High efficiency laser cleaning method and system for wafer surface cleaning

Abstract

The present application relates to the technical field of semiconductor device processing, in particular to a high-efficiency laser cleaning method and system for wafer surface cleaning. The method obtains a surface image of a wafer; extracts an impurity area in the surface image of the wafer; analyzes the morphological characteristics of the impurity area to determine a characteristic impurity coefficient of the impurity area; analyzes the color characteristics of the impurity area to determine an organic residue coefficient of the impurity area; classifies the impurity area based on the characteristic impurity coefficient and the organic residue coefficient respectively to obtain multiple impurity categories; adjusts the initial laser cleaning power of the impurity area according to the impurity category to which each impurity area belongs to obtain a corrected laser cleaning power; and determines an optimal cleaning path for wafer cleaning according to the path between the corrected laser cleaning power and the impurity area. The present application realizes efficient cleaning of the wafer surface.

Description

Technical Field

[0001] The present invention relates to the technical field of semiconductor device processing, and in particular to a high-efficiency laser cleaning method and system for cleaning wafer surfaces. Background Art

[0002] Wafers are the foundation and core of semiconductor integrated circuits. During the wafer production process, to ensure surface flatness, cleanliness, and good electrical performance from impurities such as particles, metals, and organic matter, and to prevent circuit failures such as short circuits and open circuits, wafer cleaning is required at almost every stage to remove impurities from the wafer surface. Therefore, wafer surface cleaning is a routine process.

[0003] The existing wafer cleaning method generally uses traditional wet cleaning, specifically using solvents, acids, surfactants and water to spray the wafer surface, and using different reagents to remove pollutants, organic matter and metal ion pollution on the wafer surface. However, this cleaning method will leave residual pollutants and cleaning fluid in the process of cleaning the pollutants on the wafer surface, and cannot completely remove metal particles. Therefore, in order to ensure the efficiency and completeness of wafer cleaning, in the existing wet cleaning process, laser dry cleaning is used to assist wet cleaning, so as to further remove the residual pollution on the wafer surface after wet cleaning, so as to achieve efficient cleaning of the wafer surface. Summary of the Invention

[0004] In order to solve the technical problem of residual contamination after existing wet cleaning, the present invention aims to provide an efficient laser cleaning method and system for cleaning wafer surfaces. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present invention provides an efficient laser cleaning method for cleaning a wafer surface, the method comprising:

[0006] Acquire a surface image of a wafer; extract an impurity region in the surface image of the wafer;

[0007] Analyzing the morphological characteristics of the impurity region to determine a characteristic impurity coefficient of the impurity region; analyzing the color characteristics of the impurity region to determine an organic residue coefficient of the impurity region; and classifying the impurity region based on the characteristic impurity coefficient and the organic residue coefficient to obtain a plurality of impurity categories;

[0008] According to the impurity category of each impurity area, the initial laser cleaning power of the impurity area is adjusted to obtain a corrected laser cleaning power;

[0009] According to the modified laser cleaning power and the path between the impurity regions, an optimal cleaning path for cleaning the wafer is determined.

[0010] Preferably, the impurity region in the surface image of the wafer is extracted by:

[0011] An envelope line of a gray histogram of the surface image of the wafer is fitted to determine a peak value on the envelope line;

[0012] A mean value of each peak value is obtained as a characteristic gray value;

[0013] A pixel point corresponding to the characteristic gray value is taken as a seed point, and region growing is performed based on the seed point to obtain a plurality of growing regions; and other growing regions except for a growing region with the largest area are taken as impurity regions in the surface image of the wafer.

[0014] Preferably, a calculation formula of the characteristic impurity coefficient is:

[0015] ;

[0016] wherein, is the characteristic impurity coefficient of the nth impurity region; e is a natural constant; is a probability that a pixel point with a gray value g appears in an eight-neighbor domain of a pixel point with a gray value G in the nth impurity region; is a probability that a pixel point with a gray value G appears in the nth impurity region; is a logarithmic function with 2 as a base number.

[0017] Preferably, the color feature of the impurity region is analyzed to determine an organic residue coefficient of the impurity region, including:

[0018] A variation coefficient of the gray values of all the pixel points in the impurity region is taken as the organic residue coefficient of the impurity region.

[0019] Preferably, the impurity regions are classified based on the characteristic impurity coefficient and the organic residue coefficient respectively to obtain a plurality of impurity categories, including:

[0020] The characteristic impurity coefficient is taken as a distance between the impurity regions, and the impurity regions are divided into two clustering clusters, and a clustering cluster with a minimum value of a variance of the gray values of the pixel points in the two clustering clusters is taken as a first impurity category; and a clustering cluster with a maximum value of the variance of the gray values of the pixel points in the two clustering clusters is taken as a to-be-assigned impurity category;

[0021] The organic residue coefficient is taken as a distance between the impurity regions in the to-be-assigned impurity category, and the impurity regions in the to-be-assigned impurity category are divided into two clustering clusters as a second impurity category and a third impurity category.

