OPC and PSM collaborative optimization method for advanced process mask

Abstract

The application relates to the technical field of semiconductor photoetch mask manufacturing, and discloses an OPD and PSM cooperative optimization method for advanced process mask plates, wherein the method comprises the following steps: obtaining target layout pattern data and advanced process photoetch parameters; generating an initial phase distribution diagram of a phase shift mask based on the topological features of the target layout pattern data; performing phase-aware optical proximity correction on the target layout pattern according to the initial phase distribution diagram and the process parameters to obtain corrected mask pattern data; performing photoetch imaging simulation based on the corrected mask pattern data; iteratively updating the phase distribution and the optical proximity correction parameters according to a pattern fidelity index; and outputting final cooperatively optimized mask plate data.

Description

Technical Field

[0001] Embodiments of this disclosure relate to the field of semiconductor photomask manufacturing technology, and more particularly to an OPC and PSM co-optimization method, system, electronic device, and storage medium for advanced process photomasks. Background Technology

[0002] As integrated circuit process nodes continue to advance to below 7 nanometers, the diffraction-limited effect faced by photolithography becomes increasingly significant. In 193-nanometer immersion lithography systems, although the numerical aperture has been increased to the range of 1.20 to 1.35, the ratio of exposure wavelength to feature size is still much greater than 1. This results in optical interference effects between adjacent patterns having a significant impact on image fidelity. The placement error of pattern edges and the deviation of critical dimension uniformity continue to worsen as the process node shrinks.

[0003] To address the aforementioned challenges in image fidelity, optical proximity correction (OPC) and phase-shifting masking techniques are widely used in the fabrication processes of advanced process masks. OPC applies a pre-compensation offset to the edges of the mask pattern, making the actual image contour on the wafer approximate the target pattern. Phase-shifting masking, on the other hand, introduces a 180-degree phase difference between adjacent transparent regions, utilizing destructive interference to enhance the contrast of the pattern edges. These two techniques are inherently coupled in their physical mechanisms: the phase allocation directly affects the spatial image intensity distribution upon which OPC relies, while the edge offset introduced by OPC alters the local optical field characteristics near the phase transition stripe.

[0004] The inventors of this disclosure have noted that current mask optimization schemes do not take into account the bidirectional coupling relationship between phase assignment and optical proximity correction. They typically employ a serial process of completing phase assignment first and then independently performing optical proximity correction, which results in edge placement errors near the phase transition strip being unable to be effectively compensated by subsequent optical proximity correction steps. Consequently, the final mask pattern exhibits insufficient imaging robustness within the depth of focus range. Summary of the Invention

[0005] The purpose of this invention is to provide a collaborative optimization method for OPC and PSM of advanced process masks, which solves the technical problems of image error accumulation, insufficient image fidelity and narrowing process window caused by the independent execution of phase allocation and optical proximity correction of phase-shifting masks in the prior art.

[0006] This disclosure provides at least one embodiment of an advanced process mask co-optimization method for OPC and PSM. The method includes: acquiring target layout graphic data and advanced process lithography parameters; performing phase assignment operations on the transparent regions according to the spatial adjacency relationship and spacing distribution characteristics of each transparent region in the target layout graphic data to generate an initial phase allocation map of the phase-shifting mask; incorporating the phase marker values ​​and transmittance weight coefficients of each region in the initial phase allocation map into the optical proximity correction imaging model calculation in the form of complex amplitudes, solving for the correction offset of each graphic edge to obtain corrected mask graphic data; and performing lithography imaging simulation based on the corrected mask graphic data, determining whether a preset convergence condition is met according to the graphic fidelity index in the simulation results, and if not, jointly iteratively updating the initial phase allocation map and the correction offset until the preset convergence condition is met, and then outputting the final co-optimized mask layout data, wherein the transmittance weight coefficient is determined according to the distance between each transparent region and the nearest neighbor opaque graphic edge.

[0007] Furthermore, in the method provided in at least one embodiment of this disclosure, the step of performing a phase assignment operation on the light-transmitting region includes: performing graph-based representation of the light-transmitting region in the target layout graphic data, mapping each light-transmitting region to a node in the graph, and mapping the boundary relationship between adjacent light-transmitting regions to connecting edges; performing a binary coloring algorithm based on the graph structure of the graph-based representation, assigning each node to a 0-degree phase or a 180-degree phase, such that the phase difference between adjacent light-transmitting regions sharing a boundary is 180 degrees.

[0008] Furthermore, in the method provided in at least one embodiment of this disclosure, for a topology with an odd number of loops in the graph structure, a phase transition strip is inserted between two adjacent light-transmitting regions corresponding to conflicting edges. The width of the phase transition strip does not exceed one-quarter of the ratio of the exposure wavelength to the numerical aperture, and the transmittance of the phase transition strip is set to zero. The initial phase assignment map includes the phase marker value of each light-transmitting region and the geometric position and width parameters of each phase transition strip.

[0009] Furthermore, in the method provided in at least one embodiment of this disclosure, the transmittance weighting coefficient With distance The relationship between them is determined by piecewise linear mapping: when hour, ;when hour, ,in The distance between the light-transmitting area and the nearest opaque edge of the graphic is [missing information]. The preset nearest neighbor threshold, The minimum allowable transmittance weighting coefficient.

