Precision estimation method, quality evaluation method and manufacturing method of precision metal mask plate

Abstract

The invention provides a precision estimation method, a quality evaluation method and a manufacturing method of a precision metal mask plate. The precision estimation method comprises the following steps: taking a to-be-tested precise metal mask plate without net opening, selecting a plurality of pixel holes in the to-be-tested precise metal mask plate as a plurality of test points, and arranging the plurality of selected pixel holes in a plurality of rows; respectively acquiring coordinate data of the plurality of test points; for each row of test points, a reference straight line is established, the reference straight line passes through at least two test points in the row of test points, and the distance between each test point in the row of test points and the reference straight line is obtained to serve as a precision estimated value of the row of test points in the net stretching direction after net stretching; a reference arc is established, the reference arc passes through at least three test points in the row of test points, and the distance between each test point in the row of test points and the reference arc is obtained to serve as a precision estimated value of the row of test points perpendicular to the net stretching direction after net stretching.

Description

Technical Field

[0001] This application relates to the field of metal photomasks used in the fabrication of OLED display panels, and more particularly to a method for predicting the accuracy, assessing the quality, and fabricating a precision metal photomask. Background Technology

[0002] A fine metal mask (FMM) is the core evaporation fixture for manufacturing active-matrix organic light-emitting diode (AMOLED) display panels. Its manufacturing and use typically involve: first, etching millions of micron-sized pixel holes into a thin metal sheet to form the FMM; then, using a precision mesh stretching process, stretching and welding the FMM onto a frame to achieve the required pixel hole positioning accuracy; finally, placing it into the vacuum chamber of an evaporation machine for depositing organic light-emitting materials.

[0003] Due to factors such as material stress and etching process fluctuations, there is an inherent deviation between the actual and designed pixel hole positions in the fabricated FMM. To ensure extremely high positional accuracy after screen stretching, an inward shrinkage rate is preset during FMM design, and tension is applied during screen stretching to extend it to the theoretical position. However, due to the aforementioned manufacturing deviations, the pixel hole positional accuracy of some FMMs may still fail to meet the standards after screen stretching.

[0004] In existing technologies, determining whether a Form-Mounted Machine (FMM) meets the accuracy requirements for wire mesh stretching relies entirely on the final inspection results after stretching. If the inspection fails, the FMM must be disassembled and replaced with a new one for repeated stretching. This approach has significant drawbacks: firstly, it ties up production resources such as the stretching machine and operator time with defective products, resulting in low production efficiency; secondly, for purchased FMMs, the subsequent return and exchange process further increases logistics, time, and economic costs. The fundamental reason is the current lack of a method to effectively predict or determine the positional accuracy of the FMM after stretching before the stretching process, thus preventing the pre-emptive removal of defective products and the optimization of the production process. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, a first aspect of this application provides a method for estimating the accuracy of a precision metal mask plate, used to estimate the accuracy of the precision metal mask plate after it has been stretched. Specifically, the method includes:

[0006] Take the precision metal mask to be tested, which is in an unstretched state;

[0007] Multiple pixel holes on the precision metal mask under test are selected as multiple test points. The selected multiple pixel holes are arranged in multiple rows, and the row direction is the long axis direction of the precision metal mask under test.

[0008] Obtain the coordinate data of multiple test points respectively;

[0009] Perform the following steps for each test case:

[0010] Establish a reference line that passes through at least two test points in the row of test points. Obtain the distance between each test point in the row and the reference line to serve as the accuracy estimate of the test points in the row along the stretching direction after the precision metal mask to be tested is stretched.

[0011] Establish a reference arc that passes through at least three test points in the row of test points. Obtain the distance between each test point in the row and the reference arc to serve as the accuracy estimate of the row of test points perpendicular to the stretching direction after the precision metal mask to be tested is stretched.

[0012] Optionally, the reference line passes through two test points located at both ends of the test point row.

[0013] Optionally, the reference arc passes through two test points located at both ends of the test point row and one test point located in the middle of the test point row.

[0014] Optionally, the plurality of pixel holes include pixel holes located at both ends of the precision metal mask under test along the long axis.

[0015] Optionally, the precision metal mask to be tested has multiple opening units;

[0016] The number of rows and columns of pixel holes selected in each aperture unit is greater than or equal to 3.