[0022] Preferably, the method for obtaining the initial laser cleaning power of the impurity region is as follows:

[0023] Taking the impurity region with the smallest area in each impurity category as the starting region, the optimal laser cleaning power of the starting region is determined; and the optimal laser cleaning power of the starting region is taken as the initial laser cleaning power of the impurity region in the impurity category.

[0024] Preferably, the method for adjusting the initial laser cleaning power of the impurity region according to the impurity category to which the impurity region belongs to obtain the corrected laser cleaning power comprises:

[0025] Taking the ratio of the area of the impurity region to the area of the starting region of the impurity category to which the impurity region belongs to as the power adjustment value of the impurity region;

[0026] Taking the product of the power adjustment value of the impurity region and the initial laser cleaning power as the corrected laser cleaning power.

[0027] Preferably, the method for determining the optimal cleaning path of the wafer according to the path between the corrected laser cleaning power and the impurity region comprises:

[0028] Taking the distance between two adjacent impurity regions in the cleaning path as the first parameter value; taking the difference between the corrected laser cleaning powers of two adjacent impurity regions in the cleaning path as the second parameter value; and performing weighted summation on the first parameter value and the second parameter value to obtain the third parameter value;

[0029] Continuously adjusting the cleaning path of the wafer, and taking the cleaning path corresponding to the minimum third parameter value as the optimal cleaning path.

[0030] Preferably, the method for obtaining the optimal laser cleaning power of the starting region is as follows:

[0031] Starting from 0, the laser cleaning power is gradually increased, and the cleaning effect under the current laser cleaning power is artificially judged; when the cleaning effect remains unchanged after changing the laser cleaning power, the initial laser cleaning power at which the cleaning effect remains unchanged is taken as the optimal laser cleaning power of the starting region.

[0032] In a second aspect, an efficient laser cleaning system for wafer surface cleaning is provided, and the system comprises the following modules:

[0033] A region extraction module is configured to obtain a surface image of a wafer and extract an impurity region in the surface image of the wafer.

[0034] The feature analysis module is configured to analyze morphological features of the impurity region to determine a feature impurity coefficient of the impurity region, analyze color features of the impurity region to determine an organic residue coefficient of the impurity region, and classify the impurity region based on the feature impurity coefficient and the organic residue coefficient respectively to obtain a plurality of impurity categories.

[0035] The power determination module is configured to adjust an initial laser cleaning power of the impurity region according to the impurity category to which each impurity region belongs to, to obtain a modified laser cleaning power.

[0036] The path determination module is configured to determine an optimal cleaning path of wafer cleaning according to the modified laser cleaning power and a path between the impurity region.

[0037] In a third aspect, an electronic device is provided, including a memory and a processor, the memory stores executable code, and the processor executes the executable code to implement the embodiments of each possible implementation of the first aspect.

[0038] In a fourth aspect, a computer program product is provided, which includes computer program code, and when the computer program code runs on a computer, the computer executes the method in the first aspect or any one of the possible implementation manners of the first aspect.

[0039] In a fifth aspect, a computer readable storage medium is provided, which stores a computer program, and when the computer program is executed in a computer, the computer executes the embodiments of each possible implementation of the first aspect.

[0040] The embodiments of the present application have at least the following beneficial effects:

[0041] The present application first extracts the impurity region on the wafer surface to realize subsequent analysis and cleaning of the impurity region during laser cleaning, because the non-impurity region does not need to be cleaned by laser, and if the non-impurity region is cleaned by laser, it may cause the wafer to be abraded.

[0042] Because the impurities on the wafer surface include metal particles, chemicals and organic residues, the metal particles have obvious crystal features, which are represented by the fact that the pixel points on the image are similar and have a high overall gray value, so the morphological features of the impurity region are first analyzed to determine the feature impurity coefficient of the impurity region, which represents the impurity coefficient of the metal particles; the residues of chemicals and organic matter are mainly on the wafer surface, and the overall gray value is random and relatively irregular, so the color features of the impurity region are analyzed to determine the organic residue coefficient, which represents the distinguishing coefficient of the residues of chemicals and organic matter.

[0043] The impurity regions are classified based on the characteristic impurity coefficient and the organic residue coefficient respectively to obtain multiple impurity categories, the types of the impurity regions in each impurity category are more similar, theoretically, the laser cleaning power should be the same for each impurity category, but because the sizes of different impurity regions in the same impurity category are different, when using the same initial power for cleaning, it is easy to cause the cleaning speed to be too slow, therefore, further, the initial laser cleaning power of each impurity region is adjusted according to the impurity category to which each impurity region belongs to obtain a corrected laser cleaning power. Finally, the optimal cleaning path of wafer cleaning is determined according to the path between the corrected laser cleaning power and the impurity region, and high-efficiency cleaning of the wafer surface is realized. BRIEF DESCRIPTION OF DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, and the advantages thereof, below, a brief introduction will be given to the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0045] Figure 1 A method flowchart of a high-efficiency laser cleaning method for wafer surface cleaning provided by an embodiment of the present application;

[0046] Figure 2 A method flowchart of an impurity category acquisition method provided by an embodiment of the present application;

[0047] Figure 3 A system block diagram of a high-efficiency laser cleaning system for wafer surface cleaning provided by an embodiment of the present application;

[0048] Figure 4 A structural schematic diagram of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined object, the following describes in detail the specific implementation, structure, features and effects of a high-efficiency laser cleaning method and system for wafer surface cleaning according to the present application, with reference to the drawings and preferred embodiments.