[0010] Furthermore, in the method provided in at least one embodiment of this disclosure, the step of incorporating the phase marker values ​​and transmittance weighting coefficients of each region in the initial phase allocation map into the optical proximity correction imaging model calculation in the form of complex amplitudes includes: calculating the transfer cross coefficient matrix of the optical system based on the exposure wavelength, numerical aperture, and partial coherence factor in the advanced process lithography parameters, wherein the complex amplitude of the 0-degree phase region is taken as the corresponding transmittance weighting coefficient. The positive real number, the complex amplitude of the 180-degree phase region is taken as the corresponding transmittance weighting coefficient. The negative real number, the complex amplitude of the opaque region is zero; the spatial image intensity at each evaluation point is calculated based on the transfer cross coefficient matrix, the evaluation points are arranged along the edge of each pattern with a sampling interval not exceeding half of the minimum set line width; the edge placement error is calculated according to the difference between the spatial image intensity value at each evaluation point and the photoresist contrast threshold, when the edge placement error exceeds the preset tolerance, the correction offset is obtained by inverting the sensitivity matrix of the edge placement error relative to the edge displacement.

[0011] Furthermore, in the method provided in at least one embodiment of this disclosure, for evaluation points located on both sides of the phase transition strip, a phase gradient compensation term is introduced during the solution of the correction offset. The calculation method is as follows ,in The distance from the evaluation point to the center line of the phase transition strip. For the strip width, The phase gradient compensation coefficient is the ratio of the spatial image intensity difference between the evaluation points on both sides of the strip to the diagonal elements of the sensitivity matrix. This phase gradient compensation term is only applied to conditions satisfying... The evaluation points will take effect.

[0012] Furthermore, in the method provided in at least one embodiment of this disclosure, the joint iterative update adopts an alternating direction optimization strategy, including: a phase update sub-step: fixing the current correction offset, performing position adjustment or width modification operations on the phase transition strips with error concentrations based on the edge placement error distribution of evaluation points in each phase transition strip region in the simulation results, and recalculating the transmittance weight coefficient of the affected light-transmitting region; a correction update sub-step: fixing the updated initial phase allocation map, re-performing phase-aware optical proximity correction with the correction offset of the previous iteration as the initial value, and obtaining the updated correction offset and mask pattern data; a convergence determination sub-step: re-performing lithography imaging simulation based on the updated mask pattern data and the initial phase allocation map, calculating the pattern fidelity index value of the current iteration, and terminating the iteration if the preset convergence condition is met or the preset maximum number of iterations is reached.

[0013] Furthermore, in the method provided in at least one embodiment of this disclosure, in the convergence determination sub-step, in addition to performing photolithography imaging simulation at the optimal focal plane position, simulation is also performed at multiple focal plane offset positions for positive and negative defocus to obtain the change in edge placement error of each evaluation point at different focal plane positions; if the change in edge placement error of any evaluation point within the depth of focus range exceeds the preset process window tolerance, the graphic region corresponding to the evaluation point is marked as a depth-of-focus sensitive region, and in the next phase update sub-step, the depth-of-focus sensitive region is preferentially subjected to phase reassignment operation.

[0014] At least one embodiment of this disclosure also provides an OPC and PSM collaborative optimization system for advanced process masks. The system includes a data acquisition unit, a phase allocation unit, a phase-aware correction unit, and an iterative collaborative optimization unit. The data acquisition unit is configured to acquire target layout graphic data and advanced process lithography parameters. The phase allocation unit is configured to perform phase assignment operations on the transparent regions based on the spatial adjacency relationship and spacing distribution characteristics of each transparent region in the target layout graphic data, generating an initial phase allocation map for the phase-shifting mask. The phase-aware correction unit is configured to... The phase marker values ​​and transmittance weight coefficients of each region in the phase allocation map are incorporated into the optical proximity correction imaging model calculation in the form of complex amplitudes. The correction offset is calculated for each pattern edge to obtain the corrected mask pattern data. The iterative collaborative optimization unit is configured to perform lithographic imaging simulation based on the corrected mask pattern data. It determines whether the preset convergence condition is met based on the pattern fidelity index in the simulation results. If the condition is not met, the initial phase allocation map and the correction offset are jointly iteratively updated until the preset convergence condition is met, and then the final collaboratively optimized mask pattern data is output.

[0015] At least one embodiment of this disclosure also provides an electronic device, including: at least one memory storing computer-executable instructions non-transitory; and at least one processor configured to run the computer-executable instructions, wherein the computer-executable instructions, when run by the processor, implement the OPC and PSM co-optimization method for advanced process mask as described in any embodiment of this disclosure.

[0016] Beneficial effects: The advanced process mask OPC and PSM co-optimization method provided in this disclosure incorporates the phase marker value and transmittance weight coefficient into the imaging model of optical proximity correction in the form of complex amplitudes. This allows the phase allocation information to be directly reflected in the solution of edge placement error, thereby making the correction direction of optical proximity correction and the light field modulation effect of phase allocation more consistent, which helps to reduce the edge placement error near the phase transition strip.

