A semiconductor thin film quality analysis method and system

Abstract

The application relates to a semiconductor film quality analysis method and system, which comprises the following steps: S10, acquiring an image of a semiconductor film to be measured and selecting an effective area of the image of the semiconductor film to be measured; S20, selecting a plurality of analysis points in the effective area, acquiring a color model of the analysis points, and extracting pixel attribute values of the color model of the analysis points; S30, calculating the standard deviation of the pixel attribute values of the analysis points, and if the standard deviation of the pixel attribute values of the analysis points meets a first preset value range, determining that the uniformity of the semiconductor film to be measured is qualified; and / or statistically analyzing the proportion of the number of analysis points greater than a second preset value in the effective area, and if the proportion of the number of analysis points is less than a third preset value, determining that the perforation amount of the semiconductor film to be measured is qualified.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of semiconductor thin film detection, and particularly relates to a semiconductor thin film quality analysis method and system. BACKGROUND

[0002] Perovskite solar cells are one of the new photovoltaic materials developed in the past decade, and have the advantages of high photoelectric conversion efficiency and low manufacturing cost. However, the efficiency of large-area devices is still limited by the high-quality preparation of each thin film layer in the device structure, especially the core perovskite thin film layer.

[0003] The quality of the perovskite thin film has a great influence on the efficiency of the perovskite solar cell, and therefore the detection of the thin film quality is particularly important. At present, the detection of the thin film quality mainly involves the impurity holes, in-wafer uniformity, batch uniformity, and thin film thickness of the thin film. The existing method for detecting the thin film quality mainly involves taking a picture of the thin film, and then observing the picture by the naked eye to determine the number of impurity holes, the in-wafer uniformity, the batch uniformity, and the thin film thickness. Such a detection method mainly depends on the working experience of the operator, and has a high error rate.

[0004] In view of the problems in the prior art, the application provides a semiconductor thin film quality analysis method and system. SUMMARY

[0005] In view of the problems in the prior art, the application provides a semiconductor thin film quality analysis method and system.

[0006] The technical scheme of the application is as follows:

[0007] A semiconductor thin film quality analysis method comprises the following steps:

[0008] S10: An image of a semiconductor thin film to be detected is obtained, and an effective area of the image of the semiconductor thin film to be detected is selected;

[0009] S20: A plurality of analysis points in the effective area are selected, a color model of the analysis points is obtained, and a pixel attribute value of the color model of the analysis points is extracted;

[0010] S30: The standard deviation of the pixel attribute value of the analysis points is calculated, and if the standard deviation of the pixel attribute value of the analysis points meets a first preset value range, it is determined that the uniformity of the semiconductor thin film to be detected is qualified; and / or

[0011] The proportion of the number of analysis points greater than a second preset value in the effective area is counted, and if the proportion of the number of analysis points is less than a third preset value, it is determined that the perforation amount of the semiconductor thin film to be detected is qualified.

[0012] Further, the step S30 further comprises: calculating the average value of the pixel attribute value of the analysis point, and determining that the thickness of the semiconductor film to be measured is qualified if the average value of the pixel attribute value of the analysis point meets a fourth preset value range.

[0013] Further, the step S30 further comprises:

[0014] S31: obtaining images of semiconductor films of different thicknesses with qualified quality and extracting a plurality of test points as standard sample points, obtaining a color model and a film thickness of the standard sample points, extracting pixel attribute values of the standard sample points, calculating an average value of the pixel attribute values of the standard sample points, and establishing a film thickness-pixel attribute value standard curve;

[0015] S32: obtaining the film thickness of the effective area of the image of the semiconductor film to be measured;

[0016] The middle value of the fourth preset value range is a corresponding pixel attribute value extracted from the film thickness-pixel attribute value standard curve according to the film thickness of the effective area of the image of the semiconductor film to be measured.

[0017] Further, the step S20 further comprises outputting the film thickness of the semiconductor film to be measured after determining that the thickness of the semiconductor film to be measured is qualified.

