NP_C0, NP_C1, ..., NP_Cn. Further, NP_C0 to NP_C1 can be defined as the range of the first noise interval, NP_C1 to NP_C2 as the range of the second noise interval, and so on, with NP_C(n-1) to NP_Cn defined as the range of the nth noise interval.

[0131] Then, for any noise interval, noise corresponding to the amount of noise distributed within that noise interval can be randomly generated within that interval, as follows:

[0132] Assuming the number of noises distributed in the noise interval corresponding to the first noise generation coefficient is NBN=3, then 3 noises can be randomly generated in the interval from NP_C0 to NP_C1. Assuming the number of noises distributed in the noise interval corresponding to the second noise generation coefficient is NBN=5, then 5 noises can be randomly generated in the interval from NP_C1 to NP_C2. And so on, the noises corresponding to the number of noises distributed in each noise interval can be obtained.

[0133] Finally, the noise generated in each noise interval can be added to the noise distribution dataset ND_L to obtain the noise distribution data.

[0134] In some implementations, in order to improve the randomness of the generated noise distribution data and make the generated noise distribution data closer to the characteristics of random noise distribution, the data in ND_L can be randomly shuffled to obtain the final noise distribution data ND.

[0135] In some implementations, noise corresponding to the amount of noise distributed within a noise interval can be generated randomly within the interval range.

[0136] It should be noted that in the foregoing embodiments, the calculated noise is additive noise. In some embodiments, the noise data may also include multiplicative noise. In this case, the additive noise and multiplicative noise can be combined into the total noise using the following formula:

[0137]

[0138] in, For total noise, This is additive noise, which can be generated based on the noise characteristic description data from the foregoing embodiments. Multiplicative noise can be generated based on the wafer surface response data in the corresponding scan data format and the multiplicative noise coefficient.

[0139] In some implementations, multiplicative noise can be calculated using the following methods:

[0140] First, considering that multiplicative noise is related to wafer surface response data—the larger the response data, the larger the multiplicative noise—its generation depends on the wafer surface response data. To simplify the design, a multiplicative noise coefficient Alpha can be input, simplified to α. This coefficient can be included in the noise feature description data, expressed as Alpha = v?. To avoid multiplicative noise anomalies, α is set to [0.01, 0.1], and is a fixed value during multiplicative noise generation. The standard deviation of the multiplicative noise can be calculated using the following formula before adding it:

[0141]

[0142] Where n is the index in the wafer surface response data corresponding to the scan data format. This represents the value of the wafer surface response data at index n. This represents the standard deviation of the multiplicative noise at index n.

[0143] Secondly, based on Construct a log-normal distribution, and then randomly select a value from this log-normal distribution as the current value of the multiplicative noise.

[0144] The formula for the probability density of the log-normal distribution is as follows:

[0145]

[0146] in, The mean value can be carried in the descriptive data of noise features and can be configured manually. It can be included in the descriptive data of noise features as... =v? form, The standard deviation of multiplicative noise. Let be the random variable corresponding to multiplicative noise.

[0147] In some implementations, the generated wafer surface response data (which has the same amount of data as the wafer scan data) can be traversed. During the traversal, at each step, the log-normal distribution data of the current step is continuously calculated using the method described in the previous embodiment. Then, a value is randomly selected from the log-normal distribution data as the multiplicative noise value of the current step. In addition, a value is also randomly selected from the additive noise distribution data as the additive noise of the current step. Then, the additive noise value and the multiplicative noise value of the current step can be combined to form a total noise value, and this total noise value is added to the signal of the wafer scan data of the current step, thereby realizing the process of adding noise to the wafer scan data of the current step.

