JPH11307468A - Method and equipment of ion implantation simulation, and recording medium for recording ion implantation simulation program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To contract the scale of a parameter table, by obtaining a distribution rate of first and second distribution in a distribution function from a first parameter table, and obtaining a plurality of distribution parameters from a second parameter table on the basis of the distribution rate and implantation energy. SOLUTION: Target structure formed before ion implantation process and ion implantation condition are read (S1). Setting for calculating a surface layer is performed (S2). On the basis of a plurality of implantation parameters determining ion implantation condition, a first parameter table is referred, distribution rage is obtained from a first parameter table, and on the basis of the distribution rate and implantation energy, a plurality of distribution parameters are determined from a second parameter table (S3). On the basis of each distribution parameter, concentration of a multilayer film containing different kind of films is calculated (S4-S5).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention records an ion implantation simulation method, an ion implantation simulation apparatus, and an ion implantation simulation program based on an analytical model for obtaining an implantation distribution when an ion is implanted into a crystalline semiconductor substrate through an amorphous layer. It relates to a recording medium.

[0002]

2. Description of the Related Art As an ion implantation simulation method for obtaining an implantation distribution of atoms implanted into a substance, parameters such as an average depth and a standard deviation of the implantation distribution are prepared for each implantation condition, and the parameters are referred to. There is a method (analysis model method) of calculating a distribution function to be obtained. Other ion implantation simulation methods include the Monte Carlo simulation method and the Boltzmann transport equation method. Since the model is based on a physical picture, it can be applied under a wide range of ion implantation conditions. It is impractical to do

[0003] On the other hand, the analysis model is frequently used because the calculation time is short and the accuracy is certain if parameters are created based on actual measurement results.

Next, an injection distribution function and its parameter setting method will be described.

[0005] A function f (z) representing the concentration distribution of implanted atoms in the depth direction z is described in the literature [Tasch et al., J. Electrochem.
Soc., 136, 810 (1989)]], one Pearson function in an amorphous state, and two Pearson functions f _R (z) and f _{C in} a single crystal substance. It can be expressed as shown below by the combination of (z).

F (z) = rf _R (z) + (1−r) f _C (z) where f (z), f _R (z) and f _C (z) are integrals over the entire material section. The value is normalized so as to be the injection amount. f _R (z) and f _C (z) denote the distribution shape of randomly scattered particles and the distribution shape of particles reaching deeper by so-called “channeling” along a low-index crystal axis, respectively. Will be interpreted. r represents the distribution ratio between the two. The Pearson function is a solution P (x) of the following differential equation
It is.

[0007]

(Equation 4) In many cases, the parameters of f _R (z) and f _C (z) are often indicated by the following four parameters (subscripts are omitted in the formula). b ₀ , b ₁ , and b ₂ are uniquely determined. here,

(Equation 5) From the above equation, the injection concentration distribution f (z) in the crystal is r and f
_R, two sets of parameters _{f C (R p, σ,} γ, β) defined by a total of nine distribution parameters.

[0008] The likelihood of channeling varies greatly with the ion beam implantation angle, even at the same energy. In addition, since the crystal structure collapses during implantation due to ion implantation, it depends on the implantation amount, implantation speed, substrate temperature at the time of implantation, and the like. Furthermore, it largely depends on the thickness of the oxide film on the surface. For example, when an ion beam is incident in the <100> axis direction when there is no oxide film on the surface, many particles channel along the <100> axis. However, if there is an oxide film on the surface, the injected particles are scattered in the oxide film, and the probability that the particles incident on the crystal layer will be channeled along the <100> axis is reduced. Therefore, the above 9
The two distribution parameters are, of course, the implantation energy E,
It depends on the implantation parameters such as two implantation angles θ and 表 す representing the three-dimensional incident direction, the implantation amount Q, and the surface oxide film thickness T _OX .