[0017] By introducing phase gradient compensation terms at the evaluation points on both sides of the phase transition strip, the local spatial image distortion caused by the phase abrupt change is specifically corrected, so that the solution of the correction offset has a more reasonable physical basis in the phase discontinuity region, which helps to improve the image fidelity index in this region.

[0018] By employing an alternating direction optimization strategy to jointly iteratively update the phase assignment and optical proximity correction parameters, the optimization directions of the two tend to be consistent in each iteration, rather than converging independently to local optima, which helps to improve the global convergence quality of the overall mask pattern.

[0019] By introducing depth-of-focus sensitivity assessment during the iterative convergence determination process, phase reassignment operations are preferentially performed on regions where the change in edge placement error exceeds the process window tolerance within the depth-of-focus range, which helps to enhance the imaging stability of the final mask pattern within the actual lithography process depth-of-focus range.

[0020] By storing the final co-optimized mask layout data in a hierarchical structure, the phase marker information, the corrected pattern edge data, and the phase transition strip geometric parameters are aligned through a unified spatial coordinate reference system, which facilitates direct reading in subsequent mask manufacturing processes and helps reduce information loss in the data conversion process. Attached Figure Description

[0021] Figure 1 This is a flowchart of the OPC and PSM collaborative optimization method for advanced process mask provided in this embodiment of the invention;

[0022] Figure 2 This is a schematic diagram of the overall flowchart of phase-shift mask collaborative optimization provided in an embodiment of the present invention;

[0023] Figure 3 This is a schematic diagram of the topology of the light-transmitting region and the phase allocation diagram provided in the embodiments of the present invention;

[0024] Figure 4 This is a schematic diagram of the relationship between the transmittance weighting coefficient of the light-transmitting area and the nearest neighbor distance provided in an embodiment of the present invention;

[0025] Figure 5 This is a schematic diagram of the distribution of spatial image intensity and correction offset of representative evaluation points provided in the embodiments of the present invention;

[0026] Figure 6 This is a schematic diagram of the convergence curve of the graph fidelity index during the iteration process provided in the embodiment of the present invention;

[0027] Figure 7 This is a schematic diagram comparing the graph fidelity index and convergence threshold for each iteration round provided in the embodiments of the present invention;

[0028] Figure 8 This is a schematic diagram of the flowchart of the phase-sensing optical proximity correction sub-step provided in an embodiment of the present invention;

[0029] Figure 9 This is a schematic diagram of the three-layer hierarchical storage structure of the final mask layout data provided in the embodiments of the present invention. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0031] As shown in the present invention application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "are not specifically singular and may also include plural. Generally speaking, the terms "comprising" and "including" only indicate that the steps and elements are explicitly identified, and "multiple" includes one, two, or more, and these steps and elements do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0032] While this application makes various references to certain modules of the system according to embodiments of the present invention, any number of different modules can be used and run on user terminals and / or servers. The modules are merely illustrative, and different aspects of the system and method may use different modules.

[0033] This invention application uses flowcharts to illustrate the operations performed by the system according to embodiments of the invention. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously, as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0034] Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely a part of the embodiments of the present invention, and not all of the embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0035] It is worth noting that, in this invention application, all data acquisition actions are carried out in compliance with the relevant data protection laws and policies of the country where the data is acquired, and with the authorization granted by the owner of the relevant device.

[0036] Firstly, reference Figures 1 to 9 This embodiment provides an implementation method for the collaborative optimization of OPC and PSM in advanced process masks.

[0037] The advanced process mask OPC and PSM co-optimization method provided in at least one embodiment of this disclosure includes the following steps S100-S400.

[0038] Step S100: Obtain the target layout graphic data and advanced process lithography parameters.

[0039] In step S100, the target layout pattern data of the chip layer to be processed and the advanced process lithography parameters corresponding to the target layout pattern data are obtained.

[0040] Furthermore, the target layout graphic data includes the vertex coordinate sequence of each polygon graphic in the target layer, the graphic spacing distribution, and key dimension annotation values; the advanced process lithography parameters include exposure wavelength, numerical aperture, partial coherence factor, photoresist contrast threshold, and depth of focus range.

[0041] In at least one example of the embodiments of this disclosure, the target layout graphic data is stored in GDSII or OASIS format, wherein each graphic layer is indexed by layer number and data type number; the process node corresponding to the advanced process lithography parameters is a node below 7 nanometers, wherein the exposure wavelength is the wavelength value used in the 193 nanometer immersion lithography system, and the numerical aperture value ranges from 1.20 to 1.35.

[0042] Reference Appendix Figures 2-4 Step S200: Based on the topological features of the target layout graphic data, generate an initial phase allocation map of the phase shift mask.

[0043] In step S200, based on the spatial adjacency relationship and spacing distribution characteristics of each graphic in the target layout graphic data, a phase assignment operation is performed on the light-transmitting area of ​​the mask to generate an initial phase allocation map of the phase-shifting mask.

