Spin coating simulation method, device, equipment and storage medium

Abstract

The present disclosure provides a spin coating simulation method, apparatus, device, and storage medium. The spin coating simulation method is applied to simulate the shape of a spin-coated film layer of a non-planar semiconductor structure. The method includes: obtaining spin coating process parameter information; and determining the shape information of the spin-coated film layer formed on the non-planar semiconductor structure based on a preset simulation model and the spin coating process parameter information. In the spin coating simulation method provided in the embodiments of the present disclosure, the shape of the spin-coated film layer is simulated based on the preset simulation model and the spin coating process parameter information, thereby providing a reference basis for other process steps after the spin coating step, thereby ensuring the quality of the manufactured semiconductor product.

Description

Technical Field

[0001] The present disclosure relates to the field of semiconductor technology, and in particular to a spin coating simulation method, device, equipment, and storage medium. Background Art

[0002] The spin coating process is a film layer forming process often used in the preparation of semiconductor structures. In the actual semiconductor structure process, the film layer formed by the spin coating process sometimes has the problem of uneven thickness, which in turn affects the subsequent process. Summary of the Invention

[0003] The following is an overview of the subject matter described in detail in this disclosure. This overview is not intended to limit the scope of the claims.

[0004] The present disclosure provides a spin coating simulation method, apparatus, device and storage medium.

[0005] According to a first aspect of an embodiment of the present disclosure, a spin coating simulation method is provided, which is applied to simulate the shape of a spin-coated film layer of a non-planar semiconductor structure, the method comprising:

[0006] Obtain spin coating process parameter information;

[0007] Based on a preset simulation model and the spin-coating process parameter information, shape information of a spin-coated film layer formed on the non-planar semiconductor structure is determined.

[0008] According to some embodiments of the present disclosure, the spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material, and the characteristic information of the spin coating material is used to determine fluidity information of the spin coating material.

[0009] According to some embodiments of the present disclosure, determining the shape information of the spin-coated film layer formed on the non-planar semiconductor structure based on a preset simulation model and the spin-coating process parameter information includes:

[0010] Determining surface shape information of the spin-coated film layer based on the preset simulation model and the spin-coating process parameter information;

[0011] The shape information of the spin-on film layer is determined based on the surface shape information of the spin-on film layer and the preset surface shape information of the non-planar semiconductor structure.

[0012] According to some embodiments of the present disclosure, determining the surface shape information of the spin-coated film layer based on the preset simulation model and the spin-coating process parameter information includes:

[0013] Determining a simulation curve based on the preset simulation model and the spin coating process parameter information, wherein the simulation curve is used to characterize the surface shape information of the spin coating film layer;

[0014] The determining the shape information of the spin-on film layer based on the surface shape information of the spin-on film layer and the preset surface shape information of the non-planar semiconductor structure includes:

[0015] Acquiring a preset curve, wherein the preset curve is used to represent preset surface shape information of the non-planar semiconductor structure;

[0016] Based on the simulation curve and the preset curve, a cross-sectional shape of the spin-on film layer is determined as shape information of the spin-on film layer.

[0017] According to some embodiments of the present disclosure, the preset curve is symmetrical about a preset axis, and the spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material;

[0018] The determining of a simulation curve based on the preset simulation model and the spin coating process parameter information includes:

[0019] determining a fluidity coefficient based on characteristic information of the spin-coated material;

[0020] Substituting the target film thickness and the fluidity coefficient into a first prediction function y=f(x) to obtain a first function curve corresponding to the first prediction function;

[0021] Substituting the target film thickness and the fluidity coefficient into a second prediction function -y=f(x) to obtain a second function curve corresponding to the second prediction function;

[0022] The simulation curve is determined based on the first function curve and the second function curve.

[0023] According to some embodiments of the present disclosure, the surface of the non-planar semiconductor structure includes a plane and a concave surface formed by the plane being concave, the cross-sectional shape of the non-planar semiconductor structure is symmetrical about the preset axis, and the first prediction function is an inverse function of the cubic function.

[0024] According to some embodiments of the present disclosure, determining the fluidity coefficient based on characteristic information of the spin-coated material includes:

[0025] Acquire first configuration information, where the first configuration information is used to characterize a correspondence between a material model and a fluidity coefficient;

[0026] The fluidity coefficient is determined based on a material type of the spin-coated material and the first configuration information.

[0027] According to some embodiments of the present disclosure, determining the fluidity coefficient based on characteristic information of the spin-coated material includes:

[0028] Acquiring second configuration information, where the second configuration information is used to characterize a correspondence between a liquidity characteristic value and a liquidity coefficient;

[0029] The fluidity coefficient is determined based on the fluidity characteristic value of the spin-coated material and the second configuration information.

[0030] A second aspect of the present disclosure provides a spin coating simulation device for simulating the shape of a spin-coated film layer of a non-planar semiconductor structure, the spin coating simulation device comprising:

[0031] an acquisition module, configured to acquire spin coating process parameter information;

[0032] The determining module is configured to determine shape information of a spin-coated film layer formed on the non-planar semiconductor structure based on a preset simulation model and the spin-coating process parameter information.

[0033] According to some embodiments of the present disclosure, the spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material, and the characteristic information of the spin coating material is used to determine fluidity information of the spin coating material.

