Programs, information processing systems, information processing methods, and manufacturing methods

Abstract

Obtain the desired pattern shape. [Solution] A program to be executed by a computer equipped with a processor, the program to cause the processor to perform an acquisition step of acquiring optical parameters indicating the optical properties of a material layer, the thickness of the material layer, and the interface roughness of the material layer, and a calculation step of calculating the absorbance distribution in the material layer when photons are irradiated onto the material layer based on the optical parameters, the thickness of the material layer, and the interface roughness, wherein the calculation step calculates the reflection and transmission of photons by calculating the probabilistic behavior of photons irradiated onto the material layer at the interface, and calculates the absorbance distribution based on the calculated reflection and transmission of photons.

Description

Technical Field

[0001] The present disclosure relates to a program, an information processing system, an information processing method, and a manufacturing method.

Background Art

[0002] In a material layer, after exposure through a negative film or a positive film on which a circuit pattern is formed, or exposure using a direct drawing apparatus, a fine pattern can be formed by developing a portion soluble in a developer with the developer. However, in order to obtain a desired pattern, the knowledge of an expert is required for the composition design of the material layer and the adjustment of exposure and development process conditions, and the prediction thereof is not easy. Therefore, a technique for predicting in advance the pattern shape obtained by pattern exposure on the material layer is required.

[0003] In order to predict the pattern shape obtained by pattern exposure on the material layer, it is important to accurately predict how the light exposed to the material layer is absorbed in the material layer, that is, the absorption amount distribution. In this regard, for example, in the field of resist materials formed on a semiconductor wafer, as a technique for calculating the energy accumulation distribution when irradiating a resist material with an electron beam, the technique described in Patent Document 1 is known.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Furthermore, in material layers, the surface may be roughened to improve adhesion to the substrate. However, in order to consider scattering reflection due to interface roughness, it is necessary to perform calculations that simulate internal scattering for the scattering and attenuation of reflected light, which leads to the problem of complex parameters.

[0006] The purpose of this disclosure is to predict the absorbance distribution taking into account the interface roughness. [Means for solving the problem]

[0007] To solve the above problems, a program according to one aspect of the present disclosure is a program to be executed by a computer equipped with a processor, the program to cause the processor to perform an acquisition step of acquiring optical parameters indicating the optical properties of a material layer, the thickness of the material layer, and the interface roughness of the material layer, and a calculation step of calculating the absorbance distribution in the material layer when a photon is irradiated onto the material layer based on the optical parameters, the thickness, and the interface roughness, wherein the calculation step calculates the reflection and transmission of the photon by calculating the probabilistic behavior of the photon irradiated onto the material layer at the interface, and calculates the absorbance distribution based on the calculated reflection and transmission of the photon. [Effects of the Invention]

[0008] According to this disclosure, it is possible to predict the absorbance distribution taking into account the interface roughness. [Brief explanation of the drawing]

[0009] [Figure 1] This is a block diagram showing an example of the overall system configuration. [Figure 2] This is a schematic cross-sectional view of the laminate that will be used to calculate the absorbance distribution. [Figure 3] This is an explanatory diagram of the interface between two layers. [Figure 4] This is a block diagram showing an example of a server device configuration. [Figure 5]This is a block diagram showing the functional section implemented by the control unit of the server device. [Figure 6] This is a block diagram showing an example of a terminal device hardware configuration. [Figure 7] This is a block diagram showing the functional section realized by the control unit of the terminal device. [Figure 8] This is a flowchart showing the process for calculating the absorbance distribution. [Figure 9] This is a diagram showing the absorbance distribution. [Figure 10] This figure shows the pattern shape after development, derived from the absorbance distribution. [Modes for carrying out the invention]

[0010] The embodiments of this disclosure will be described below with reference to the drawings. In all the drawings illustrating the embodiments, common components are denoted by the same reference numerals, and repeated explanations are omitted. The following embodiments are not intended to unduly limit the content of this disclosure as described in the claims. Not all components shown in the embodiments are necessarily essential components of this disclosure. Also, each drawing is a schematic diagram and is not necessarily a strict illustration.

[0011] Furthermore, in the following description, "processor" refers to one or more processors. A processor may be expressed, for example, as processing circuitry. At least one processor is typically a microprocessor such as a CPU (Central Processing Unit), but may be other types of processors such as a GPU (Graphics Processing Unit). At least one processor may be single-core or multi-core. Also, at least one processor may be a general-purpose processor or a purpose-specific processor.

[0012] Further, at least one processor may be a processor in a broad sense, such as a hardware circuit (e.g., FPGA (Field-Programmable Gate Array), ASIC (Application Specific Integrated Circuit)) that performs part or all of the processing.

[0013] The program may be pre-installed in the information processing device shown below, or, for example, may be on a recording medium (e.g., non-transitory) readable by the information processing device, and this program may be installed in the information processing device. Further, the program may be transmitted from a program distribution server to the information processing device and installed. Also, in the following description, two or more programs may be realized as one program, or one program may be realized as two or more programs.