[0050] In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0051] In the description of the embodiments of the present application, unless otherwise specified, " / " represents the meaning of or, for example, A / B can represent A or B: "and / or" in the text is only a description of the association relationship of the associated object, which means that there can be three relationships, for example, A and / or B, which can represent: A exists alone, A and B exist together, and B exists alone, and in addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0052] Hereinafter, the terms "first", "second" are only for descriptive purposes, and cannot be understood as implying or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more features.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by a person skilled in the art of the technology to which the present application belongs.

[0054] The embodiments of the present application will be described below with reference to the accompanying drawings. Those skilled in the art can know that with the development of technology and the appearance of new scenes, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0055] The embodiments of the present application provide a specific implementation method of a high-efficiency laser cleaning method and system for wafer surface cleaning. The method is suitable for wafers that have been cleaned by wet cleaning. In the existing wet cleaning process, laser dry cleaning is used to assist wet cleaning to further remove the pollution residues on the wafer surface after wet cleaning, so as to realize high-efficiency cleaning of the wafer surface.

[0056] The specific scheme of the high-efficiency laser cleaning method and system for wafer surface cleaning provided by the present application will be described below with reference to the accompanying drawings.

[0057] Please refer to Figure 1 which shows a step flowchart of a high-efficiency laser cleaning method for wafer surface cleaning provided by an embodiment of the present application. The method comprises the following steps:

[0058] Step S100, obtaining a surface image of a wafer; extracting an impurity area in the surface image of the wafer.

[0059] The high-definition image of the wafer surface is collected by the information collection module, and the high-definition image of the wafer surface is preprocessed to obtain the surface image of the wafer. The preprocessing of the high-definition image of the wafer surface includes denoising enhancement and other preprocessing operations. The information collection module can be a camera.

[0060] In the process of cleaning the contaminants on the wafer surface, the traditional way is generally to use the traditional wet cleaning to remove the contaminants, organic matter and metal ion pollution on the wafer surface with different reagents.

[0061] This cleaning process will cause the existence of stains and the residue of cleaning liquid, and the metal particles cannot be effectively cleaned. In the natural drying process after wet cleaning, the sensor is used to collect the surface information of the wafer after wet cleaning, and the surface image of the wafer is obtained, and then the information of the surface image of the wafer is analyzed, and the best laser cleaning path is obtained according to the analysis result, and the wet residue cleaning of the wafer surface is realized.

[0062] The main principle of using laser dry cleaning of the surface contaminants of the wafer is to use high-energy laser beam to irradiate on the contaminants on the wafer surface, and the contaminants are rapidly heated, evaporated or peeled off through photo-thermal effect. When using laser cleaning, the power of the laser is too large, which will inevitably cause damage to the wafer surface, so it is necessary to use appropriate power to clean different impurity areas. However, because the size of the impurity area on the wafer surface is different and the factors causing pollution are different, without a reasonable cleaning path, it is necessary to frequently adjust the power of the laser, which leads to low cleaning efficiency. Therefore, the present application classifies different impurity areas based on the surface image of the wafer, and then plans the cleaning path of the wafer according to the classification result to realize efficient cleaning of the wafer surface.

[0063] Firstly, the impurity area on the wafer surface is determined, secondly, the classification of the impurity area on the wafer surface is divided, then the initial laser cleaning power of different impurities is determined, and then the path of laser cleaning is determined by using the morphological characteristics of each impurity area combined with different initial powers.

[0064] In the process of using laser to clean the impurities on the wafer surface, it is actually a feedback regulation process, that is, the impurity information on the wafer surface is fed back, and then the laser power and path are adjusted to realize the cleaning of the impurities by laser. Since the impurities are randomly distributed on the surface of the wafer, before adjusting the laser, the impurities on the wafer surface need to be determined, that is, the impurity area in the surface image of the wafer is determined.

[0065] Because the types of impurities in the wafer are different, there is a difference in gray value in the surface image of the wafer, so in the embodiment of the present application, the region division of the impurities on the wafer surface is realized by using the region growing algorithm of multiple seed points.

[0066] The impurity region in the surface image of the wafer is extracted, specifically: firstly, a gray level histogram of the surface image of the wafer is obtained, and then envelope line fitting is performed on the gray level histogram by using an envelope line algorithm, and all peak values on the fitted envelope line are determined by using a local maximum value method, that is, the envelope line of the gray level histogram of the surface image of the wafer is fitted, and the peak values on the envelope line are determined; for each peak value, the mean value of all gray values corresponding to each peak value is calculated as a characteristic gray value; the pixel point corresponding to the characteristic gray value is taken as a seed point, and region growing is performed based on the seed point to obtain a plurality of growing regions; other growing regions except the largest growing region are taken as the impurity region in the surface image of the wafer.