[0034] According to some embodiments of the present disclosure, the determining module is configured to:

[0035] Determining surface shape information of the spin-coated film layer based on the preset simulation model and the spin-coating process parameter information;

[0036] The shape information of the spin-on film layer is determined based on the surface shape information of the spin-on film layer and the preset surface shape information of the non-planar semiconductor structure.

[0037] According to some embodiments of the present disclosure, the determining module is configured to:

[0038] Determining a simulation curve based on the preset simulation model and the spin coating process parameter information, wherein the simulation curve is used to characterize the surface shape information of the spin coating film layer;

[0039] Acquiring a preset curve, wherein the preset curve is used to represent preset surface shape information of the non-planar semiconductor structure;

[0040] Based on the simulation curve and the preset curve, a cross-sectional shape of the spin-on film layer is determined as shape information of the spin-on film layer.

[0041] According to some embodiments of the present disclosure, the preset curve is symmetrical about a preset axis, and the spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material;

[0042] The determining module is configured to:

[0043] determining a fluidity coefficient based on characteristic information of the spin-coated material;

[0044] Substituting the target film thickness and the fluidity coefficient into a first prediction function y=f(x) to obtain a first function curve corresponding to the first prediction function;

[0045] Substituting the target film thickness and the fluidity coefficient into a second prediction function -y=f(x) to obtain a second function curve corresponding to the second prediction function;

[0046] The simulation curve is determined based on the first function curve and the second function curve, and the simulation curve is symmetrical about the preset axis.

[0047] According to some embodiments of the present disclosure, the surface of the non-planar semiconductor structure includes a plane and a concave surface formed by the plane being concave, the cross-sectional shape of the non-planar semiconductor structure is symmetrical about the preset axis, and the first prediction function is an inverse function of the cubic function.

[0048] According to some embodiments of the present disclosure, the determining module is configured to:

[0049] Acquire first configuration information, where the first configuration information is used to characterize a correspondence between a material model and a fluidity coefficient;

[0050] The fluidity coefficient is determined based on a material type of the spin-coated material and the first configuration information.

[0051] According to some embodiments of the present disclosure, the determining module is configured to:

[0052] Acquiring second configuration information, where the second configuration information is used to characterize a correspondence between a liquidity characteristic value and a liquidity coefficient;

[0053] The fluidity coefficient is determined based on the fluidity characteristic value of the spin-on material and the second configuration information.

[0054] A third aspect of the present disclosure provides a spin coating simulation device, comprising:

[0055] processor;

[0056] a memory for storing processor-executable instructions;

[0057] The processor is configured to execute:

[0058] Obtain spin coating process parameter information;

[0059] Based on a preset simulation model and the spin-coating process parameter information, shape information of a spin-coated film layer formed on the non-planar semiconductor structure is determined.

[0060] According to a fourth aspect of the embodiments of the present disclosure, a non-transitory computer-readable storage medium is provided. When instructions in the storage medium are executed by a processor of a spin coating simulation device, the spin coating simulation device is enabled to perform:

[0061] Obtain spin coating process parameter information;

[0062] Based on a preset simulation model and the spin-coating process parameter information, shape information of a spin-coated film layer formed on the non-planar semiconductor structure is determined.

[0063] In the spin coating simulation method provided in the embodiment of the present disclosure, the shape of the spin-coated film layer is simulated according to a preset simulation model and spin coating process parameter information, thereby providing a reference basis for other process steps after the spin coating step to ensure the quality of the prepared semiconductor product.

[0064] Still other aspects will become apparent upon reading and understanding the accompanying drawings and detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The accompanying drawings, which are incorporated into and constitute a part of the specification, illustrate embodiments of the present disclosure and, together with the description, are used to explain the principles of the embodiments of the present disclosure. In these drawings, similar reference numerals are used to represent similar elements. The drawings described below are some embodiments of the present disclosure, not all embodiments. For those skilled in the art, other drawings can be derived from these drawings without inventive effort.

[0066] Figure 1a It is a structural schematic diagram of a semiconductor structure in the related art;

[0067] Figure 1b yes Figure 1a Schematic diagram of the structure after the back-etching step;

[0068] Figure 1c yes Figure 1b Schematic diagram of the structure after the etching step;

[0069] Figure 1d yes Figure 1c Schematic diagram of the structure after the etching step;

[0070] Figure 1e yes Figure 1d Schematic diagram of the structure after removing the mask layer, the protective layer, the first sacrificial layer and the second sacrificial layer;

[0071] Figure 2 is a flow chart showing a spin coating simulation method according to an exemplary embodiment;

[0072] Figure 3is a flow chart showing a spin coating simulation method according to an exemplary embodiment;

[0073] Figure 4 is a flow chart showing a spin coating simulation method according to an exemplary embodiment;

[0074] Figure 5a is a schematic diagram of the cross-sectional shape of a spin-coated film layer simulated by a spin-coating simulation method according to an exemplary embodiment;

[0075] Figure 5b is a schematic diagram of the cross-sectional shape of a spin-coated film layer simulated by a spin-coating simulation method according to an exemplary embodiment;

[0076] Figure 5c is a schematic diagram of the cross-sectional shape of a spin-coated film layer simulated by a spin-coating simulation method according to an exemplary embodiment;

[0077] Figure 6 is a first function curve diagram obtained by fitting different mobility coefficients according to an exemplary embodiment;

[0078] Figure 7a : is an actual surface shape of a spin-coated film layer according to an exemplary embodiment;

[0079] Figure 7b is with Figure 7a The corresponding simulated curve graph;