[0014] FIG. 1 is a block diagram showing an example of the overall configuration of system 1. System 1 calculates the absorption amount distribution inside the material layer by simulation. The system 1 shown in FIG. 1 includes, for example, a server device 10 and a terminal device 20. The server device 10 and the terminal device 20 are communicatively connected via, for example, a network 80. Although FIG. 1 shows one terminal device 20, system 1 may include a plurality of terminal devices 20.

[0015] The server device 10 is an information processing device and is realized by a computer connected to the network 80. The server device 10 calculates, for example, the absorption amount distribution considering the interface roughness of the material layer.

[0016] The terminal device 20 is an information processing device operated by the user. The terminal device 20 may be implemented as, for example, a stationary PC (Personal Computer), a laptop PC, etc. The terminal device 20, for example, receives operation input from the user and transmits the parameters necessary for running the simulation to the server device 10. The terminal device 20 also displays the simulation results received from the server device 10 (for example, absorbance distribution, predicted pattern shape, etc.).

[0017] Figure 2 is a schematic cross-sectional view of a laminate, which is an example of a material layer subject to absorption distribution calculation. In this embodiment, exposure to a solder resist layer will be explained as an example. As shown in Figure 2, in the laminate 40, a solder resist layer 42 and a support layer (e.g., a PET layer) 43 are laminated on a substrate (e.g., a copper substrate) 41. The laminate 40 comprises a substrate 41 and a solder resist layer 42, which are two or more layers having different optical properties, and further comprises a support layer 43. The solder resist layer 42 is a scattering layer containing a scattering element. The solder resist layer 42 contains a scattering element which is at least one of a scattering component 44 such as an inorganic filler, an organic filler, or a pigment, and a scattering region such as a phase separation structure of a resin component or surface irregularities. Therefore, light absorption and scattering occur inside the solder resist layer 42. In other words, the solder resist layer 42 is also a scattering absorber.

[0018] As shown in Figure 2, when light is irradiated from the support layer 43 towards the substrate 41, the light propagates through the solder resist layer 42 while being absorbed or scattered. The solder resist layer 42 that has absorbed a certain amount of light or more hardens, and in the subsequent developing process, the hardened solder resist layer 42 in the exposed areas remains as a pattern. The solder resist layer 42 in the unexposed areas may also remain as a pattern.

[0019] Figure 3 is an explanatory diagram of the interface between two layers. In materials such as solder resist, the interlayer material and wiring are roughened to improve adhesion. As a result, for example, irregularities are formed on the interface 50 between the substrate 41 and the solder resist layer 42. In the system 1 according to this embodiment, the absorbance distribution is calculated taking into account the interface roughness at such an interface 50.

[0020] Figure 4 is a block diagram showing an example configuration of the server device 10 shown in Figure 1. As shown in Figure 4, the server device 10 comprises a control unit 110, a storage unit 120, a communication unit 130, and an input / output IF 140. The control unit 110 executes various processes by executing various programs stored in the storage unit 120. The control unit 110 is, for example, a processor such as a CPU. A processor is hardware for executing instruction sets described in a program. A processor consists of an arithmetic unit, registers, peripheral circuits, etc.

[0021] The storage unit 120 includes a main memory and an auxiliary memory. The storage unit 120 stores various programs and various information. For example, the storage unit 120 stores an application program 121.

[0022] Application program 121 is application software for calculating absorbance distribution. Application program 121 includes, for example, a programming language such as JavaScript® that is executed on a web browser application stored in terminal device 20.

[0023] The communication unit 130 performs modulation and demodulation processing for the server device 10 to communicate with an external device (for example, a terminal device 20). The communication unit 130 performs transmission processing on the signal generated by the control unit 110 and transmits it to the external device. The communication unit 130 performs reception processing on the signal received from the external device and outputs it to the control unit 110.

[0024] Figure 5 is a block diagram showing the functional units implemented by the control unit 110. The control unit 110 includes, as functional units, a parameter acquisition unit 111, an absorbance distribution calculation unit 112, a pattern shape prediction unit 113, an optimal condition identification unit 114, and an output processing unit 115. Specifically, the control unit 110 implements each functional unit by reading a program (including an application program 121) stored in the storage unit 120 and executing the instructions contained in the program.

[0025] The parameter acquisition unit 111 acquires various parameters. The absorbance distribution calculation unit 112 calculates the absorbance distribution. The pattern shape prediction unit 113 predicts the pattern shape of the material layer after development based on the absorbance distribution. The optimal condition identification unit 114 determines the optimal conditions for obtaining the desired pattern shape based on the absorbance distribution and pattern shape.

[0026] The output processing unit 115 outputs various types of information. Specifically, the output processing unit 115 transmits information to be presented to the user to the terminal device 20 via the network 80. The terminal device 20 outputs the information to be presented from the output unit 250, which will be described later. Here, as will be described later, the output unit 250 includes a display unit and a speaker. In other words, presenting information includes displaying the information and outputting audio corresponding to the information.

