KR20230018970A - Simulation system and computer readable recording medium - Google Patents

Abstract

Provided are a simulation system for providing semiconductor devices with improved product reliability and a computer-readable recording medium. The simulation system comprises a processor and a storage for storing a simulation program executed by the processor, wherein the simulation program includes: an optical analysis module that calculates thermal energy data generated by light energy provided to a simulation area using a finite difference method (FDM); a thermal analysis module that receives the thermal energy data calculated by the optical analysis module and calculates temperature change data over time in the simulation area and phase change data in the simulation area using the finite element method (FEM); and a silicon loss calculation module that calculates a silicon loss in the simulation area using the temperature change data and phase change data calculated by the thermal analysis module.

Description

Simulation system and computer readable recording medium

The present invention relates to a simulation system and a computer readable recording medium.

As semiconductors become highly integrated and miniaturized, various unintended electrical characteristics may occur in semiconductor devices due to a complex effect of factors at each stage of designing and manufacturing semiconductor devices. Therefore, the semiconductor industry's demand for a TCAD (Technology Computer Aided Design) process-device simulation environment based on physical simulation is increasing in order to overcome the limitations of semiconductor processes and devices, understand phenomena and reduce experiment costs. . In addition, in order to provide accurate product specifications of semiconductor devices, it is necessary to predict and simulate characteristics of semiconductor devices.

A technical problem to be solved by the present invention is to provide a simulation system for providing a semiconductor device with improved product reliability.

Another technical problem to be solved by the present invention is to provide a computer-readable recording medium containing a simulation program for providing a semiconductor device with improved product reliability.

The technical problems of the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the following description.

A simulation system according to some embodiments of the present invention for achieving the above technical problem includes a processor and a storage for storing a simulation program executed by the processor, but the simulation program uses a finite difference method (FDM) method , An optical analysis module, which calculates thermal energy data generated by light energy provided to the simulation area, and the thermal energy data calculated by the optical analysis module are provided, and using a finite element method (FEM) method, the simulation area A thermal analysis module that calculates temperature change data over time and phase change data in the simulation area, and a silicon loss amount calculation module that calculates silicon loss in the simulation area using the temperature change data and phase change data calculated by the thermal analysis module includes

A simulation system according to some embodiments of the present invention for achieving the above technical problem includes a processor and a storage for storing a simulation program, but when the simulation program is executed, the processor divides the simulation area into an unstructured mesh and , Using the parameters of the unstructured mesh through the FDM method, the heat energy data generated by the light energy provided to the simulation area is calculated, and the parameters of the unstructured mesh are interpolated with the parameters of the structured mesh. Based on the thermal energy data, using the parameters of the mesh structured through the FEM method, the temperature change data of the simulation area over time and the phase change data of the simulation area are calculated, and the temperature change data and the phase change data are used. Thus, the amount of silicon loss in the simulation area is calculated.

A computer-readable recording medium according to some embodiments of the present invention for achieving the above technical problem includes a simulation program for calculating the number of voids occurring in the simulation area and a defect rate of the simulation area due to the voids, the simulation program An optical analysis module, which calculates thermal energy data generated by light energy provided to the simulation area using parameters stored in a tensor mesh through the FDM method, and stored in the tensor mesh Using an interpolation module that interpolates parameters with parameters stored in a tetrahedral mesh, thermal energy data calculated by the optical analysis module through the FEM method, and parameters stored in the tetrahedral mesh generated by the interpolation module, A thermal analysis module that calculates temperature change data over time in the simulation area and phase change data in the simulation area, and silicon that calculates silicon loss in the simulation area using the temperature change data and phase change data calculated by the thermal analysis module A loss amount calculation module and a void analysis module that calculates the number of voids generated in the simulation area and a defect rate of the simulation area due to the voids using the silicon loss amount calculated from the silicon loss amount calculation module.

Details of other embodiments are included in the detailed description and drawings.

