A mask precision measurement method and system

Abstract

The application discloses a kind of mask precision measurement method and system, it is related to semiconductor technical field, it solves the problem that existing mask precision measurement is susceptible to abnormal point position, measurement area is small, scheme main point is: multiple point positions are selected from the measurement area to be measured, the measurement data and design data of each point position are obtained;According to measurement data, construct measurement matrix, according to design data, construct design matrix, measurement matrix and design matrix are two-dimensional matrix, the row and column order of two-dimensional matrix corresponds with the row and column order of point position, the element of two-dimensional matrix is the combination of corresponding point position horizontal coordinate X and vertical coordinate Y;According to measurement matrix and design matrix, calculate X total length variance component, Y total length variance component, X direction perpendicular deviation variance component, Y direction perpendicular deviation variance component and XY combined perpendicular deviation;By constructing measurement matrix, combine calculation formula to calculate various accuracy values, it can reduce the influence of abnormal point position on measurement result, while expand measurement range.

Description

Technical Field

[0001] This invention relates to the field of semiconductor technology, and more specifically, to a method and system for measuring the accuracy of photomasks. Background Technology

[0002] With the development of display and semiconductor technologies, the precision requirements for photomask production are becoming increasingly stringent. Current methods for measuring photomask precision use a four-point measurement method. This involves selecting four points on the photomask to form a rectangle, comparing the total length of these four points with the designed total length, and calculating the offset values ​​of each point on the x-axis and y-axis to obtain precision values ​​such as total length deviation and perpendicularity. However, due to the limited number of points selected, this method is susceptible to the influence of abnormal points, leading to measurement fluctuations. Furthermore, the effective measurement area is small, limited to the area between the four points.

[0003] Based on this, this application provides a method and system for measuring the accuracy of photomasks, thereby solving the above-mentioned problems. Summary of the Invention

[0004] The purpose of this application is to provide a method and system for measuring the accuracy of a photomask, which solves the problems of existing photomask accuracy measurements being easily affected by abnormal points and having a small measurement area. By constructing a measurement matrix and combining it with calculation formulas to calculate various accuracy values, the influence of abnormal points on the measurement results can be reduced, while the measurement range can be expanded.

[0005] This application first provides a method for measuring the accuracy of a photomask, including:

[0006] Select multiple points in the area to be measured and obtain the measurement data and design data for each point;

[0007] A measurement matrix is ​​constructed based on the measurement data, and a design matrix is ​​constructed based on the design data. Both the measurement matrix and the design matrix are two-dimensional matrices. The row and column order of the two-dimensional matrix corresponds to the row and column order of the points. The elements of the two-dimensional matrix are the combination of the x-coordinate (X) and y-coordinate (Y) of the corresponding points.

[0008] Calculate the total variance components of X, Y, X-direction vertical deviation, Y-direction vertical deviation, and XY combined vertical deviation based on the measurement matrix and design matrix.

[0009] Specifically, the total length variance component of X is calculated by summing the product of the deviations of the x-coordinate and the x-coordinate deviation and summing the squares of the deviations of the x-coordinate; the total length variance component of Y is calculated by summing the product of the deviations of the y-coordinate and the y-coordinate deviation and summing the squares of the deviations of the y-coordinate; the vertical deviation variance component of X is calculated by summing the product of the deviations of the y-coordinate and the x-coordinate deviation and summing the squares of the deviations of the y-coordinate; the vertical deviation variance component of Y is calculated by summing the product of the deviations of the x-coordinate and the y-coordinate deviation and summing the squares of the deviations of the x-coordinate; and the combined vertical deviation of XY is obtained by summing the vertical deviation variance components of X and Y.

[0010] Using the above technical solution, multiple points are selected from the area to be measured to construct a measurement matrix and a design matrix. Through the operation of the measurement matrix and the design matrix, the total variance component of X, the total variance component of Y, the variance component of vertical deviation in the X direction, the variance component of vertical deviation in the Y direction, and the combined vertical deviation of X and Y are calculated. By combining the data of multiple points to construct the measurement matrix and the design matrix, the total variance component of every two points and the variance components of each point in the horizontal coordinate X and the vertical deviation are calculated through the matrix. This method is less affected by outliers, greatly improves the measurement accuracy, and the result error is only affected by the accuracy of the measuring instrument.

[0011] In one possible implementation, calculating the X total length variance component, Y total length variance component, X direction vertical deviation variance component, Y direction vertical deviation variance component, and XY combined vertical deviation based on the measurement matrix and design matrix includes:

[0012] Calculate the deviation matrix Δx of the abscissa based on the measurement matrix and the design matrix. ij The deviation matrix Δy from the ordinate ij ;

[0013] Based on the deviation matrix Δx of the horizontal axis ij Calculate the mean matrix of row deviations on the x-axis. Mean matrix of column deviations from the x-axis Based on the deviation matrix Δy of the ordinate ij Calculate the mean matrix of row deviations on the y-axis. Mean matrix of column deviations from the ordinate

[0014] Based on the row deviation mean matrix of the horizontal axis Calculate the mean of the row deviation of the x-axis. Based on the column deviation mean matrix of the horizontal axis Calculate the mean of the column deviations of the x-axis. Based on the mean matrix of row deviations on the ordinate Calculate the mean of the row deviation of the y-axis. Based on the column deviation mean matrix of the ordinate Calculate the mean of the column deviations of the ordinate.

