Mask pattern applied to super-resolution photoetching and boundary optimization method thereof

Abstract

The invention provides a mask pattern applied to super-resolution lithography and a boundary optimization method thereof, and relates to the technical field of integrated circuit manufacturing, the boundary optimization method comprises the following steps: obtaining pattern boundary information of the mask pattern, the pattern boundary being the boundary of a pattern area and a non-pattern area in the mask pattern; performing forward simulation and accompanying simulation on the mask pattern to respectively obtain forward electric field distribution and accompanying electric field distribution; calculating the gradient of each image boundary based on the image boundary information, the forward electric field distribution and the adjoint electric field distribution; iteratively updating the pattern boundary of the mask plate pattern according to the gradient of each image boundary; and repeating the steps until the pattern error between the photoresist pattern corresponding to the updated mask pattern and the target pattern is within the error range or the number of iterations is greater than the maximum number of iterations, and outputting the mask pattern after boundary optimization.

Description

Technical Field

[0001] The present disclosure relates to the technical field of integrated circuit manufacturing, specifically to the technical field of photolithography resolution enhancement, and in particular to a mask layout applied to super-resolution photolithography and a method for optimizing its boundary. Background Art

[0002] With the development of integrated circuits, the requirements for lithography resolution are getting higher and higher. Due to the limitation of the diffraction limit, the lithography resolution of traditional projection lithography technology can only reach half the wavelength of the light source. Reducing the wavelength of the incident wave will greatly increase the complexity of the lithography system.

[0003] In recent years, surface plasmon-related technologies have made great progress. Surface plasmons have unique super-diffraction optical properties, including super-diffraction transmission properties smaller than the wavelength in the medium, field distribution bound to the surface, and electromagnetic localization under sub-wavelength scale structures. Using these properties to achieve super-resolution lithography can break through the diffraction limit of traditional optical imaging and focusing resolution, and achieve a lithography resolution far lower than the wavelength of the incident light. It has the advantages of low cost and high efficiency, which is of great significance for promoting the development of the integrated circuit industry and the advancement of micro-nano processing technology.

[0004] When the super-resolution lithography system images the mask layout, due to light diffraction and interference, there will be optical proximity effects (OPE), such as line end indentation and corner rounding defects in the photoresist pattern. These defects will affect the performance of the integrated circuit, and in severe cases, will cause the integrated circuit to fail. In order to reduce the impact of the optical proximity effect, some optical proximity effect correction methods have been proposed and adopted in recent years. Among them, the rule-based optical proximity effect correction method corrects the mask layout by establishing a correction rule library, but as the size of the lithography feature decreases, there are problems such as limited correction effect and increasingly complex correction rule library. The pixelated optical proximity effect correction method can compensate for the distortion of the output pattern by optimizing the mask layout pixel by pixel, and usually has a good correction effect, but the mask layout obtained by this method is more complex, and has disadvantages such as difficult processing and high processing costs. Summary of the invention

[0005] In view of this, a first aspect of an embodiment of the present disclosure provides a boundary optimization method for a mask layout applied to super-resolution lithography, comprising: obtaining graphic boundary information of the mask layout, wherein the graphic boundary is the boundary between a graphic area and a non-graphic area in the mask layout; performing forward simulation and adjoint simulation on the mask layout to obtain a forward electric field distribution and an adjoint electric field distribution, respectively; calculating the gradient of each image boundary based on the graphic boundary information, the forward electric field distribution and the adjoint electric field distribution; iteratively updating the graphic boundary of the mask layout according to the gradient of each image boundary; repeating the above steps until the graphic error between the photoresist graphic corresponding to the updated mask layout and the target graphic is within an error range or the number of iterations is greater than the maximum number of iterations, and outputting the mask layout with optimized boundaries.

[0006] According to an embodiment of the present disclosure, forward simulation of a mask layout is performed based on a super-resolution lithography model, including: simulating the mask layout based on the super-resolution lithography model, obtaining imaging light intensity distribution in the photoresist layer, and obtaining forward electric field distribution in the mask layer. Concomitant simulation of the mask layout is performed, including: performing concomitant simulation of the mask layout based on the super-resolution lithography model, and obtaining concomitant electric field distribution in the mask layer.

[0007] According to an embodiment of the present disclosure, the method further includes: inputting the imaging light intensity distribution into a photoresist model and outputting a photoresist pattern; and calculating a pattern error between the photoresist pattern and a target pattern.

[0008] According to an embodiment of the present disclosure, the photoresist model includes a constant threshold photoresist model, and the constant threshold photoresist model includes a relationship formula that characterizes the relationship between the photoresist pattern and the imaging light intensity distribution, the photoresist factor, and the photoresist threshold.

[0009] According to an embodiment of the present disclosure, a graphic error between a photoresist graphic and a target graphic is calculated, including: converting the photoresist graphic and the target graphic into a first binarization matrix and a second binarization matrix, respectively; and calculating the sum of squares of differences between corresponding elements of the first binarization matrix and the second binarization matrix as the graphic error.