[0044] Furthermore, the transparent regions in the target map graphic data are represented using graph theory, where each transparent region is mapped to a node in the graph, and the boundary relationship between adjacent transparent regions is mapped to connecting edges. Based on the graph structure represented by the graph theory, a binary coloring algorithm is executed to assign each node to a 0-degree phase or a 180-degree phase, so that the phase difference between adjacent transparent regions sharing a boundary is 180 degrees, thereby utilizing the destructive interference effect to improve edge contrast.

[0045] In at least one example of the embodiments of this disclosure, for a topology with an odd number of loops (i.e., a graph-colored conflict region), a phase transition strip with a width not exceeding one-quarter of the ratio of the exposure wavelength to the numerical aperture is inserted between two adjacent transparent regions corresponding to the conflict edge. The transmittance of the phase transition strip is set to zero, thereby physically cutting off the propagation path of the phase conflict. The initial phase assignment map includes the phase marker values ​​of each transparent region and the geometric position and width parameters of each phase transition strip.

[0046] In at least one example of the embodiments of this disclosure, the initial phase assignment map further includes a transmittance weighting coefficient for each transparent region, which is obtained based on the distance between the transparent region and the nearest neighbor opaque edge; when the distance is less than a preset nearest neighbor threshold, the transmittance weighting coefficient is adaptively reduced to compensate for the impact of edge placement error on the phase effect in the subsequent optical proximity correction step.

[0047] It should be noted that the transmittance weighting coefficient With distance The relationship between them is determined by piecewise linear mapping: when hour, ;when hour, ,in The distance between the light-transmitting area and the nearest opaque edge of the graphic is [missing information]. The preset nearest neighbor threshold, This is the minimum permissible transmittance weighting coefficient. In the formula... and If the two quantities have the same dimension, their ratio is a dimensionless ratio. and All are dimensionless transmittance weighting coefficients, and all dimensions are consistent.

[0048] Reference Appendix Figure 4 , Figure 5 and Figure 8 Step S300: Based on the initial phase assignment map and process parameters, perform phase-aware optical proximity correction on the target layout pattern to obtain the corrected mask pattern data.

[0049] In step S300, the phase marker values ​​and transmittance weighting coefficients of each region in the initial phase allocation map are introduced into the optical proximity correction imaging model calculation, and the position offset of each graphic edge in the target pattern graphic data is solved to obtain the corrected mask graphic data.

[0050] Furthermore, the execution process of the phase-sensing optical proximity correction includes:

[0051] Based on the exposure wavelength, numerical aperture, and partial coherence factor in the advanced process lithography parameters, the transmission cross coefficient matrix of the optical system is calculated. The phase marker value and transmittance weighting coefficient of each transparent region are incorporated into the representation of the object's spectrum in the form of complex amplitudes: the complex amplitude of the 0-degree phase region is taken as the corresponding transmittance weighting coefficient of the transparent region. The positive real number, i.e., the amplitude is The complex amplitude of the 180-degree phase region is taken as the transmittance weighting coefficient corresponding to the light-transmitting region. The negative real number, i.e., the amplitude is The complex amplitude of the opaque region is zero; transmittance weighting coefficient. The piecewise linear mapping relationship described in step S200 determines the value of the object's spectrum. The value of the map changes with the distance between each transparent region and the nearest opaque edge of the graphic, thereby suppressing the amplitude of the object's spectrum in the nearest edge region.

[0052] Based on the transfer cross coefficient matrix, the spatial image intensity at each evaluation point in the target map graphic data is calculated to obtain the spatial image intensity value at each evaluation point; the evaluation points are arranged along the edges of each graphic at a preset sampling interval, and the preset sampling interval does not exceed half of the minimum set line width;

[0053] Based on the difference between the spatial image intensity value at each evaluation point and the photoresist contrast threshold, the edge placement error at each evaluation point is calculated; when the edge placement error exceeds the preset tolerance, a correction offset is applied along the normal direction of the corresponding graphic edge, and the correction offset is obtained by inverting the sensitivity matrix of the edge placement error relative to the edge displacement.

[0054] In the process of solving for each correction offset, an additional phase gradient compensation term is introduced for evaluation points located on both sides of the phase transition strip; the phase gradient compensation term Based on the distance of the evaluation point from the center line of the phase transition strip and strip width The calculation method is as follows: ,in The distance from the evaluation point to the center line of the phase transition strip. For the strip width, The phase gradient compensation coefficient is determined by the spatial image intensity difference between the evaluation points on both sides of the phase transition strip in the current iteration, and its value is the ratio of the spatial image intensity difference between the evaluation points on both sides of the strip to the diagonal elements of the sensitivity matrix. and If the two quantities have the same dimension, their ratio is a dimensionless ratio. Dimensions and They are consistent, both being edge placement error correction amounts in the dimension of length; Used to correct the contribution of local spatial image distortion caused by phase abrupt changes to edge placement errors, only for satisfying... The evaluation points will take effect.