[0027] The following describes in detail the processing of the parameter acquisition unit 111, the absorbance distribution calculation unit 112, the pattern shape prediction unit 113, and the optimal condition identification unit 114.

[0028] The parameter acquisition unit 111 acquires various parameters necessary for calculating the absorbance distribution. The parameters acquired by the parameter acquisition unit 111 include at least optical parameters indicating the optical properties of the material layer, the thickness of the material layer, and the interface roughness of the material layer. These parameters are used to define the material layer model to be simulated.

[0029] Optical parameters are physical quantities that define the response of a material layer to light. Examples of optical parameters include the complex refractive index (composed of the real part n and the extinction coefficient κ), the absorption coefficient μa, the scattering coefficient μs, and the scattering anisotropy parameter g. Optical parameters are typically obtained from literature or experimentally measured values. These optical parameters usually depend on the wavelength of the irradiated light and are therefore obtained as wavelength-specific values. Furthermore, process conditions, including the wavelength of the irradiated light, are assumed to be provided. These process conditions include, in addition to wavelength, exposure, development time, temperature, etc.

[0030] The optical parameters may be input via the input unit 240 in the terminal device 20 and transmitted to the server device 10, or, as another example, they may be stored in the storage unit 120 or an external storage device. The storage unit 120 may store, for example, optical parameters indicating the optical properties of the material layer in a database or table format, for each type of material, wavelength, etc.

[0031] The film thickness parameter indicates the thickness of the material layer being simulated. If the material layer has a multilayer structure consisting of multiple layers, the film thickness of each layer is obtained separately.

[0032] Interface roughness is a parameter that quantitatively indicates the degree of unevenness at the interface of a material layer. In this embodiment, the roughness index α used in microfacet theory is used. However, interface roughness is not limited to this and may be determined based on other surface roughness index values ​​such as root mean square height (Rq) or arithmetic mean roughness (Ra). This interface roughness makes it possible to treat differences in surface state as independent parameters, even for materials with the same physical properties.

[0033] Next, the absorbance distribution calculation unit 112 will be described. Based on optical parameters, film thickness, and interface roughness, the absorbance distribution calculation unit 112 calculates the absorbance distribution in a material layer when light of a predetermined wavelength is irradiated onto a predetermined irradiation point. In this embodiment, the absorbance distribution calculation unit 112 uses the Monte Carlo method to calculate the amount of energy lost by photons and their coordinates.

[0034] Using the Monte Carlo method, a specific absorbance distribution can be obtained for a material layer corresponding to a specific film thickness and optical parameters when light of a predetermined wavelength is irradiated at a predetermined irradiation point. The Monte Carlo method is a technique that enables statistical simulation using random numbers, and by using the Monte Carlo method, the behavior of each individual photon can be simulated. Specifically, by dividing light into many photons (groups), and treating them as energy particles of light that scatter, change direction, and are absorbed, the propagation path of photons and the attenuation of light intensity during that process can be simulated. The absorbance distribution calculation unit 112 may obtain a predetermined reflectance and transmittance corresponding to the film thickness and optical parameters of each layer, as well as the absorbance distribution of photons incident from a single irradiation point, by performing calculations using the Monte Carlo method under these conditions, based on the film thickness and optical parameters (refractive index n, absorption coefficient μa, scattering coefficient μs, scattering anisotropy parameter g) of the material layer. The distribution of light intensity lost by photons at each coordinate calculated here can be considered as the absorbance distribution.

[0035] Next, we will detail the method for calculating the absorbance distribution using the Monte Carlo method. Consider the case where a single photon is incident on the surface of a material with a scattering coefficient of μs, an absorption coefficient of μa, and a scattering anisotropy parameter of g, the mean free path L of that photon is expressed by the following equation (1). Here, r1 is a random number between 0 and 1.

number

number

number

number

number

[0036] Using these equations, it is possible to simulate the propagation path of a photon and the attenuation of light intensity during that process, based on the scattering coefficient μs, the absorption coefficient μa, and the scattering anisotropy parameter g. If the light intensity of a photon becomes sufficiently small (for example, to less than 1 / 10,000th of the incident light intensity), the photon can be considered to have been annihilated. If the photon is emitted from the incident surface of the material, it can be considered to have been reflected.

[0037] When a photon reaches the interface of a material, it may be assumed that the photon has been transmitted or reflected, taking into account the interface roughness. For example, if the interface is the interface between the substrate 41 and the solder resist layer 42, the photon may be assumed to have been transmitted or reflected based on a probability calculated taking into account the interface roughness.

[0038] When an incident photon is annihilated, transmitted, or reflected and emitted outside the material, the Monte Carlo calculation for that photon is completed, and the coordinates where the photon's energy decayed and the amount of energy decay at those coordinates are recorded.