[0010] According to an embodiment of the present disclosure, a super-resolution lithography model includes: a substrate structure, a metal reflective layer, a photoresist layer, a metal transmissive layer, an air spacer layer, and a mask layer stacked in sequence; or, a substrate structure, a photoresist layer, a metal transmissive layer, an air spacer layer, a multi-layer film structure, and a mask layer stacked in sequence; or, a substrate structure, a photoresist layer, a metal transmissive layer, an air spacer layer, a multi-layer film structure, and a mask layer stacked in sequence; or, a substrate structure, a metal transmissive layer, a photoresist layer, an air spacer layer, a multi-layer film structure, and a mask layer stacked in sequence; or, a substrate structure, a metal reflective layer, a photoresist layer, a metal transmissive layer, an air spacer layer, a multi-layer film structure, and a mask layer stacked in sequence.

[0011] According to an embodiment of the present disclosure, each graphic boundary information includes multiple component coordinate points, an external normal direction and a tangent direction; based on the graphic boundary information, the forward electric field distribution and the accompanying electric field distribution, the gradient of each image boundary is calculated, including: obtaining the dielectric constant of the mask material applied to the mask pattern, the relative dielectric constant of the mask pattern material and the vacuum dielectric constant; for each component coordinate point, based on the boundary conditions of Maxwell's equations, according to the external normal direction, the tangent direction, the forward electric field distribution, the accompanying electric field distribution, the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material and the vacuum dielectric constant, calculate the various gradient components of the component coordinate point, and obtain the corresponding total gradient based on the various gradient components of each component coordinate point; the average value of the total gradients of the multiple component coordinate points is determined as the gradient of the graphic boundary.

[0012] According to an embodiment of the present disclosure, each gradient component of a constituent coordinate point is calculated according to an external normal direction, a tangent direction, a forward electric field distribution, a concomitant electric field distribution, a dielectric constant of a mask material, a relative dielectric constant of a mask pattern material, and a vacuum dielectric constant, and a corresponding total gradient is obtained based on each gradient component of each constituent coordinate point, including: determining a first gradient component according to the tangent direction, the dielectric constant of a mask material, the relative dielectric constant of a mask pattern material, a component of a forward electric field distribution in a first direction and a component of a second direction, and a component of a concomitant electric field distribution in a first direction and a component of a second direction; determining a first gradient component according to the external normal direction, The second gradient component is determined by the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material, the dielectric constant of vacuum, the component of the forward electric displacement vector distribution related to the forward electric field distribution in the first direction and the component of the second direction, and the component of the accompanying electric displacement vector distribution related to the accompanying electric field distribution in the first direction and the component of the second direction; the third gradient component is determined according to the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material, the component of the forward electric field distribution in the third direction, and the component of the accompanying electric field distribution in the third direction; the first gradient component, the second gradient component and the third gradient component are summed to obtain the total gradient.

[0013] According to an embodiment of the present disclosure, a finite difference time domain, a strictly coupled wave or a finite element method is used to perform forward simulation and adjoint simulation on a mask layout.

[0014] A second aspect of the embodiments of the present disclosure provides a mask layout applied to super-resolution lithography. The mask layout applied to super-resolution lithography is obtained using the above-mentioned boundary optimization method.

[0015] The mask layout and boundary optimization method for super-resolution lithography provided by the embodiments of the present disclosure have at least the following technical effects:

[0016] This method obtains the gradient of the graphic boundary in the mask layout through forward simulation and adjoint simulation, and adjusts the light field intensity distribution in the photoresist layer by changing the graphic boundary position, ultimately achieving the effect of improving the fidelity of the lithography result. This method can realize the correction of the optical proximity effect without increasing the complexity of the mask layout, obtain the lithography result closer to the target graphic, and has the advantages of high optimization efficiency and wide applicability. This method also does not need to establish a complex correction rule library, and can be applied to various mask layouts with different feature sizes and areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0018] Figure 1 A flowchart of a method for optimizing a mask layout boundary applied to super-resolution lithography according to an embodiment of the present disclosure is schematically shown;

[0019] Figure 2 A flowchart of a method for optimizing a mask layout boundary applied to super-resolution lithography according to another embodiment of the present disclosure is schematically shown;

[0020] Figure 3 The schematic diagram of the structure of the super-resolution lithography model according to Embodiment 1 of the present disclosure is shown;

[0021] Figure 4 Schematically shows an initial mask layout distribution diagram used according to Embodiment 1 of the present disclosure;

[0022] Figure 5 Schematically showing the imaging light intensity distribution corresponding to the initial mask pattern distribution according to Embodiment 1 of the present disclosure;

[0023] Figure 6 A schematic diagram showing a graph showing a change in the graphic error with the number of iterations according to Embodiment 1 of the present disclosure;