[0018] Further, the step S10 of obtaining the image of the semiconductor film to be measured comprises:

[0019] The focal length and exposure of the photographing device are selected and fixed, the semiconductor film to be measured is placed above a surface light source, light emitted uniformly by the surface light source passes through the semiconductor film to be measured upwards, and the image of the semiconductor film to be measured is obtained by the photographing device above the semiconductor film to be measured.

[0020] Further, the pixel attribute value of the analysis point in the step S20 is a brightness value, and the second preset value is 80% of the brightness of the surface light source.

[0021] Further, the step S10 of selecting the effective area of the image of the semiconductor film to be measured comprises:

[0022] A plurality of boundary coordinates input by a user are obtained, and an area surrounded by the boundary coordinates is taken as the effective area; or

[0023] A centroid coordinate of the image of the semiconductor film to be measured is obtained, a distance between an edge of the image of the semiconductor film to be measured and the centroid coordinate is calculated at every fixed angle with the centroid coordinate as the center, and a circle with the centroid coordinate as the center and the minimum distance as the radius is taken as the effective area.

[0024] Further, the step S20 of selecting a plurality of analysis points in the effective region comprises:

[0025] acquiring a plurality of test coordinates input by a user, and selecting pixel points corresponding to the test coordinates as the analysis points; or,

[0026] acquiring a plurality of boundary coordinates and a centroid coordinate in the effective region, and selecting pixel points corresponding to the boundary coordinates and the centroid coordinate as the analysis points; or,

[0027] extracting pixel points in the effective region as the analysis points at equal intervals.

[0028] Further, the color model comprises one of a Lab color model and an XYZ color model.

[0029] Further provided is a semiconductor thin film quality analysis system adopting the semiconductor thin film quality analysis method, comprising:

[0030] an image acquisition module, configured to acquire an image of a semiconductor thin film to be measured, and select an effective region of the image of the semiconductor thin film to be measured;

[0031] an analysis point pixel attribute acquisition module, configured to select a plurality of analysis points in the effective region, acquire a color model of the analysis points, and extract pixel attribute values of the analysis points;

[0032] a uniformity analysis module, configured to calculate a standard deviation of the pixel attribute values of the analysis points, and determine that the uniformity of the semiconductor thin film to be measured is qualified if the standard deviation of the pixel attribute values of the analysis points meets a first preset value range; and / or

[0033] a hole analysis module, configured to calculate a proportion of the number of analysis points whose pixel attribute values are greater than a second preset value, and determine that the perforation amount of the semiconductor thin film to be measured is qualified if the proportion of the number of analysis points is less than a third preset value.

[0034] Therefore, the present application provides the following effects and / or advantages:

[0035] The method provided by the present application can determine the film thickness, film thickness uniformity and perforation amount of the semiconductor thin film to be measured by identifying the pixel attribute values (such as brightness) of the image of the semiconductor thin film to be measured, calculating and counting the average value, standard deviation and proportion of the number of analysis points greater than a preset value of the pixel attribute values of a plurality of analysis points, so as to determine whether the quality of the semiconductor thin film meets the requirements.

[0036] Further, the method provided by the present application selects a surface light source to provide a light source, such as a backlight plate. The light emitted by the backlight plate has a color temperature of 6500-7000 K and a brightness of 1000-2000 lux, which can increase the contrast between the normal area and the non-normal area of the semiconductor film to be measured, and is beneficial to confirming the perforation amount of the semiconductor film to be measured.

[0037] Further, the present application uses the image of the semiconductor film with qualified thickness as a standard for measuring the quality of the film, and establishes a thickness-pixel attribute value standard curve as a standard database in the early stage, so as to quantitatively analyze the basic data of the quality of the semiconductor film. After determining the thickness of the semiconductor film to be measured, the thickness-pixel attribute value standard curve can be used to obtain the pixel attribute value in the fixed shooting environment of the backlight source and the focal length, so as to fit the thickness of the semiconductor film.

[0038] It should be understood that the above summary and the following detailed description of the present application are exemplary and explanatory, and are intended to provide further explanation of the present application as claimed. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 A flowchart of a semiconductor film quality analysis method provided by the present application.