[0039] The absorption calculation performed by the absorbance distribution calculation unit 112 is an absorption simulation of a single photon incident from a single irradiation point. By performing similar absorption simulations for multiple photons at a single irradiation point, the absorbance distribution of light incident from a single irradiation point can be calculated. The absorbance distribution calculation unit 112 then calculates the absorbance distribution during pattern exposure by integrating the absorbance distributions calculated at each of the multiple irradiation points. This makes it possible to calculate the absorbance distribution of the material layer during pattern exposure.

[0040] In particular, in predicting the pattern shape of a photosensitive resin composition, the absorbance distribution near the edges of the pattern exposure area is important. Therefore, irradiation points may be selected only from defined regions with a predetermined width and size, and calculations may be performed using the Monte Carlo method. These calculations can then be integrated to calculate the absorbance distribution of the entire region, including regions other than the defined region.

[0041] The absorbance distribution calculation unit 112 may weight the absorbance distributions calculated for each of the multiple irradiation points based on the light intensity distribution. By weighting based on the light intensity distribution, it becomes possible to take into account the effects of wave optics, such as the focus shift of the exposure machine.

[0042] The light intensity distribution can be calculated using conventionally known methods, for example, by using the ideal lens approximation or Fourier transform, taking into account the mask pattern, the NA of the exposure device, aberrations, etc.

[0043] Next, we will explain the calculation of behavior at the interface, taking into account the interface roughness. The absorbance distribution calculation unit 112 models the behavior of an interface that is macroscopically flat but microscopically uneven, and determines whether individual photons are reflected or transmitted at that interface by performing a probabilistic behavior calculation based on the interface roughness.

[0044] The absorbance distribution calculation unit 112 uses microfacet theory to perform this probabilistic behavior calculation. Microfacet theory models a rough surface as a collection of tiny planes (microfacets) that are invisible to the naked eye. Each microfacet is assumed to exhibit perfect specular reflection (Fresnel reflection). The overall reflection characteristics of the surface are determined by the distribution of the orientations of these countless microfacets and their interactions.

[0045] The absorbance distribution calculation unit 112 calculates a reflection model (BRDF: Bidirectional Reflectance Distribution Function) based on microfacet theory using equation (6). The reflection model uses a normal distribution function (D term), a geometrical attenuation factor (G2 term), and a Fresnel term (F term). Note that the reflection model only needs to use at least one of these terms.

number

[0046] The normal distribution term is a function that defines the statistical distribution of which direction and with what probability the normal vectors of microfacets point. The larger the value of the interface roughness α, the wider the distribution of normals, representing a state where normals point in a wider variety of directions, i.e., a rougher surface. The absorbance distribution calculation unit 112 can selectively use various known functions as the normal distribution term, such as the Beckmann distribution function, the Phong distribution function, or the GGX distribution function.

[0047] The geometric attenuation term is a function that models the light shielding effect caused by the uneven shape of the microfacets. Specifically, it defines the phenomenon of light incident from an oblique angle being hidden by the microfacet and not reaching the facet behind it (shadowing function), and the phenomenon of light reflected by the facet behind being blocked by the microfacet in front of it and not escaping to the outside (masking function). Shadowing and masking depend on the interface roughness α. The absorbance distribution calculation unit 112 can use various known models as the geometric attenuation term, such as the Smith model, its improved model, or the V-groove model.

[0048] The reflection coefficient term (Fresnel's equation) is a function that defines the reflectance of light at each microfacet. This reflectance depends on the angle of incidence of light (the angle of incident light relative to the normal of the microfacet), the polarization state of the light, and the complex refractive index of the two media flanking the interface, and is calculated using Fresnel's equation. The absorbance distribution calculation unit 112 uses this Fresnel term to determine what proportion of the light energy reaching the microfacet is reflected and what proportion is transmitted (refracted).

[0049] In the Monte Carlo method of photon tracking simulation, the absorbance distribution calculation unit 112 performs probability calculations using these terms each time a photon reaches a rough interface. This calculation can be conceptually divided into two steps. That is, in the first step, the absorbance distribution calculation unit 112 probabilistically determines the normal vector of the microfacet, and in the second step, it determines whether it is reflected or transmitted based on that normal vector.

[0050] In the first step, the absorbance distribution calculation unit 112 probabilistically samples the normal vector of the microfacet at the point where the photon collides, using a normal distribution term characterized by the interface roughness α. A known probabilistic sampling method is used for this sampling. In sampling, the determination formula is f1 = DG i / A1 is used. A1 is a coefficient for the variable transformation in the integral, etc. G i This is the geometric decay term (shadowing function).

[0051] In the second step, the absorbance distribution calculation unit 112 calculates the angle of incidence to the microfacet from the normal vector and the incident light vector determined in the first step. Then, it calculates the Fresnel term using this angle of incidence and the optical parameters of the material to determine the reflectance. Furthermore, it has a function to probabilistically determine whether the photon is ultimately reflected or transmitted by considering geometric attenuation terms (shadowing function and masking function). The determination formula is f2 = FG o / A2 is used. A2 is a coefficient for the variable transformation in the integral, etc. G o This is the geometric decay term (masking function).