[0067] When the impurity region in the surface image of the wafer is extracted, the largest growing region is removed because the surface structure of the wafer is simple, so the peak with the largest area of the gray level histogram corresponds to a non-polluted region, and different peak values correspond to different impurity regions of the wafer, and therefore the region growing algorithm with multiple seed points can obtain different impurity regions.

[0068] The surface image of the wafer is analyzed to obtain a polluted region of the wafer surface, which is also an impurity region, and in a subsequent step, the impurity region is classified and the cleaning power of each impurity region is predicted according to the performance of the impurity region, and then the optimal wafer cleaning path is obtained by using the predicted power.

[0069] In step S200, the morphological characteristics of the impurity region are analyzed to determine a characteristic impurity coefficient of the impurity region, the color characteristics of the impurity region are analyzed to determine an organic residue coefficient of the impurity region, and the impurity region is classified based on the characteristic impurity coefficient and the organic residue coefficient respectively to obtain a plurality of impurity categories.

[0070] Because the impurities on the wafer surface are not all of the same type, there may be different impurities such as particles, chemicals, metals and organic matter, and different impurities are easily damaged or not cleaned completely when treated by using the same size laser power due to different structures, therefore, the morphological characteristics and color characteristics of different impurity regions are analyzed in the embodiments of the present application to realize classification of different impurity regions.

[0071] In some embodiments, a plurality of impurity categories are obtained by analyzing the morphological characteristics and color characteristics of different impurity regions, that is, step S200 can be realized by Figure 2 as shown in the following steps:

[0072] In step S210, the morphological characteristics of the impurity region are analyzed to determine a characteristic impurity coefficient of the impurity region.

[0073] Impurities on the wafer surface primarily consist of metal particles, chemical residues, and organic residues. Metal particles differ from chemical and organic residues in their distinct crystalline characteristics, manifesting as highly similar grayscale values ​​for adjacent pixels in the image, resulting in a relatively stable grayscale across the entire region. Chemical and organic residues, on the other hand, exhibit a random, irregular grayscale appearance, primarily distinguished by their varying grayscale values.

[0074] The characteristic impurity coefficient is primarily used to distinguish metal particle impurities. Compared to other impurities, such as chemical and organic residues, metal particle impurities have a more stable form and a more regular color. Characteristic distinction is achieved by calculating the characteristic impurity coefficient.

[0075] Taking the nth impurity region as an example, the characteristic impurity coefficient of the nth impurity region is The calculation formula is: ; Among them, e is a natural constant; is the probability that a pixel with gray value g appears in the eight-neighborhood of all pixels with gray value G in the nth impurity region; is the probability of the pixel with gray value G appearing in the nth impurity area; is the logarithmic function with base 2.

[0076] In the calculation formula of the characteristic impurity coefficient, the denominator represents the degree of disorder of all grayscale values ​​in the nth impurity region, that is, the complexity of the appearance of different grayscale values. If the nth impurity region is a metal particle region, the corresponding denominator is smaller, and vice versa. The construction of the numerator is based on the crystal characteristic of metal particles, that is, several adjacent pixels have highly similar grayscale values, so conditional probability is used to represent the grayscale value distribution around different pixels. As a weight to filter the high similarity of grayscale. Combining the above logic, we have the characteristic impurity coefficient The bigger, The greater the probability that an impurity region is contaminated by metal particles, the greater the probability that the impurity region is contaminated by metal particles, and vice versa.

[0077] Step S220 , analyzing the color characteristics of the impurity region to determine the organic residue coefficient of the impurity region.

[0078] The organic residual coefficient represents the chemical and organic residual distinguishing coefficients. The organic residual coefficient is used to distinguish the impurity area of chemical residual and organic residual. The residual of chemical and organic on the wafer surface is random and relatively irregular in overall gray scale performance. The main difference between them is the difference in gray value. Therefore, the application realizes the above features by using the variation coefficient of the gray value of the pixel points in the impurity area to process and calculate different areas.

[0079] The variation coefficient of the gray value of all pixel points in the impurity area is used as the organic residual coefficient of the impurity area. More specifically, the standard deviation of the gray value of all pixel points in the impurity area is used as the numerator, and the average of the gray value of all pixel points in the impurity area is used as the denominator. The ratio of the numerator and the denominator is used as the organic residual coefficient of the impurity area.

[0080] Step S230, classifying the impurity area based on the feature impurity coefficient and the organic residual coefficient respectively, to obtain a plurality of impurity categories.

[0081] Firstly, the feature impurity coefficient is used as the distance between the impurity areas, and the impurity areas are divided into two clustering clusters. The clustering cluster with the minimum value of the variance of the gray value of the pixel points in the two clustering clusters is used as the first impurity category. More specifically, the k-means clustering algorithm is used, and the feature impurity coefficient is used as the distance between the impurity areas to cluster the impurity areas. The value of k is set to 2.