[0017] Optionally, the number of rows and columns of the selected pixel holes in each opening unit can be 3 to 7.

[0018] Optionally, the number of rows and columns of the selected pixel holes in each opening unit is 3.

[0019] Optionally, the selected plurality of pixel holes include those in each opening unit:

[0020] Pixel holes located at the four corners;

[0021] Pixel holes located in the middle of the four edges;

[0022] The pixel hole is located in the center.

[0023] Optionally, the precision metal mask to be tested has an odd number of opening cells.

[0024] A second aspect of this application provides a method for quality assessment of a precision metal mask, the method specifically including:

[0025] Take the precision metal mask to be tested, which is in an unstretched state;

[0026] The precision metal mask to be tested is subjected to the precision estimation method described in the first aspect of the technical solution and any of its optional solutions, and the precision estimation value of all test points after the precision metal mask to be tested is stretched is obtained. The precision estimation value includes the precision estimation value along the stretching direction of the stretching and the precision estimation value perpendicular to the stretching direction of the stretching.

[0027] If the accuracy estimates at all test points meet the accuracy threshold range, the precision metal mask under test is deemed qualified.

[0028] Optionally, the accuracy threshold range is from -2μm to 2μm.

[0029] A third aspect of this application provides a method for manufacturing a precision metal mask, which specifically includes the accuracy estimation method described in the solution of the first aspect and any of its optional solutions, or the quality assessment method described in the solution of the second aspect and any of its optional solutions.

[0030] In summary, the precision metal mask accuracy prediction method provided in this application provides a technical means to quantitatively predict the pixel hole position accuracy of a precision metal mask (FMM) before the actual screen is applied. This method addresses the problem of "lack of a pre-screening accuracy prediction method" in the prior art, enabling production personnel to know the potential accuracy performance of the FMM in advance.

[0031] The accuracy prediction method provided in this application embodiment utilizes the coordinate data of a limited number of test points on an unstretched FMM (Fixed Metal Measuring Machine). Prediction can be completed through simple geometric calculations (such as calculating the distance from a point to a specified straight line or arc), effectively distinguishing between qualified products and potentially defective products, providing a reliable quantitative basis for subsequent decision-making. This method requires no expensive specialized equipment or complex algorithms, is easily integrated into existing optical inspection processes, has low implementation costs, and is convenient for widespread application in production lines. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of this application or the background art, the accompanying drawings used in the embodiments of this application or the background art will be described below.

[0033] Figure 1 This is a schematic diagram of the selection of test points in the precision metal mask plate accuracy prediction method provided in this application;

[0034] Figure 2 This is a schematic diagram showing the selection of each opening unit on the mask and the test point in each opening unit in the precision metal mask accuracy prediction method provided in this application.

[0035] Figure 3 In one embodiment of the precision metal mask estimation method provided in this application, the offset along the Y-axis between the actual position of each test point when the mask is not stretched and the ideal position after the design stretching;

[0036] Figure 4 This is a schematic diagram of the execution flow of an embodiment of the precision metal mask estimation method provided in this application.

[0037] The image is labeled as follows:

[0038] 100: Precision metal mask, 110: Aperture unit, 101: Test point;

[0039] n: number of test point columns in a single open cell, m: number of test point rows in a single open cell, Q: number of open cells in the mask. Detailed Implementation

[0040] This application will now be described more fully below with reference to the accompanying drawings. However, this application can be implemented in many different ways and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided herein to make this application more detailed and complete, and to fully convey the scope of this application to those skilled in the art. The same reference numerals denote the same objects throughout the drawings.

[0041] To address or improve upon the aforementioned problems in the prior art, this application first provides a method for predicting the accuracy of a precision metal mask (FMM). This method is used to predict the accuracy of the precision metal mask after it has been stretched. Specifically, as shown in the flowchart— Figure 4 As shown, the method includes:

[0042] S1: Take the precision metal mask to be tested. The precision metal mask to be tested is in an unstretched state.

[0043] S2: Select multiple pixel holes on the precision metal mask to be tested as multiple test points. The selected multiple pixel holes are arranged in multiple rows, and the row direction is the long axis direction of the precision metal mask to be tested.