1 is an exemplary flow chart of annealing of a semiconductor device for describing a simulation in accordance with some embodiments.
2 is a diagram for explaining a simulation system according to some embodiments.
Figure 3 is a diagram for explaining the operation of the simulation system according to some embodiments.
4 is a flowchart illustrating operations of an optical analysis module and a thermal analysis module of a simulation system according to some embodiments.
5 and 6 are diagrams for describing meshes used by an optical analysis module and a thermal analysis module of a simulation system according to some embodiments.
7 is a flowchart illustrating an operation of a silicon loss calculation module of a simulation system according to some embodiments.
8 is a diagram for explaining a silicon loss amount simulation through a silicon loss amount calculation module of a simulation system according to some embodiments.
9A and 9B are flow charts illustrating the operation of the void analysis module of the simulation system according to some embodiments.
10 to 14 are diagrams for explaining simulation of a simulation system according to some embodiments.
15 is a diagram for explaining a simulation system according to some other embodiments.
16 is a flowchart illustrating operations of an optical analysis module and a thermal analysis module of a simulation system according to some embodiments.
17 is an exemplary block diagram for describing a computing system including a simulation system according to some embodiments.

Hereinafter, embodiments according to the technical idea of the present invention will be described with reference to the accompanying drawings.

1 is an exemplary flow chart of annealing of a semiconductor device for describing a simulation in accordance with some embodiments.

Referring to FIG. 1 , when the semiconductor device is annealed, light energy may be applied to the semiconductor device (S10). Thermal energy is generated inside the semiconductor device by light energy applied to the semiconductor device (S20), and the temperature and phase of the semiconductor device are changed due to the generated thermal energy (S30).

Silicon (Si) included in the semiconductor device may be lost in an existing region as the temperature and phase of the semiconductor device change (S40). Specifically, silicon (Si) may diffuse from a region previously containing silicon to another adjacent region according to a temperature change and a phase change of a semiconductor device. For example, silicon included in the substrate region of the semiconductor device may diffuse into an insulating region disposed on the substrate and a conductive metal region disposed on the substrate.

As silicon diffuses into other regions, voids may be formed in the existing region where silicon exists (S50). A void formed in a semiconductor device may deteriorate the performance of the semiconductor device, such as causing a short-circuit defect. Accordingly, when light energy is applied, such as annealing the semiconductor device, the need for simulation of voids included in the semiconductor device increases.

Accordingly, the simulation system can verify performance by simulating physical and electrical characteristics of a simulation target such as a semiconductor device. Hereinafter, a case where a simulation target of the simulation system is a semiconductor device will be described as an example. However, the embodiment is not limited thereto, and the simulation system may simulate objects other than semiconductor devices.

2 is a diagram for explaining a simulation system according to some embodiments.

Referring to FIG. 2 , the simulation system 1 includes an optical analysis module 100, an interpolation module 200, a thermal analysis module 300, a silicon loss calculation module 400, and a void analysis module 500.

The simulation system 1 may receive a simulation domain to be simulated from the thermal analysis module 300 . The simulation area is an area to be simulated by the simulation system 1 and may include a part of a semiconductor device.

The optical analysis module 100 may analyze a change in physical properties of the simulation area that appears due to light energy applied to the simulation area, which is a simulation target of the simulation system 1 . Specifically,

The interpolation module 200 may interpolate parameters so that the parameters used by the optical analysis module 100 and the thermal analysis module 300 are compatible in each module.

The thermal analysis module 300 may analyze changes in physical properties caused by thermal energy generated by light energy applied to the simulation area. Specifically, the thermal analysis module 300 may analyze temperature change and phase change of the simulation area due to thermal energy.

The silicon loss amount calculation module 400 may calculate the amount of silicon loss in the simulation area caused by the temperature change and the phase change in the simulation area. Specifically, the silicon loss calculation module 400 may calculate an amount of silicon diffused into an insulating region such as an insulating film disposed on the substrate and a conductive metal region disposed on the substrate.

Figure 3 is a diagram for explaining the operation of the simulation system according to some embodiments. 4 is a flowchart illustrating operations of an optical analysis module and a thermal analysis module of a simulation system according to some embodiments. 5 and 6 are diagrams for describing meshes used by an optical analysis module and a thermal analysis module of a simulation system according to some embodiments. 7 is a flowchart illustrating an operation of a silicon loss calculation module of a simulation system according to some embodiments. 8 is a diagram for explaining a silicon loss amount simulation through a silicon loss amount calculation module of a simulation system according to some embodiments. 9A and 9B are flow charts illustrating the operation of the void analysis module of the simulation system according to some embodiments.

Referring to FIGS. 2 to 4 , when the simulation system 1 starts a simulation operation, a simulation area to be simulated is loaded (S001). Specifically, a simulation domain may be provided or input to the thermal analysis module 300 .