[0080] Figure 8 is a flow chart showing a spin coating simulation method according to an exemplary embodiment;

[0081] Figure 9a is a structural schematic diagram of an initial state of material removal in a spin coating simulation method according to an exemplary embodiment;

[0082] Figure 9b Yes Figure 9a Schematic diagram of the structure after a relocation;

[0083] Figure 9c Yes Figure 9b Schematic diagram of the structure after the second relocation;

[0084] Figure 10 is a block diagram of a spin coating simulation device according to an exemplary embodiment;

[0085] Figure 11 The figure is a block diagram of a spin coating simulation device according to an exemplary embodiment. DETAILED DESCRIPTION

[0086] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the disclosed embodiments will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. 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 those skilled in the art without making creative work are within the scope of protection of the present disclosure. It should be noted that, in the absence of conflict, the embodiments in the present disclosure and the features in the embodiments can be arbitrarily combined with each other.

[0087] In response to the problem that the film layer formed by the spin coating process in the related art sometimes has uneven thickness and affects the subsequent process, the inventors of the present disclosure found that since the fluidity of the spin-coating material is limited, when spin coating is performed on a semiconductor structure with an uneven surface, the spin-coated film layer formed on the uneven semiconductor structure surface will be affected by the structure and the fluidity of the spin-coating material. The thickness will be uneven. Specifically, in areas with higher structural density, the thickness of the spin-coated film layer formed by spin coating is smaller, and in areas with lower structural density, the thickness of the spin-coated film layer formed by spin coating is larger.

[0088] For example, Figure 1a As shown, the semiconductor structure includes a substrate 100, a target etching layer 200, a mask layer 300, a protective layer 400, a first sacrificial layer 500, and a second sacrificial layer 600, which are stacked in sequence. The mask layer 300 has a plurality of first recesses 310 in the central region, while the peripheral region has a flat surface. The first sacrificial layer 500 covers the protective layer 400 and the sidewalls and bottom walls of the first recesses 310 in the mask layer 300. The second sacrificial layer 600 is a spin-on film formed by a spin coating process. The central region of the mask layer is a region with relatively high structural density, while the peripheral region is a region with relatively low structural density. The spin-on film layer formed by the spin coating process, i.e., the second sacrificial layer 600, has a thinner thickness covering the central region and a thicker thickness covering the peripheral region.

[0089] The uneven thickness of the spin-coated film layer will affect the subsequent process and thus affect the quality of the semiconductor products produced. Figure 1a For example, in Figure 1a After etching back on the second sacrificial layer 600, a Figure 1b The structure shown, then Figure 1b The first sacrificial layer 500, the protective layer 400 and the second sacrificial layer 600 are etched to obtain Figure 1cAs shown in the figure, the second grooves 510 are spaced apart. Since the second sacrificial layer 600 has a height difference between the middle area and the peripheral area, during the etching process, the first sacrificial layer 500 in the middle area is exposed first, and the first sacrificial layer 500 in the peripheral area is exposed later, resulting in the second grooves 510 in the middle area having a greater depth than the second grooves 510 in the peripheral area. When the first sacrificial layer 500 and the target etching layer 200 are further etched to form a plurality of third grooves 210, as shown in FIG. Figure 1d As shown in FIG, the depth difference of the groove depth will continue to be transferred to the target etching layer 210. Figure 1e As shown, after the mask layer 300 , the protection layer 400 , the first sacrificial layer 500 and the second sacrificial layer 600 are removed, the third groove 210 in the peripheral area may be under-etched.

[0090] Based on this, the present disclosure provides a spin coating simulation method. In this method, the shape of the spin-coated film layer is simulated according to a preset simulation model and spin coating process parameter information, thereby providing a reference basis for other process steps after the spin coating step to ensure the quality of the prepared semiconductor product.

[0091] In an exemplary embodiment of the present disclosure, a spin coating simulation method is provided for simulating the shape of a spin-coated film layer of a non-planar semiconductor structure. The non-planar semiconductor structure herein refers to a semiconductor structure whose surface, i.e., the surface for supporting the spin-coated film layer, is non-planar. For example, the non-planar surface may be a surface with protrusions or a surface with grooves. Figure 2 As shown, Figure 2 1 is a flow chart showing a method for spin coating simulation according to an exemplary embodiment of the present disclosure:

[0092] S100: Obtain spin coating process parameter information.

[0093] In this step, the spin-coating process parameter information is the basic data or indicators for completing the spin-coating process. The spin-coating process parameter information affects the shape of the final spin-coated film layer. As an example, the spin-coating process parameter information includes the target film thickness, characteristic information of the spin-coating material, surface shape information of the non-planar semiconductor structure, etc. The characteristic information of the spin-coating material is used to determine the fluidity information of the spin-coating material. For example, it can be parameter information that characterizes the fluidity of the spin-coating material. Since different types of spin-coating materials have corresponding fluidity information, the characteristic information of the spin-coating material can also be the type of the spin-coating material. The fluidity information of the spin-coating material can also be obtained by looking up the table based on the type of the spin-coating material.

[0094] In some embodiments, the spin coating process parameter information is input by a user before the spin coating simulation. For example, the user operates on a terminal device such as a mobile phone or a computer to input the spin coating process parameter information. In other embodiments, the spin coating process parameter information is extracted from the complete semiconductor process.

[0095] S200 : Determine shape information of a spin-coated film layer formed on a non-planar semiconductor structure based on a preset simulation model and spin-coating process parameter information.