[0052] The absorbance distribution calculation unit 112 combines calculations of behavior at such interfaces with calculations of absorption and scattering within the material layer to track the trajectories of numerous photons.

[0053] Next, the pattern shape prediction unit 113 will be described. The pattern shape prediction unit 113 predicts the pattern shape of the pattern formed in the exposure and development process based on the absorbance distribution of the material layer during pattern exposure calculated by the absorbance distribution calculation unit 112, the photosensitive properties of the material layer, and the development properties of the material layer. Photosensitive properties are characteristics that define the progress of the chemical reaction that occurs when the material absorbs light energy, and show the relationship between the amount of absorbed light and the amount of chemical reaction. Development properties are characteristics that define how much the material dissolves or remains in the development process according to the amount of chemical reaction caused by exposure, and show the relationship between the amount of chemical reaction and the dissolution rate in the developer. As development properties, for example, a development rate function that shows the relationship between the amount of absorbed light energy and the dissolution rate of the material in the developer may be used, or a predetermined threshold may be set for the amount of chemical reaction, and dissolution and remaining in the development process may be determined based on that threshold. Alternatively, a trained model may be constructed using machine learning methods to predict shape data from the amount of absorbed light energy and process conditions, and the shape may be predicted.

[0054] The pattern shape prediction unit 113 calculates the distribution of chemical reaction amounts within the material layer by applying the photosensitive properties of the material to the absorbance distribution. The photosensitive properties may be defined as a conversion function of the reaction amount to the absorbance amount, or as a model including multiple parameters. Furthermore, based on the distribution of chemical reaction amounts, the pattern shape prediction unit 113 calculates a three-dimensional development rate distribution within the material layer by applying the development properties (development rate function) of the material, and predicts the pattern shape based on the development time.

[0055] The optimal condition identification unit 114 searches for the optimal conditions to obtain the target pattern shape. Here, the conditions include interface roughness and process conditions. The optimal condition identification unit 114 sets multiple conditions in which at least one of the interface roughness and process conditions differs, predicts the pattern shape for each condition, and identifies the conditions that form the pattern shape closest to the ideal pattern shape as the optimal conditions. For the optimal conditions, it is sufficient to identify at least one of the interface roughness and process conditions. For example, the interface roughness may be set to a certain value, and only the process conditions may be identified as optimal conditions. Note that the interface roughness and process conditions included in the identified optimal conditions are examples of ideal values.

[0056] The optimal conditions are output to the terminal device 20. Furthermore, the optimal conditions are input to the manufacturing equipment (exposure device, developing device, etching device, etc.), and the pattern shape is formed in the manufacturing equipment according to the optimal conditions. In this way, the pattern shape can be formed based on the optimal conditions.

[0057] Furthermore, the optimal conditions may be a combination selected by the user from among multiple combinations. Alternatively, a threshold for the difference between the predicted pattern shape and the ideal pattern shape may be pre-set, and the combination corresponding to the predicted pattern shape where the difference is below the threshold may be determined as the optimal condition. Another example is that a predetermined value may be set for the interface roughness, and one process condition may be determined as the optimal condition from among multiple process conditions.

[0058] Figure 6 is a block diagram showing an example of the hardware configuration of the terminal device 20 shown in Figure 1. As shown in Figure 6, the terminal device 20 comprises a control unit 210, a storage unit 220, a communication unit 230, an input unit 240, and an output unit 250. Each part included in the terminal device 20 is electrically connected, for example, by a bus.

[0059] The control unit 210, storage unit 220, and communication unit 230 are the same as the control unit 110, storage unit 120, and communication unit 130 of the server device 10, respectively. The control unit 210 performs various processes by executing various programs stored in the storage unit 220.

[0060] The memory unit 220 stores, for example, an application program 221. The application program 221 includes, for example, a programming language that runs on a web browser application (not shown) stored in the memory unit 220.

[0061] The communication unit 230 performs processing such as modulation and demodulation processing for the terminal device 20 to communicate with an external device (for example, the server device 10).

[0062] The input unit 240 receives information input from the user. The input unit 240 may be implemented by, for example, a touch-sensitive device that receives instructions or other information by touching an operating surface. If the terminal device 20 is a PC or the like, the input unit 240 may be implemented by a reader, keyboard, mouse, or the like. The input unit 240 converts the instructions or other information input by the user into electrical signals and outputs them to the control unit 210. The input unit 240 may also include, for example, a receiving port that receives electrical signals input from an external input device. The input unit 240 may also include a microphone that receives audio input.

[0063] The output unit 250 outputs various information. The output unit 250 includes, for example, a display unit. The display unit displays various information according to the control of the control unit 101. The output unit 250 may also include a speaker for outputting sound. The output unit 250 may also include an output port for outputting electrical signals to an external output device.