[0148] Furthermore, considering that the standard deviation is calculated and a new log-normal distribution is generated for each wafer surface response data in the aforementioned embodiments, resulting in a large computational load, in some implementations, a window of size WinSize can be used to apply a step size (Step is used for design simplification) to the wafer surface response data stream. The process involves sliding the window (where `Step` can be smaller than `WinSize` but not larger than `WinSize`) to calculate the mean of the wafer surface response data within that window. This mean is multiplied by the multiplicative noise coefficient `Alpha` to obtain the standard deviation of the multiplicative noise within that window. A log-normal distribution is then calculated based on this standard deviation. This process iterates through each wafer scan data point in the current window, randomly selecting a multiplicative noise value from the generated log-normal distribution. Additionally, for each wafer scan data point in the current window, an additive noise value can be randomly selected from the additive noise distribution. Finally, the total noise value for each wafer scan data point in the current window is synthesized using the total noise synthesis formula. This total noise is then added to the signal of the corresponding wafer scan data, thus adding noise to the wafer scan data within the current window. This process is repeated by moving the window until all data has been traversed, completing the noise addition for all wafer scan data.

[0149] The method described above for generating system noise distribution data can simulate the actual noise distribution of a wafer scanning device when scanning a wafer, thereby improving the accuracy of the final simulated wafer scanning data.

[0150] In some embodiments of the present invention, after obtaining data such as wafer defect feature description data, wafer surface response feature description data, and noise feature description data, data preprocessing can be performed to facilitate subsequent processing. For example, the descriptors in the description table corresponding to the wafer defect feature description data can be parsed to generate the corresponding data structure. Alternatively, the Fourier series expression and the variable values ​​of the parameter variables can be preprocessed to verify the validity and completeness of the data, and to perform data structure transformation.

[0151] Figure 4 This is a flowchart of a verification method for a semiconductor testing system according to an embodiment of the present invention. This method can be executed by a computer device. Figure 4 As shown, the verification method of this semiconductor testing system may include:

[0152] S410. Verify the semiconductor inspection system based on wafer scan data, wherein the wafer scan data is obtained based on the wafer scan data acquisition method.

[0153] In this embodiment of the invention, after acquiring wafer scan data, the semiconductor inspection system can be verified using the wafer scan data. For example, the semiconductor inspection system may include functions such as classifying wafer defect features and calculating attributes. After acquiring wafer scan data, the execution of functions such as classification and attribute calculation in the semiconductor inspection system can be verified.

[0154] Figure 5 The diagram shown is a block diagram of a wafer scanning data acquisition device according to an embodiment of the present invention. Figure 5 As shown, the wafer scanning data acquisition device 500 includes: a first acquisition module 510 and a generation module 520, wherein:

[0155] The first acquisition module 510 is used to acquire scanning simulation parameters and descriptive data of wafer scanning features;

[0156] The generation module 520 is used to generate the wafer scan data based on the scan simulation parameters and the description data of the wafer scan features.

[0157] In another embodiment of the present invention, the description data of the wafer scanning features includes description data of wafer defect features and description data of wafer surface response features. The generation module 520 includes:

[0158] The first generation submodule is used to generate wafer surface response data in a corresponding scan data format based on the scan simulation parameters and the description data of the wafer surface response characteristics.

[0159] The second generation submodule is used to generate wafer defect data corresponding to the scan data format based on the scan simulation parameters and the description data of the wafer defect features.

[0160] The third generation submodule is used to generate the wafer scan data based on the wafer surface response data corresponding to the scan data format and the wafer defect data.

[0161] In another embodiment of the present invention, the descriptive data of the wafer surface response features includes a simulation expression of the wafer surface response features and variable value data of the parameter variables in the simulation expression. The first generation submodule is further configured to solve the simulation expression using the variable value data to obtain wafer surface response data corresponding to the first coordinate system; and to perform scan mapping on the wafer surface response data corresponding to the first coordinate system based on the scan simulation parameters to obtain wafer surface response data corresponding to the scan data format.

[0162] In another embodiment of the invention, the simulation expression is a Fourier series expression.