[0096] In this step, the spin coating process parameter information is input into a preset simulation model, and the preset simulation model is used to simulate the shape information of the spin-coated film layer 20, thereby determining the shape information of the spin-coated film layer 20 formed on the non-planar semiconductor structure 10. This can provide a reference basis for other process steps after the spin coating step, thereby ensuring the quality of the manufactured semiconductor product, for example, avoiding the above-mentioned under-etching or over-etching problems.

[0097] The shape information of the spin-on film layer 20 can be displayed in the form of patterns, texts, or a combination of patterns and texts. For example, a simulated stereoscopic view or cross-sectional view of the spin-on film layer can be displayed on a display screen of a terminal.

[0098] In one embodiment, if Figure 3 As shown, step S200 specifically includes:

[0099] S210, determining surface shape information of the spin-coated film layer based on a preset simulation model and spin-coating process parameter information;

[0100] S220 , determining shape information of the spin-on film layer based on the surface shape information of the spin-on film layer and preset surface shape information of the non-planar semiconductor structure.

[0101] In this embodiment, Figure 5a 、 Figure 5b and Figure 5c As can be seen, the surface shape information of the formed spin-coated film layer 20 is determined based on the spin-coating process parameter information. For example, the surface shape S1 (typically a curved surface) of the spin-coated film layer 20 is simulated based on the spin-coating process parameters. Because the spin-coated film layer 20 is formed on the surface S2 of the non-planar semiconductor structure 10, the bottom surface S2 of the spin-coated film layer 20 is adapted to the surface S2 of the non-planar semiconductor structure 10. In this way, the surface shape S1 of the spin-coated film layer 20 is synthesized with the shape of the surface S2 of the non-planar semiconductor structure 10 to obtain the overall shape information of the spin-coated film layer 20.

[0102] In some embodiments, the non-planar semiconductor structure 10 has one preset surface shape information, thereby simulating the shape of the spin-coated film layer 20 formed on the non-planar semiconductor structure 10. In other embodiments, the non-planar semiconductor structure 10 has multiple preset surface shape information. In this case, the preset surface shape of the non-planar semiconductor structure 10 can be selected in advance. For example, the user selects the preset surface of the non-planar semiconductor structure 10 before performing the spin-coating simulation. For another example, the user inputs the surface shape parameters of the non-planar semiconductor structure 10 before the spin-coating simulation, and the preset surface shape information of the non-planar semiconductor structure 10 is determined based on the surface shape parameters of the non-planar semiconductor structure 10 input by the user. As an example, a groove is provided on the surface of the non-planar semiconductor structure 10 that needs to be spin-coated. The user can input the groove depth and groove width of the groove before the spin-coating simulation.

[0103] It is understood that in embodiments where there is multiple pieces of preset surface shape information for the non-planar semiconductor structure 10, in step S210, the surface shape information of the spin-coated film layer 20 may also be determined based on the preset simulation model, the spin-coating process parameter information, and the preset surface shape information of the non-planar semiconductor structure 10. Since the preset surface shape information of the non-planar semiconductor structure 10 is incorporated into the determination of the surface shape information of the spin-coated film layer 20, the accuracy of the surface shape information of the spin-coated film layer 20 can be further improved.

[0104] Considering the structural characteristics of semiconductor structures, the thickness characteristics of the spin-coated film layer 20 can actually be reflected through its cross-sectional shape. Based on this, the cross-sectional shape of the spin-coated film layer 20 can be determined and used as the shape information of the spin-coated film layer 20. In one embodiment, step S210 specifically determines a simulation curve based on a preset simulation model and spin-coating process parameter information. The simulation curve is used to represent the surface shape information of the spin-coated film layer 20.

[0105] In the above steps, the simulation curve determined is, for example, a portion of the edge of the cross section of the spin-coated film layer 20, that is, a curve S1 obtained by cutting the surface of the spin-coated film layer 20 in the cross section. After obtaining the simulation curve, it can be combined with a predetermined curve representing predetermined surface shape information of the non-planar semiconductor structure 10 to obtain the cross-sectional shape of the spin-coated film layer 20. The use of the simulation curve can reduce the computational complexity of the simulation process and improve the simulation speed.

[0106] Since the grooves or protrusions on the non-planar semiconductor structure 10 are usually symmetrical structures, two symmetrical prediction functions can be used when determining the simulation curve. For example, Figure 4 As shown, step S210 includes:

[0107] S211, determining a fluidity coefficient based on characteristic information of the spin-coated material;

[0108] S212, substituting the target film thickness and the fluidity coefficient into the first prediction function y=f(x) to obtain a first function curve corresponding to the first prediction function;

[0109] S213, substituting the target film thickness and the fluidity coefficient into the second prediction function -y=f(x) to obtain a second function curve corresponding to the second prediction function;

[0110] S214 : Determine a simulation curve based on the first function curve and the second function curve.

[0111] The fluidity coefficient a is a coefficient related to the fluidity of the spin-coated material. The coefficients in the first prediction function and the second prediction function both include the thickness d and the fluidity coefficient a. The relationship between the thickness d and the fluidity coefficient a and the first function curve and the second function curve can be determined by experimental calibration, empirical values, etc. In a specific embodiment, Figure 5a As shown, the surface of the non-planar semiconductor structure 10 includes a plane 11 and a concave surface 12 formed by the plane 11 being concave. The cross-sectional shape of the non-planar semiconductor structure 10 is symmetrical about a preset axis L. The first prediction function is an inverse function of the cubic function, that is, the first prediction function is:

[0112]

[0113] Then the second prediction function is:

[0114]

[0115] Wherein, a is the fluidity coefficient, which is related to the fluidity of the spin-coated material. The better the fluidity, the larger the a value.