Therefore, in many simulators, distribution parameter values (tables) are prepared on a matrix for several to several tens of points for each injection parameter, and the distribution parameters of the injection conditions to be simulated are several similar to those. (See, for example, the document “Morris et al., IEEE Trans.
micond.Manuf., 8,408 (1995). "). That is, the procedure for obtaining the ion implantation distribution parameter is as shown in FIG.
The distribution parameters are obtained using a parameter table having dimensions equal to the number of types of the injection parameters.

[0010]

(Equation 6) The interpolation method from the values in the parameter table shown in FIG.
For the sake of simplicity, it depends only on a certain implantation energy and implantation amount, and a case where the required conditions are implantation energy E and implantation amount Q will be described.

First, E = E ₁ , E ₂ , E ₃ ,..., E _NE-1 ,
E _NE , Q = Q ₁ , Q ₂ , Q ₃ ,..., Q _{NQ -1} , Q _NQ , the closest and large values E ₊ , Q ₊ and the closest and small value E
_-, Q _- find. Next, interpolation is performed in the order of implantation energy and implantation amount. Normally, the injection amount is logarithmic interpolation. That is,

(Equation 7) After that,

(Equation 8) Asking.

The problem here is that the prepared parameter table becomes huge. If there are five dependent injection parameters, the prepared table must be a five-dimensional matrix. Set each injection parameter to 1
Even if the number is 0, if the number of the injection parameters is 5, 100,000 and the number of the distribution parameters is 9, the number is 900,000. This means that after calculating the concentration distribution under 100,000 ion implantation conditions by Monte Carlo simulation or by SIMS analysis or the like, nine parameters must be prepared as numerical data in the program. This makes it difficult to handle table data, and at the same time, uses a very large amount of memory.

On the other hand, in a semiconductor manufacturing process, what is on the surface of a silicon crystal substrate to be ion-implanted is not limited to a single oxide film, but is often a laminate including a nitride film and a resist. It is practically impossible to prepare a comprehensive parameter table with such complicated conditions.
It was unrealistic.

[0014]

As described above,
In a conventional method for obtaining a distribution parameter of an injection distribution function in an analysis model for obtaining an implantation distribution when ions are implanted into a crystalline semiconductor substrate through an amorphous layer, a distribution parameter is previously determined by a combination of all implantation parameters. Is prepared as a parameter table,
By referring to this parameter table, a distribution parameter is determined from the injection parameter.

In such a method, when the number of injection parameters and distribution parameters increases, the size of the parameter table becomes large, the handling of the table becomes difficult, and the memory for storing the numerical data of the table becomes large. Had the disadvantage of becoming

On the other hand, when ions are implanted into a semiconductor substrate through various films stacked on the semiconductor substrate, it is necessary to prepare a parameter table in consideration of these various films. However, there are various types of films other than oxide films, and it is extremely impractical to create a parameter table covering all of them.

Accordingly, the present invention has been made in view of the above, and an object of the present invention is to reduce the scale of a parameter table for obtaining a distribution parameter from an implantation parameter, or to reduce the size of a semiconductor substrate through various films. The present invention provides an ion implantation simulation method, an ion implantation simulation apparatus, and a recording medium on which an ion implantation simulation program is recorded, which facilitates setting of distribution parameters when ions are implanted into a semiconductor device.

[0018]

In order to achieve the above object, according to the present invention, when ions are implanted into a single-crystal semiconductor substrate via an amorphous film, the ion-implantation of the semiconductor substrate is prevented. Is obtained as a superposition of a distribution function represented by the sum of a first distribution of particles randomly scattered in the semiconductor substrate and a second distribution of particles by channeling. The distribution parameter of
In an ion implantation simulation method that depends on an implantation parameter including at least an implantation energy and an amorphous film thickness, a first parameter table is referred to based on the plurality of implantation parameters that determine ion implantation conditions. A first step of obtaining a distribution rate of a first distribution and a second distribution in the distribution function from the first parameter table; and a distribution rate and an implantation energy obtained in the first step. A second step of referring to a second parameter table and obtaining the plurality of distribution parameters from the second parameter table.