[0024] Figure 7 The figure schematically shows the distribution diagram of the mask layout after optimization according to the embodiment 1 of the present disclosure;

[0025] Figure 8 The diagram schematically shows the imaging light intensity distribution corresponding to the optimized mask layout distribution according to Embodiment 1 of the present disclosure;

[0026] Fig. 9 Schematically shows an iterative curve diagram after the photoresist threshold is modified according to Embodiment 1 of the present disclosure;

[0027] Fig.10 Schematically showing an iterative curve diagram after simultaneously modifying the target pattern distribution and the photoresist threshold according to Embodiment 1 of the present disclosure;

[0028] Fig.11 Schematically showing a rectangular mask pattern before and after boundary optimization according to Embodiment 1 of the present disclosure and a contour comparison diagram of an output pattern in a corresponding photoresist and a target pattern;

[0029] Fig.12 The figure schematically shows a contour comparison diagram of a polygonal mask pattern before and after boundary optimization according to Embodiment 1 of the present disclosure and an output pattern in the corresponding photoresist and a target pattern. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present disclosure.

[0031] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0032] Similarly, in order to simplify the present disclosure and help understand one or more of the various disclosed aspects, in the above description of the exemplary embodiments of the present disclosure, the various features of the present disclosure are sometimes grouped together into a single embodiment, figure, or description thereof. The description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0033] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the feature. In the description of the present disclosure, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0034] The problem to be solved by the embodiments of the present disclosure is to provide a boundary optimization method for the optical proximity effect in super-resolution lithography, obtain the gradient of the pattern boundary in the mask layout through forward simulation and adjoint simulation, adjust the light field intensity distribution in the photoresist layer by changing the pattern boundary position, and finally achieve the effect of improving the fidelity of the lithography result. This boundary optimization method can obtain a lithography result closer to the target pattern without increasing the complexity of the mask layout, and has the advantages of high optimization efficiency and wide applicability.

[0035] The boundary optimization method of the embodiment of the present disclosure is described in detail below with reference to the accompanying drawings.

[0036] Figure 1 The flowchart of a method for optimizing the boundary of a mask layout applied to super-resolution lithography according to an embodiment of the present disclosure is schematically shown.

[0037] like Figure 1 As shown, the boundary optimization method of this embodiment may include operations S110 to S140.

[0038] In operation S110, pattern boundary information of the mask layout is acquired.

[0039] In operation S120, forward simulation and adjoint simulation are performed on the mask layout to obtain forward electric field distribution and adjoint electric field distribution, respectively.

[0040] In operation S130, the gradient of each image boundary is calculated based on the image boundary information, the forward electric field distribution, and the companion electric field distribution.

[0041] In operation S140, the pattern boundaries of the mask layout are iteratively updated according to the gradients of the respective image boundaries.

[0042] In operation S150, the above steps are repeated until the pattern error between the pattern of the updated mask layout and the target pattern is within the error range or the number of iterations is greater than the maximum number of iterations, and the mask layout with optimized boundaries is output.

[0043] According to an embodiment of the present disclosure, the initial mask layout can be set to be the same as the target pattern. The closer the photolithography imaging result is to the target pattern, the higher the imaging fidelity. The pattern boundary can be the boundary between the pattern area and the non-pattern area in the mask layout, and all edges of all polygons in the mask layout are pattern boundaries, that is, each mask layout has at least one pattern boundary, for example, the pattern boundary of a rectangle is four edges of top, bottom, left, and right.

[0044] According to the embodiments of the present disclosure, after each update of the pattern of the mask layout, the pattern error between the updated mask layout and the target pattern can be calculated. If the pattern error is not within the preset error range, operation S110 can be performed to obtain the pattern boundary of the updated mask layout, and then operations S120 to S140 can be performed, and the pattern error between the updated mask layout and the target pattern is within the preset error range, and the mask layout obtained by this update is used as the final optimized mask layout. The pattern error is used to measure the fidelity of the imaging result. Its size is related to parameters such as the number of mask patterns and the area of ​​the mask pattern. The closer the photoresist pattern is to the target pattern, the smaller the pattern error is, and the higher the fidelity of the imaging result is.

[0045] In addition, during the boundary optimization process, an iteration number threshold (i.e., the maximum iteration number) can be set. When the iteration number reaches the iteration number threshold, the mask layout obtained by the last iteration update is used as the final optimized mask layout.

[0046] The method of this embodiment can correct the optical proximity effect in super-resolution lithography and obtain higher fidelity of lithography results without increasing the complexity of the mask layout.

[0047] Based on the above embodiment, the forward simulation of the mask layout based on the super-resolution lithography model in operation S120 may include:

[0048] Based on the super-resolution lithography model, the mask layout is simulated to obtain the imaging electric field distribution and imaging light intensity distribution in the photoresist layer, and the forward electric field distribution in the mask layer. The imaging electric field distribution can be used to calculate the accompanying light source and perform accompanying simulation.