[0116] d is the target film thickness;

[0117] b and c are both constants, for example, they can both be 0.

[0118] The first function curve fitted by different mobility coefficients a is as follows Figure 6 As shown by Figure 6 It can be seen that the larger the mobility coefficient a is, the higher the smoothness of the first function curve is. As an example, when the mobility coefficient a→0, it is considered that the spin-coated material cannot flow, and the fitted simulation curve S1 is as follows: Figure 5a As shown, when the mobility coefficient 0<a<∞, the fitted simulation curve S1 is as follows Figure 5b As shown, when the mobility coefficient a∝∞, the fitted simulation curve S1 is as follows Figure 5c shown.

[0119] Figure 7ais the actual surface shape of the spin-coated film layer, Figure 7b is the simulation curve of the spin-coated film layer simulated by the inverse function of the cubic function. Figure 7a and Figure 7b By comparison, it can be seen that using the inverse function of the cubic function to fit the simulation curve can more accurately characterize the surface shape information of the spin-coated film layer.

[0120] In one embodiment, in step S211, the method for determining the fluidity coefficient based on the characteristic information of the spin-coated material may be:

[0121] Acquire first configuration information, where the first configuration information is used to characterize a correspondence between a material model and a fluidity coefficient;

[0122] The fluidity coefficient is determined based on the material type of the spin-coated material and the first configuration information.

[0123] As an example, the first configuration information can be a first correspondence table of material models and fluidity coefficients. After obtaining the material model of the spin-coated material, the first correspondence table is searched according to the material model of the spin-coated material to find the fluidity coefficient corresponding to the material model of the spin-coated material.

[0124] In another embodiment, the method for determining the fluidity coefficient based on the characteristic information of the spin-coated material may also be:

[0125] Acquire second configuration information, where the second configuration information is used to characterize a correspondence between a liquidity characteristic value and a liquidity coefficient;

[0126] A fluidity coefficient is determined based on the fluidity characteristic value of the spin-coated material and the second configuration information.

[0127] As an example, the second configuration information may be a second correspondence table of fluidity characteristic values ​​and fluidity coefficients. After obtaining the fluidity characteristic value, the second correspondence table is searched based on the fluidity characteristic value to find the fluidity coefficient corresponding to the material type of the spin-coated material. The fluidity characteristic value ranges from 0 to 1, with 0 representing complete fluidity and 1 representing complete non-fluidity. The greater the fluidity, the greater the fluidity characteristic value. The user can estimate the fluidity characteristic value of the spin-coated material and input a preset simulation model.

[0128] The first function curve is used to characterize part of the surface shape information of the spin-coated film layer 20, and the second function curve is used to characterize another part of the surface shape information of the spin-coated film layer 20. The first function curve and the second function curve are combined to obtain a simulation curve for characterizing the complete surface information of the spin-coated film layer 20.

[0129] In this embodiment, Figure 8 As shown, step S220 includes:

[0130] S221. Obtain a preset curve, where the preset curve is used to represent preset surface shape information of the non-planar semiconductor structure;

[0131] S222 : Based on the simulation curve and the preset curve, determine the cross-sectional shape of the spin-coated film layer as shape information of the spin-coated film layer.

[0132] In this embodiment, the simulated curve S1 representing the surface shape information of the spin-on film layer 20 is combined with the preset curve S2 representing the surface information of the non-planar semiconductor structure 10 to obtain the cross-sectional shape of the spin-on film layer 20. The calculation process is simple and the calculation speed is fast.

[0133] In some embodiments, there is one preset curve S2, thereby simulating the cross-sectional shape of the spin-coated film layer 20 corresponding to the preset curve S2. In other embodiments, there are multiple preset curves S2, in which case the preset curve S2 can be selected in advance. For example, the user selects the preset curve S2 before performing the spin-coating simulation. For another example, the user inputs the surface shape parameters of the non-planar semiconductor structure 10 before the spin-coating simulation, and the preset curve S2 is determined based on the surface shape parameters of the non-planar semiconductor structure 10 input by the user. As an example, a groove is provided on the surface of the non-planar semiconductor structure 10 that needs to be spin-coated, and the user can input the groove depth and groove width values ​​of the groove before the spin-coating simulation.

[0134] It will be appreciated that in step S222, when the simulated curve S1 and the preset curve S2 are combined to form the cross-sectional shape of the spin-coated film layer 20, the law of conservation of mass is observed, i.e., the total amount of the spin-coated material is guaranteed not to change. In one embodiment, the intersection of the first function curve and the second function curve is transitioned via a smooth curve, thereby further improving the simulation accuracy of the shape of the spin-coated film layer 20. In another embodiment, only the first function curve may be generated, and the cross-sectional shape of half of the spin-coated film layer 20 may be obtained based on the first function curve and the preset curve S2. This half cross-sectional shape is then symmetrically matched to obtain the cross-sectional shape of the complete spin-coated film layer 20.