Subsequently, referring to FIGS. 4 and 5 , the simulation system 1 divides the loaded simulation area into meshes (S002). Specifically, the simulation system 1 may divide the loaded simulation area into unstructured meshes. The unstructured mesh may store parameters used in the thermal analysis module 300 . Although not shown, the simulation system 1 may include a mesh generation module that divides the simulation area into meshes.

A mesh may refer to a spatial grid dividing a simulation area. Specifically, a mesh may be a unit for spatial discretization of a simulation domain.

In some embodiments, the unstructured mesh used in thermal analysis module 300 may include a tetrahedral shaped mesh. An unstructured mesh can be convenient for spatial discretization of simulation domains such as complex structures and curved structures. Unstructured meshes can be used in the finite element method (FEM).

Subsequently, referring to FIGS. 2 to 4 and 6 , the simulation system 1 may interpolate the unstructured mesh generated in step S002 into a structured mesh (S200). Specifically, the interpolation module 200 may interpolate parameters stored in the unstructured mesh with parameters stored in the structured mesh. In some embodiments, the interpolation module 200 may linearly interpolate the unstructured mesh used in the thermal analysis module 300 with the structured mesh used in the optical analysis module 100 .

In some embodiments, the structured mesh used in the optical analysis module 100 may include a hexahedral shaped mesh. A structured mesh can be used to simulate a simulation area in a short time. Structured meshes can be used in the finite difference method (FDM).

Subsequently, referring to FIGS. 3 and 4 again, the simulation system 1 performs optical analysis (S100).

The optical analysis module 100 may receive the structured mesh generated by the interpolation module 200 (S003). The optical analysis module 100 may simulate a change in thermal energy due to light energy applied to the simulation area using the structured mesh.

Subsequently, the optical analysis module 100 may receive a refractive index (n) and an extinction coefficient (k) according to the intensity of light energy applied to the simulation area (S101). Specifically, the optical analysis module 100 may receive a refractive index (n) and an extinction coefficient (k) from the thermal analysis module 300 .

Subsequently, the optical analysis module 100 may perform finite difference method (FDM) using the structured mesh (S102). Specifically, the optical analysis module 100 may perform a finite difference time domain method (FDTD), which is one of finite difference methods (FDM), using the structured mesh.

[수학식 1a]

[Equation 1a]

[수학식 1b]

[Equation 1b]

[수학식 1c]

[Equation 1c]

[수학식 1d]

[Equation 1d]

[Equation 1e]

[Equation 1f]

[Equation 1g]

[Equation 1h]

[Equation 1i]

[Equation 1j]

,

,

,

)(

,

,

,

)

In some embodiments, the optical analysis module 100 may perform a simulation of the light energy applied to the simulation area through a finite difference time domain method (FDTD) using [Equation 1a] to [Equation 1j]. .

Subsequently, the optical analysis module 100 calculates heat energy absorbed in the simulation area due to light energy applied to the simulation area as a result of performing the finite difference time domain method (S103). Specifically, the thermal energy calculated by the optical analysis module 100 may include thermal energy generated due to light energy applied to the simulation area. The optical analysis module 100 may provide the calculated thermal energy to the thermal analysis module 300 .

Then, the simulation system 1 analyzes the temperature change and the phase change of the simulation area due to the generated thermal energy (S300).

Specifically, the thermal analysis module 300 determines whether the refractive index (n) and extinction coefficient (k) exceed threshold values using the unstructured mesh generated in step S002 (S301). If the refractive index n and extinction coefficient k exceed the threshold value, the thermal analysis module 300 provides the refractive index n and extinction coefficient k to the optical analysis module 100 .

Next, the thermal analysis module 300 analyzes the heat transfer phenomenon using the thermal energy calculated by the optical analysis module 100 in step S103 if the refractive index n and the extinction coefficient k do not exceed the threshold value. (S302). Specifically, the heat energy calculated by the optical analysis module 100 in step S103 may be regarded as the generated heat energy, and the calculation may be performed by applying the heat transfer equation.

[수학식 2]

[Equation 2]

In some embodiments, the thermal analysis module 300 may calculate the changed temperature of the simulation area using [Equation 2]. Specifically, the thermal analysis module 300 substitutes the thermal energy generated by the light energy applied to the simulation area, calculated by the optical analysis module 100, into the term G of [Equation 2] to obtain [Equation 2] ] can be calculated.