[0040] Figure 2 A schematic diagram of a method for obtaining an effective area.

[0041] Figure 3 A schematic diagram of another method for obtaining an effective area.

[0042] Figure 4 A schematic diagram of a semiconductor film of sample 1.

[0043] Figure 5 A schematic diagram of a semiconductor film of sample 2.

[0044] Figure 6 A schematic diagram of a semiconductor film of sample 3.

[0045] Figure 7 A schematic diagram of a semiconductor film of sample 4.

[0046] Figure 8 A schematic diagram of a semiconductor film of sample 5. DETAILED DESCRIPTION

[0047] In order to facilitate the understanding of those skilled in the art, the present application will be further described in detail in combination with the drawings: it should be understood that, in the present embodiment, the order of the steps mentioned can be adjusted according to the actual needs, even can be executed simultaneously or partially simultaneously, except for the order specified.

[0048] Reference Figure 1 A semiconductor thin film quality analysis method, comprising the following steps:

[0049] S10: Obtain an image of a semiconductor thin film to be measured, and select an effective area of the image of the semiconductor thin film to be measured.

[0050] The semiconductor thin film can be a perovskite thin film layer, which can be used to prepare a perovskite solar cell. The semiconductor thin film can be prepared by outputting a corresponding liquid raw material to a preparation platform by a doctor blade coating device, then coating the liquid raw material into a thin film by a doctor blade, and finally drying. In the preparation process, due to the small thickness of the semiconductor thin film, the distance fluctuation between the doctor blade coating device and the preparation platform, and the liquid raw material accumulation at the tail, etc., the prepared semiconductor thin film may have abnormal film thickness, poor uniformity, and holes, etc. Therefore, the film thickness, film thickness uniformity, and perforation of the semiconductor thin film are all parameters that need to be analyzed in the quality detection process of the semiconductor thin film.

[0051] In step S10, obtaining the image of the semiconductor thin film to be measured includes: selecting and fixing the focal length and exposure of the shooting device, placing the semiconductor thin film to be measured above the area light source, and passing the light emitted uniformly by the area light source through the semiconductor thin film to be measured, and obtaining the image of the semiconductor thin film to be measured above the semiconductor thin film to be measured by the shooting device.

[0052] A backlight panel can be used to provide a light source, and the light emitted uniformly by the backlight panel passes through the semiconductor thin film to be measured upwards, so that the semiconductor thin film has a certain color and brightness, and the holes of the semiconductor thin film are highlighted and exposed. The light emitted by the backlight panel has a color temperature of 6500-7000 K and a brightness of 1000-2000 lux. The backlight with a color temperature of 6500-7000 K corresponds to a cold color light, while the perovskite thin film is generally slightly brown, which belongs to warm color tone, and the corresponding color temperature is 2000-3000 K. Using 6500-7000 K, which is far from the color temperature of the perovskite thin film, as the color temperature of the backlight panel light source, the holes of the perovskite thin film are more prominent after being exposed by the light and captured by the camera, which can increase the contrast between the normal and abnormal regions of the semiconductor thin film to be measured, and is beneficial to confirming the perforation amount of the semiconductor thin film to be measured.

[0053] In step S10, selecting the effective area of the image of the semiconductor thin film to be measured includes:

[0054] Obtaining a plurality of boundary coordinates input by a user, and regarding an area surrounded by the boundary coordinates as an effective area; or

[0055] The centroid coordinate of the image of the semiconductor thin film to be measured is obtained, a distance between the edge of the image of the semiconductor thin film to be measured and the centroid is calculated at every fixed angle with the centroid as the center, and a circle with the centroid as the center and the minimum distance as the radius is taken as the effective region.

[0056] Further, in step S10, to obtain the effective region of the image of the semiconductor thin film to be measured, the pixel attribute value of the analysis point to be extracted subsequently is prevented from being other non-measurement region on the sample table, and the effective region of the image of the semiconductor thin film to be measured comprises:

[0057] The first method is that a plurality of boundary coordinates input by a user are obtained, and a region surrounded by the input boundary coordinates is taken as the effective region.