[0015] Calculate the row design mean matrix for the x-axis based on the design matrix. The column design of the mean matrix and the vertical axis

[0016] Based on the x-coordinate of the design matrix p The row design mean matrix of the horizontal axis Column deviation mean matrix of the horizontal axis Mean deviation of column from the horizontal axis The total variance component of X, Scale X, is calculated.

[0017] Based on the ordinate y of the design matrix p The column design of the y-axis is the mean matrix. The mean matrix of row deviations on the y-axis mean of row deviation from the y-axis The total variance component of Y, Scale Y, is calculated.

[0018] Based on the ordinate y of the design matrix p The column design of the y-axis is the mean matrix. Row deviation mean matrix of the x-axis Mean of row deviation from the x-axis The variance component of the vertical deviation in the X direction, Ortho X, is calculated.

[0019] Based on the x-coordinate of the design matrix p The row design mean matrix of the horizontal axis Column deviation mean matrix of the y-axis Mean of column deviation from the vertical axis Calculate the variance component of the vertical deviation in the Y direction, Ortho Y;

[0020] The combined vertical deviation Ortho is calculated based on the variance components of the vertical deviation in the X direction (Ortho X) and the variance components of the vertical deviation in the Y direction (Ortho Y).

[0021] In one possible implementation, the total variance component X (Scale X) and the total variance component Y (Scale Y) are:

[0022]

[0023]

[0024] Where, x p To design the x-coordinate of the matrix, Design a mean matrix for the rows of the x-axis. The x-axis is the matrix of column deviations and mean values. y is the mean of the column deviations on the x-axis, j is the number of columns in the measurement matrix, and y is the mean of the column deviations on the x-axis. p To design the ordinate of the matrix, Design a mean matrix for the columns of the y-axis. The matrix represents the mean of the row deviations on the y-axis. Let be the mean of the row deviations of the ordinate, and i be the number of rows in the measurement matrix.

[0025] In one possible implementation, the vertical deviation variance component Ortho X in the X direction and the vertical deviation variance component Ortho Y in the Y direction are:

[0026]

[0027]

[0028] Among them, y p To design the ordinate of the matrix, Design a mean matrix for the columns of the y-axis. This is the mean matrix of row deviations on the x-axis. Let x be the mean of the row deviations on the x-axis, i be the number of rows in the measurement matrix, and x be the mean of the row deviations on the x-axis. p To design the x-coordinate of the matrix, Design a mean matrix for the rows of the x-axis. The ordinate is the column deviation mean matrix. denoted as the mean of the column deviations of the ordinate, and j is the number of columns in the measurement matrix.

[0029] In one possible implementation, the XY combined vertical deviation Ortho is:

[0030] Ortho = Ortho X + Ortho Y

[0031] Where Ortho X is the variance component of the vertical deviation in the X direction, and Ortho Y is the variance component of the vertical deviation in the Y direction.

[0032] This application also provides a mask accuracy measurement system, including:

[0033] The point selection module is used to select multiple points from the area to be measured and obtain the measurement data and design data of each point.

[0034] The measurement matrix / design matrix construction module is used to construct a measurement matrix based on the measurement data and a design matrix based on the design data. Both the measurement matrix and the design matrix are two-dimensional matrices. The row and column order of the two-dimensional matrix corresponds to the row and column order of the points. The elements of the two-dimensional matrix are the combination of the x-coordinate (X) and y-coordinate (Y) of the corresponding points.

[0035] The accuracy measurement module is used to calculate the total length variance component of X, the total length variance component of Y, the vertical deviation variance component of X direction, the vertical deviation variance component of Y direction, and the combined vertical deviation of XY based on the measurement matrix and the design matrix.

[0036] Specifically, the total length variance component of X is calculated by summing the product of the deviations of the x-coordinate and the x-coordinate deviation and summing the squares of the deviations of the x-coordinate; the total length variance component of Y is calculated by summing the product of the deviations of the y-coordinate and the y-coordinate deviation and summing the squares of the deviations of the y-coordinate; the vertical deviation variance component of X is calculated by summing the product of the deviations of the y-coordinate and the x-coordinate deviation and summing the squares of the deviations of the y-coordinate; the vertical deviation variance component of Y is calculated by summing the product of the deviations of the x-coordinate and the y-coordinate deviation and summing the squares of the deviations of the x-coordinate; and the combined vertical deviation of XY is obtained by summing the vertical deviation variance components of X and Y.

[0037] In one possible implementation, the accuracy measurement module includes:

[0038] The deviation matrix calculation module is used to calculate the deviation matrix Δx of the abscissa based on the measurement matrix and the design matrix. ij The deviation matrix Δy from the ordinate ij ;

[0039] The deviation mean matrix calculation module is used to calculate the deviation matrix Δx based on the horizontal axis. ij Calculate the mean matrix of row deviations on the x-axis. Mean matrix of column deviations from the x-axis Based on the deviation matrix Δy of the ordinate ij Calculate the mean matrix of row deviations on the y-axis. Mean matrix of column deviations from the ordinate

[0040] The deviation mean calculation module is used to calculate the mean value of the row deviations on the horizontal axis. Calculate the mean of the row deviation of the x-axis. Based on the column deviation mean matrix of the horizontal axis Calculate the mean of the column deviations of the x-axis. Based on the mean matrix of row deviations on the ordinate Calculate the mean of the row deviation of the y-axis. Based on the column deviation mean matrix of the ordinate Calculate the mean of the column deviations of the ordinate.