[0055] In at least one example of the embodiments of this disclosure, the application of the correction offset follows mask manufacturability constraints, specifically including: the length of any corrected pattern edge segment is not less than the minimum resolution size for mask manufacturing; the spacing between any adjacent edge segments is not less than the minimum spacing rule value for the mask; and the width of any auxiliary feature is limited to the sub-resolution size range so that it is not imaged on the wafer. The corrected mask pattern data includes the vertex coordinate sequence of each pattern edge adjusted by the correction offset and the geometric definition of the added sub-resolution auxiliary features.

[0056] Reference Appendix Figure 6 , Figure 7 and Figure 9 Step S400: Perform lithography imaging simulation based on the corrected mask pattern data, iteratively update the phase allocation and optical proximity correction parameters according to the pattern fidelity index in the simulation results, and output the final co-optimized mask pattern data.

[0057] In step S400, the corrected mask pattern data is superimposed with the initial phase allocation map and used as simulation input to perform full-chip-level lithography imaging simulation. The image fidelity index of each evaluation point in the simulation results is used to determine whether the preset convergence condition is met. If not, the initial phase allocation map and the correction offset are jointly iteratively updated until the preset convergence condition is met, and then the final co-optimized mask pattern data is output.

[0058] Furthermore, the graphic fidelity index includes the root mean square value of global edge placement error, the critical dimension uniformity deviation, and the graphic end shrinkage. The preset convergence condition is defined as follows: the root mean square value of global edge placement error does not exceed five percent of the target critical dimension, the critical dimension uniformity deviation is within the allowable fluctuation range, and the graphic end shrinkage does not exceed the preset end tolerance value.

[0059] In at least one example of the embodiments of this disclosure, the iterative update process employs an alternating direction optimization strategy, specifically including:

[0060] Phase update sub-step: Fix the current correction offset, and based on the edge placement error distribution of evaluation points within each phase transition strip region in the current simulation results, perform position adjustment or width modification operations on the phase transition strips with error concentrations; for regions where phase conflicts still exist and error exceeding limits cannot be eliminated by strip position adjustment, perform local topology reanalysis and reassign phase values ​​to the light-transmitting region nodes of the region; after completing the geometric modification and phase reassignment operations of the phase transition strips, recalculate the transmittance weight coefficient of the affected light-transmitting region according to the piecewise linear mapping relationship described in step S200, so as to ensure that the complex amplitude used for object spectrum representation in subsequent correction update sub-steps is consistent with the geometric state of the current initial phase allocation map;

[0061] Correction update sub-step: Fix the updated initial phase assignment map (including the updated transmittance weight coefficient), use the correction offset of the previous iteration as the initial value, and re-execute the phase sensing optical proximity correction process described in step S300 to obtain the updated correction offset and mask pattern data.

[0062] Convergence determination sub-step: Based on the updated mask pattern data and the initial phase allocation map, re-execute the lithography imaging simulation and calculate the pattern fidelity index value of the current iteration; if the pattern fidelity index value meets the preset convergence condition, or the current iteration number reaches the preset maximum iteration number, then terminate the iteration and output the current mask pattern data and the initial phase allocation map as the final co-optimized mask pattern data.

[0063] It should be noted that the coupling relationship between the phase update sub-step and the correction update sub-step in the alternating direction optimization strategy is manifested in the following way: the geometric modification of the phase transition strip in the phase update sub-step will change the calculation result of the transfer cross coefficient matrix in the local region in the correction update sub-step, thereby affecting the phase gradient compensation term. The value of changes accordingly; the coupling relationship makes the initial phase assignment map and the optimization direction of optical proximity correction tend to be consistent in each iteration, rather than converging to a local optimum independently.

[0064] In at least one example of the embodiments of this disclosure, a depth-of-focus sensitivity assessment is also introduced in the iterative update process: in each convergence determination sub-step, in addition to performing lithographic imaging simulation at the optimal focal plane position, simulations are also performed at multiple focal plane offset positions for positive and negative defocus to obtain the change in edge placement error of each evaluation point at different focal plane positions; if the change in edge placement error of any evaluation point within the depth-of-focus range exceeds the preset process window tolerance, the graphic region corresponding to the evaluation point is marked as a depth-of-focus sensitive region, and in the next phase update sub-step, a phase reassignment operation is preferentially performed on the depth-of-focus sensitive region to enhance imaging robustness.

[0065] In at least one example of the embodiments of this disclosure, the final co-optimized mask pattern data is stored in a hierarchical structure, including: a first data layer recording the phase marker value and transmittance weight coefficient of each light-transmitting region; a second data layer recording the pattern edge coordinate sequence and sub-resolution auxiliary feature definition after optical proximity correction; and a third data layer recording the final geometric parameters of each phase transition strip. The three layers of data are aligned through a unified spatial coordinate reference system so that they can be directly read in subsequent mask manufacturing processes.

[0066] Secondly, this invention provides an advanced process mask OPC and PSM co-optimization system, including: at least one processor, a data acquisition unit, a phase allocation unit, a phase sensing correction unit, and an iterative co-optimization unit.

[0067] The data acquisition unit is configured to acquire target layout graphic data and advanced process lithography parameters. For a detailed description of the data acquisition unit, please refer to the relevant description of step S100 in the embodiment of the advanced process mask OPC and PSM co-optimization method described above; it will not be repeated here.