[0049] The accompanying simulation of the mask layout in operation S120 may include:

[0050] Based on the super-resolution lithography model, the mask layout is simulated and the accompanying electric field distribution is obtained in the mask layer.

[0051] According to an embodiment of the present disclosure, during one iterative update process, one forward simulation and one adjoint simulation may be performed, and then the gradients of all graphic boundaries may be obtained.

[0052] Furthermore, the super-resolution lithography model may include:

[0053] A base structure, a metal reflective layer, a photoresist layer, a metal transmission layer, an air spacer layer, and a mask layer stacked in sequence;

[0054] Alternatively, a base structure, a photoresist layer, an air spacer layer, a multilayer film structure, and a mask layer are stacked in sequence;

[0055] Alternatively, a base structure, a photoresist layer, a metal transmission layer, an air spacer layer, a multilayer film structure, and a mask layer are stacked in sequence;

[0056] Alternatively, a base structure, a metal transmission layer, a photoresist layer, an air spacer layer, a multilayer film structure, and a mask layer are stacked in sequence;

[0057] Alternatively, a base structure, a metal reflective layer, a photoresist layer, a metal transmission layer, an air spacer layer, a multi-layer film structure, and a mask layer are stacked in sequence.

[0058] That is, the boundary optimization method provided by the embodiment of the present disclosure has good applicability to various types of super-resolution lithography models.

[0059] Figure 2 A flowchart of a boundary optimization method applied to a super-resolution lithography mask layout according to another embodiment of the present disclosure is schematically shown.

[0060] like Figure 2 As shown, the boundary optimization method of this embodiment may include:

[0061] In operation S210, pattern boundary information of a mask layout is acquired.

[0062] In operation S220, forward simulation is performed on the mask pattern to obtain forward electric field distribution in the mask layer, and imaging electric field distribution and imaging light intensity distribution are obtained in the photoresist layer; and concomitant simulation is performed on the mask pattern to obtain concomitant electric field distribution in the mask layer.

[0063] In operation S230, the imaging light intensity distribution is input into a photoresist model, and a photoresist pattern is output.

[0064] In operation S240, a pattern error between the photoresist pattern and the target pattern is calculated to determine whether the pattern error is within an error range.

[0065] If the graphic error is within the error range, operation S270 is performed; if the graphic error is not within the error range, operation S240 is performed.

[0066] In operation S250, the gradient of each image boundary is calculated based on the image boundary information, the forward electric field distribution, and the companion electric field distribution.

[0067] In operation S260, the graphic boundaries of the mask layout are iteratively updated according to the gradients of the image boundaries, and the above steps are repeated until the graphic error between the photoresist pattern corresponding to the updated mask layout and the target pattern is within the error range or the number of iterations is greater than the maximum number of iterations.

[0068] In operation S270, the mask layout after boundary optimization is output.

[0069] In the embodiments of the present disclosure, the determined gradient may be a position gradient of an image boundary, and the specific gradient type may be selected according to actual application, and the present disclosure does not limit this.

[0070] In an embodiment of the present disclosure, the photoresist model may include a constant threshold photoresist model, and the constant threshold photoresist model may include a relationship formula that characterizes the relationship between the photoresist pattern and the imaging light intensity distribution, the photoresist factor, and the photoresist threshold.

[0071] In an embodiment of the present disclosure, calculating the pattern error between the photoresist pattern and the target pattern includes:

[0072] The photoresist pattern and the target pattern are converted into a first binarization matrix and a second binarization matrix respectively.

[0073] The sum of squares of differences between corresponding elements of the first binarized matrix and the second binarized matrix is ​​calculated as a graphic error.

[0074] On the basis of the above embodiment, based on the graphic boundary information, the forward electric field distribution and the accompanying electric field distribution, calculating the gradient of each image boundary may include:

[0075] Obtain the dielectric constant of the mask material used in the mask layout, the relative dielectric constant of the mask pattern material, and the vacuum dielectric constant. The mask material is the mask absorption layer material (such as Cr), and the mask pattern material is the material (such as air) filling the gaps in the pattern formed by the mask absorption layer.

[0076] For each component coordinate point, based on the boundary conditions of Maxwell's equations, the gradient components of the component coordinate point are calculated according to the external normal direction, tangent direction, forward electric field distribution, accompanying electric field distribution, dielectric constant of mask material, relative dielectric constant of mask pattern material and vacuum dielectric constant, and the corresponding total gradient is obtained based on the gradient components of each component coordinate point.

[0077] The average value of the total gradient of the plurality of component coordinate points is determined as the gradient of the graphic boundary.