[0041] The design mean matrix calculation module is used to calculate the row design mean matrix of the x-axis based on the design matrix. The column design of the mean matrix and the vertical axis

[0042] The X-axis total variance component calculation module is used to calculate the x-axis of the design matrix. p The row design mean matrix of the horizontal axis Column deviation mean matrix of the horizontal axis Mean deviation of column from the horizontal axis The total variance component of X, Scale X, is calculated.

[0043] The Y-axis total variance component calculation module is used to calculate the y-axis of the design matrix. p The column design of the y-axis is the mean matrix. The mean matrix of row deviations on the y-axis mean of row deviation from the y-axis The total variance component of Y, Scale Y, is calculated.

[0044] The X-direction vertical deviation variance component calculation module is used to calculate the variance component based on the ordinate y of the design matrix. p The column design of the y-axis is the mean matrix. Row deviation mean matrix of the x-axis Mean of row deviation from the x-axis The variance component of the vertical deviation in the X direction, Ortho X, is calculated.

[0045] The Y-direction vertical deviation variance component calculation module is used to calculate the x-coordinate of the design matrix. p The row design mean matrix of the horizontal axis Column deviation mean matrix of the y-axis Mean of column deviation from the vertical axis Calculate the variance component of the vertical deviation in the Y direction, Ortho Y;

[0046] The XY combined vertical deviation calculation module is used to calculate the XY combined vertical deviation Ortho based on the variance component Ortho X of the vertical deviation in the X direction and the variance component Ortho Y of the vertical deviation in the Y direction.

[0047] In one possible implementation, the X total variance component Scale X in the X total variance component calculation module and the Y total variance component Scale Y in the Y total variance component calculation module are:

[0048]

[0049]

[0050] Where, x p To design the x-coordinate of the matrix, Design a mean matrix for the rows of the x-axis. The x-axis is the matrix of column deviations and mean values. y is the mean of the column deviations on the x-axis, j is the number of columns in the measurement matrix, and y is the mean of the column deviations on the x-axis. p To design the ordinate of the matrix, Design a mean matrix for the columns of the y-axis. The matrix represents the mean of the row deviations on the y-axis. Let be the mean of the row deviations of the ordinate, and i be the number of rows in the measurement matrix.

[0051] In one possible implementation, the X-direction vertical deviation variance component Ortho X in the X-direction vertical deviation variance component calculation module and the Y-direction vertical deviation variance component Ortho Y in the Y-direction vertical deviation variance component calculation module are:

[0052]

[0053]

[0054] Among them, y p To design the ordinate of the matrix, Design a mean matrix for the columns of the y-axis. This is the mean matrix of row deviations on the x-axis. Let x be the mean of the row deviations on the x-axis, i be the number of rows in the measurement matrix, and x be the mean of the row deviations on the x-axis. p To design the x-coordinate of the matrix, Design a mean matrix for the rows of the x-axis. The ordinate is the column deviation mean matrix. denoted as the mean of the column deviations of the ordinate, and j is the number of columns in the measurement matrix.

[0055] In one possible implementation, the XY combined vertical deviation Ortho in the XY combined vertical deviation calculation module is:

[0056] Ortho = Ortho X + Ortho Y

[0057] Where Ortho X is the variance component of the vertical deviation in the X direction, and Ortho Y is the variance component of the vertical deviation in the Y direction.

[0058] Compared with the prior art, this application has the following advantages: by combining data from multiple points to construct a measurement matrix and a design matrix, any point with more than or equal to 4 points can be monitored; by calculating the total variance component of every two points and the variance components of each point in the horizontal coordinate X and vertical coordinate Y respectively through the matrix, the vertical deviation is calculated, which is not easily affected by outliers, the monitoring effectiveness is greatly improved, the monitoring accuracy is high, and the result error is only affected by the accuracy of the measuring instrument. Attached Figure Description

[0059] The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and form part of this application, do not constitute a limitation thereof. In the drawings:

[0060] Figure 1 A schematic flowchart illustrating a mask accuracy measurement method provided in an embodiment of the present invention;

[0061] Figure 2 This is a schematic diagram of a mask accuracy measurement system provided in an embodiment of the present invention;

[0062] Figure 3 This is a schematic diagram of the points provided in an embodiment of the present invention;

[0063] Figure 4 The deviation matrix Δx of the abscissa of the point provided in the embodiment of the present invention ij Row deviation mean matrix Row deviation mean matrix of the x-axis Column deviation mean matrix of the horizontal axis A schematic diagram of the calculation;

[0064] Figure 5 The deviation matrix Δy of the ordinate of the point provided in the embodiment of the present invention ij The mean matrix of row deviations on the y-axis Column deviation mean matrix of the y-axis A calculation diagram. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the embodiments and accompanying drawings. The illustrative embodiments and descriptions of this application are only for explaining this application and are not intended to limit this application.