[0058] As shown in the figure, Figure 2 The user can input four boundary coordinates: (x1, y1), (x2, y2), (x3, y3), and (x4, y4), or directly click on the image of the semiconductor thin film to be measured to obtain the boundary coordinates, and then connect the boundary coordinates to form a closed figure, and the region framed by the closed figure is taken as the effective region.

[0059] The second method is that the centroid coordinate of the image of the semiconductor thin film to be measured is obtained, a distance between the edge of the image of the semiconductor thin film to be measured and the centroid is calculated at every fixed angle with the centroid as the center, and a circle with the centroid as the center and the minimum distance as the radius is taken as the effective region. The calculation of the centroid of the figure is a prior art, which can be obtained by processing the document disclosed in "Improvement of Centroid and Matching Tracking Algorithm", Li Qiang, etc., April 2000. As shown in the figure, Figure 3 The centroid coordinate of the image of the semiconductor thin film to be measured is obtained, a plurality of rays are arranged around the centroid coordinate with the centroid coordinate as the center, each ray has a fixed angle, for example, the angle of the ray in the present application is 20°, the distance from the centroid to the edge of the image is calculated for each ray, 18 distances are obtained, the minimum distance in the 18 distances is taken as the radius, and a circle with the centroid coordinate as the center is drawn. The region framed by the circle is taken as the effective region, which can cover the coating film layer part in the image of the semiconductor thin film to be measured as much as possible, and can make the region cover only the semiconductor thin film as much as possible, so that the pixel attribute value of the analysis point to be extracted subsequently is prevented from being other non-measurement region on the sample table.

[0060] S20: A plurality of analysis points in the effective region are selected, a color model of the analysis point is obtained, and a pixel attribute value of the color model of the analysis point is extracted.

[0061] In the embodiment, the pixel attribute value includes chrominance value, luminance value, saturation, transmittance and the like. The embodiment is described by taking the luminance value as an example. In other embodiments, the chrominance value, saturation and transmittance are used to determine the quality of the semiconductor film in the same way as the luminance value.

[0062] Optionally, the analysis points can be manually selected coordinates in the effective area, or can be coordinate points obtained according to the following method.

[0063] Further, the step S20 of selecting a plurality of analysis points in the effective area includes:

[0064] obtaining a plurality of test coordinates input by a user, and selecting pixel points corresponding to the test coordinates as the analysis points; or

[0065] obtaining a plurality of boundary coordinates and a centroid coordinate in the effective area, and selecting pixel points corresponding to the boundary coordinates and the centroid coordinate as the analysis points; or

[0066] extracting pixel points in the effective area as the analysis points at equal intervals.

[0067] In the step S20 of the embodiment, the plurality of analysis points in the effective area includes:

[0068] In a first method, a plurality of test coordinates input by a user are obtained, and pixel points corresponding to the test coordinates are selected as the analysis points. The coordinates input by the user can be manually input coordinate values (x1, y1), (x2, y2), (x3, y3)…(xn, yn), or can be directly clicked on a plurality of points in the effective area by a mouse or the like.

[0069] In a second method, a plurality of boundary coordinates and a centroid coordinate in the effective area are obtained, and pixel points corresponding to the boundary coordinates and the centroid coordinate are selected as the analysis points. Since the thickness of the wet film is generally gradually thinned in the coating direction when the semiconductor film is coated, the boundary coordinates and the centroid coordinate in the effective area are the most representative and can better reflect the thickness change of the semiconductor film.

[0070] In a third method, pixel points in the effective area are extracted as the analysis points at equal intervals. For example, a point is selected as the analysis point at equal intervals in a matrix manner in the effective area.

[0071] Further, the color model includes one of a Lab color model and an XYZ color model. The luminance value is taken as the pixel attribute value as an example. The luminance value can be an L value of the Lab color model or a Y value of the XYZ color model.