[0078] Further, calculating each gradient component of the constituent coordinate points according to the external normal direction, the tangent direction, the forward electric field distribution, the accompanying electric field distribution, the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material, and the vacuum dielectric constant, and obtaining the corresponding total gradient based on the gradient component of each constituent coordinate point may include:

[0079] Determine a first gradient component according to a tangent direction, a dielectric constant of a mask material, a relative dielectric constant of a mask pattern material, a component of a forward electric field distribution in a first direction and a component of a second direction, and a component of a companion electric field distribution in a first direction and a component of a second direction;

[0080] The second gradient component is determined based on the external normal direction, the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material, the dielectric constant of vacuum, the component of the forward electric displacement vector distribution associated with the forward electric field distribution in the first direction and the component of the second direction, and the component of the accompanying electric displacement vector distribution associated with the accompanying electric field distribution in the first direction and the component of the second direction.

[0081] The third gradient component is determined according to the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material, the component of the forward electric field distribution in the third direction, and the component of the accompanying electric field distribution in the third direction.

[0082] The first gradient component, the second gradient component, and the third gradient component are summed to obtain a total gradient.

[0083] In order to more clearly illustrate the above boundary optimization method, a specific embodiment is listed below to illustrate the above boundary optimization method. It should be understood that this embodiment is for more clearly illustrating the present disclosure and is not used to limit the present disclosure.

[0084] Example 1

[0085] The boundary optimization method of this embodiment may include the following operations:

[0086] Step 1: Set the target shape , set the initial mask layout to be the same as the target graphic, and obtain all graphic boundary information of the initial mask layout.

[0087] Each graphic boundary information contains component coordinate points, external normal direction and tangent direction. The component coordinate points are composed of the starting coordinate point, the final coordinate point and the intermediate coordinate point, where the number of intermediate coordinate points is determined by the number of grid divisions during lithography simulation. The external normal direction and tangent direction of each graphic boundary are represented by a coordinate point respectively.

[0088] For example, for Manhattan graphics, there are only four directions of the external normal of the graphics boundary, namely (-1, 0), (0,1), (1, 0), (0, -1), and the tangent direction is perpendicular to the external normal direction, corresponding to (0, 1), (1, 0), (0,-1), (-1, 0). The variable to be optimized for each graphics boundary is the graphics boundary position , the graphic boundary position is included in the component coordinate points of the graphic boundary information, which can be selected as the starting coordinate point or the final coordinate point.

[0089] Step 2: Use the super-resolution lithography model to simulate the mask layout and obtain the imaging electric field distribution in the photoresist layer and imaging light intensity distribution , and at the same time obtain the positive electric field distribution in the mask layer .

[0090] The mask layout is forward simulated using finite-difference time-domain, rigorous coupled-wave or finite element methods.

[0091] Step 3: Use the imaging light intensity distribution and photoresist model in step 2 to obtain the photoresist pattern, calculate the pattern error between the photoresist pattern and the target pattern, and determine whether the stop iteration condition is met based on the pattern error. If the pattern error is less than the set error threshold, or the number of iterations is greater than the maximum number of iterations, go to step 7, otherwise go to step 4.

[0092] The input of the photoresist model is the imaging light intensity distribution, and the output is the photoresist pattern. The photoresist model can adopt a constant threshold photoresist model. The constant threshold photoresist model can be expressed as ,in, is the photoresist factor, Tr is the photoresist threshold, and the output photoresist pattern is .

[0093] In this embodiment, the pattern error is defined as the sum of the squares of the differences between the target pattern and the photoresist pattern, that is, ,in The target graphic.

[0094] Step 4: Use the super-resolution lithography model to perform accompanying simulation on the mask layout and obtain the accompanying electric field distribution in the mask layer.

[0095] In the companion simulation, first disable the source in the forward simulation, and then add the companion source. The companion source for the constant threshold resist model is (x, y), where * represents the complex conjugate, (x, y) represents the imaging electric field distribution The complex conjugate of . The accompanying electric field distribution of the mask layer is obtained through the accompanying simulation .

[0096] The mask layout can be simulated using finite-difference time-domain, rigorous coupled-wave or finite element methods.

[0097] Step 5: Based on all the graphic boundary information in step 1, the forward electric field distribution in step 2 and the accompanying electric field distribution in step 4, the gradient of the graphic error relative to the graphic boundary is calculated.

[0098] For example, for each shape boundary, with an external normal direction N and a tangent direction T, each component coordinate point can be calculated Gradient According to the boundary conditions of Maxwell's equations, the electric field is continuous in the tangent direction of the boundary and the electric displacement vector is continuous in the normal direction of the boundary, and the first gradient component of the graphic error can be calculated. , the second gradient component , the third gradient component and the total gradient .

[0099]

[0100] ]

[0101]

[0102]

[0103] in and are the dielectric constant of the mask material and the relative dielectric constant of the mask pattern material, respectively. is the dielectric constant of vacuum, and The forward electric field distribution is and the accompanying electric field distribution The p component (p = x, y or z), and The forward electric displacement vector distributions related to the forward electric field distribution and the accompanying electric field distribution are and the accompanying electric displacement vector distribution The p component of .

[0104] The gradient of each shape border is the gradient of all the coordinate points that make up the boundary of the graphic The number of gradients of the graph boundaries obtained in this step is equal to the number of graph boundaries that can be optimized.