[0064] Figure 7 is a block diagram showing the functional units implemented by the control unit 210. The control unit 210 includes a reception unit 211, a communication processing unit 212, and an output processing unit 213 as functional units. Specifically, the control unit 210 implements each functional unit by reading the application program 221 stored in the storage unit 220 and executing the instructions contained in the application program 221.

[0065] The reception unit 211 receives instructions or information input from the input unit 240. The communication processing unit 212 transmits and receives data with external devices via the network 80. The output processing unit 213 outputs various types of information from the output unit 250.

[0066] Figure 8 is a flowchart showing the absorbance distribution calculation process performed by the server device 10. In step S100, the parameter acquisition unit 111 acquires optical parameters, material layer thickness, and interface roughness.

[0067] Next, in step S102, the absorbance distribution calculation unit 112 calculates the absorbance distribution in the material layer when light of a predetermined wavelength is irradiated to a predetermined irradiation point, based on the optical parameters, film thickness, and interface roughness.

[0068] Next, in step S104, the pattern shape prediction unit 113 predicts the pattern shape based on the absorbance distribution obtained from the interface roughness, the photosensitive characteristics, and the development characteristics.

[0069] Next, in step S106, the output processing unit 115 outputs a pattern shape image showing the pattern shape. As a result, the pattern shape image is displayed on the display unit, which is the output unit 250 of the terminal device 20. With this, the absorbance distribution calculation process is completed.

[0070] As described above, according to System 2 of this embodiment, the absorbance distribution in a material layer when light is irradiated onto the material layer can be calculated based on optical parameters, film thickness, and interface roughness. In other words, it is possible to predict the absorbance distribution that takes interface roughness into account.

[0071] In this embodiment, the absorbance distribution considering the interface roughness at the interface 50 between the substrate 41 and the solder resist layer 42 has been described, but the interface also includes the surface which is the interface between the air layer and the material layer.

[0072] Furthermore, although this embodiment describes a laminate 40 consisting of two or more layers as an example of a material layer, the material layer is not limited to a laminate and may also include a single-layer material layer. In this case, the interface is the surface that is the boundary between the air layer and the material layer.

[0073] Furthermore, it is possible to similarly calculate the absorbance distribution that takes into account the interface roughness at multiple interfaces, for example, when irregularities are formed not only at the interface 50 between the substrate 41 and the solder resist layer 42, but also at the interface between the solder resist layer 42 and the support layer 43. The absorbance distribution calculation unit 112, when the simulation target is a laminate in which multiple layers are stacked and irregularities are formed at the interfaces between each layer, performs the aforementioned probabilistic behavior calculation based on the interface roughness and optical parameters set for each interface each time a photon reaches an interface between layers.

[0074] Another example is that the output processing unit 115 may output an absorbance distribution image showing the absorbance distribution calculated in step S102. In this case, the absorbance distribution image will be displayed on the display unit of the terminal device 20.

[0075] Table 1 shows the measured total reflectance and the total reflectance obtained by simulation using System 1 of this embodiment. The values ​​for copper substrate 1 and copper substrate 2 in Table 1 are all values ​​for actual copper substrates. Copper substrate 1 is a copper substrate that has not undergone interface roughening treatment, and copper substrate 2 is a copper substrate that has undergone interface roughening treatment compared to copper substrate 1. Due to the roughening treatment, the total reflectance decreased from 32% to 9.2%. In the conventional method that considers only the refractive index, it was not possible to obtain a value close to the above total reflectance. In contrast, in the simulation of this embodiment, when the interface roughness α is 2.3, a total reflectance of 32%, which is equal to the measured value of copper substrate 1, was obtained, and when the interface roughness α is 13.6, a total reflectance of 9.2%, which is equal to the measured value of copper substrate 2, was obtained. Thus, by considering the interface roughness α, results that are in line with the measured total reflectance were obtained even when using literature values ​​for the refractive index. [Table 1]

[0076] Figure 9 shows the absorbance distribution obtained by System 1. The left column is the graph corresponding to an incident angle of 0°, and the right column is the graph corresponding to an incident angle of 40°. The interface roughness α is 0, 0.3, and 13.6 from top to bottom. The horizontal axis shows the plane direction, and the vertical axis shows the depth direction. Depths of 25-50 correspond to the material layer, and around 50 corresponds to the interface. In all cases, it can be confirmed that as the interface roughness α increases, the system can reproduce a state where light is scattered more at the interface.

[0077] Figure 10 shows the pattern shape after development, derived from the absorbance distribution obtained by System 1. As the interface roughness α increases, the amount of reflectance decreases, and a shape closer to a cylinder can be observed.