[0072] Since the pixel point corresponding to the analysis point is selected as the data basis for judging the quality of the semiconductor thin film in the embodiment, the color model of the pixel point has multiple types, such as Lab color model, XYZ color model, etc. The Lab color model is established according to an international standard for color measurement formulated by Commission International Eclairage (CIE) in 1931. The Lab color model is composed of three elements, one element is brightness (L), and a and b are two color channels. The color included by a is from dark green (low brightness value) to gray (medium brightness value) to bright pink (high brightness value); b is from bright blue (low brightness value) to gray (medium brightness value) to yellow (high brightness value). The XYZ color model is based on the RGB system, and uses mathematical methods to select three ideal primary colors to replace the actual three primary colors, so that the spectral tristimulus values and color coordinates r, g, and b in the CIE-RGB system are all changed to positive values, including color coordinates and brightness coordinates.

[0073] S30: calculating the standard deviation of the pixel attribute values of the analysis points, if the standard deviation of the pixel attribute values of the analysis points meets a first preset value range, determining that the uniformity of the semiconductor thin film to be measured is qualified; and / or

[0074] The proportion of the number of pixels greater than the second preset value in the effective area is counted, and if the proportion of the number of pixels is less than a third preset value, it is determined that the perforation amount of the semiconductor thin film to be measured is qualified.

[0075] Further, in step S20, the pixel attribute value of the analysis point is a brightness value, and the second preset value is 80% of the brightness of the area light source.

[0076] The second preset value of the embodiment is 80% of the brightness of the area light source, for example, in the picture taken by the camera, the brightness of the picture taken against the blank area, that is, the back light plate, is 255, and the second preset value is 204.

[0077] The first preset value range, the second preset value, and the third preset value can be set through the process experience in the actual industrial process, that is, the set first preset value range, second preset value, and third preset value meet the requirement that the influence on the yield of the later stage and the performance of the terminal product is small.

[0078] Further, step S30 further includes calculating the average value of the pixel attribute value of the analysis point, and if the average value of the pixel attribute value of the analysis point meets a fourth preset value range, it is determined that the thickness of the semiconductor thin film to be measured is qualified.

[0079] Further, step S20 further includes outputting the film thickness of the semiconductor thin film to be measured after determining that the thickness of the semiconductor thin film to be measured is qualified.

[0080] In the embodiment, the fourth preset value interval can be obtained by process experience and blade data in actual industrial process. For example, the thickness value of a semiconductor thin film with a certain coating amount is obtained by blade test, the thickness value is taken as the center value of the fourth preset value interval corresponding to the coating amount, and the upper limit and the lower limit of the fourth preset value interval are set under the requirement of less affecting the yield of the later stage and the performance of the end product.

[0081] Further, the step S30 further comprises:

[0082] S31: obtaining images of a plurality of qualified semiconductor thin films with different thicknesses, extracting a plurality of test points as standard sample points, obtaining color models and thicknesses of the standard sample points, extracting pixel attribute values of the standard sample points, calculating average values of the pixel attribute values of the standard sample points, and establishing a thickness-pixel attribute value standard curve;

[0083] In the embodiment, the color models and thicknesses of the standard sample points can be obtained by blade test, thereby providing a data basis for subsequent extraction of pixel attribute values, calculation of average values of pixel attribute values, and establishment of a curve.

[0084] S32: obtaining the thickness of the effective area of the image of the semiconductor thin film to be measured;

[0085] In the embodiment, the thickness of the effective area of the image of the semiconductor thin film to be measured is obtained, which can be estimated by coating amount. The thickness value of the semiconductor thin film corresponding to the coating amount is obtained by blade test, and the value is taken as the thickness corresponding to the coating amount. For example, in the process of preparing a semiconductor thin film, the coating amount output by the blade coating equipment is X, and the thickness of the semiconductor thin film obtained after subsequent drying is Y, and a functional relationship between X and Y is established, so that the coating amount output by the subsequent blade coating equipment can be directly obtained, and the thickness of the current semiconductor thin film can be directly calculated according to the functional relationship between X and Y. Alternatively, the thickness of the semiconductor thin film can be directly tested by blade test.