[0066] First, the existing technology needs to be explained. Current mask accuracy measurement methods can only measure the accuracy of four points. This is mainly done by comparing the total length of these four points with the designed total length to measure the overall length accuracy; and by measuring the vertical accuracy through the offset values ​​of the four points in the X and Y coordinates. While the algorithm is simple, it suffers from poor detection accuracy and a small range. A deviation at any point will lead to a large error, and the measurement range is limited to the four points, resulting in a small detection range.

[0067] Based on the above, this application provides a method for measuring the accuracy of a mask. By constructing a measurement matrix and combining it with calculation formulas to calculate various accuracy values, the accuracy of the mask can be efficiently monitored. The accuracy includes: the total variance component of X, the total variance component of Y, the variance component of vertical deviation in the X direction, the variance component of vertical deviation in the Y direction, and the combined vertical deviation of XY. Moreover, the matrix can be arbitrarily expanded to increase the detection range.

[0068] The technical solutions of this application can be applied to the accuracy monitoring of photomasks of various sizes, including but not limited to photomasks, and can also be extended to all products with requirements for total length accuracy, vertical accuracy, positional accuracy and fitting accuracy.

[0069] Please see Figure 1 As shown, Figure 1 This is a flowchart illustrating a mask accuracy measurement method provided in an embodiment of the present invention. Figure 1 As shown, the method includes:

[0070] S1. Select multiple points from the area to be measured and obtain the measurement data and design data of each point;

[0071] S2. Construct a measurement matrix based on the measurement data and a design matrix based on the design data. Both the measurement matrix and the design matrix are two-dimensional matrices. The row and column order of the two-dimensional matrix corresponds to the row and column order of the points. The elements of the two-dimensional matrix are the combination of the x-coordinate and y-coordinate of the corresponding points.

[0072] S3. Calculate the total length variance component of X, the total length variance component of Y, the vertical deviation variance component of X direction, the vertical deviation variance component of Y direction, and the combined vertical deviation of XY based on the measurement matrix and the design matrix; here, X refers to the horizontal coordinate, Y refers to the vertical coordinate, X direction refers to the horizontal coordinate direction, and Y direction refers to the vertical coordinate direction.

[0073] In step S3: the total length variance component Scale X is calculated by summing the product of the deviations of the x-coordinate and the x-coordinate deviation and summing the squares of the deviations of the x-coordinate; the total length variance component Scale Y is calculated by summing the product of the deviations of the y-coordinate and the y-coordinate deviation and summing the squares of the deviations of the y-coordinate; the vertical deviation variance component Ortho X in the x-direction is calculated by summing the product of the deviations of the y-coordinate and the x-coordinate deviation and summing the squares of the deviations of the y-coordinate; the vertical deviation variance component Ortho Y in the y-direction is calculated by summing the product of the deviations of the x-coordinate and the y-coordinate deviation and summing the squares of the deviations of the x-coordinate; and the combined vertical deviation Ortho XY is obtained by summing the vertical deviation variance components in the x-direction and the y-direction.

[0074] Compared to existing technologies, this solution selects multiple points in the area to be measured to construct a measurement matrix and a design matrix. Through the operation of the measurement matrix and the design matrix, it calculates the total variance component of X, the total variance component of Y, the variance component of vertical deviation in the X direction, the variance component of vertical deviation in the Y direction, and the combined vertical deviation of X and Y. By combining the data from multiple points to construct the measurement matrix and the design matrix, the vertical deviation is calculated by calculating the total variance component of every two points and the variance components of each point in the x-coordinate and y-coordinate, respectively. This method is less affected by outliers, greatly improves the measurement accuracy, and the result error is only affected by the accuracy of the measuring instrument.

[0075] The accuracy calculation formula of this scheme can be simply understood as fitting a series of points to a linear equation Y = a + bX. All accuracy values, including Scale X, Scale Y, Ortho X, Ortho Y, and Ortho, are expanded around the slope coefficient b of the equation. For example, Scale X is the slope b of the deviation component of X on the horizontal axis in the fitted linear equation. Similarly, Scale Y is the slope b of the deviation component of Y on the vertical axis in the fitted linear equation. Ortho X is the slope b of the deviation component of X on the vertical axis in the fitted linear equation. Ortho Y is the slope b of the deviation component of Y on the horizontal axis in the fitted linear equation.

[0076] It should be noted that the elements in the design matrix are: (x p y p ), measuring the elements in the matrix: (x m y m Measurement matrix: i rows, j columns. Number of measurement points: N = i * j - NA (number of null values), na i The number of null values ​​in the i-th row, na j The number of null values ​​in column j.

[0077] In one possible implementation, calculating the X total length variance component, Y total length variance component, X direction vertical deviation variance component, Y direction vertical deviation variance component, and XY combined vertical deviation based on the measurement matrix and design matrix includes:

[0078] Calculate the deviation matrix Δx of the abscissa based on the measurement matrix and the design matrix. ij The deviation matrix Δy from the ordinate ij :

[0079] Δx ij =x mij -x pij Δy ij =y mij -y pij

[0080] Based on the deviation matrix Δx of the horizontal axis ij Calculate the mean matrix of row deviations on the x-axis. Mean matrix of column deviations from the x-axis

[0081]

[0082] Based on the deviation matrix Δy of the ordinate ij Calculate the mean matrix of row deviations on the y-axis. Mean matrix of column deviations from the ordinate

[0083]

[0084] Based on the row deviation mean matrix of the horizontal axis Calculate the mean of the row deviation of the x-axis. Based on the column deviation mean matrix of the horizontal axis Calculate the mean of the column deviations of the x-axis.