[0078] Next, a manufacturing method for forming a pattern shape will be described. The optimal condition identification unit 114 acquires a target pattern shape, for example, in response to user operations on the terminal device 20. Next, the optimal condition identification unit 114 identifies the interface roughness and process conditions as optimal conditions based on the target pattern shape. For example, the optimal condition identification unit 114 sets multiple conditions by varying the interface roughness and process conditions, calculates the absorbance distribution for each condition, and predicts the pattern shape from the absorbance distribution. Then, the optimal condition identification unit 114 compares each of the obtained multiple pattern shapes with the target pattern shape and identifies the conditions (interface roughness and process conditions) corresponding to the pattern shape with the smallest difference as the optimal conditions. Alternatively, the optimal condition identification unit 114 may identify the conditions corresponding to the pattern shape whose difference is below a threshold as the optimal conditions. Alternatively, the determination of the optimal conditions may be made by the user's judgment, and the optimal conditions may be input in response to user operations on the terminal device 20. Here, the interface roughness and process conditions as optimal conditions are examples of ideal values.

[0079] The optimal conditions identified in this way are input into the manufacturing equipment, where the pattern shape is actually formed. This creates the desired pattern shape. Note that it is sufficient for at least one of the interface roughness and process conditions to be identified as the optimal conditions. For example, the interface roughness may be set to a certain value, and only the process conditions may be identified as the optimal conditions.

[0080] In the above embodiments, the case in which the functional unit is implemented by a processor has been described, but it is not limited to this. The functional unit may be any hardware known to perform processing.

[0081] Furthermore, although the server device 10 is configured as a single unit in the above embodiment, in other examples, it may be configured as an information processing system which is a collection of multiple devices. Also, the method of distributing the multiple functions required to realize the server device 10 to multiple devices may be determined according to the processing capacity of each device, the specifications required for the server device 10, etc. Some or all of the functions of the server device 10 according to this embodiment may be provided in the terminal device 20 instead of the server device 10.

[0082] Although several embodiments of this disclosure have been described above, these embodiments can be implemented in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. For example, configurations and processes in one embodiment may be combined with configurations and processes in another embodiment, or a modification of one embodiment may be applied to another embodiment. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents.

[0083] (Note) The details described in each of the above embodiments are noted below.

[0084] (Note 1) A program to be executed on a computer equipped with a processor, The aforementioned processor, An acquisition step to obtain optical parameters indicating the optical properties of the material layer, the film thickness of the material layer, and the interface roughness of the material layer, A calculation step of calculating the absorbance distribution in the material layer when photons are irradiated onto the material layer, based on the optical parameters, the film thickness, and the interface roughness. Make it run, The program calculates the reflection and transmission of photons by calculating the probabilistic behavior of photons irradiated onto the material layer at the interface, and calculates the absorbance distribution based on the calculated reflection and transmission of photons.

[0085] (Note 2) The program described in Appendix 1 employs the microfacet method, which treats the interface as a collection of minute planes, in the behavior calculation.

[0086] (Note 3) In the behavior calculation, at least the statistical distribution of the normal to the minute plane, the shielding and attenuation of light due to the uneven shape of the minute plane, and the reflectance according to the angle of incidence to the interface are considered. One is used, attached Note 2 The program described above.

[0087] (Note 4) The program described in Appendix 1 to 3 uses at least one of the normal distribution function, shadowing function, masking function, and Fresnel's equation in the behavior calculation.

[0088] (Note 5) The normal distribution function is the program described in Appendix 4, which includes either the Beckmann distribution function, the Phong distribution function, or the GGX distribution function.

[0089] (Note 6) A program according to any one of Appendix 1 to 5, which further performs a prediction step to predict the pattern shape of the material layer after exposure and development, based on the absorbance distribution, the photosensitive properties of the material layer, the development properties of the material layer, and the process conditions of the exposure and development process.

[0090] (Note 7) A selection step of identifying an ideal value for at least one of the interface roughness and the process conditions of the exposure and development process based on the predicted pattern shape, An output step that outputs the aforementioned ideal value, The program described in Appendix 6 further executes the following:

[0091] (Note 8) An information processing system comprising one or more processors, The one or more processors described above are: An acquisition step to obtain optical parameters indicating the optical properties of the material layer, the film thickness of the material layer, and the interface roughness of the material layer, A calculation step of calculating the absorbance distribution in the material layer when photons are irradiated onto the material layer, based on the optical parameters, the film thickness, and the interface roughness. Execute, The information processing system, in the calculation step, estimates the reflection and transmission of photons by calculating the probabilistic behavior of photons irradiated onto the material layer at the interface, and calculates the absorbance distribution based on the estimated reflection and transmission of photons.

[0092] (Note 9) An information processing method performed by one or more processors, The one or more processors perform an acquisition step of obtaining optical parameters indicating the optical properties of the material layer, the thickness of the material layer, and the interface roughness of the material layer. The calculation step involves one or more processors calculating the absorbance distribution in the material layer when photons are irradiated onto the material layer, based on the optical parameters, the film thickness, and the interface roughness. Includes, The calculation step involves estimating the reflection and transmission of photons by calculating the probabilistic behavior of photons irradiated onto the material layer at the interface, and calculating the absorbance distribution based on the estimated reflection and transmission of photons.