[0044] S3: Obtain the coordinate data of multiple test points respectively;

[0045] Perform the following steps for each test case:

[0046] S41: Establish a reference line that passes through at least two test points in the row of test points;

[0047] S51: Obtain the distance between each test point in the row and the reference line;

[0048] S61: Obtain the accuracy estimate of the test point along the tension direction of the tensioned wire mesh.

[0049] Specifically, in step S51, the distance between each test point in the row of test points and the reference line is obtained respectively, so as to serve as the accuracy estimate of the row of test points along the stretching direction after the precision metal mask to be tested is stretched in step S61.

[0050] S42: Establish a reference arc that passes through at least three test points in this row of test points;

[0051] S52: Obtain the distance between each test point in the row and the reference arc;

[0052] S62: Obtain the accuracy estimate of the test point in this row perpendicular to the tensioning direction of the tensioning net.

[0053] Specifically, in step S52, the distance between each test point in the row of test points and the reference arc is obtained respectively, so as to serve as the accuracy estimate of the row of test points perpendicular to the stretching direction after the precision metal mask to be tested is stretched in step S62.

[0054] In a typical embodiment, the selection of multiple pixel holes, i.e., the formation of multiple test points, is as follows: Figure 1 As shown, the precision metal mask has multiple aperture cells, and multiple test points in each aperture cell are arranged in a specific pattern. The matrix arrangement.

[0055] That is, the multiple test points formed satisfy:

[0056] Σ p = m × n × Q

[0057] In the above formula, Q represents the number of opening units in the precision metal mask, m represents the number of rows of test points in a single opening unit, and n represents the number of columns of test points in a single opening unit.

[0058] In the preferred embodiment, m≥3, n≥3.

[0059] In a preferred embodiment, m and n take values ​​from 3 to 7 (integers).

[0060] In a preferred embodiment, both m and n are 3.

[0061] In a typical embodiment, the reference line passes through two test points located at both ends of the row of test points. In this embodiment, a straight line (passing through the two test points) is established by connecting the two test points at both ends of a row of test points, and this straight line is used as the reference line.

[0062] In a typical embodiment, the reference arc passes through two test points located at both ends of the row of test points and one test point located in the middle of the row of test points. In this embodiment, an arc is established using two test points at both ends and one test point in the center of a row of test points, and this arc is used as the reference arc.

[0063] In this application, the core meaning of "a test point located in the middle of the test point row" or "a test point in the center" is to select a test point that can represent the positional characteristics of the middle area of ​​the test point row, so as to jointly define a reference arc reflecting the overall curvature trend of the row with the test points at both ends.

[0064] Specifically, when the number of test points in a row is odd, it is preferable to select the test point located in the exact middle of the sequence (i.e., the geometric center). For example, for 5 test points arranged in sequence (points 1 to 5), the central test point is point 3.

[0065] When the number of test points in a row is even, or due to limitations imposed by actual measurement conditions, the "middle test point" or "center test point" can be the test point closest to the geometric center of the row. For example, for 6 test points (points 1 to 6), point 3 or point 4 can both be considered as test points that meet the definition and are "close to the exact center".

[0066] In a preferred embodiment of this application, the step of "acquiring coordinate data of multiple test points" is implemented using a Total Pitch and Critical Dimension measurement equipment (TPCD device).

[0067] Explained, a TPCD device is a high-precision optical coordinate measurement system widely used in the semiconductor and display panel industries. Its core typically includes: a high-resolution optical imaging module (such as a CCD camera with a telecentric lens), a high-precision motion platform (XYZ axes), an autofocus system, and dedicated image processing and coordinate calculation software. By capturing clear optical images of the target and utilizing algorithms such as sub-pixel edge detection, this device can quickly and non-contactly measure the absolute or relative coordinates of specific feature points on a sample with sub-micron repeatability (typically 0.1μm to 0.5μm).

[0068] Using TPCD equipment for coordinate acquisition has significant advantages: First, non-contact measurement avoids potential physical damage to the delicate and fragile FMM; second, high precision and repeatability ensure the reliability of input data, which is the basis for accurate prediction in the future; third, the highly automated process can be integrated with the production line to achieve rapid, batch online or offline inspection, meeting the efficiency requirements of industrial applications.

[0069] In the embodiments of this application, in order to accurately reflect the offset direction of the test point relative to the reference straight line and the reference arc, the "distance" between the test point and the reference straight line and the reference arc is calculated and recorded using directional distance.