Subsequently, the thermal analysis module 300 updates the refractive index (n) and extinction coefficient (k) from the heat transfer phenomenon analysis in step S302 (S303). At this time, updating the refractive index (n) and the extinction coefficient (k) means to reflect the temperature change and phase change of the simulation area caused by the thermal energy generated in the simulation area.

Subsequently, the thermal analysis module 300 reports the update time of the refractive index (n) and extinction coefficient (k) as a time exceeding the time before updating the refractive index (n) and extinction coefficient (k) by a small amount of time (S304 ), it is determined whether the time has reached the set final time (S305). The final time can be set by the user using the simulation system.

When the simulated time reaches the set final time, the thermal analysis module 300 provides the silicon loss calculation module 400 with data on temperature change and phase change in the simulation area. If the simulated time does not reach the set time, the thermal analysis module 300 returns to step S301 and determines again whether the refractive index n and extinction coefficient k exceed the threshold value.

Referring to FIGS. 2, 3, 7, and 8, the silicon loss calculation module 400 simulates the temperature change and the phase change data (transient) of the simulation area calculated by the thermal analysis module 300. The diffusion of silicon in the region is updated (S401).

[수학식 3a]

[Equation 3a]

[수학식 3b]

[Equation 3b]

(D: diffusivity of silicon, E _a : activation energy of diffusion)

The silicon loss calculation module 400 calculates the amount of silicon diffused by the Kirkendall effect (S402). Specifically, the silicon loss calculation module 400 may calculate the amount of silicon diffused from the substrate of the simulation region to the metal region disposed on the substrate.

In some embodiments, the silicon loss calculation module 400 may calculate the amount of silicon diffused into the metal region using [Equation 3a] and [Equation 3b].

[수학식 4]

[Equation 4]

,

)(

,

)

The silicon loss amount calculation module 400 calculates the amount of silicon diffused from the substrate of the simulation region to the insulating region disposed on the substrate (S403). Specifically, the silicon loss calculation module 400 may calculate a silicon loss amount occurring at an interface between a substrate containing silicon and an insulating region containing nitride. In some embodiments, the silicon loss amount calculation module 400 may calculate the amount of silicon diffused into the insulating region using [Equation 4].

Next, the silicon loss amount calculation module 400 calculates the total silicon loss amount of the simulation area by summing the silicon loss amounts calculated in steps S402 and S403 (S404).

In FIG. 7 , the loss amount of silicon diffused into the metal region due to the Kirkendall effect is first calculated in step S402, and the loss amount of silicon diffused into the insulating region is calculated in step S403, but the embodiment is not limited thereto. For another example, a loss amount of silicon diffused into the insulating region may be first calculated, and then a loss amount of silicon diffused into the metal region due to the Kirkendall effect may be calculated. In addition, the loss amount of silicon diffused into the metal region and the loss amount of silicon diffused into the insulating region due to the Kirkendall effect can be calculated in parallel.

Referring again to FIGS. 2, 3 and 9a, the simulation system 1 analyzes the void in the simulation area (S500). Specifically, the void analysis module 500 of the simulation system 1 may analyze voids in the simulation area.

The void analysis module 500 uses the silicon loss amount calculated by the silicon loss amount calculation module 400 to determine whether the size of the void included in the simulation area exceeds a predetermined size (S501). At this time, the preset size can be set by a user using the simulation system 1 .

If the size of the void does not exceed the preset size, the void analysis module 500 counts the number of voids included in the simulation area (S502).

If the size of the void exceeds the predetermined size, the void analysis module 500 calculates a defect rate of the simulation area due to the void included in the simulation area (S503).

Even if voids included in the same simulation area are analyzed, objects to be analyzed in steps S502 and S503 may be different. For example, the size of the voids counted in step S502 and the size of the voids considered when calculating the defect rate in step S503 may be different.

Meanwhile, referring to FIG. 9B , in some embodiments, when the simulation system 1 analyzes voids in the simulation area, the location where the void is formed in the simulation area may be considered together.

When the size of the void exceeds the predetermined size, the simulation system 1 determines whether the position of the void included in the simulation area is detected (S503). Next, if the position of the void in the simulation area is not detected, the simulation system 1 roughly calculates the defect rate in the simulation area (S504). When the position of the void in the simulation area is detected, the simulation system 1 specifically calculates the defect rate in the simulation area (S505).

That is, when the location of the void in the simulation area can be detected, the calculated defect rate in the simulation area can be highly accurate. Also, the defect rate of the simulation area may vary according to the position of the void formed in the simulation area. For example, even if the same number of voids are formed in the same simulation area, if the positions where the voids are formed in the simulation area are different, the defect rate in the simulation area may be different.