[0093] (Note 10) A step of obtaining optical parameters that indicate the optical properties of the material layer, the film thickness of the material layer, and the interface roughness of the material layer. A calculation step of calculating the absorbance distribution in the material layer when photons are irradiated onto the material layer, based on the optical parameters, the film thickness, and the interface roughness. A prediction step that predicts the pattern shape of the material layer after exposure and development based on the absorbance distribution, the photosensitive properties of the pre-material layer, the development properties of the material layer, and the process conditions of the exposure and development process. A selection step to identify an ideal value for at least one of the interface roughness and the process conditions of the exposure and development process, based on the predicted pattern shape, A forming step of forming a pattern on the material layer based on the aforementioned ideal value, A manufacturing method that includes this. [Explanation of Symbols]

[0094] 1 System 10 Server devices 20 Terminal devices 80 Networks 110 Control Unit 111 Parameter acquisition unit 112 Absorption amount distribution calculation section 113 Pattern shape prediction unit 114 Manufacturing Condition Determination Unit 115 Output Processing Unit 120 Storage section 121 Application Programs 130 Communications Department 140 Input / Output Interfaces 210 Control Unit 211 Reception Department 212 Communication Processing Unit 213 Output Processing Unit 220 Storage section 221 Application Programs 230 Communications Department 240 Input section 250 Output section

Claims

1. A program to be executed on a computer equipped with a processor, The aforementioned processor, An acquisition step to obtain optical parameters indicating the optical properties of the material layer, the film thickness of the material layer, and the interface roughness of the material layer, A calculation step is performed to calculate the absorbance distribution in the material layer when a photon is irradiated onto the material layer, based on the optical parameters, the film thickness, and the interface roughness. The program calculates the reflection and transmission of photons by calculating the probabilistic behavior of photons irradiated onto the material layer at the interface, and calculates the absorbance distribution based on the calculated reflection and transmission of photons.

2. The program according to claim 1, wherein the behavior calculation employs a microfacet method that treats the interface as a collection of minute planes.

3. The program according to claim 2, wherein the behavior calculation uses at least one of the statistical distribution of the normal of the minute plane, the shielding and attenuation of light due to the uneven shape of the minute plane, and the reflectance according to the angle of incidence to the interface.

4. The program according to claim 3, wherein at least one of the normal distribution function, shadowing function, masking function, and Fresnel's equation is used in the behavior calculation.

5. The program according to claim 4, wherein the normal distribution function includes any one of the Beckmann distribution function, the Phong distribution function, or the GGX distribution function.

6. The program according to claim 1, further comprising a prediction step of predicting the pattern shape of the material layer after exposure and development, based on the absorbance distribution, the photosensitive properties of the material layer, the development properties of the material layer, and the process conditions of the exposure and development process.

7. A selection step of identifying an ideal value for at least one of the interface roughness and the process conditions of the exposure and development process based on the predicted pattern shape, The program according to claim 6, further comprising an output step that outputs the aforementioned ideal value.

8. An information processing system comprising one or more processors, The one or more processors described above are: An acquisition step to obtain optical parameters indicating the optical properties of the material layer, the film thickness of the material layer, and the interface roughness of the material layer, A calculation step is performed to calculate the absorbance distribution in the material layer when a photon is irradiated onto the material layer, based on the optical parameters, the film thickness, and the interface roughness. The information processing system, in the calculation step, estimates the reflection and transmission of photons by calculating the probabilistic behavior of photons irradiated onto the material layer at the interface, and calculates the absorbance distribution based on the estimated reflection and transmission of photons.

9. An information processing method performed by one or more processors, The one or more processors perform an acquisition step of obtaining optical parameters indicating the optical properties of the material layer, the film thickness of the material layer, and the interface roughness of the material layer. The one or more processors include a calculation step of calculating the absorbance distribution in the material layer when photons are irradiated onto the material layer, based on the optical parameters, the film thickness, and the interface roughness. The calculation step involves estimating the reflection and transmission of photons by calculating the probabilistic behavior of photons irradiated onto the material layer at the interface, and calculating the absorbance distribution based on the estimated reflection and transmission of photons.

10. A step of obtaining optical parameters that indicate the optical properties of the material layer, the film thickness of the material layer, and the interface roughness of the material layer. A calculation step of calculating the absorbance distribution in the material layer when photons are irradiated onto the material layer, based on the optical parameters, the film thickness, and the interface roughness. A prediction step that predicts the pattern shape of the material layer after exposure and development based on the absorbance distribution, the photosensitive properties of the pre-material layer, the development properties of the material layer, and the process conditions of the exposure and development process. A selection step to identify an ideal value for at least one of the interface roughness and the process conditions of the exposure and development process, based on the predicted pattern shape, A manufacturing method comprising: a forming step of forming a pattern on the material layer based on the aforementioned ideal values.

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