[0068] The phase allocation unit is configured to generate an initial phase allocation map for the phase shift mask based on the topological features of the target layout graphic data. For a detailed explanation of the phase allocation unit, please refer to the relevant description of step S200 in the embodiment of the advanced process mask OPC and PSM co-optimization method described above; it will not be repeated here.

[0069] The phase-aware correction unit is configured to perform phase-aware optical proximity correction on the target layout pattern based on the initial phase assignment map and process parameters. For a detailed description of the phase-aware correction unit, please refer to the relevant description of step S300 in the embodiment of the advanced process mask OPC and PSM co-optimization method described above; it will not be repeated here.

[0070] The iterative co-optimization unit is configured to iteratively update the initial phase assignment map and optical proximity correction parameters based on the lithography imaging simulation results, and output the final co-optimized mask pattern data. For a detailed description of the iterative co-optimization unit, please refer to the relevant description of step S400 in the embodiment of the advanced process mask OPC and PSM co-optimization method described above; it will not be repeated here.

[0071] The technical effects of the advanced process mask OPC and PSM co-optimization system are the same as those of the advanced process mask OPC and PSM co-optimization method described above, and will not be repeated here.

[0072] The steps of this implementation method are as follows:

[0073] Step S100: Obtain the target layout graphic data and advanced process lithography parameters;

[0074] In the chip fabrication preparation stage for processes below 7 nm, for the photolithography mask fabrication task of the metal interconnect layer (Metal2 layer, layer number 42, data type number 0), the target layout graphic data of this layer is extracted from the layout file in GDSII format, and the process parameter set corresponding to the 193 nm immersion lithography process is read simultaneously. The target layer contains several horizontal / vertical line patterns, with a critical dimension (CD) of 22 nm and a minimum pattern spacing of 20 nm. In the process parameters, the numerical aperture is set to 1.35, the partial coherence factor is set to 0.85, the photoresist contrast threshold is 0.32, and the depth of focus range is ±80 nm, as shown in Table 1 below.

[0075] Table 1 Target layout graphic data and photolithography process parameters

[0076]

[0077] Step S200: Based on the topological features of the target layout graphic data, generate an initial phase allocation map of the phase shift mask;

[0078] Using the Metal2 layer layout data extracted in step S100 as input, graph-theoretic representation and phase assignment operations are performed on the transparent regions in this layer to generate an initial phase allocation map. Specifically, this layer identifies 6 independent transparent regions (labeled as regions 1 to 6), where regions 1 and 2, 2 and 3, 3 and 4, 4 and 5, and 5 and 6 have boundary adjacency relationships. The overall topology graph does not contain odd-numbered loops, and the binary coloring algorithm can converge directly. Regions 1, 3, and 5 are assigned a 0-degree phase, and regions 2, 4, and 6 are assigned a 180-degree phase. The phase difference between adjacent regions is 180 degrees, and the destructive interference effect is established at all adjacent boundaries.

[0079] Since the minimum pattern spacing of this layer is 20 nanometers, the ratio of exposure wavelength to numerical aperture is... The nanometers, one-quarter of which is approximately 36 nanometers, have no odd number of loops in the topology in this example and do not require the insertion of phase transition strips, as shown in Table 2 below.

[0080] In the calculation of transmittance weighting coefficients, a nearest neighbor threshold is preset. Nanometers, minimum transmittance weighting factor Taking region 2 as an example, its distance from the edge of its nearest opaque graphic is... Nano, due to The weighting coefficients are calculated using a piecewise linear mapping:

[0081]

[0082] Table 2 Initial Phase Allocation and Transmittance Weighting Coefficients for Transmittable Regions

[0083]

[0084] Step S300: Based on the initial phase assignment map and process parameters, perform phase-aware optical proximity correction on the target layout pattern to obtain the corrected mask pattern data;

[0085] The initial phase assignment map (including phase marker values ​​and transmittance weighting coefficients for each region) obtained in step S200 is introduced into the phase-sensing optical proximity correction process along with the process parameters in step S100, and sub-steps a to d are executed sequentially.

[0086] In sub-step a, the transfer cross coefficient matrix is ​​calculated based on the 193 nm exposure wavelength, numerical aperture of 1.35, and partial coherence factor of 0.85; each transparent region is incorporated into the object's spectrum with complex amplitude: the complex amplitude of the 0-degree phase region is... (e.g., take region 1) Take area 3 Area 5 The complex amplitude of the 180-degree phase region is (e.g., take region 2) Take area 4 Take area 6 The complex amplitude of the opaque region is zero.

[0087] In sub-step b, evaluation points are set up along the edges of each pattern at a sampling interval of no more than 11 nanometers (half of the critical size of 22 nanometers), and the spatial image intensity at each evaluation point is calculated.

[0088] In sub-step c, using a photoresist contrast threshold of 0.32 as a benchmark, the edge placement error at each evaluation point is calculated, and the correction offset is obtained by inverting the sensitivity matrix. Taking a representative evaluation point P1 at the boundary between region 1 and region 2 as an example, the calculated spatial image intensity is 0.29, which differs from the threshold of 0.32 by -0.03, corresponding to a diagonal element of 0.018 in the sensitivity matrix. Edge placement error is Nanometers, and accordingly apply a correction offset of approximately +1.67 nanometers (outward along the edge normal direction).