[0135] In another embodiment, if Figure 9a 、 Figure 9b and Figure 9c As shown, the preset simulation model simulates the flow of the spin-coated material by material transfer, and sets different transfer termination conditions according to the different fluidity of the spin-coated material to simulate the shape information of the spin-coated film layer 20. The material transfer process is specifically described below using the example of a non-planar semiconductor structure 10 having a surface including a planar surface 11 and a concave surface 12 formed by the concavity of the planar surface 11.

[0136] like Figure 9aAs shown, the initial condition for material relocation is to set the entire plane 11 area to be deposited with the same thickness of spin-coated material as on the control block, and no spin-coated material on the concave surface 12. Afterwards, the spin-coated material on the plane 11 area on both sides of the concave surface 12 is relocated, and the minimum relocation unit is relocated to the concave surface 12 in sequence. During the relocation process, the law of conservation of mass is followed, that is, the area removed from the plane 11 area is equal to the area added to the concave surface 12. The minimum relocation unit can be, for example, Figure 9b The triangle shown may also be a quadrilateral or other shapes.

[0137] During the relocation process, the relocation is carried out according to the curvature radius, and the position with the smallest curvature radius on the flat area is first relocated, and then placed at the position with the smallest curvature radius on the concave surface, and the relocation of the spin-coated material is carried out in sequence according to the above relocation principles. For example, Figure 9a In the embodiment shown, the spin-coated material at the sharp corner position (the position circled by the solid line) on the plane 11 near the concave surface 12 is first moved and placed at the corner area (the position circled by the dotted line) of the concave surface 12, thereby forming Figure 9b The structure shown, such as Figure 9b As shown, after the first relocation, two sharp angle positions (positions circled by solid lines) are formed on the plane 11 area near the concave surface 12 side, and two obtuse angle positions (positions circled by dotted lines) are formed on the corner area of ​​the concave surface 12. The two sharp angle positions formed on the plane 11 area near the concave surface 12 side are relocated and relocated to the two obtuse angle positions of the concave surface 12, thereby forming Figure 9c As shown in the structure, three sharp-angled positions (positions circled by solid lines) are formed on the plane 11 area close to the concave surface 12, and three obtuse-angled positions (positions circled by dotted lines) are formed in the corner area of ​​the concave surface 12, and the relocation is continued until the relocation termination conditions are met.

[0138] The fluidity of the spin-coated material is different, and its relocation termination conditions are also different. The relocation termination conditions are determined based on the principle that the better the fluidity, the greater the relocation amount. For example, the relocation termination conditions are determined by the ratio of the thickness of the spin-coated material formed on the concave surface 12 to the average thickness of the spin-coated material on the plane 11. That is, when the ratio of the thickness of the spin-coated material formed on the concave surface 12 to the average thickness of the spin-coated material on the plane 11 reaches the termination preset value, the relocation is terminated. The better the fluidity of the spin-coated material, the greater the amount of material relocated during spin coating, and the greater the termination preset value. Conversely, the worse the fluidity of the spin-coated material, the smaller the amount of material relocated during spin coating, and the smaller the termination preset value. The user can select the termination preset value according to the fluidity of the spin-coated material before the spin coating simulation, or perform the following steps:

[0139] Acquire third configuration information, where the third configuration information is used to characterize a correspondence between a material model and a termination preset value;

[0140] The preset value is terminated based on the material model of the spin-coated material and the third configuration information.

[0141] As an example, the third configuration information can be a third correspondence table of material models and termination preset values. After obtaining the material model of the spin-coated material, the third correspondence table is searched according to the material model of the spin-coated material to find the termination preset value corresponding to the material model of the spin-coated material.

[0142] Figure 10 A block diagram of a spin coating simulation device is shown according to an exemplary embodiment. Figure 10 As shown, the device at least includes an acquisition module 301 and a template determination module 302 .

[0143] An acquisition module 301 is configured to acquire spin coating process parameter information;

[0144] Determine template 302, based on a preset simulation model and the spin coating process parameter information, determine shape information of the spin coating film layer formed on the non-planar semiconductor structure.

[0145] In an exemplary embodiment, the spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material, and the characteristic information of the spin coating material is used to determine fluidity information of the spin coating material.

[0146] In an exemplary embodiment, the determination module is configured to:

[0147] Determining the surface shape information of the spin-coated film layer based on a preset simulation model and spin-coating process parameter information;

[0148] The shape information of the spin-on film layer is determined based on the surface shape information of the spin-on film layer and the preset surface shape information of the non-planar semiconductor structure.

[0149] In an exemplary embodiment, the determination module is configured to:

[0150] Determining a simulation curve based on a preset simulation model and spin coating process parameter information, where the simulation curve is used to characterize surface shape information of the spin coating film layer;

[0151] Obtaining a preset curve, where the preset curve is used to characterize preset surface shape information of the non-planar semiconductor structure;

[0152] Based on the simulation curve and the preset curve, a cross-sectional shape of the spin-coated film layer is determined as shape information of the spin-coated film layer.

[0153] In an exemplary embodiment, the preset curve is symmetrical about a preset axis, and the spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material;

[0154] Determine the module, which is configured as:

[0155] Determining the fluidity coefficient based on characteristic information of the spin-coated material;

[0156] Substituting the target film thickness and the fluidity coefficient into the first prediction function y=f(x) to obtain a first function curve corresponding to the first prediction function;

[0157] Substituting the target film thickness and the fluidity coefficient into the second prediction function -y=f(x) to obtain a second function curve corresponding to the second prediction function;

[0158] A simulation curve is determined based on the first function curve and the second function curve, and the simulation curve is symmetrical about a preset axis.