[0070] For the reference line (equation is) The direction pointed to by its normal vector (A, B) is defined as the positive direction, and the other side as the negative direction. Test point (x p y p The formula for calculating the directed distance d from the line is:

[0071]

[0072] According to this formula, when the test point is located on the positive side, d > 0; when it is located on the negative side, d < 0; and when it is on a straight line, d = 0. The distance values ​​recorded in the examples (such as Tables 3 and 4 below) are calculated according to this directed distance formula, and their positive or negative signs indicate the offset direction of the test point relative to the reference line.

[0073] Similarly, for the reference arc (equation is...) To characterize its bending shape, the direction from the center (h, k) to a reference point on the arc is defined as the reference. Test point (x... p y p The directed distance D to the arc is defined as:

[0074]

[0075] In this formula, D > 0 when the test point is on the outside of the arc; D = 0 when it is on the arc; and D < 0 when it is on the inside of the arc. In the example, the accuracy estimate perpendicular to the tensioning direction of the tensioning net is calculated based on this directional distance, and its sign reflects the concavity or convexity of the test point relative to the fitted arc.

[0076] By employing directional distance, the accuracy estimate obtained in the embodiment includes not only the magnitude of the offset but also the direction of the offset, thereby enabling a more comprehensive and accurate characterization of the deformation trend of the mask during the mesh stretching process, providing a more refined basis for subsequent quality assessment.

[0077] In a preferred embodiment of this application, the coordinate data of each of the aforementioned test points are obtained from the same coordinate point.

[0078] In the preferred embodiment of this application, such as Figure 2 As shown, the multiple pixel holes serving as test points 101 include pixel holes located at both ends of the precision metal mask 100 under test along the long axis (the horizontal direction in the figure).

[0079] In the preferred embodiment of this application, such as Figure 2 As shown, the precision metal mask 100 under test has a plurality of opening units 110, which are arranged along the long axis of the precision metal mask 100 under test.

[0080] In the preferred embodiment of this application, such as Figure 2 As shown, the selected multiple pixel holes include those in each opening unit:

[0081] Pixel holes located at the four corners, pixel holes located in the middle of the four edges, and pixel holes located in the center of the opening unit.

[0082] In this application, the location of the test points selected for each opening unit is described as "pixel hole located in the middle of the four edges" and "pixel hole located in the center of the opening unit", which aims to define a set of key sampling points that can effectively characterize the overall position and deformation distribution of the unit.

[0083] Specifically, a "pixel hole located in the middle of the four edges" refers to a pixel hole located on each edge, roughly in the middle of the two endpoints (i.e., corner pixel holes) of that edge. It does not necessarily have to be precisely located at the geometric midpoint of the edge. In practice, the pixel hole closest to the midpoint on that edge can be selected, or, based on the periodicity of the pixel hole array, a pixel hole that best represents the characteristics of the middle region of that edge can be selected. A "pixel hole located at the center of the opening unit" refers to a pixel hole located inside the opening unit, roughly in the geometric center region of that unit. It does not necessarily have to be precisely located at the absolute center of the rectangle defined by the four corner pixel holes. Preferably, the pixel hole closest to the geometric center of the unit is selected; in the actual structure, if there is no pixel hole exactly located in the center, one or a group of pixel holes closest to the center region can be selected as representative.

[0084] Optionally, the precision metal mask under test has an odd number of opening cells. Figure 2 The typical embodiment shown includes 5 opening units. Depending on the actual process requirements, the number of opening units can be selected as, for example, 3, 5, 7, 9, etc.

[0085] The precision metal mask accuracy prediction method provided in the foregoing embodiments offers a technical means to quantitatively predict the pixel hole position accuracy of a precision metal mask (FMM) before the actual screen is applied. This method addresses the problem of "lack of a pre-screening accuracy prediction method" in existing technologies, enabling production personnel to know the potential accuracy performance of the FMM in advance.

[0086] The accuracy prediction method provided in the foregoing embodiments utilizes the coordinate data of a limited number of test points on the unstretched FMM (Fixed Mirror Machine) and can complete the prediction through simple geometric calculations (such as calculating the distance from a point to a specified straight line or arc), providing a reliable quantitative basis for evaluating subsequent wire mesh stretching. This method does not require expensive specialized equipment or complex algorithms, is easy to integrate into existing optical inspection processes, has low implementation costs, and is easy to promote and apply in production lines.