[0089] In sub-step d, this example has no phase transition stripe and no phase gradient compensation term. This does not apply to any of the evaluation points.

[0090] The corrected sequence of vertex coordinates of the graphic edge has been updated, and a sub-resolution auxiliary feature (SRAF) with a width of 10 nm has been added to the end region of the isolated line to meet the mask manufacturability constraints (minimum edge fragment length ≥ 20 nm, minimum spacing ≥ 20 nm), as shown in Table 3 below.

[0091] Table 3. Data for representative evaluation points before and after optical proximity correction.

[0092]

[0093] Step S400: Perform lithography imaging simulation based on the corrected mask pattern data, iteratively update the phase allocation and optical proximity correction parameters according to the pattern fidelity index in the simulation results, and output the final co-optimized mask pattern data.

[0094] The corrected mask pattern data obtained in step S300 is superimposed with the initial phase allocation map and used as simulation input to perform full-chip-level photolithography imaging simulation and calculate the pattern fidelity index. The preset convergence conditions are: the root mean square value of the global edge placement error does not exceed 5% of the target critical dimension of 22 nanometers (i.e., not more than 1.10 nanometers), the critical dimension uniformity deviation does not exceed ±1.5 nanometers, and the pattern end retraction does not exceed 5 nanometers.

[0095] After the first iteration, simulation results showed that the root mean square error of the global edge placement was 1.83 nm, exceeding the convergence threshold and triggering alternating direction optimization. In the phase update sub-step, the current correction offset was fixed, and region 5 (transmittance weight coefficient) was adjusted. The phase transition boundary (where the nearest neighbor distance is too small) is fine-tuned, and the transmittance weighting coefficient of region 5 is recalculated based on the piecewise linear mapping relationship (the nearest neighbor distance is corrected from 9 nm to 12 nm). In the correction update sub-step, phase-aware optical proximity correction is re-executed with the first round of correction offset as the initial value to obtain the updated mask pattern data.

[0096] After the second iteration, the root mean square value of the global edge placement error obtained from the simulation at the optimal focal plane decreased to 0.87 nm, the critical dimension uniformity deviation was ±1.2 nm, and the pattern end retraction was 3.8 nm. All three indicators met the convergence conditions. Simultaneously, simulations were performed at a focal plane offset of ±80 nm, and the changes in edge placement error at each evaluation point did not exceed the process window tolerance, with no depth-of-focus sensitive areas being marked. The iteration terminated, and the final co-optimized mask layout data was output.

[0097] The final mask layout data is stored in a three-layer hierarchical structure: the first data layer records the phase marker values ​​and final transmittance weight coefficients of regions 1 to 6; the second data layer records the pattern edge coordinate sequence and sub-resolution auxiliary feature definition after two rounds of correction and update; and the third data layer is empty (no phase transition strip in this example). The three layers of data are aligned through a unified Metal2 layer spatial coordinate reference system, as shown in Table 4 below.

[0098] Table 4 Summary of Graphic Fidelity Indicators for Each Iteration Round

[0099]

[0100] The embodiments of the present invention have been described above. However, the embodiments are not limited to the specific implementation methods described above. The specific implementation methods described above are merely illustrative and not restrictive. Those skilled in the art can make more equivalent embodiments under the guidance of the present embodiments, and all of them are within the protection scope of the present embodiments.

[0101] This invention also provides an electronic device having a computer program stored thereon, which, when executed by a processor, is implemented to perform the methods provided in the above embodiments.

[0102] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for collaborative optimization of OPC and PSM in advanced process masking, characterized in that, include: Acquire target layout graphic data and advanced process lithography parameters; Based on the spatial adjacency relationship and spacing distribution characteristics of each light-transmitting region in the target layout graphic data, a phase assignment operation is performed on the light-transmitting region to generate an initial phase allocation map of the phase-shifting mask; The phase marker values ​​and transmittance weighting coefficients of each region in the initial phase allocation map are incorporated into the optical proximity correction imaging model calculation in the form of complex amplitudes. The correction offset is calculated for each graphic edge to obtain the corrected mask graphic data. Based on the corrected mask pattern data, a photolithography imaging simulation is performed. The pattern fidelity index in the simulation results is used to determine whether the preset convergence condition is met. If not, the initial phase allocation map and the correction offset are jointly iterated and updated until the preset convergence condition is met, and then the final co-optimized mask pattern data is output. The transmittance weight coefficient is determined based on the distance between each transparent area and the nearest neighbor opaque pattern edge.

2. The method according to claim 1, characterized in that, The phase assignment operation on the light-transmitting area includes: The light-transmitting areas in the target map graphic data are represented using graph theory, mapping each light-transmitting area to a node in the graph, and mapping the boundary relationship between adjacent light-transmitting areas to connecting edges. The binary coloring algorithm is executed based on the graph structure represented by the graph theory, and each node is assigned a phase of 0 degrees or 180 degrees, so that the phase difference between adjacent transparent areas with shared boundaries is 180 degrees.