[0086] The middle value of the fourth preset value interval is the corresponding pixel attribute value extracted from the thickness-pixel attribute value standard curve according to the thickness of the effective area of the image of the semiconductor thin film to be measured.

[0087] Through the above steps, the result of whether the quality of the semiconductor thin film is qualified can be output. In actual industrial production, the main measurement indexes of thin film quality analysis are usually determined according to the production line stage of the semiconductor thin film. For example, when the semiconductor thin film production line is started or stopped abnormally, in order to strictly confirm the influence of each process condition on the film forming quality, the uniformity, the hole quantity and the film thickness of the semiconductor thin film to be tested can be respectively confirmed by a person skilled in the art according to the technical solution; when a large number of semiconductor thin films are produced in the semiconductor thin film production line, in order to save production capacity and reduce offline test waiting time, the uniformity, the hole quantity and the film thickness of the semiconductor thin film to be tested can be single-index sampling or double-index inspection.

[0088] The application further provides a semiconductor thin film quality analysis system adopting the semiconductor thin film quality analysis method, comprising:

[0089] An image acquisition module is configured to acquire an image of the semiconductor thin film to be tested and select an effective area of the image of the semiconductor thin film to be tested.

[0090] An analysis point pixel attribute acquisition module is configured to select a plurality of analysis points in the effective area, acquire a color model of the analysis points and extract pixel attribute values of the analysis points.

[0091] An uniformity analysis module is configured to calculate a standard deviation of the pixel attribute values of the analysis points, and if the standard deviation of the pixel attribute values of the analysis points meets a first preset value range, it is determined that the uniformity of the semiconductor thin film to be tested is qualified; and / or

[0092] A hole analysis module is configured to calculate a proportion of the number of analysis points whose pixel attribute values are greater than a second preset value, and if the proportion of the number of analysis points is less than a third preset value, it is determined that the hole quantity of the semiconductor thin film to be tested is qualified.

[0093] A semiconductor thin film quality analysis system is the same as the principle of a semiconductor thin film quality analysis method, and will not be described here.

[0094] Embodiment one

[0095] The color model of this embodiment selects a Lab color model, the pixel attribute value adopts a brightness L value of the Lab color model, and the brightness L value of the analysis points is extracted. The area light source adopts a backlight plate with 6500-7000 K and 1000-2000 lux.

[0096] The effective area operation of this embodiment selects the selection method shown in Figure 2 , that is, the effective area is selected by clicking the upper left (x1, y1), the upper right (x2, y2), the lower left (x3, y3) and the lower right (x4, y4) respectively by a mouse, and a plurality of analysis points are selected in the effective area surrounded by the four coordinates.

[0097] The same batch and qualified semiconductor thin film is selected as a standard sample, and a plurality of standard sample points of the standard sample are extracted, the brightness values of each sample point are tested, and the brightness average value and brightness standard deviation range of the standard sample points are calculated. The proportion range of the number of sample points greater than the second preset value in the effective area of each semiconductor thin film is 19.935, 0.314-5.155, and 0.431%-1.174%.

[0098] The first preset value interval of the embodiment adopts the brightness standard deviation interval of the standard sample points, that is, 0.314-5.155; the second preset value is 80% of the brightness of the backlight panel. If the measured blank area brightness value of the embodiment is 255, the second preset value is 204, and all analysis points greater than the second preset value in the effective area are analysis points with brightness values greater than 204; the third preset value adopts the sample point proportion range of the standard sample points, that is, 0.431%-1.174%; the center point of the fourth preset value interval adopts the brightness average value of the standard sample points, and the upper and lower range is set to be floating by 5%. The floating range meets the requirement that the influence on the yield of the later stage and the performance of the terminal product is small, that is, the fourth preset value interval is 19.935±5%. Semiconductor thin film samples 1-5 are detected respectively, and the semiconductor thin film schematic diagram is shown in Figures 4-8 , and the test results are shown in Tables 1-5.