[0087] Based on a similar concept, this application also provides a specific embodiment of a quality assessment method for precision metal photomasks, wherein the quality assessment method in the embodiment specifically includes:

[0088] Take the precision metal mask to be tested, which is in an unstretched state;

[0089] The precision metal mask to be tested is subjected to the precision estimation method described in any of the foregoing embodiments to obtain the precision estimation value of all test points after the precision metal mask to be tested is stretched. The precision estimation value includes the precision estimation value along the stretching direction of the stretching and the precision estimation value perpendicular to the stretching direction of the stretching.

[0090] If the accuracy estimates at all test points meet the accuracy threshold range, the precision metal mask under test is deemed qualified.

[0091] In a typical embodiment, the accuracy threshold range is from -2μm to 2μm (i.e., the expected accuracy of all test points is acceptable if it is between ±2μm).

[0092] The aforementioned "accuracy threshold range of -2μm to 2μm" is an exemplary range determined based on the general process requirements of metal mask (FMM) for typical high-precision AMOLED display panels. In actual production, the specific value of this threshold is not fixed, but can be flexibly configured and adjusted according to the design specifications of specific products, customer customization requirements, process capabilities, and accuracy requirements of different application scenarios.

[0093] For highly demanding micro-displays or ultra-high resolution panels, the threshold can be set to a more stringent range of ±1.5μm, ±1.0μm, or even smaller.

[0094] For applications requiring moderate precision or specific designs, the threshold can be appropriately relaxed to ±3.0μm or ±5.0μm.

[0095] In certain process development or prototype verification stages, asymmetric thresholds (such as -1.5μm to +2.0μm) can be used to adapt to deviation characteristics in specific directions in order to analyze process capability.

[0096] This application also provides a specific embodiment of a method for manufacturing a precision metal mask, which specifically includes the accuracy estimation method as described in the foregoing embodiments, or the quality assessment method as described in the foregoing embodiments.

[0097] In the method embodiments described in this application, each step is executed by a computer system or an automated device integrated with a processor. Specifically, operations such as "selection," "acquisition," "establishment," "calculation," "comparison," and "determination" are all implemented by the computer system running corresponding program algorithms and driving or interacting with physical measurement hardware (such as optical sensors and motion platforms). The entire process is completed automatically, and the results are directly applied to material flow and process control on the production line.

[0098] The following examples will illustrate this application in more detail.

[0099] Examples include, for example Figure 2 The precision metal mask 100 shown has five opening units 110. In the examples below, three opening units 110 are selected in total. 3 = 9 test points, arranged in a 3x3 grid, with a total of 9 test points selected for the entire mask. 5 = 45 test points.

[0100] Example 1

[0101] In this example, the offset (i.e., pixel position accuracy PPA) between the actual position of each test point in the mask without meshing and the ideal position after meshing is designed is shown in Table 1 below (along the long axis of the mask or the direction of tension application during meshing, i.e., along the direction of the mask's long axis or the direction of tension application during meshing). Figure 2 (lateral offset) and Table 2 (perpendicular to the direction of the netting, i.e.) Figure 2 (Central longitudinal offset).

[0102] Table 1

[0103]

[0104] Table 2

[0105]

[0106] Because the precision metal mask plate has a shrinkage ratio before being stretched, the offsets of each test point in Tables 1 and 2 are the results after adding the shrinkage ratio. Therefore, it is impossible to determine whether the accuracy requirements are met after stretching based solely on the data in Tables 1 and 2. Figure 3 As shown, due to the influence of pressure film and etching stress in the etching process, the straightness in the Y direction presents an outward convex C-shape.

[0107] The precision metal mask 100 of this example is subjected to the precision estimation method as described in the previous embodiment. The obtained precision estimates of each test point along the tensioning direction are shown in Table 3, and the obtained precision estimates of each test point perpendicular to the tensioning direction are shown in Table 4.