[0159] In an exemplary embodiment, the surface of the non-planar semiconductor structure includes a plane and a concave surface formed by concaving the plane, the cross-sectional shape of the non-planar semiconductor structure is symmetrical about a preset axis, and the first prediction function is an inverse function of a cubic function.

[0160] In an exemplary embodiment, the determination module is configured to:

[0161] Acquire first configuration information, where the first configuration information is used to characterize a correspondence between a material model and a fluidity coefficient;

[0162] The fluidity coefficient is determined based on the material type of the spin-coated material and the first configuration information.

[0163] In an exemplary embodiment, the determination module is configured to:

[0164] Acquire second configuration information, where the second configuration information is used to characterize a correspondence between a liquidity characteristic value and a liquidity coefficient;

[0165] A fluidity coefficient is determined based on the fluidity characteristic value of the spin-coated material and the second configuration information.

[0166] Figure 11 FIG. 9 is a block diagram of a spin coating simulation device, namely a computer device 900, according to an exemplary embodiment. For example, the computer device 900 may be provided as a terminal device. Figure 11Computer device 900 includes a processor 901, which can be one or more processors as needed. Computer device 900 also includes a memory 902 for storing instructions executable by processor 901, such as application programs. The memory can be one or more memory devices as needed. The memory device can store one or more application programs. Processor 901 is configured to execute instructions to perform the above method.

[0167] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, devices (equipment), or computer program products. Therefore, the present disclosure may take the form of a fully hardware embodiment, a fully software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. Computer storage media include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data), including but not limited to RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVDs) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and may include any information delivery medium.

[0168] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is provided, such as a memory 902 including instructions, and the instructions can be executed by a processor 901 of an apparatus 900 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0169] A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of a spin coating simulation device, enables the spin coating simulation device to perform:

[0170] Obtain spin coating process parameter information;

[0171] Based on a preset simulation model and spin coating process parameter information, shape information of a spin-coated film layer formed on a non-planar semiconductor structure is determined.

[0172] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, apparatus (devices) and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0173] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0174] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0175] In this disclosure, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that an article or device comprising a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such article or device. In the absence of further limitations, an element defined by the phrase "comprising..." does not preclude the presence of additional identical elements in the article or device comprising the element.

[0176] Although the preferred embodiments of the present disclosure have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present disclosure.

[0177] Obviously, those skilled in the art may make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is intended to include such modifications and variations.

Claims

1. A spin coating simulation method for simulating the shape of a spin-coated film layer of a non-planar semiconductor structure, characterized in that: The method comprises: Obtain spin coating process parameter information; Determining shape information of a spin-coated film layer formed on the non-planar semiconductor structure based on a preset simulation model and the spin-coating process parameter information; The spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material, wherein the characteristic information of the spin coating material is used to determine the fluidity information of the spin coating material; The determining of shape information of a spin-coated film layer formed on a non-planar semiconductor structure based on a preset simulation model and the spin-coating process parameter information includes: Determining surface shape information of the spin-coated film layer based on the preset simulation model and the spin-coating process parameter information; determining shape information of the spin-on film layer based on the surface shape information of the spin-on film layer and preset surface shape information of the non-planar semiconductor structure; The determining the surface shape information of the spin-coated film layer based on the preset simulation model and the spin-coating process parameter information includes: Determining a simulation curve based on the preset simulation model and the spin coating process parameter information, wherein the simulation curve is used to characterize the surface shape information of the spin coating film layer; The relationship between the target film thickness, the characteristic information of the spin-coated material and the simulation curve can be determined by experimental calibration or empirical value.

2. The method according to claim 1, characterized in that The determining the shape information of the spin-on film layer based on the surface shape information of the spin-on film layer and the preset surface shape information of the non-planar semiconductor structure includes: Acquiring a preset curve, wherein the preset curve is used to represent preset surface shape information of the non-planar semiconductor structure; Based on the simulation curve and the preset curve, a cross-sectional shape of the spin-on film layer is determined as shape information of the spin-on film layer.

3. The method according to claim 2, characterized in that The preset curve is symmetrical about a preset axis, and the spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material; The determining of a simulation curve based on the preset simulation model and the spin coating process parameter information includes: determining a fluidity coefficient based on characteristic information of the spin-coated material; Substituting the target film thickness and the fluidity coefficient into a first prediction function y=f(x) to obtain a first function curve corresponding to the first prediction function; Substituting the target film thickness and the fluidity coefficient into a second prediction function -y=f(x) to obtain a second function curve corresponding to the second prediction function; The simulation curve is determined based on the first function curve and the second function curve.

4. The method according to claim 3, characterized in that The surface of the non-planar semiconductor structure includes a plane and a concave surface formed by concaving the plane. The cross-sectional shape of the non-planar semiconductor structure is symmetrical about the preset axis. The first prediction function is an inverse function of a cubic function.

5. The method according to claim 3, characterized in that The determining of the fluidity coefficient based on the characteristic information of the spin-coated material includes: Acquire first configuration information, where the first configuration information is used to characterize a correspondence between a material model and a fluidity coefficient; The fluidity coefficient is determined based on a material type of the spin-coated material and the first configuration information.