[0163] In another embodiment of the present invention, the descriptive data of the wafer defect features includes the positional distribution information of the wafer defect in a second coordinate system and the first defect signal value corresponding to the wafer defect. The second generation submodule is further configured to perform scan mapping on the positional distribution information of the wafer defect based on the scan simulation parameters to obtain the wafer defect position corresponding to the scan data format; process the first defect signal value corresponding to the wafer defect based on the scan simulation parameters to obtain the second defect signal value corresponding to the scan data format; and obtain wafer defect data corresponding to the scan data format based on the wafer defect position corresponding to the scan data format and the second defect signal value.

[0164] In another embodiment of the present invention, the wafer scan data acquisition device 500 further includes:

[0165] The second acquisition module is used to acquire the distribution data of system noise;

[0166] The noise addition module is used to add noise to the wafer scan data based on the system noise distribution data to obtain wafer scan data with added noise.

[0167] In another embodiment of the present invention, the second acquisition module includes:

[0168] The acquisition submodule is used to acquire descriptive data of noise features;

[0169] The fourth generation submodule is used to generate the distribution data of the system noise based on the description data of the noise characteristics.

[0170] In another embodiment of the present invention, the noise feature description data includes noise boundary values, a noise generation coefficient sequence, and the number of samples in the noise space. The fourth generation submodule is further configured to: obtain the number of noises distributed within a noise interval corresponding to each noise generation coefficient based on each noise generation coefficient in the noise generation coefficient sequence and the number of samples in the noise space; obtain the interval span of each noise interval based on the noise boundary values ​​and the number of noise generation coefficients in the noise generation coefficient sequence; obtain the interval range of each noise interval based on the noise boundary values ​​and the interval span of each noise interval; generate noise corresponding to the number of noises distributed within the noise interval within the interval range of any noise interval; and obtain the system noise distribution data based on the noise generated within each noise interval.

[0171] In another embodiment of the present invention, the scanning simulation parameters include a scanning start point, a scanning end point, and a scanning motion equation, and the generation module 520 includes:

[0172] The fifth generation submodule is used to simulate scanning the wafer scanning feature description data using the scanning start point and the scanning end point as scanning position constraints and the scanning motion equation to obtain the wafer scanning data.

[0173] Figure 6 The diagram shown is a block diagram of a verification apparatus for a semiconductor testing system according to an embodiment of the present invention. Figure 6 As shown, the verification device 600 of the semiconductor testing system includes: a verification module 610, wherein:

[0174] The verification module 610 is used to verify the semiconductor inspection system based on wafer scanning data.

[0175] The wafer scanning data is based on Figure 5 The data was acquired by the wafer scanning data acquisition device 500.

[0176] The specific implementation process of the functions and roles of each module in the above-mentioned device can be found in the implementation process of the corresponding steps of the wafer scanning data acquisition method and the semiconductor detection system verification method in the above embodiments, and will not be repeated here.

[0177] Figure 7The diagram shown is a block diagram of an electronic device 700 provided in an embodiment of the present invention.

[0178] Reference Figure 7 The electronic device 700 includes a processing component 710, which further includes one or more processors, and memory resources represented by a memory 720 for storing instructions executable by the processing component 710, such as application programs. The application programs stored in the memory 720 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 710 is configured to execute instructions to perform the aforementioned wafer scan data acquisition method or the verification method of a semiconductor inspection system.

[0179] Electronic device 700 may also include a power supply component configured to perform power management of electronic device 700, a wired or wireless network interface configured to connect electronic device 700 to a network, and an input / output (I / O) interface. Electronic device 700 can operate on an operating system stored in memory 720, such as Windows Server™, Mac OSX™, Unix™, Linux™, FreeBSD™, or similar.

[0180] A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by the processor of the electronic device 700, enables the electronic device 700 to perform the wafer scan data acquisition method or the verification method of the semiconductor inspection system.

[0181] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0182] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0183] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0184] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0185] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0186] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program verification codes, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0187] Furthermore, it should be noted that the combination of the various technical features in this case is not limited to the combination methods described in the claims of this case or the combination methods described in the specific embodiments. All technical features described in this case can be freely combined or combined in any way, unless they contradict each other.