[0108] Table 3

[0109]

[0110] Table 4

[0111]

[0112] The precision metal mask in this example is stretched, and the actual measurement results of the mask after stretching are obtained (the offset between the actual position of each test point on the mask after stretching and the ideal position designed after stretching). The actual measurement values ​​of the accuracy of each test point along the stretching direction are shown in Table 5, and the actual measurement values ​​of the accuracy of each test point perpendicular to the stretching direction are shown in Table 6.

[0113] Table 5

[0114]

[0115] Table 6

[0116]

[0117] In Example 1 above, the unit of the relevant data for each test point in Tables 1 to 6 is “μm” (the same applies to subsequent examples).

[0118] Analysis of the accuracy estimates obtained for each test point in Example 1: The maximum value of the accuracy estimate along the tension direction of the wire mesh is 1.6 μm, and the minimum value is -1.9 μm (see Table 3); the maximum value of the accuracy estimate perpendicular to the tension direction of the wire mesh is 1.8 μm, and the minimum value is -0.9 μm (see Table 4).

[0119] Threshold determination: In a typical embodiment, the determination accuracy threshold range is set to -2μm to 2μm. The accuracy estimates obtained in Example 1 all fall within this threshold range.

[0120] Judgment Result: Since the accuracy prediction value meets the threshold condition, it can be determined that the deformation uniformity of the precision metal mask under test is good in the stretching direction and perpendicular to the stretching direction, and its accuracy is good. The accuracy prediction is qualified. This judgment result is consistent with the overall qualified trend reflected by the detailed actual measurement values ​​after stretching provided in Example 1 (Tables 5 and 6).

[0121] Example 2

[0122] In this example, the offsets between the actual positions of each test point in the mask without mesh and the ideal positions after meshing are shown in Tables 7 and 8 below. Table 7 shows the offsets along the long axis of the mask or the direction of tension application during meshing (i.e., along the long axis of the mask or along the direction of tension application during meshing). Figure 2 The offset (horizontal) is shown in Table 8, which is perpendicular to the direction of the netting (i.e., horizontal). Figure 2 The offset (vertical direction).

[0123] Table 7

[0124]

[0125] Table 8

[0126]

[0127] The precision metal mask 100 of this example is subjected to the precision estimation method as described in the previous embodiment. The obtained precision estimates of each test point along the tensioning direction are shown in Table 9, and the obtained precision estimates of each test point perpendicular to the tensioning direction are shown in Table 10.

[0128] Table 9

[0129]

[0130] Table 10

[0131]

[0132] The precision metal mask in this example is stretched, and the actual measurement results of the mask after stretching are obtained (same as in Example 1). The actual measurement values ​​of the accuracy of each test point along the stretching direction are shown in Table 11, and the actual measurement values ​​of the accuracy of each test point perpendicular to the stretching direction are shown in Table 12.

[0133] Table 11

[0134]

[0135] Table 12

[0136]

[0137] In Example 2, the determination is also made based on the accuracy threshold range set in the typical embodiment.

[0138] Threshold determination: According to Table 9, in all three open units 1 to 3, the accuracy prediction of the test points in the tension direction of the tensioned net does not fall within the threshold range of -2μm to 2μm.

[0139] Judgment Result: Since the accuracy estimates of the test points in opening units 1 to 3 do not meet the threshold range conditions, it can be determined that the accuracy of the corresponding parts of the precision metal mask under test in the meshing direction is poor and therefore unqualified. This judgment result is basically consistent with the overall qualified trend reflected by the detailed actual measurement values ​​after meshing provided in Example 2 (Tables 11 and 12).

[0140] Example 3

[0141] In this example, the offsets between the actual positions of each test point in the mask without mesh and the ideal positions after meshing are shown in Tables 13 and 14 below. Table 13 shows the offsets along the long axis of the mask or the direction of tension application during meshing (i.e., along the long axis of the mask or along the direction of tension application during meshing). Figure 2 The offset (horizontal) is shown in Table 14, which is perpendicular to the direction of the netting (i.e., horizontal). Figure 2 The offset (vertical direction).

[0142] Table 13

[0143]

[0144] Table 14

[0145]

[0146] The precision metal mask 100 in this example is subjected to the precision estimation method as described in the previous embodiment. The obtained precision estimates of each test point along the tensioning direction are shown in Table 15, and the obtained precision estimates of each test point perpendicular to the tensioning direction are shown in Table 16.