6. The method according to claim 3, characterized in that The determining of the fluidity coefficient based on the characteristic information of the spin-coated material includes: Acquiring second configuration information, where the second configuration information is used to characterize a correspondence between a liquidity characteristic value and a liquidity coefficient; The fluidity coefficient is determined based on the fluidity characteristic value of the spin-on material and the second configuration information.

7. A spin coating simulation device for simulating the shape of a spin-coated film layer of a non-planar semiconductor structure, characterized in that: The spin coating simulation device comprises: an acquisition module, configured to acquire spin coating process parameter information; a determining module configured to determine shape information of a spin-coated film layer formed on the non-planar semiconductor structure based on a preset simulation model and the spin-coating process parameter information; The spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material, wherein the characteristic information of the spin coating material is used to determine the fluidity information of the spin coating material; The determining module is configured to: Determining surface shape information of the spin-coated film layer based on the preset simulation model and the spin-coating process parameter information; determining shape information of the spin-on film layer based on the surface shape information of the spin-on film layer and preset surface shape information of the non-planar semiconductor structure; The determining module is configured to: Determining a simulation curve based on the preset simulation model and the spin coating process parameter information, wherein the simulation curve is used to characterize the surface shape information of the spin coating film layer; The relationship between the target film thickness, the characteristic information of the spin-coated material and the simulation curve can be determined by experimental calibration or empirical value.

8. The device according to claim 7, characterized in that The determining module is further configured to: Acquiring a preset curve, wherein the preset curve is used to represent preset surface shape information of the non-planar semiconductor structure; Based on the simulation curve and the preset curve, a cross-sectional shape of the spin-on film layer is determined as shape information of the spin-on film layer.

9. The device according to claim 8, characterized in that The preset curve is symmetrical about a preset axis, and the spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material; The determining module is configured to: determining a fluidity coefficient based on characteristic information of the spin-coated material; Substituting the target film thickness and the fluidity coefficient into a first prediction function y=f(x) to obtain a first function curve corresponding to the first prediction function; Substituting the target film thickness and the fluidity coefficient into a second prediction function -y=f(x) to obtain a second function curve corresponding to the second prediction function; The simulation curve is determined based on the first function curve and the second function curve, and the simulation curve is symmetrical about the preset axis.

10. The device according to claim 9, characterized in that The surface of the non-planar semiconductor structure includes a plane and a concave surface formed by concaving the plane. The cross-sectional shape of the non-planar semiconductor structure is symmetrical about the preset axis. The first prediction function is an inverse function of a cubic function.

11. The device according to claim 10, characterized in that The determining module is configured to: Acquire first configuration information, where the first configuration information is used to characterize a correspondence between a material model and a fluidity coefficient; The fluidity coefficient is determined based on a material type of the spin-coated material and the first configuration information.

12. The device according to claim 10, characterized in that The determining module is configured to: Acquiring second configuration information, where the second configuration information is used to characterize a correspondence between a liquidity characteristic value and a liquidity coefficient; The fluidity coefficient is determined based on the fluidity characteristic value of the spin-on material and the second configuration information.

13. A spin coating simulation device, characterized in that The spin coating simulation device comprises: processor; a memory for storing processor-executable instructions; The processor is configured to execute: Obtain spin coating process parameter information; Determining shape information of a spin-coated film layer formed on the non-planar semiconductor structure based on a preset simulation model and the spin-coating process parameter information; The spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material, wherein the characteristic information of the spin coating material is used to determine the fluidity information of the spin coating material; The determining of shape information of a spin-coated film layer formed on a non-planar semiconductor structure based on a preset simulation model and the spin-coating process parameter information includes: Determining surface shape information of the spin-coated film layer based on the preset simulation model and the spin-coating process parameter information; determining shape information of the spin-on film layer based on the surface shape information of the spin-on film layer and preset surface shape information of the non-planar semiconductor structure; The determining the surface shape information of the spin-coated film layer based on the preset simulation model and the spin-coating process parameter information includes: Determining a simulation curve based on the preset simulation model and the spin coating process parameter information, wherein the simulation curve is used to characterize the surface shape information of the spin coating film layer; The relationship between the target film thickness, the characteristic information of the spin-coated material and the simulation curve can be determined by experimental calibration or empirical value.

14. A non-transitory computer-readable storage medium, characterized in that When the instructions in the storage medium are executed by the processor of the spin coating simulation device, the spin coating simulation device is enabled to perform: Obtain spin coating process parameter information; Determining shape information of a spin-coated film layer formed on the non-planar semiconductor structure based on a preset simulation model and the spin-coating process parameter information; The spin coating process parameter information includes: target film thickness and characteristic information of the spin coating material, wherein the characteristic information of the spin coating material is used to determine the fluidity information of the spin coating material; The determining of shape information of a spin-coated film layer formed on a non-planar semiconductor structure based on a preset simulation model and the spin-coating process parameter information includes: Determining surface shape information of the spin-coated film layer based on the preset simulation model and the spin-coating process parameter information; determining shape information of the spin-on film layer based on the surface shape information of the spin-on film layer and preset surface shape information of the non-planar semiconductor structure; The determining the surface shape information of the spin-coated film layer based on the preset simulation model and the spin-coating process parameter information includes: Determining a simulation curve based on the preset simulation model and the spin coating process parameter information, wherein the simulation curve is used to characterize the surface shape information of the spin coating film layer; The relationship between the target film thickness, the characteristic information of the spin-coated material and the simulation curve can be determined by experimental calibration or empirical value.

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