[0099] Table 1: Test results of each analysis point of semiconductor thin film sample 1

[0100]

[0101] Table 2: Test results of each analysis point of semiconductor thin film sample 2

[0102]

[0103] Table 3: Test results of each analysis point of semiconductor thin film sample 3

[0104]

[0105] Table 4: Test results of each analysis point of semiconductor thin film sample 4

[0106]

[0107] Table 5: Test results of each analysis point of semiconductor thin film sample 5

[0108]

[0109] Table 6: Test results of semiconductor thin film samples 1-5

[0110]

[0111] As shown in Tables 1-6, the semiconductor thin film samples 1-5 are all unqualified, and the film thickness, film thickness uniformity, and number of perforations of the semiconductor thin film can be quickly evaluated.

[0112] Those skilled in the art will appreciate that embodiments of the application can be supplied as methods, systems, or computer program products. Accordingly, the application can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the application can be embodied in the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk memory, CD-ROMs, optical storage media, etc.) having computer usable program code embodied therein.

[0113] The present application is described in reference to the flowchart and / or block diagrams of the method, apparatus (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce the functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for performing the function specified by the flow or flows and / or block or blocks.

[0114] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including instruction means that implement the function specified in the flowchart and / or block diagram flow or flows and / or block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for performing the function specified by the flow or flows and / or block or blocks.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable data processing apparatus to produce a computer implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide the functions specified in the flowchart and / or block diagram flow or flows and / or block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for performing the function specified by the flow or flows and / or block or blocks.

[0116] It should be noted that in the claims the reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps other than those listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. It is further stated that a plurality of items, structural parts and / or components can be presented in a claim in the format of "at least one", for example "one or more". The application can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the claims the word "comprising" does not exclude other elements being added. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The word "first", "second" and the like do not imply any order, quantity, or importance, but rather are used to distinguish one element from another. The terms "preferably", "preferred", "preferably", "desired", "desirable", "suitable", "in an embodiment", or "in some embodiments" are no means to restrict or narrow the application or any exemplified embodiment. The term "exemplary" in the context of this specification means "serving as an example, instance, or illustration;" and not "preferred" over other examples. The disclosure of at least one feature recited in any claim can not imply that all of the features and or objects have to be combined to provide the technical effect that is stated in that claim. The word "comprising" does not exclude the presence of elements or steps other than those listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. It is further stated that a plurality of items, structural parts and / or components can be presented in a claim in the format of "at least one", for example "one or more". The application can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the claims the word "comprising" does not exclude other elements being added. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The word "first", "second" and the like do not imply any order, quantity, or importance, but rather are used to distinguish one element from another. The terms "preferably", "preferred", "preferably", "desired", "desirable", "suitable", "in an embodiment", or "in some embodiments" are no means to restrict or narrow the application or any exemplified embodiment. The term "exemplary" in the context of this specification means "serving as an example, instance, or illustration;" and not "preferred" over other examples. The disclosure of at least one feature recited in any claim can not imply that all of the features and or objects have to be combined to provide the technical effect that is stated in that claim.

[0117] Although preferred embodiments of the application have been described herein, it will be apparent to those skilled in the art that various modifications and changes can be made to the embodiments without departing from the spirit and scope of the application. Accordingly, it is intended that all such modifications and changes be included within the scope of the application as claimed.

[0118] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

[0119] In the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connecting", "fixed", and the like should be interpreted broadly, for example, can be fixed connection, can also be detachable connection, or integral; can be mechanical connection, can also be electrical connection; can be direct connection, can also be indirect connection through an intermediate medium, can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0120] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms should not be understood as necessarily referring to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of different embodiments or examples without contradiction.