[0105] Step 6: According to the gradient of the graphic boundary in step 5, use the steepest descent method to iteratively update each graphic boundary position, that is, , and update all graphic boundary information and mask layouts, where the iterative step length of the steepest descent method is , go to step 2.

[0106] Step 7: Output the optimized mask layout.

[0107] Figure 3 A schematic diagram of the structure of a super-resolution lithography model according to Embodiment 1 of the present disclosure is shown schematically.

[0108] like Figure 3As shown, the super-resolution lithography model used in Example 1 includes a base structure, a metal reflective layer, a photoresist layer, a metal transmission layer, an air spacer layer, and a mask layer stacked in sequence. The thickness of the mask layer is 40 nm, the air spacer is 40 nm, the thickness of the metal transmission layer is 20 nm, the thickness of the metal reflective layer is 30 nm, and the thickness of the photoresist layer is 50 nm. To simplify the calculation, the lithography model result can be set to a two-dimensional model, and the photoresist threshold is set to 0.8 and the photoresist factor is set to 50 during the optimization. It should be understood that the boundary optimization method disclosed in the present invention is also applicable to a three-dimensional super-resolution lithography model structure.

[0109] Figure 4 The diagram schematically shows an initial mask layout distribution diagram used in Embodiment 1 of the present disclosure.

[0110] like Figure 4 As shown, the target pattern contains 5 line patterns, each line width is 45 nm, and the spacing between lines is 660 nm. For this mask pattern, there are 10 pattern boundaries, each of which is marked with a pattern boundary position. In the boundary optimization, a total of 10 variables need to be optimized, and the distribution corresponds to the left and right boundaries of the 5 lines. Figure 4 The interval with a median value of 0 represents an opaque metal material, and the line interval with a value of 1 represents an air slot.

[0111] Figure 5 The imaging light intensity distribution corresponding to the initial mask pattern distribution according to Example 1 of the present disclosure is schematically shown.

[0112] like Figure 5 As shown, the imaging light intensity distribution corresponding to the initial mask layout distribution provides the photoresist threshold as a reference.

[0113] Figure 6 A curve diagram showing the variation of the graphic error with the number of iterations according to Embodiment 1 of the present disclosure is schematically shown.

[0114] like Figure 6 As shown, the horizontal axis is the number of iterations, and the vertical axis is the image error. It can be seen that as the iteration proceeds, the image error gradually decreases from 37.97 to 1.39. The substantial decrease in the image error indicates that the fidelity of the imaging result has been substantially improved. In this embodiment, the maximum number of iterations set is 20, the error threshold is 0.5, and the steepest descent method iteration step is 0.25.

[0115] Figure 7 The diagram schematically shows the mask layout distribution diagram after optimization according to Example 1 of the present disclosure.

[0116] like Figure 7As shown, the line widths of each line in the mask layout after boundary optimization are 54.1 nm, 61.0 nm, 62.9 nm, 61.9 nm, and 54.1 nm, respectively.

[0117] Figure 8 The imaging light intensity distribution corresponding to the optimized mask pattern distribution according to Example 1 of the present disclosure is schematically shown.

[0118] like Figure 8 As shown, the mask layout distribution after optimization gives the photoresist threshold as a reference.

[0119] Fig. 9 The iterative curve diagram after the photoresist threshold is modified according to the embodiment 1 of the present disclosure is schematically shown.

[0120] like Fig. 9 As shown in FIG. 1 , the graphic error variation curve obtained by iterating after modifying the photoresist to 0.6, after 20 iterations, the graphic error dropped from 6.02 to 0.97, indicating that the method disclosed in the present invention has good applicability to different photoresist models.

[0121] Fig.10 The iterative curve diagram after simultaneously modifying the target pattern distribution and the photoresist threshold according to Embodiment 1 of the present disclosure is schematically shown.

[0122] like Fig.10 As shown in FIG. 1 , the graphic error variation curve is obtained by iterating after changing the spacing between line graphics to 130 nm and changing the photoresist threshold to 1.0. After 20 iterations, the graphic error decreases from 60.8 to 26.6, which indicates that the boundary optimization method disclosed in the present invention has good applicability to different mask layouts.

[0123] Fig.11 The following schematically shows a comparison diagram of the outlines of a rectangular mask pattern and its corresponding output pattern and target pattern in the photoresist before and after boundary optimization according to Embodiment 1 of the present disclosure.

[0124] like Fig.11 As shown, Fig.11 111 is the photoresist target pattern in the 3D super-resolution lithography model, which is also the initial mask layout distribution. It contains a rectangle with a length of 300nm and a width of 60nm. A total of four variables need to be optimized, which are the positions of the four boundaries of the rectangle. The interval with a value of 0 represents an opaque metal material, and the line interval with a value of 1 represents an air slot.