10 to 14 are diagrams for explaining simulation of a simulation system according to some embodiments.

Referring to FIG. 10 , a temperature profile of a semiconductor device may vary according to the amount of light energy applied to the semiconductor device.

The simulation system 1 may calculate the temperature of the simulation area according to the magnitude of light energy applied to the simulation area. Specifically, as the light energy applied to the simulation area increases, the temperature profile of the simulation area generally rises. The profile of B having higher light energy than the profile of A having the smallest light energy is confirmed from the upper side. In addition, the profile of C having the highest light energy than the profile of B is confirmed further up. That is, when light energies of different magnitudes are applied to the same simulation area and measurements are taken at the same time, the temperature of the simulation area to which the large amount of light energy is applied is higher.

In addition, regardless of the magnitude of the light energy applied to the simulation area, the temperature of the simulation area sequentially increases and then decreases over time, maintains a constant temperature in the phase change section, and then decreases again. That is, when the temperature of the same simulation area is measured by varying the light energy level, the temperature change profile of the simulation area may have the same shape.

Referring to FIG. 11 , the simulation system 1 may calculate silicon loss according to an optical critical dimension (OCD) of a semiconductor device. Specifically, as described with reference to FIGS. 2 and 8 , the silicon loss amount calculation module 400 may calculate the silicon loss amount according to the OCD. In this case, OCD may represent the size of the semiconductor device including the simulation region. In the simulation region, silicon loss increases as OCD decreases.

In addition, when light energy of different magnitudes is applied to the simulation area having the same OCD, silicon loss in the simulation area increases as the light energy increases. The profile of the amount of silicon loss when light energy A with the lowest light energy and C with the highest light energy are applied increases sequentially.

Referring to FIG. 12 , the simulation system 1 may analyze voids in the simulation area according to the amount of silicon loss in the simulation area using an error function. Specifically, as described with reference to FIGS. 2 , 9A and 9B , the void analysis module 500 may analyze voids using an error function. In this case, the error function used by the void analysis module 500 may include an error function based on a normal distribution.

The first error function profile erf1 may represent a profile of the number of voids in the simulation area according to the amount of silicon loss in the simulation area. As the amount of silicon loss in the simulation region increases, the number of voids in the simulation region may increase.

The second error function profile erf2 may indicate a defect rate profile of the simulation region according to the amount of silicon loss in the simulation region. As the amount of silicon loss in the simulation region increases, the defect rate in the simulation region may increase.

In the same simulation area with the same amount of silicon loss, the profile of the number of voids in the simulation area may be higher than the profile of the defect rate in the simulation area. This may be due to the difference between voids considered when calculating the number of voids and voids considered when calculating the defect rate of the simulation area for the same simulation area.

Voids to be analyzed when calculating the number of voids in the simulation area may include voids that are smaller in size than voids to be analyzed when calculating the defect rate in the simulation area. Also, the number of voids in the simulation area may be calculated regardless of the location where the voids are generated in the simulation area.

Unlike this, when calculating the defect rate of the simulation area due to voids, only voids of a predetermined size or larger may be considered as voids to be analyzed. In addition, the defect rate of the simulation area due to voids may vary depending on the location where the void is generated in the simulation area. For example, even if voids of the same size are generated within the same simulation area, a higher defect rate may be calculated when a void is generated at a specific location.

Referring to FIG. 13 , the simulation system 1 may simulate the number of voids according to the OCD of the simulation area. The number of voids in the simulation region decreases as the OCD of the simulation region increases. In other words, as the OCD of the simulation area decreases, the number of voids in the simulation area may increase.

Referring to FIG. 14 , the simulation system 1 may calculate the defect rate of the simulation area according to the OCD of the simulation area by varying the light energy applied to the simulation area. As the amount of light energy applied to the simulation area with the same OCD increases, the defect rate of the simulation area increases. The defect rate increases sequentially when light energy A with the lowest light energy and C with the highest light energy are applied to the simulation area of the same OCD. In addition, the simulated area to which the same amount of light energy is applied decreases as the OCD increases.

As described with reference to FIGS. 11 to 14 , the simulation system 1 applies light energy to the simulation area (eg, laser treatment for annealing), heat energy generated in the simulation area, and temperature of the simulation area. , phase change, refractive index (n), extinction coefficient (k), physical and electrical property changes can be simulated. The simulation system 1 may calculate silicon loss in the simulation area by numerically or statistically analyzing changes in physical properties and electrical properties, and thus analyze voids in the simulation area.