[0082] Then, the clustering cluster with the maximum value of the variance of the gray value of the pixel points in the two clustering clusters is used as the impurity category to be assigned. The organic residual coefficient is used as the distance between the impurity areas in the impurity category to be assigned, and the impurity areas in the impurity category to be assigned are divided into two clustering clusters as the second impurity category and the third impurity category.

[0083] The different impurity areas on the wafer surface are divided into three impurity categories, including the first impurity category, the second impurity category and the third impurity category.

[0084] Step S300, adjusting the initial laser cleaning power of the impurity area according to the belonging impurity category of each impurity area, to obtain the corrected laser cleaning power.

[0085] The impurity areas on the wafer surface are divided into three different impurity categories. In theory, the laser cleaning power for each impurity category should be the same. However, because the sizes of different impurity areas in the same impurity category are different, using the same initial power for cleaning may cause slow cleaning speed. Therefore, the application predicts and corrects the laser cleaning power of the impurity areas in each category.

[0086] With any impurity category in the three impurity categories as a target impurity category, with the smallest impurity area in the target impurity category as a starting area, the optimal laser cleaning power of the starting area is determined, and the method for obtaining the optimal laser cleaning power of the starting area is more specific: the laser cleaning power is gradually increased from 0, and the cleaning effect under the current laser cleaning power is artificially judged, when the cleaning effect starts to remain unchanged after the laser cleaning power is changed, the initial laser cleaning power of the starting area is taken as the optimal laser cleaning power of the starting area, that is, the initial laser cleaning power of the impurity area in the impurity category to which the starting area belongs is the same. It should be noted that the step length of the increased laser cleaning power is 1, and the laser cleaning power should not exceed the maximum power value, and the maximum power value is the maximum working power value of the laser cleaning equipment.

[0087] Further, the initial laser cleaning power corresponding to each impurity category is obtained, since the initial laser cleaning power is obtained for the smallest impurity area in the category, the initial laser cleaning power is the minimum power corresponding to the current category, and the power is adjusted on the basis of the minimum power to obtain the corrected laser cleaning power of each impurity area.

[0088] In some embodiments of the present application, the initial laser cleaning power of the impurity area is adjusted according to the impurity category to which the impurity area belongs to obtain the corrected laser cleaning power, and specifically: the ratio of the area of the impurity area to the area of the starting area of the impurity category to which the impurity area belongs is taken as the power adjustment value of the impurity area; and the product of the power adjustment value of the impurity area and the initial laser cleaning power is taken as the corrected laser cleaning power. It should be noted that in the embodiments of the present application, the area of the region is the number of pixel points in the region.

[0089] In other embodiments of the present application, the calculation formula of the corrected laser cleaning power is: ; wherein, is the corrected laser cleaning power of the nth impurity area; e is a natural constant; γ is an inhibition coefficient; is the area of the nth impurity area; is the area of the starting area of the impurity category to which the nth impurity area belongs; is the power adjustment value of the nth impurity area; is the initial laser cleaning power of the nth impurity area. In the embodiments of the present application, the inhibition coefficient is 0, and in other embodiments, the inhibition coefficient can also be set by the implementer according to the actual situation.

[0090] The embodiment of the present application uses the ratio of the initial laser cleaning power in the same impurity category and the area corresponding to the impurity area to determine the prediction of the modified laser cleaning power of the impurity area. Since the pollution sources of the impurity areas in the same impurity category are the same, the embodiment of the present application uses the ratio of the area size of the initial laser power of the impurity area to be predicted and the impurity category as the power adjustment parameter of the predicted area. It should be noted that, since the impurities exist in the three-dimensional attachment state, in order to avoid the laser power being too large to cause damage to the wafer, the inhibition coefficient can also be used to limit the power.

[0091] The initial laser cleaning power of all impurity areas is adjusted to obtain the modified laser cleaning power of each impurity area.

[0092] In step S400, the optimal cleaning path of the wafer cleaning is determined according to the path between the modified laser cleaning power and the impurity area.

[0093] The modified laser cleaning power of different impurity areas is obtained through steps S200-S300, and then the optimal cleaning path of the laser cleaning is obtained by using the optimal algorithm. The main purpose of planning the cleaning path to clean the wafer is to minimize the overall cleaning time and minimize the number of laser cleaning power adjustments when cleaning different areas of impurities. That is, when determining the optimal cleaning path, two aspects are considered, one is to minimize the time, because the size of all impurity areas on the wafer is fixed, that is, the laser cleaning speed is fixed, so the only way to minimize the cleaning time is to reasonably arrange the cleaning path. Therefore, in the embodiment of the present application, the shortest path is limited between different impurity areas. The other aspect is to minimize the total number of laser cleaning power adjustments, which is represented by the difference accumulation of the total laser cleaning power of different areas in the embodiment of the present application.

[0094] The distance between the two adjacent impurity areas in the cleaning path is used as the first parameter value, and the difference between the modified laser cleaning power of the two adjacent impurity areas in the cleaning path is used as the second parameter value, that is, the absolute value of the difference between the modified laser cleaning power of the two adjacent impurity areas in the cleaning path is used as the second parameter value; the first parameter value and the second parameter value are weighted and summed to obtain a third parameter value.