[0188] It should be noted that the above examples are merely specific embodiments of the present invention, and the present invention is obviously not limited to the above embodiments, with many similar variations. All modifications that can be directly derived or conceived by those skilled in the art from the content disclosed in this invention should fall within the protection scope of this invention.

[0189] It should be understood that the terms "first," "second," etc., mentioned in the embodiments of the present invention are merely for the purpose of more clearly describing the use of the technical solutions in the embodiments of the present invention, and are not intended to limit the scope of protection of the present invention.

[0190] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for acquiring wafer scanning data, characterized in that, include: The scanning simulation parameters and wafer scanning feature description data are obtained. The wafer scanning feature description data includes wafer defect feature description data and wafer surface response feature description data. The wafer surface response feature description data includes the simulation expression of the wafer surface response feature and the variable value data of the parameter variables in the simulation expression. The wafer defect feature description data includes the position distribution information of the wafer defect in the second coordinate system and the first defect signal value corresponding to the wafer defect. The wafer scan data is generated based on the scan simulation parameters and the description data of the wafer scan features; The step of generating the wafer scan data based on the scan simulation parameters and the description data of the wafer scan features includes: The simulation expression is solved using the variable value data to obtain the wafer surface response data corresponding to the first coordinate system; Based on the scanning simulation parameters, the wafer surface response data corresponding to the first coordinate system is scanned and mapped to obtain wafer surface response data corresponding to the scanning data format; Based on the scanning simulation parameters, the location distribution information of the wafer defects is scanned and mapped to obtain the wafer defect location corresponding to the scanning data format; Based on the scanning simulation parameters, the first defect signal value corresponding to the wafer defect is processed to obtain the second defect signal value corresponding to the scanning data format of the wafer defect; Based on the wafer defect location corresponding to the scan data format and the second defect signal value, wafer defect data corresponding to the scan data format is obtained; The wafer scan data is generated based on the wafer surface response data corresponding to the scan data format and the wafer defect data.

2. The method according to claim 1, characterized in that, The simulation expression is a Fourier series expression.

3. The method according to claim 1, characterized in that, The method further includes: Obtain the distribution data of system noise; The wafer scan data is subjected to noise addition processing based on the system noise distribution data to obtain wafer scan data with added noise.

4. The method according to claim 3, characterized in that, The acquisition of system noise distribution data includes: Obtain descriptive data of noise characteristics; Based on the description data of the noise characteristics, the distribution data of the system noise is generated.

5. The method according to claim 4, characterized in that, The noise feature description data includes noise boundary values, noise generation coefficient sequences, and the number of samples in the noise space. Generating the system noise distribution data based on the noise feature description data includes: Based on each noise generation coefficient in the noise generation coefficient sequence and the number of samples in the noise space, the number of noises distributed within the noise interval corresponding to each noise generation coefficient is obtained. The span of each noise interval is obtained based on the boundary value of the noise and the number of noise generation coefficients in the noise generation coefficient sequence. Based on the boundary values ​​of the noise and the span of each noise interval, the range of each noise interval is obtained; For any noise interval, generate noise within the interval that corresponds to the amount of noise distributed within that noise interval. Based on the noise generated in each noise interval, the distribution data of the system noise is obtained.

6. The method according to any one of claims 1-5, characterized in that, The scanning simulation parameters include a scan start point, a scan end point, and a scan motion equation. Generating the wafer scan data based on the scanning simulation parameters and the descriptive data of the wafer scan features includes: Using the scanning start point and the scanning end point as scanning position constraints, the wafer scanning feature description data is simulated and scanned using the scanning motion equation to obtain the wafer scanning data.

7. A verification method for a semiconductor testing system, characterized in that, include: The semiconductor inspection system is verified based on wafer scan data, which is obtained using the wafer scan data acquisition method according to any one of claims 1 to 6.

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