15 is a diagram for explaining a simulation system according to some other embodiments. 16 is a flowchart illustrating operations of an optical analysis module and a thermal analysis module of a simulation system according to some embodiments. For convenience of description, the description will focus on differences from those described with reference to FIGS. 1 to 14 .

Referring to FIGS. 15 and 16 , the simulation system 2 may receive a simulation domain to be simulated from the optical analysis module 100 .

When the simulation system 2 starts a simulation operation, it loads a simulation area to be simulated (S001). Specifically, a simulation domain may be provided or input to the optical analysis module 100 .

Subsequently, the simulation system 2 divides the loaded simulation area into structured meshes (S002). For example, the simulation system 1 may divide the simulation area into hexahedron-shaped meshes. Unlike the simulation system 1 described with reference to FIG. 2 , the simulation system 2 may first generate a structured mesh rather than an unstructured mesh.

Subsequently, the simulation system 2 may interpolate the structured mesh generated in step S002 into an unstructured mesh (S200). Specifically, the interpolation module 200 may interpolate parameters stored in the structured mesh with parameters stored in the unstructured mesh. In some embodiments, the interpolation module 200 may linearly interpolate the structured mesh used in the optical analysis module 100 to the unstructured mesh used in the thermal analysis module 300 .

Then, as described with reference to FIG. 2 , the simulation system 2 may perform a simulation operation for the simulation region of the semiconductor device through steps S100 to S500 .

17 is an exemplary block diagram for describing a computing system including a simulation system according to some embodiments.

Referring to FIG. 17 , a computing system 1000 including a simulation system according to some embodiments includes a processor 1100, a memory 1300, an input/output device 1200, a storage device 1400, and a bus 1900. can include For example, the computing system 1000 may perform the simulation operation described above with reference to FIGS. 1 to 16 . In some embodiments, computing system 1000 may be implemented as an integrated device, and thus may be referred to as an integrated circuit design apparatus.

The computing system 1000 may be provided as a dedicated device for simulating a semiconductor device, but may also be a computer for driving various simulation tools or design tools. The computing system 1000 may be a fixed computing system such as a desktop computer, a workstation, or a server, or a portable computing system such as a laptop computer.

The processor 1100 may be configured to execute instructions for performing at least one of various operations for simulating a semiconductor device. The processor 1100 may communicate with the memory 1300 , the input/output device 1200 and the storage device 1400 through the bus 1900 . The processor 1100 may execute application programs loaded into the memory 1300 . For example, the processor 1100 may execute the simulation program 1310 stored in the memory 1300.

The simulation program 1310 may include instructions for the computing system 1000 to perform the simulation operation described with reference to FIGS. 1 to 16 . That is, the simulation program 1310 can simulate a change in physical properties of the semiconductor device that occurs as light energy is applied to the simulation region of the semiconductor device.

The memory 1300 may store a simulation program 1310 including instructions for performing a simulation of a semiconductor device. The memory 1300 may further store various tools such as simulation tools. The memory 1300 is a volatile memory such as static random access memory (SRAM) or dynamic RAM (DRAM), phase-change RAM (PRAM), magnetic RAM (MRAM), resistive RAM (ReRAM), ferroelectrics RAM (FRAM), It may be a non-volatile memory such as a flash memory.

The input/output device 1200 may control user input and output from user interface devices. For example, the input/output device 1200 may include an input device such as a keyboard, a mouse, or a touch pad to receive integrated circuit design data. For example, the input/output device 1200 may include an output device such as a display or a speaker to display simulation results.

The storage device 1400 may store a program such as the simulation program 1310 and a model parameter file 1320, and before the program is executed by the processor 1100, the program or at least a part thereof is stored in the storage device 1400. may be loaded into the memory 1300. The storage device 1400 may also store data to be processed by the processor 1100 or data processed by the processor 1100 . For example, the storage device 1400 stores data to be processed by the simulation program 1310, such as the amount of silicon loss in the simulation area, the number of voids in the simulation area, or the defect rate in the simulation area, generated by the simulation program 1310. characteristic data of a semiconductor device may be stored. The simulation program 1310 may extract electrical characteristics of a semiconductor device included in an integrated circuit based on model parameter information of a model parameter file stored in the storage device 1400 .