[0125] Fig.11 Reference numeral 112 is the light intensity distribution of the photoresist layer imaging corresponding to the target pattern as the initial mask layout distribution.

[0126] Fig.11113 is a photoresist profile of a photoresist layer obtained by using a target pattern as an initial mask pattern, which is obtained by performing photoresist model processing using the imaging light intensity in 112 .

[0127] Fig.11 114 in the middle is the mask layout obtained after boundary optimization, which is obtained by optimizing the position of each edge. The optimized figure is still a Manhattan figure, and the complexity of the mask layout is not increased.

[0128] Fig.11 Reference numeral 115 is the imaging light intensity distribution corresponding to the optimized mask pattern distribution.

[0129] Fig.11 Reference numeral 116 is a photoresist profile corresponding to the mask layout distribution after optimization.

[0130] Fig.11 Figure 117 is a comparison of the photoresist profile and the target pattern obtained before and after optimization. It can be seen that the optimized photoresist profile is closer to the target pattern.

[0131] Fig.11 Figure 118 is an iteration curve during the boundary optimization process during iteration, the horizontal axis is the number of iterations, and the vertical axis is the graphic error.

[0132] from Fig.11 It can be seen that as the iteration proceeds, the pattern error gradually decreases from 184 to 40. The substantial decrease in the pattern error indicates that the fidelity of the imaging result has been substantially improved. In this embodiment, the maximum number of iterations is set to 15, the photoresist threshold is 0.19, the pattern error threshold is 10, and the steepest descent method iteration step is 0.1.

[0133] Fig.12 The figure schematically shows a contour comparison diagram of a polygonal mask pattern before and after boundary optimization according to Embodiment 1 of the present disclosure and an output pattern in the corresponding photoresist and a target pattern.

[0134] like Fig.12 As shown, Fig.12 121 is another photoresist target pattern, which is a polygon. The side lengths of the polygon starting from the lower left corner are 50 nm, 100 nm, 200 nm, 50 nm, 250 nm, and 150 nm. A total of six variables need to be optimized, which are the positions of the six boundaries of the polygon. The interval with a value of 0 in the figure represents an opaque metal material, and the line interval with a value of 1 represents an air slot.

[0135] Fig.12 Reference numeral 122 is the light intensity distribution of the photoresist layer imaging corresponding to the target pattern as the initial mask layout distribution.

[0136] Fig.12123 is a photoresist profile of a photoresist layer obtained by using a target pattern as an initial mask pattern, which is obtained by performing photoresist model processing using the imaging light intensity in 122 .

[0137] Fig.12 124 in the figure is the mask layout obtained after boundary optimization, and the complexity of the mask layout is not increased.

[0138] Fig.12 In the middle, 125 is the imaging light intensity distribution corresponding to the optimized mask pattern distribution.

[0139] Fig.12 Reference numeral 126 is the photoresist profile corresponding to the mask layout distribution after optimization.

[0140] Fig.12 Figure 127 is a comparison of the photoresist profile and the target pattern obtained before and after optimization. It can be seen that the optimized photoresist profile is closer to the target pattern.

[0141] Fig.12 Figure 128 is an iteration curve in the iterative boundary optimization process, the horizontal axis is the number of iterations, and the vertical axis is the graphic error.

[0142] from Fig.12 It can be seen that as the iteration proceeds, the graphic error gradually decreases from 628 to 69. The substantial decrease in the graphic error indicates that the fidelity of the imaging result has been substantially improved. In this embodiment, the maximum number of iterations is set to 15, the photoresist threshold is 0.1, the error threshold is 10, and the steepest descent method iteration step is 0.1.

[0143] It can be seen from this that in the process of optimizing the graphic boundaries of the mask layout, the present invention only needs to use one forward simulation and one accompanying simulation method to obtain the gradients of all graphic boundaries, and then use the steepest descent method to iteratively update the position of the graphic boundaries. It has the characteristics of wide applicability and high optimization efficiency.

[0144] It should be noted that the specific parameters, material types and processing methods involved in the above examples are all for the purpose of more clearly illustrating the boundary optimization method provided by the embodiments of the present disclosure, and are not intended to limit the present disclosure.

[0145] The embodiments of the present disclosure further provide a mask layout for super-resolution lithography, which is obtained by using the above-mentioned boundary optimization method. The specific implementation details are not repeated here.

[0146] The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present disclosure in detail. It should be understood that the above are only preferred embodiments of the present disclosure and the technical principles used. Those skilled in the art will understand that the present disclosure is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present disclosure. Therefore, although the present disclosure is described in more detail through the above embodiments, the present disclosure is not limited to the above embodiments, and may also include more other equivalent embodiments without departing from the concept of the present disclosure, all of which belong to the protection scope of the present disclosure.