[0085]

[0086] Based on the mean matrix of row deviations on the ordinate Calculate the mean of the row deviation of the y-axis. Based on the column deviation mean matrix of the ordinate Calculate the mean of the column deviations of the ordinate.

[0087]

[0088] Calculate the row design mean matrix for the x-axis based on the design matrix. The column design of the mean matrix and the vertical axis

[0089]

[0090] Based on the x-coordinate of the design matrix p The row design mean matrix of the horizontal axis Column deviation mean matrix of the horizontal axis Mean deviation of column from the horizontal axis The total variance component of X is calculated and scaled to X:

[0091]

[0092] in, It is the sum of the products of the x-axis and the x-axis deviation. This represents the sum of squared deviations of the x-axis.

[0093] Based on the ordinate y of the design matrix p The column design of the y-axis is the mean matrix. The mean matrix of row deviations on the y-axis mean of row deviation from the y-axis The total variance component of Y is calculated and scaled to Y:

[0094]

[0095] in, It is the sum of the products of the ordinate and the ordinate deviation. The sum of squared deviations of the ordinate;

[0096] Based on the ordinate y of the design matrix p The column design of the y-axis is the mean matrix. Row deviation mean matrix of the x-axis Mean of row deviation from the x-axis The variance component of the vertical deviation in the X direction, Ortho X, is calculated as follows:

[0097]

[0098] in, It is the sum of the deviations of the vertical and horizontal coordinates. The sum of squared deviations of the ordinate;

[0099] Based on the x-coordinate of the design matrix p The row design mean matrix of the horizontal axis Column deviation mean matrix of the y-axis Mean of column deviation from the vertical axis Calculate the variance component of the vertical deviation in the Y direction, Ortho Y:

[0100]

[0101] in, The sum of squared deviations of the x-axis. This represents the sum of squared deviations of the x-axis.

[0102] The combined vertical deviation Ortho is calculated based on the variance components of the vertical deviation Ortho X in the X direction and the variance components of the vertical deviation Ortho Y in the Y direction:

[0103] Ortho = Ortho X + Ortho Y

[0104] Where Ortho X is the variance component of the vertical deviation in the X direction, and Ortho Y is the variance component of the vertical deviation in the Y direction.

[0105] Understandably, this method has the following beneficial effects: by combining data from multiple points to construct a measurement matrix and a design matrix, any point with four or more points can be monitored; by calculating the total variance component of every two points and the variance components of each point in the x-coordinate and y-coordinate respectively, the vertical deviation is calculated, which is less susceptible to outliers, greatly improving the effectiveness of monitoring, resulting in high monitoring accuracy, and the result error is only affected by the accuracy of the measuring instrument.

[0106] Please see Figure 2 As shown, Figure 2This is a schematic diagram of the structure of a mask accuracy measurement system provided in this application, according to an embodiment of the present invention. Figure 2 As shown, the system and methods correspond one-to-one, including:

[0107] The point selection module is used to select multiple points from the area to be measured and obtain the measurement data and design data of each point.

[0108] The measurement matrix / design matrix construction module is used to construct a measurement matrix based on the measurement data and a design matrix based on the design data. Both the measurement matrix and the design matrix are two-dimensional matrices. The row and column order of the two-dimensional matrix corresponds to the row and column order of the points. The elements of the two-dimensional matrix are the combination of the x-coordinate (X) and y-coordinate (Y) of the corresponding points.

[0109] The accuracy measurement module is used to calculate the total length variance component of X, the total length variance component of Y, the vertical deviation variance component of X direction, the vertical deviation variance component of Y direction, and the combined vertical deviation of XY based on the measurement matrix and the design matrix.

[0110] Specifically, the total length variance component of X is calculated by summing the product of the deviations of the x-coordinate and the x-coordinate deviation and summing the squares of the deviations of the x-coordinate; the total length variance component of Y is calculated by summing the product of the deviations of the y-coordinate and the y-coordinate deviation and summing the squares of the deviations of the y-coordinate; the vertical deviation variance component of X is calculated by summing the product of the deviations of the y-coordinate and the x-coordinate deviation and summing the squares of the deviations of the y-coordinate; the vertical deviation variance component of Y is calculated by summing the product of the deviations of the x-coordinate and the y-coordinate deviation and summing the squares of the deviations of the x-coordinate; and the combined vertical deviation of XY is obtained by summing the vertical deviation variance components of X and Y.