The storage device 1400 may include non-volatile memory such as Electrically Erasable Programmable Read-Only Memory (EEPROM), flash memory, PRAM, RRAM, MRAM, FRAM, or the like, or a memory card (MMC, eMMC, SD, MicroSD, etc.) , SSD (Solid State Drive), HDD (Hard Disk Drive), magnetic tape, optical disk, may include a storage medium such as a magnetic disk. Also, the storage device 1400 may be detachable from the computing system 1000 for integrated circuit design.

The bus 1900 may be a system bus for providing a network inside a computer system. Through the bus 1900, the processor 1100, the memory 1300, the input/output device 1200, and the storage device 1400 are electrically connected and may exchange data with each other. However, the configuration of the bus 1900 is not limited to the above description and may further include mediation means for efficient management.

Although the embodiments of the present invention have been described with reference to the accompanying drawings, the present invention is not limited to the above embodiments and can be manufactured in a variety of different forms, and those skilled in the art in the art to which the present invention belongs A person will understand that the present invention may be embodied in other specific forms without changing the technical spirit or essential features. Therefore, the embodiments described above should be understood as illustrative in all respects and not limiting.

100: optical analysis module 200: interpolation module
300: thermal analysis module 400: silicon loss calculation module
500: void analysis module

Claims (10)

processor; and
Including a storage for storing a simulation program executed by the processor,
The simulation program,
An optical analysis module that calculates thermal energy data generated by light energy provided to a simulation area using a finite difference method (FDM) method;
A thermal analysis module receiving the thermal energy data calculated by the optical analysis module and calculating temperature change data of the simulation area over time and phase change data of the simulation area using a finite element method (FEM) method. class,
And a silicon loss calculation module for calculating a silicon loss amount of the simulation region using the temperature change data and the phase change data calculated by the thermal analysis module. According to claim 1,
The FDM scheme used by the optical analysis module includes a finite difference time domain (FDTD) scheme. According to claim 1,
The simulation system further comprises an interpolation module that linearly interpolates the parameters used in the FDM used by the optical analysis module with the parameters used in the FEM used by the thermal analysis module. According to claim 1,
The simulation system further comprises a void analysis module for analyzing a void generated in the simulation region by applying the silicon loss amount calculated by the silicon loss amount calculation module to an error function. According to claim 4,
The void analysis module counts the number of voids generated in the simulation area, the simulation system. According to claim 4,
The void analysis module calculates a defect rate of the simulation area due to voids generated in the simulation area, the simulation system. According to claim 1,
The simulation area is
A substrate comprising silicon;
a metal region disposed on the substrate;
An insulating region disposed on the substrate;
The silicon loss amount includes a sum of an amount of silicon diffused from the substrate to the metal region and an amount of silicon diffused from the substrate to the insulating region. According to claim 1,
The simulation area is
A simulation system, including an asymmetric structure. processor; and
Including a storage for storing the simulation program,
When the simulation program runs,
the processor,
Divide the simulation region into unstructured meshes,
Calculate heat energy data generated by the light energy provided to the simulation area using the parameters of the unstructured mesh through the FDM method;
Interpolating the parameters of the unstructured mesh with the parameters of the structured mesh,
Based on the thermal energy data, calculating temperature change data of the simulation region over time and phase change data of the simulation region using parameters of the structured mesh through the FEM method,
A simulation system for calculating the amount of silicon loss in the simulation region using the temperature change data and the phase change data. A simulation program for calculating the number of voids occurring in the simulation area and the defect rate of the simulation area due to the voids,
The simulation program,
An optical analysis module that calculates thermal energy data generated by light energy provided to the simulation area using parameters stored in a tensor mesh through an FDM method;
An interpolation module for interpolating parameters stored in the hexahedral mesh with parameters stored in the tetrahedral mesh;
Through the FEM method, using the thermal energy data calculated by the optical analysis module and parameters stored in the tetrahedral mesh generated by the interpolation module, temperature change data over time of the simulation area and the simulation A thermal analysis module that calculates phase change data of the region;
a silicon loss calculation module for calculating a silicon loss amount of the simulation region using the temperature change data and the phase change data calculated by the thermal analysis module;
A computer-readable record comprising a void analysis module for calculating the number of voids generated in the simulation area and a defect rate of the simulation area due to the voids, using the silicon loss amount calculated from the silicon loss amount calculation module media.

Images