[0095] The absolute value of the difference between the modified laser cleaning power of the two adjacent impurity areas in the cleaning path can also be rounded down, and the result value after rounding down is used as the second parameter value.

[0096] The cleaning path of the wafer is continuously adjusted, and the cleaning path corresponding to the minimum third parameter value is used as the optimal cleaning path.

[0097] It can also be understood that, according to the path between the modified laser cleaning power and the impurity area, a target function is constructed to determine the optimal cleaning path of the wafer cleaning. The purpose of obtaining the optimal cleaning path is to minimize the overall cleaning time and minimize the number of laser cleaning power adjustments when cleaning different areas of impurities, so the establishment of the target function can also be based on these two requirements.

[0098] The formula of the target function is: ; wherein, is the target function value; min is the minimum value function; is the path weight coefficient; is the power weight coefficient; N is the number of impurity areas; is the coordinate of the nth impurity area being cleaned in the current path; is the coordinate of the next impurity area to be cleaned; is the modified laser cleaning power of the next impurity area to be cleaned; is the target function value corresponding to the cth cleaning path of the wafer. Obtain The cleaning path with the minimum value is the optimal cleaning path.

[0099] The path weight coefficient and the power weight coefficient are used to balance the importance of the path length and the power adjustment. In the embodiment of the present application, the values of the path weight coefficient and the power weight coefficient are both 1.

[0100] Wherein, the constraint condition of the target function is: (1) each impurity area must be visited once and only once; (2) .

[0101] Solving the target function, the cleaning path corresponding to the minimum value obtained is the optimal cleaning path for wafer cleaning.

[0102] Therefore, the purpose of the constraint condition of the target function here is: first, to avoid multiple stays and multiple cleanings between different areas during laser cleaning, which may cause wafer loss; second, to allow areas with similar laser cleaning power to be cleaned with the same power, avoiding multiple invalid adjustments of the laser cleaning power.

[0103] Correspondingly, it can also be understood that the first parameter value is determined to avoid multiple stays and multiple cleanings between different areas during laser cleaning, which may cause wafer loss; the second parameter value is determined to allow areas with similar laser cleaning power to be cleaned with the same power, avoiding multiple invalid adjustments of the laser cleaning power.

[0104] The algorithm used for solving the above objective function is a particle swarm optimization algorithm, which will not be described here. The particle swarm optimization algorithm is used to solve the objective function to obtain the optimal cleaning path of the wafer cleaning.

[0105] After obtaining the optimal cleaning path of the laser cleaning wafer, the surface of the wafer is cleaned according to the optimal cleaning path, and the specific steps of the laser cleaning wafer are as follows:

[0106] First, perform equipment inspection to ensure that the laser cleaning equipment is operating normally, including the laser, optical system and safety protection device;

[0107] Second, perform wafer positioning to place the wafer on the cleaning table and ensure that it is fixed and stable to avoid movement during cleaning;

[0108] Third, perform information collection to collect the image of the wafer surface and pre-process it to obtain the surface image of the wafer and the impurity area on the wafer surface;

[0109] Fourth, perform power prediction and path calculation: obtain the corrected laser cleaning power and the optimal cleaning path during the wafer cleaning process according to the above method;

[0110] Fifth, perform wafer cleaning to use the corrected laser cleaning power and the optimal cleaning path to perform laser point scanning cleaning on different impurity areas;

[0111] Sixth, perform cooling to allow the wafer to cool naturally after cleaning to avoid thermal stress caused by rapid cooling;

[0112] Seventh, perform detection to use a microscope or other detection equipment to check the cleaning effect and confirm whether the contaminants have been effectively removed;

[0113] Eighth, perform data recording to record the parameters and detection results during the cleaning process for subsequent analysis and improvement.

[0114] In summary, the present application relates to the field of semiconductor device processing technology. The method analyzes the impurity area of the wafer to predict and correct the laser cleaning power, obtain the corrected laser cleaning power and the optimal cleaning path of the wafer cleaning, and realize the cleaning operation on the wafer surface.

[0115] Please refer to Figure 3 which shows a high-efficiency laser cleaning system for wafer surface cleaning provided by an embodiment of the present application, which includes the following modules:

[0116] The area extraction module 10 is used to obtain the surface image of the wafer and extract the impurity area in the surface image of the wafer.

[0117] The feature analysis module 20 is configured to analyze the morphological features of the impurity region, determine a feature impurity coefficient of the impurity region, analyze the color features of the impurity region, determine an organic residue coefficient of the impurity region, and classify the impurity region based on the feature impurity coefficient and the organic residue coefficient respectively to obtain a plurality of impurity categories.

[0118] The power determination module 30 is configured to adjust the initial laser cleaning power of the impurity region according to the impurity category to which each impurity region belongs, to obtain a corrected laser cleaning power.

[0119] The path determination module 40 is configured to determine an optimal cleaning path for wafer cleaning according to the corrected laser cleaning power and the path between the impurity region.