[0111] In one possible implementation, the accuracy measurement module includes:

[0112] The deviation matrix calculation module is used to calculate the deviation matrix Δx of the abscissa based on the measurement matrix and the design matrix. ij The deviation matrix Δy from the ordinate ij ;

[0113] The deviation mean matrix calculation module is used to calculate the deviation matrix Δx based on the horizontal axis. ij Calculate the mean matrix of row deviations on the x-axis. Mean matrix of column deviations from the x-axis Based on the deviation matrix Δy of the ordinate ij Calculate the mean matrix of row deviations on the y-axis. Mean matrix of column deviations from the ordinate

[0114] The deviation mean calculation module is used to calculate the mean value of the row deviations on the horizontal axis. Calculate the mean of the row deviation of the x-axis. Based on the column deviation mean matrix of the horizontal axis Calculate the mean of the column deviations of the x-axis. Based on the mean matrix of row deviations on the ordinate Calculate the mean of the row deviation of the y-axis. Based on the column deviation mean matrix of the ordinate Calculate the mean of the column deviations of the ordinate.

[0115] The design mean matrix calculation module is used to calculate the row design mean matrix of the x-axis based on the design matrix. The column design of the mean matrix and the vertical axis

[0116] The X-axis total variance component calculation module is used to calculate the x-axis of the design matrix. p The row design mean matrix of the horizontal axis Column deviation mean matrix of the horizontal axis Mean deviation of column from the horizontal axis The total variance component of X, Scale X, is calculated.

[0117] The Y-axis total variance component calculation module is used to calculate the y-axis of the design matrix. p The column design of the y-axis is the mean matrix. The mean matrix of row deviations on the y-axis mean of row deviation from the y-axis The total variance component of Y, Scale Y, is calculated.

[0118] The X-direction vertical deviation variance component calculation module is used to calculate the variance component based on the ordinate y of the design matrix. p The column design of the y-axis is the mean matrix. Row deviation mean matrix of the x-axis Mean of row deviation from the x-axis The variance component of the vertical deviation in the X direction, Ortho X, is calculated.

[0119] The Y-direction vertical deviation variance component calculation module is used to calculate the x-coordinate of the design matrix. p The row design mean matrix of the horizontal axis Column deviation mean matrix of the y-axis Mean of column deviation from the vertical axis Calculate the variance component of the vertical deviation in the Y direction, Ortho Y;

[0120] The XY combined vertical deviation calculation module is used to calculate the XY combined vertical deviation Ortho based on the variance component Ortho X of the vertical deviation in the X direction and the variance component Ortho Y of the vertical deviation in the Y direction.

[0121] In one possible implementation, the X total variance component Scale X in the X total variance component calculation module and the Y total variance component Scale Y in the Y total variance component calculation module are:

[0122]

[0123]

[0124] Where, x p To design the x-coordinate of the matrix, Design a mean matrix for the rows of the x-axis. The x-axis is the matrix of column deviations and mean values. y is the mean of the column deviations on the x-axis, j is the number of columns in the measurement matrix, and y is the mean of the column deviations on the x-axis. p To design the ordinate of the matrix, Design a mean matrix for the columns of the y-axis. The matrix represents the mean of the row deviations on the y-axis. Let be the mean of the row deviations of the ordinate, and i be the number of rows in the measurement matrix.

[0125] In one possible implementation, the X-direction vertical deviation variance component Ortho X in the X-direction vertical deviation variance component calculation module and the Y-direction vertical deviation variance component Ortho Y in the Y-direction vertical deviation variance component calculation module are:

[0126]

[0127]

[0128] Among them, y p To design the ordinate of the matrix, Design a mean matrix for the columns of the y-axis. This is the mean matrix of row deviations on the x-axis. Let x be the mean of the row deviations on the x-axis, i be the number of rows in the measurement matrix, and x be the mean of the row deviations on the x-axis. p To design the x-coordinate of the matrix, Design a mean matrix for the rows of the x-axis. The ordinate is the column deviation mean matrix. denoted as the mean of the column deviations of the ordinate, and j is the number of columns in the measurement matrix.

[0129] In one possible implementation, the XY combined vertical deviation Ortho in the XY combined vertical deviation calculation module is:

[0130] Ortho = Ortho X + Ortho Y

[0131] Where Ortho X is the variance component of the vertical deviation in the X direction, and Ortho Y is the variance component of the vertical deviation in the Y direction.

[0132] It is understood that this system corresponds one-to-one with the methods described above and is used to implement those methods. It has the same beneficial effects as the methods described above.

[0133] Please see Figure 3 As shown, Figure 3 This is a schematic diagram of the points provided in an embodiment of the present invention. The following section describes the measurement of the mask accuracy using the method described above. For example... Figure 3 As shown, there are a total of 50 points, and the horizontal and vertical design values ​​for each point are marked on the figure. The measured and design values ​​for each point are summarized in Table 1 below.

[0134] Table 1. Measured and Design Values ​​for Each Location

[0135]

[0136] Please see Figure 4-5 As shown, Figure 4 The deviation matrix Δx of the x-coordinate of the point. ij Row deviation mean matrix Row deviation mean matrix of the x-axis Column deviation mean matrix of the horizontal axis Calculation diagram, Figure 5 The deviation matrix Δy of the ordinate of the point ij The mean matrix of row deviations on the y-axis Column deviation mean matrix of the y-axis A calculation diagram is provided. The specific calculation process is as follows:

[0137] Measurement matrix: i = 14 rows, j = 15 columns

[0138] Number of measurement points: 50 = 14 * 15 - 160 (blank value)

[0139] Δx ij =x mij -x pij =-515,-435,-37,-289,…,343(nm)

[0140] Δy ij =y mij -y pij=-3, 41, 132, 256, 243,…, 54(nm)

[0141]

[0142]

[0143]

[0144]

[0145]

[0146]

[0147]

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155] Ortho = Ortho X + Ortho Y

[0156] =0.312 + (-0.073) = 0.239

[0157] Furthermore, the positional accuracy can also be calculated using the following formula:

[0158]

[0159]

[0160]

[0161]

[0162] Substitute the data from Table 1:

[0163]

[0164]

[0165]

[0166]

[0167]

[0168] Furthermore, the accuracy of CD can be calculated by referring to the data in Table 2:

[0169] Table 2 CD accuracy data

[0170]

[0171] GTM Zone: Measured CD value (maximum or minimum) of GTM zone - Designed CD value of GTM zone, take the larger absolute value.