3. The method according to claim 2, characterized in that, For a topology with an odd number of loops in the graph structure, a phase transition strip is inserted between two adjacent light-transmitting regions corresponding to conflict edges. The width of the phase transition strip does not exceed one-quarter of the ratio of the exposure wavelength to the numerical aperture, and the transmittance of the phase transition strip is set to zero. The initial phase assignment map includes the phase marker value of each light-transmitting region and the geometric position and width parameters of each phase transition strip.

4. The method according to claim 1, characterized in that, The transmittance weighting coefficient With distance The relationship between them is determined by piecewise linear mapping: when hour, ;when hour, ,in The distance between the light-transmitting area and the nearest opaque edge of the graphic is [missing information]. The preset nearest neighbor threshold, The minimum allowable transmittance weighting coefficient.

5. The method according to claim 1, characterized in that, The step of incorporating the phase marker values ​​and transmittance weighting coefficients of each region in the initial phase assignment map into the optical proximity correction imaging model calculation in the form of complex amplitudes includes: The transmission cross coefficient matrix of the optical system is calculated based on the exposure wavelength, numerical aperture, and partial coherence factor in the advanced process lithography parameters, where the complex amplitude of the 0-degree phase region is taken as the corresponding transmittance weighting coefficient. The positive real number, the complex amplitude of the 180-degree phase region is taken as the corresponding transmittance weighting coefficient. For negative real numbers, the complex amplitude in the opaque region is zero; The spatial image intensity at each evaluation point is calculated based on the transmission cross coefficient matrix. The evaluation points are arranged along the edges of each graphic with a sampling interval not exceeding half of the minimum set line width. The edge placement error is calculated based on the difference between the spatial image intensity value and the photoresist contrast threshold at each evaluation point. When the edge placement error exceeds the preset tolerance, the correction offset is obtained by inverting the sensitivity matrix of the edge placement error relative to the edge displacement.

6. The method according to claim 5, characterized in that, For evaluation points located on both sides of the phase transition strip, a phase gradient compensation term is introduced in the process of solving for the correction offset. The calculation method is as follows ,in The distance from the evaluation point to the center line of the phase transition strip. For the strip width, The phase gradient compensation coefficient is the ratio of the spatial image intensity difference between the evaluation points on both sides of the strip to the diagonal elements of the sensitivity matrix. This phase gradient compensation term applies only to conditions satisfying... The evaluation points will take effect.

7. The method according to claim 1, characterized in that, The joint iterative update employs an alternating direction optimization strategy, including: Phase update sub-step: Fix the current correction offset, and based on the edge placement error distribution of evaluation points in each phase transition strip area in the simulation results, perform position adjustment or width modification operations on the phase transition strips with error concentration, and recalculate the transmittance weight coefficient of the affected light transmission area. Correction update sub-step: Fix the updated initial phase assignment map, and re-execute phase-aware optical proximity correction with the correction offset of the previous iteration as the initial value to obtain the updated correction offset and mask pattern data; Convergence determination sub-step: Based on the updated mask pattern data and the initial phase allocation map, re-execute the lithography imaging simulation, calculate the pattern fidelity index value of the current iteration, and terminate the iteration if the preset convergence condition is met or the preset maximum number of iterations is reached.

8. The method according to claim 7, characterized in that, In the convergence determination sub-step, in addition to performing photolithography imaging simulation at the optimal focal plane position, simulation is also performed at multiple focal plane offset positions of positive defocus and negative defocus to obtain the change in edge placement error of each evaluation point at different focal plane positions. If the change in edge placement error of any evaluation point within the depth of focus exceeds the preset process window tolerance, the graphic region corresponding to the evaluation point is marked as a depth-of-focus sensitive region, and a phase reassignment operation is preferentially performed on the depth-of-focus sensitive region in the next phase update sub-step.

9. An electronic device, characterized in that, include: At least one memory stores computer-executable instructions non-transiently; At least one processor, configured to run the computer-executable instructions, The computer-executable instructions are executed by the processor to implement the method according to any one of claims 1 to 8.

10. An advanced process mask OPC and PSM co-optimization system, used to execute the method according to any one of claims 1 to 8, characterized in that, include: The data acquisition unit is configured to acquire target layout graphic data and advanced process lithography parameters. The phase allocation unit is configured to perform a phase assignment operation on the light-transmitting regions based on the spatial adjacency relationship and spacing distribution characteristics of each light-transmitting region in the target layout graphic data, thereby generating an initial phase allocation map of the phase-shifting mask. The phase sensing correction unit is configured to incorporate the phase marker values ​​and transmittance weight coefficients of each region in the initial phase allocation map into the optical proximity correction imaging model calculation in the form of complex amplitudes, perform the correction offset calculation on each graphic edge, and obtain the corrected mask graphic data. The iterative collaborative optimization unit is configured to perform lithography imaging simulation based on the corrected mask pattern data, determine whether the preset convergence condition is met based on the pattern fidelity index in the simulation results, and if not, jointly iteratively update the initial phase allocation map and the correction offset until the preset convergence condition is met, and then output the final collaboratively optimized mask pattern data.

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