Claims

1. A method for optimizing the boundary of a mask layout for super-resolution lithography, characterized in that: include: Acquire graphic boundary information of the mask layout, wherein the graphic boundary is a boundary between a graphic area and a non-graphic area in the mask layout; Performing forward simulation and adjoint simulation on the mask pattern to obtain forward electric field distribution and adjoint electric field distribution respectively; Calculating the gradient of each image boundary based on the graphic boundary information, the forward electric field distribution and the accompanying electric field distribution; Iteratively updating the graphic boundaries of the mask layout according to the gradients of the boundaries of each image; Repeat the above steps until the graphic error between the photoresist pattern corresponding to the updated mask layout and the target pattern is within the error range or the number of iterations is greater than the maximum number of iterations, and output the mask layout with optimized boundaries.

2. The method according to claim 1, characterized in that The forward simulation of the mask layout based on the super-resolution lithography model includes: Simulating the mask pattern based on a super-resolution lithography model to obtain imaging light intensity distribution in the photoresist layer and the forward electric field distribution in the mask layer; The accompanying simulation of the mask layout includes: The accompanying electric field distribution is obtained on the mask layer by performing accompanying simulation on the mask layout based on the super-resolution lithography model.

3. The method according to claim 2, characterized in that Also includes: Inputting the imaging light intensity distribution into a photoresist model and outputting the photoresist pattern; The pattern error between the photoresist pattern and the target pattern is calculated.

4. The method according to claim 3, characterized in that The photoresist model includes a constant threshold photoresist model, and the constant threshold photoresist model includes a relationship formula that characterizes the relationship between the photoresist pattern and the imaging light intensity distribution, the photoresist factor, and the photoresist threshold.

5. The method according to claim 3, characterized in that: The calculating the pattern error between the photoresist pattern and the target pattern comprises: Converting the photoresist pattern and the target pattern into a first binarization matrix and a second binarization matrix respectively; The sum of squares of differences between corresponding elements of the first binarization matrix and the second binarization matrix is ​​calculated as the graphic error.

6. The method according to claim 2, characterized in that The super-resolution lithography model comprises: A base structure, a metal reflective layer, a photoresist layer, a metal transmission layer, an air spacer layer, and a mask layer stacked in sequence; Alternatively, a base structure, a photoresist layer, an air spacer layer, a multilayer film structure, and a mask layer are stacked in sequence; Alternatively, a base structure, a photoresist layer, a metal transmission layer, an air spacer layer, a multilayer film structure, and a mask layer are stacked in sequence; Alternatively, a base structure, a metal transmission layer, a photoresist layer, an air spacer layer, a multilayer film structure, and a mask layer are stacked in sequence; Alternatively, a base structure, a metal reflective layer, a photoresist layer, a metal transmission layer, an air spacer layer, a multi-layer film structure, and a mask layer are stacked in sequence.

7. The method according to claim 1, characterized in that Each of the graphic boundary information includes a plurality of component coordinate points, an external normal direction and a tangent direction; The step of calculating the gradient of each image boundary based on the graphic boundary information, the forward electric field distribution and the accompanying electric field distribution comprises: Obtaining the dielectric constant of the mask material used in the mask layout, the relative dielectric constant of the mask pattern material, and the vacuum dielectric constant; For each component coordinate point, based on the boundary conditions of Maxwell's equations, the gradient components of the component coordinate point are calculated according to the external normal direction, the tangent direction, the forward electric field distribution, the accompanying electric field distribution, the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material, and the vacuum dielectric constant, and the corresponding total gradient is obtained based on the respective gradient components of each component coordinate point; The average value of the total gradients of the plurality of component coordinate points is determined as the gradient of the graphic boundary.

8. The method according to claim 7, characterized in that The step of calculating the gradient components of the constituent coordinate points according to the external normal direction, the tangent direction, the forward electric field distribution, the accompanying electric field distribution, the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material, and the dielectric constant of the vacuum, and obtaining the corresponding total gradient based on the gradient components of each constituent coordinate point includes: Determine a first gradient component according to the tangent direction, the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material, the component of the forward electric field distribution in the first direction and the component of the second direction, and the component of the accompanying electric field distribution in the first direction and the component of the second direction; Determine a second gradient component according to the external normal direction, the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material, the dielectric constant of vacuum, the component of the forward electric displacement vector distribution related to the forward electric field distribution in the first direction and the component of the second direction, and the component of the accompanying electric displacement vector distribution related to the accompanying electric field distribution in the first direction and the component of the second direction; Determine a third gradient component according to the dielectric constant of the mask material, the relative dielectric constant of the mask pattern material, the component of the forward electric field distributed in the third direction, and the component of the accompanying electric field distributed in the third direction; The first gradient component, the second gradient component and the third gradient component are summed to obtain the total gradient.

9. The method according to claim 1, characterized in that: The forward simulation and adjoint simulation of the mask pattern are performed by using a time-domain finite difference method, a strictly coupled wave method or a finite element method.

10. A mask layout for super-resolution lithography, characterized in that: The mask pattern used for super-resolution lithography is obtained by the method according to any one of claims 1 to 9.

Images