[0172] CD precision = 2.560 - 2.5 = 0.06 ≤ 0.1um

[0173] Non-GTM area: Measured CD value (maximum or minimum) in the non-GTM area - Design CD value in the non-GTM area, take the larger absolute value.

[0174] CD precision = 4.121 - 4 = 0.121 ≤ 0.25um.

[0175] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for measuring the accuracy of a photomask, characterized in that, include: Select multiple points in the area to be measured and obtain the measurement data and design data for each point; A measurement matrix is ​​constructed based on the measurement data, and a design matrix is ​​constructed based on the design data. Both the measurement matrix and the design matrix are two-dimensional matrices. The row and column order of the two-dimensional matrix corresponds to the row and column order of the points. The elements of the two-dimensional matrix are the combination of the x-coordinate (X) and y-coordinate (Y) of the corresponding points. Calculate the total variance components of X, Y, X-direction vertical deviation, Y-direction vertical deviation, and XY combined vertical deviation based on the measurement matrix and design matrix. The total length variance component of X, the total length variance component of Y, the vertical deviation variance component of X direction, the vertical deviation variance component of Y direction, and the combined vertical deviation of X and Y are calculated based on the measurement matrix and the design matrix, including: Calculate the deviation matrix of the abscissa based on the measurement matrix and the design matrix. Deviation matrix between the vertical axis and the vertical axis ; Based on the deviation matrix of the horizontal axis Calculate the mean matrix of row deviations on the x-axis. Mean matrix of column deviations from the x-axis According to the deviation matrix of the ordinate Calculate the mean matrix of row deviations on the y-axis. Mean matrix of column deviations from the ordinate ; Based on the row deviation mean matrix of the horizontal axis Calculate the mean of the row deviation of the x-axis. Based on the column deviation mean matrix of the horizontal axis Calculate the mean of the column deviations of the x-axis. Based on the mean matrix of row deviations on the ordinate Calculate the mean of the row deviation of the y-axis. Based on the column deviation mean matrix of the ordinate Calculate the mean of the column deviations of the ordinate. ; Calculate the row design mean matrix for the x-axis based on the design matrix. The column design of the mean matrix and the vertical axis ; Based on the x-coordinate of the design matrix The row design mean matrix of the horizontal axis The mean matrix of column deviations on the horizontal axis Mean deviation of column from the horizontal axis The total variance component of X, Scale X, is calculated. Based on the ordinate of the design matrix The column design of the y-axis is the mean matrix. The mean matrix of row deviations on the y-axis mean of row deviation from the y-axis The total variance component of Y, Scale Y, is calculated. Based on the ordinate of the design matrix The column design of the y-axis is the mean matrix. The mean matrix of row deviations on the x-axis Mean of row deviation from the x-axis The variance component of the vertical deviation in the X direction, Ortho X, is calculated. Based on the x-coordinate of the design matrix The row design mean matrix of the horizontal axis The mean matrix of column deviations on the y-axis Mean of column deviation from the vertical axis Calculate the variance component of the vertical deviation in the Y direction, Ortho Y; The combined vertical deviation Ortho is calculated based on the variance components of the vertical deviation in the X direction (Ortho X) and the variance components of the vertical deviation in the Y direction (Ortho Y).

2. The method for measuring the accuracy of a photomask according to claim 1, characterized in that, The total variance component X (Scale X) and the total variance component Y (Scale Y) are: Scale X= ; Scale Y= ; in, To design the x-coordinate of the matrix, Design a mean matrix for the rows of the x-axis. The x-axis is the matrix of column deviations and mean values. The mean of the column deviations on the x-axis. To measure the number of columns in the matrix, To design the ordinate of the matrix, Design a mean matrix for the columns of the y-axis. The matrix represents the mean of the row deviations on the y-axis. The mean of the row deviations on the ordinate is... This is to measure the number of rows in the matrix.

3. The method for measuring the accuracy of a photomask according to claim 1, characterized in that, The variance components of the vertical deviation in the X direction (Ortho X) and the variance components of the vertical deviation in the Y direction (Ortho Y) are: Ortho X= ; Ortho Y= ; in, To design the ordinate of the matrix, Design a mean matrix for the columns of the y-axis. This is the mean matrix of row deviations on the x-axis. The mean of the row deviations on the horizontal axis. To measure the number of rows in a matrix, To design the x-coordinate of the matrix, Design a mean matrix for the rows of the x-axis. The ordinate is the column deviation mean matrix. The mean of the column deviations on the y-axis. This is the number of columns in the measurement matrix.