[0120] Optionally, the transmission medium can be a wired link such as, but not limited to, a coaxial cable, an optical fiber, a digital subscriber line, etc., or a wireless link such as, but not limited to, Wireless Fidelity (WIFI), Bluetooth, and a mobile device network, etc.

[0121] It should be noted that the apparatus provided in the above embodiments is only exemplarily described above by dividing the above functional modules, and in actual applications, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the above described functions.

[0122] Figure 4 is a structural schematic diagram of a computer device provided by an embodiment of the present application. As shown in the example, Figure 4 the computer device 500 includes a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and running on the processor 520, wherein when the processor 520 executes the computer program 530, the computer device can execute any of the above-described efficient laser cleaning methods for wafer surface cleaning.

[0123] In addition, an embodiment of the present application also protects an apparatus which can include a memory and a processor, wherein the memory stores executable program code, and the processor is configured to call and execute the executable program code to execute the efficient laser cleaning method for wafer surface cleaning provided by the embodiment of the present application.

[0124] The embodiment of the present application can divide the functions of the device according to the above method examples, for example, each function module can be divided, two or more functions can be integrated in one processing module, and the integrated module can be realized in the form of hardware. It should be noted that the division of the modules in the embodiment is illustrative, and is only a logical function division. In actual implementation, another division mode can be used.

[0125] In the case of dividing each module according to each function, the device can further include a signal uploading module, a determining module, an adjusting module, and the like. It should be noted that all related contents of each step involved in the above method embodiment can be cited to the function description of the corresponding function module, and will not be described here.

[0126] It should be understood that the device provided by the embodiment of the present application is used to execute the above-mentioned efficient laser cleaning method for wafer surface cleaning, and thus the same effect as the above-mentioned implementation method can be achieved.

[0127] In the case of using an integrated unit, the device can include a processing module and a storage module. When the device is applied to equipment, the processing module can be used to control and manage the actions of the equipment. The storage module can be used to support the equipment to execute mutual program codes and the like. The processing module can be a processor or a controller, which can realize or execute various exemplary logical blocks, modules and circuits described in combination with the disclosure of the present application. The processor can also be a combination of computing functions, such as one or more microprocessor combinations, a combination of digital signal processing (Digital Signal Processing, DSP) and microprocessor, and the like. The storage module can be a memory.

[0128] In addition, the device provided by the embodiment of the present application can be a chip, an assembly or a module. The chip can include a connected processor and a memory. The memory is used to store instructions. When the processor calls and executes the instructions, the chip can execute the efficient laser cleaning method for wafer surface cleaning provided by the above-mentioned embodiment.

[0129] The embodiment of the present application further provides a computer readable storage medium, which stores computer program codes. When the computer program codes run on a computer, the computer executes the above-mentioned related method steps to realize the efficient laser cleaning method for wafer surface cleaning provided by the above-mentioned embodiment.

[0130] The embodiment of the present application further provides a computer program product. When the computer program product runs on a computer, the computer executes the above-mentioned related steps to realize the efficient laser cleaning method for wafer surface cleaning provided by the above-mentioned embodiment.

[0131] Among them, the device, computer readable storage medium, computer program product or chip provided by the embodiments of the present application are used to execute the corresponding methods provided above, so the beneficial effects that can be achieved are referred to the beneficial effects of the corresponding methods provided above, which will not be repeated here. Through the description of the above implementation mode, those skilled in the art can understand that, for the convenience and brevity of description, only the above-mentioned division of functional modules is taken as an example, and in actual application, the above-mentioned functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In the embodiments provided by the present application, it should be understood that the disclosed device and method can be implemented in other ways.

[0132] The device embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed each other can be indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0133] It should also be noted that the terms "comprising", "including", or any other variant thereof, are intended to cover non-exclusive inclusion, so that processes, methods, articles or terminal devices including a series of elements not only include those elements, but also include other elements not explicitly listed or inherent to such processes, methods, articles or terminal devices. Without more limitations, the element defined by the statement "including a" does not exclude the presence of additional identical elements in the process, method, article or terminal device including the element.

[0134] It should be noted that: the above-mentioned sequence of the embodiments of the present application is only for description, not representing the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0135] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other, and each embodiment mainly describes the difference from other embodiments.

[0136] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application.

Claims

1. A high efficiency laser cleaning method for wafer surface cleaning, characterized in that, The method comprises the following steps: Obtaining a surface image of a wafer; extracting a foreign matter area in the surface image of the wafer; wherein the method for obtaining the foreign matter area is: fitting an envelope line of a gray histogram of the surface image of the wafer, determining a peak value on the envelope line; obtaining a mean value of each peak value as a characteristic gray value; taking a pixel point corresponding to the characteristic gray value as a seed point, and performing region growing based on the seed point to obtain a plurality of growth regions; taking other growth regions except the largest growth region as the foreign matter area in the surface image of the wafer; Analyzing a morphological feature of the foreign matter area to determine a characteristic foreign matter coefficient of the foreign matter area; analyzing a color feature of the foreign matter area to determine an organic residue coefficient of the foreign matter area; classifying the foreign matter area based on the characteristic foreign matter coefficient and the organic residue coefficient respectively to obtain a plurality of foreign matter categories; Adjusting an initial laser cleaning power of the foreign matter area according to a foreign matter category to which each foreign matter area belongs to obtain a corrected laser cleaning power; Determining an optimal cleaning path of wafer cleaning according to a path between the corrected laser cleaning power and the foreign matter area.