[0147] Table 15

[0148]

[0149] Table 16

[0150]

[0151] The precision metal mask in this example is stretched, and the actual measurement results of the mask after stretching are obtained (same as in Example 1). The actual measurement values ​​of the accuracy of each test point along the stretching direction are shown in Table 17, and the actual measurement values ​​of the accuracy of each test point perpendicular to the stretching direction are shown in Table 18.

[0152] Table 17

[0153]

[0154] Table 18

[0155]

[0156] In Example 3, the determination is also made based on the accuracy threshold range set in the typical embodiment.

[0157] Threshold determination: According to Tables 15 and 16, in all open units 1 to 5, the accuracy prediction values ​​of the test points in the tension direction of the tensioned wire mesh and the accuracy prediction values ​​perpendicular to the tension direction of the tensioned wire mesh do not fall within the threshold range of -2μm to 2μm.

[0158] Judgment Result: Since the accuracy estimates of the relevant test points in opening units 1 to 5 do not meet the threshold range conditions, it can be determined that the accuracy of the corresponding parts of the precision metal mask under test is poor and unqualified. This judgment result is basically consistent with the overall qualified trend reflected by the detailed actual measurement values ​​after screen tensioning provided in Example 3 (Tables 17 and 18).

[0159] The above description is only a partial embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the embodiments of this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for predicting the accuracy of a precision metal mask, used to predict the accuracy of a precision metal mask after it has been stretched, characterized in that, include: Take a precision metal mask to be tested, which is in an unstretched state; Multiple pixel holes on the precision metal mask under test are selected as multiple test points. The selected multiple pixel holes are arranged in multiple rows, and the row direction is the long axis direction of the precision metal mask under test. Obtain the coordinate data of the multiple test points respectively; Perform the following steps for each test case: Establish a reference line that passes through at least two test points in the row of test points. Obtain the distance between each test point in the row of test points and the reference line, so as to use as the accuracy estimate of the row of test points along the stretching direction after the precision metal mask to be tested is stretched. A reference arc is established, which passes through at least three test points in the row of test points. The distance between each test point in the row and the reference arc is obtained as an estimated value of the accuracy of the row of test points perpendicular to the stretching direction after the precision metal mask to be tested is stretched.

2. The accuracy prediction method according to claim 1, characterized in that, The reference line passes through two test points located at both ends of the test point row.

3. The accuracy prediction method according to claim 1, characterized in that, The reference arc passes through two test points located at both ends of the row of test points, and one test point located in the middle of the row of test points.

4. The accuracy prediction method according to claim 2 or 3, characterized in that, The plurality of pixel holes include pixel holes located at both ends of the precision metal mask under test along the long axis.

5. The accuracy prediction method according to claim 2 or 3, characterized in that, The precision metal mask to be tested has multiple opening units; The number of rows and columns of pixel holes selected in each aperture unit is greater than or equal to 3.

6. The accuracy prediction method according to claim 5, characterized in that, The number of rows and columns of the selected pixel holes in each opening unit ranges from 3 to 7.

7. The accuracy prediction method according to claim 6, characterized in that, The number of rows and columns of pixel holes selected in each aperture unit is 3.

8. The accuracy prediction method according to claim 7, characterized in that, The selected multiple pixel holes include those in each opening unit: Pixel holes located at the four corners; Pixel holes located in the middle of the four edges; The pixel hole is located in the center.

9. The accuracy prediction method according to claim 5, characterized in that, The precision metal mask to be tested has an odd number of opening units.

10. A method for quality assessment of a precision metal photomask, characterized in that, include: Take a precision metal mask to be tested, which is in an unstretched state; The precision metal mask to be tested is subjected to the precision estimation method as described in any one of claims 1 to 9 to obtain the precision estimation value of all test points after the precision metal mask to be tested is stretched. The precision estimation value includes the precision estimation value along the stretching direction of the stretching and the precision estimation value perpendicular to the stretching direction of the stretching. If the accuracy estimates at all test points meet the accuracy threshold range, the precision metal mask under test is deemed qualified.

11. The quality assessment method according to claim 10, characterized in that, The accuracy threshold range is from -2μm to 2μm.

12. A method for manufacturing a precision metal mask, characterized in that, The manufacturing method includes the accuracy prediction method as described in any one of claims 1 to 9 or the quality assessment method as described in any one of claims 10 to 11.

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