4. The method for measuring the accuracy of a photomask according to claim 1, characterized in that, The XY combined vertical deviation Ortho is: Ortho = Ortho X + Ortho Y; Where Ortho X is the variance component of the vertical deviation in the X direction, and Ortho Y is the variance component of the vertical deviation in the Y direction.

5. A mask accuracy measurement system, characterized in that, include: The point selection module is used to select multiple points from the area to be measured and obtain the measurement data and design data of each point. The measurement matrix / design matrix construction module is used to construct a measurement matrix based on the measurement data and a design matrix based on the design data. Both the measurement matrix and the design matrix are two-dimensional matrices. The row and column order of the two-dimensional matrix corresponds to the row and column order of the points. The elements of the two-dimensional matrix are the combination of the x-coordinate (X) and y-coordinate (Y) of the corresponding points. The accuracy measurement module is used to calculate the total length variance component of X, the total length variance component of Y, the vertical deviation variance component of X direction, the vertical deviation variance component of Y direction, and the combined vertical deviation of XY based on the measurement matrix and the design matrix. The accuracy measurement module includes: The deviation matrix calculation module is used to calculate the deviation matrix of the abscissa based on the measurement matrix and the design matrix. Deviation matrix between the vertical axis and the vertical axis ; The deviation mean matrix calculation module is used to calculate the deviation matrix based on the horizontal axis. Calculate the mean matrix of row deviations on the x-axis. Mean matrix of column deviations from the x-axis According to the deviation matrix of the ordinate Calculate the mean matrix of row deviations on the y-axis. Mean matrix of column deviations from the ordinate ; The deviation mean calculation module is used to calculate the mean value of the row deviations on the horizontal axis. Calculate the mean of the row deviation of the x-axis. Based on the column deviation mean matrix of the horizontal axis Calculate the mean of the column deviations of the x-axis. Based on the mean matrix of row deviations on the ordinate Calculate the mean of the row deviation of the y-axis. Based on the column deviation mean matrix of the ordinate Calculate the mean of the column deviations of the ordinate. ; The design mean matrix calculation module is used to calculate the row design mean matrix of the x-axis based on the design matrix. The column design of the mean matrix and the vertical axis ; The X-axis total variance component calculation module is used to calculate the x-axis of the design matrix. The row design mean matrix of the horizontal axis The mean matrix of column deviations on the horizontal axis Mean deviation of column from the horizontal axis The total variance component of X, Scale X, is calculated. The Y-axis total variance component calculation module is used to calculate the Y-axis based on the ordinate of the design matrix. The column design of the y-axis is the mean matrix. The mean matrix of row deviations on the y-axis mean of row deviation from the y-axis The total variance component of Y, Scale Y, is calculated. The X-direction vertical deviation variance component calculation module is used to calculate the variance component based on the ordinate of the design matrix. The column design of the y-axis is the mean matrix. The mean matrix of row deviations on the x-axis Mean of row deviation from the x-axis The variance component of the vertical deviation in the X direction, Ortho X, is calculated. The Y-direction vertical deviation variance component calculation module is used to calculate the variance component based on the abscissa of the design matrix. The row design mean matrix of the horizontal axis The mean matrix of column deviations on the y-axis Mean of column deviation from the vertical axis Calculate the variance component of the vertical deviation in the Y direction, Ortho Y; The XY combined vertical deviation calculation module is used to calculate the XY combined vertical deviation Ortho based on the variance component Ortho X of the vertical deviation in the X direction and the variance component Ortho Y of the vertical deviation in the Y direction.

6. The mask accuracy measurement system according to claim 5, characterized in that, The X total variance component Scale X and the Y total variance component Scale Y in the X total variance component calculation module are: Scale X= ; Scale Y= ; in, To design the x-coordinate of the matrix, Design a mean matrix for the rows of the x-axis. The x-axis is the matrix of column deviations and mean values. The mean of the column deviations on the x-axis. To measure the number of columns in the matrix, To design the ordinate of the matrix, Design a mean matrix for the columns of the y-axis. The matrix represents the mean of the row deviations on the y-axis. The mean of the row deviations on the ordinate is... This is to measure the number of rows in the matrix.

7. The mask accuracy measurement system according to claim 5, characterized in that, The X-direction vertical deviation variance component Ortho X in the X-direction vertical deviation variance component calculation module and the Y-direction vertical deviation variance component Ortho Y in the Y-direction vertical deviation variance component calculation module are: Ortho X= ; Ortho Y= ; in, To design the ordinate of the matrix, Design a mean matrix for the columns of the y-axis. This is the mean matrix of row deviations on the x-axis. The mean of the row deviations on the horizontal axis. To measure the number of rows in a matrix, To design the x-coordinate of the matrix, Design a mean matrix for the rows of the x-axis. The ordinate is the column deviation mean matrix. The mean of the column deviations on the y-axis. This is the number of columns in the measurement matrix.

8. The mask accuracy measurement system according to claim 5, characterized in that, The XY combined vertical deviation Ortho in the XY combined vertical deviation calculation module is: Ortho = Ortho X + Ortho Y; Where Ortho X is the variance component of the vertical deviation in the X direction, and Ortho Y is the variance component of the vertical deviation in the Y direction.

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