2. The efficient laser cleaning method for wafer surface cleaning according to claim 1, wherein, The calculation formula of the characteristic foreign matter coefficient is: ； wherein, is a characteristic impurity coefficient of the nth impurity region; e is a natural constant; is a probability that a pixel point with a gray value of g appears in the eight-neighborhood of a pixel point with a gray value of G in the nth impurity region; is a probability that a pixel point with a gray value of G appears in the nth impurity region; is a logarithm function with base 2.

3. The efficient laser cleaning method for wafer surface cleaning according to claim 1, wherein, The analysis of the color feature of the foreign matter area to determine the organic residue coefficient of the foreign matter area comprises: Taking a coefficient of variation of gray values of all pixel points in the foreign matter area as the organic residue coefficient of the foreign matter area.

4. The efficient laser cleaning method for wafer surface cleaning according to claim 1, wherein, The classification of the foreign matter area based on the characteristic foreign matter coefficient and the organic residue coefficient respectively to obtain a plurality of foreign matter categories comprises: Taking the characteristic foreign matter coefficient as a distance between the foreign matter areas, and dividing the foreign matter areas into two clustering clusters, taking a clustering cluster with a minimum value of variance of gray values of pixel points in the two clustering clusters as a first foreign matter category; taking a clustering cluster with a maximum value of variance of gray values of pixel points in the two clustering clusters as a foreign matter category to be distributed; Taking the organic residue coefficient as a distance between the foreign matter areas in the foreign matter category to be distributed, and dividing the foreign matter areas in the foreign matter category to be distributed into two clustering clusters as a second foreign matter category and a third foreign matter category.

5. The efficient laser cleaning method for wafer surface cleaning according to claim 1, wherein, The method for obtaining the initial laser cleaning power of the foreign matter area comprises: Taking a foreign matter area with the smallest area in each foreign matter category as a starting area, and determining a best laser cleaning power of the starting area; taking the best laser cleaning power of the starting area as the initial laser cleaning power of the foreign matter area in the foreign matter category.

6. The efficient laser cleaning method for wafer surface cleaning according to claim 5, wherein, The adjustment of the initial laser cleaning power of the foreign matter area according to the foreign matter category to which each foreign matter area belongs to obtain the corrected laser cleaning power comprises: Taking a ratio of areas of the foreign matter area and a starting area of the foreign matter category to which the foreign matter area belongs to as a power adjustment value of the foreign matter area; Taking a product of the power adjustment value of the foreign matter area and the initial laser cleaning power as the corrected laser cleaning power.

7. The efficient laser cleaning method for wafer surface cleaning according to claim 1, wherein, The determination of the optimal cleaning path of wafer cleaning according to the path between the corrected laser cleaning power and the foreign matter area comprises: The distance between two adjacent impurity regions in the cleaning path is taken as the first parameter value, and the difference in the modified laser cleaning power between two adjacent impurity regions in the cleaning path is taken as the second parameter value; the first parameter value and the second parameter value are weighted and summed to obtain a third parameter value; The cleaning path of the wafer is continuously adjusted, and the cleaning path corresponding to the minimum third parameter value is taken as the optimal cleaning path.

8. The efficient laser cleaning method for wafer surface cleaning according to claim 5, wherein, The method for obtaining the optimal laser cleaning power of the starting region is as follows: The laser cleaning power is gradually increased from 0, and the cleaning effect under the current laser cleaning power is artificially judged. When the cleaning effect remains unchanged after the laser cleaning power is changed, the initial laser cleaning power at which the cleaning effect remains unchanged is taken as the optimal laser cleaning power of the starting region.

9. A high efficiency laser cleaning system for wafer surface cleaning, characterized by, The system comprises the following modules: The region extraction module is configured to obtain a surface image of the wafer, and extract an impurity region in the surface image of the wafer. The impurity region is obtained by fitting an envelope line of a gray histogram of the surface image of the wafer, determining a peak value on the envelope line, obtaining a mean value of each peak value as a characteristic gray value, and taking a pixel point corresponding to the characteristic gray value as a seed point, and performing region growing based on the seed point to obtain a plurality of growth regions, and taking other growth regions except the largest growth region as the impurity region in the surface image of the wafer. The feature analysis module is configured to analyze the morphological features of the impurity region to determine a characteristic impurity coefficient of the impurity region, analyze the color features of the impurity region to determine an organic residue coefficient of the impurity region, and classify the impurity region based on the characteristic impurity coefficient and the organic residue coefficient to obtain a plurality of impurity categories. The power determination module is configured to adjust the initial laser cleaning power of the impurity region according to the impurity category to which each impurity region belongs, and obtain a modified laser cleaning power. The path determination module is configured to determine an optimal cleaning path for cleaning the wafer according to the path between the modified laser cleaning power and the impurity region.

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