Claims

1. A method of semiconductor thin film mass analysis, comprising: The method comprises the following steps: S10: acquiring an image of a semiconductor film to be measured, and selecting an effective area of the image of the semiconductor film to be measured; wherein the acquisition of the image of the semiconductor film to be measured comprises: selecting and fixing a focal length and an exposure of a shooting device, placing the semiconductor film to be measured above a surface light source, uniformly emitting light upward through the semiconductor film to be measured by the surface light source, and acquiring the image of the semiconductor film to be measured by the shooting device above the semiconductor film to be measured; S20: selecting a plurality of analysis points in the effective area, acquiring a color model of the analysis points, and extracting pixel attribute values of the color model of the analysis points; wherein the color model comprises a Lab color model or an XYZ color model; and the pixel attribute values of the analysis points are luminance values; S30: calculating a standard deviation of the pixel attribute values of the analysis points, determining that the uniformity of the semiconductor film to be measured is qualified if the standard deviation of the pixel attribute values of the analysis points meets a first preset value interval, and / or statistically determining a proportion of the number of analysis points in the effective area that is greater than a second preset value, and determining that the perforation amount of the semiconductor film to be measured is qualified if the proportion of the number of analysis points is less than a third preset value; wherein the first preset value interval is 0.314-5.155, the second preset value is 80% of the luminance of the surface light source, and the third preset value is 0.431%-1.174%; The step S30 further comprises: calculating an average value of the pixel attribute values of the analysis points, and determining that the thickness of the semiconductor film to be measured is qualified if the average value of the pixel attribute values of the analysis points meets a fourth preset value interval; The step S30 further comprises: S31: acquiring images of a plurality of semiconductor films of different thicknesses that are qualified in quality and extracting a plurality of test points as standard sample points, acquiring color models and thicknesses of the standard sample points, extracting pixel attribute values of the standard sample points, calculating an average value of the pixel attribute values of the standard sample points, and establishing a thickness-pixel attribute value standard curve; and S32: acquiring a thickness of the effective area of the image of the semiconductor film to be measured; and a middle value of the fourth preset value interval is a corresponding pixel attribute value extracted from the thickness-pixel attribute value standard curve according to the thickness of the effective area of the image of the semiconductor film to be measured.

2. A method of semiconductor thin film mass analysis according to claim 1, wherein, The step S20 further comprises outputting the thickness of the semiconductor film to be measured after determining that the thickness of the semiconductor film to be measured is qualified.

3. The method of claim 1, wherein the semiconductor thin film is a semiconductor thin film of a compound semiconductor. The selection of the effective area of the image of the semiconductor film to be measured in the step S10 comprises: acquiring a plurality of boundary coordinates input by a user, and taking an area surrounded by the boundary coordinates as the effective area; or acquiring a centroid coordinate of the image of the semiconductor film to be measured, calculating distances between edges of the image of the semiconductor film to be measured and the centroid coordinate at fixed angles, and taking a circle with the centroid coordinate as a center and a minimum distance as a radius as the effective area.

4. The method of claim 1, wherein the semiconductor thin film is a semiconductor thin film of a compound semiconductor. The selection of the plurality of analysis points in the effective area in the step S20 comprises: Obtaining several test coordinates input by a user, selecting pixel points corresponding to the test coordinates as analysis points; or Obtaining several boundary coordinates and a centroid coordinate in the effective area, selecting pixel points corresponding to the boundary coordinates and the centroid coordinate as analysis points; or Extracting pixel points in the effective area as analysis points at equal intervals.

5. A semiconductor thin film mass analysis system, characterized by comprising: The semiconductor thin film quality analysis method of any one of claims 1-4 comprises: An image acquisition module, configured to acquire an image of a semiconductor thin film to be measured, and select an effective area of the image of the semiconductor thin film to be measured; An analysis point pixel attribute acquisition module, configured to select several analysis points in the effective area, acquire a color model of the analysis points, and extract pixel attribute values of the analysis points; A uniformity analysis module, configured to calculate a standard deviation of the pixel attribute values of the analysis points, and determine that the uniformity of the semiconductor thin film to be measured is qualified if the standard deviation of the pixel attribute values of the analysis points meets a first preset value range; and / or A hole analysis module, configured to calculate a proportion of the number of analysis points whose pixel attribute values are greater than a second preset value, and determine that the perforation amount of the semiconductor thin film to be measured is qualified if the proportion of the number of analysis points is less than a third preset value.

Images