According to a second aspect of the present invention, when ions are implanted into a single-crystal semiconductor substrate through an amorphous film, the distribution of implanted ions in the semiconductor substrate is randomly scattered in the semiconductor substrate. Simulation as a superposition of a distribution function represented by the sum of a first distribution of particles obtained and a second distribution of particles by channeling, wherein a plurality of distribution parameters of the distribution function are at least implantation energy and amorphous film. In an ion implantation simulation apparatus that depends on implantation parameters including thickness, a distribution ratio of a first distribution and a second distribution in the distribution function is obtained from the plurality of implantation parameters that determine ion implantation conditions. The plurality of distribution parameters are obtained from a first parameter table and the distribution rate and the implantation energy obtained in the first parameter table. A second parameter table for obtaining a meter, wherein a distribution ratio of a first distribution and a second distribution in the distribution function is obtained from the plurality of injection parameters with reference to the first parameter table; The method is characterized in that the plurality of distribution parameters are obtained from the distribution ratio and the implantation energy with reference to a parameter table to calculate the distribution function.

According to a third aspect of the present invention, when ions are implanted into a single crystalline semiconductor substrate through an amorphous film, the distribution of implanted ions in the semiconductor substrate is randomly scattered in the semiconductor substrate. The simulation apparatus simulates as a superposition of a distribution function represented by the sum of the first distribution of the particles obtained and the second distribution of the particles by channeling. In a recording medium on which an ion implantation simulation program is assumed to be dependent on an implantation parameter including a crystalline film thickness, a first parameter table is referred to based on the plurality of implantation parameters that determine ion implantation conditions. A first distribution and a second distribution in the distribution function from the first parameter table.
And a second parameter table based on the distribution rate and the implantation energy determined in the first step, and the plurality of parameters are referred to from the second parameter table. A program for causing the simulation apparatus to execute a second step of obtaining a distribution parameter is recorded.

According to a fourth aspect of the present invention, when ions are implanted into a single-crystal semiconductor substrate via the first amorphous film,
In the ion implantation simulation method for simulating the distribution of implanted ions in the semiconductor substrate by superimposing a distribution function having a plurality of distribution parameters, (in the first amorphous film, Film thickness)
× (average range of the second amorphous film) / (average range of the first amorphous film) The distribution parameters other than the average range are obtained.

According to a fifth aspect of the present invention, the thicknesses T1, T2,
When ions are implanted into a single-crystal semiconductor substrate through a multilayer film in which amorphous materials D1, D2,..., Dn of Tn are stacked, a distribution function having a plurality of distribution parameters is superimposed. In the ion implantation simulation method for simulating the distribution of implanted ions in the semiconductor substrate, the surface of the semiconductor substrate may have a surface thickness.

(Equation 9) The distribution parameter other than the average range in the semiconductor substrate is determined assuming that there is an amorphous substance A represented by the following formula.

According to a sixth aspect of the present invention, when ions are implanted into a single-crystal semiconductor substrate via the first amorphous film,
An ion implantation simulation apparatus that simulates an implanted ion distribution in the semiconductor substrate by superimposing a distribution function having a plurality of distribution parameters,
A calculating means for calculating (film thickness of the first amorphous film) × (average range of the second amorphous film) / (average range of the first amorphous film); Determining the distribution parameters other than the average range in the semiconductor substrate, assuming that there is a second amorphous film having a film thickness obtained by the arithmetic means in place of the first amorphous film. I do.

According to a seventh aspect of the present invention, the thicknesses T1, T2,
When ions are implanted into a single-crystal semiconductor substrate through a multilayer film in which amorphous materials D1, D2,..., Dn of Tn are stacked, a distribution function having a plurality of distribution parameters is superimposed. In an ion implantation simulation apparatus for simulating the distribution of implanted ions in the semiconductor substrate,

(Equation 10) And an amorphous material A having a thickness determined by the arithmetic means is provided on the surface of the semiconductor substrate.
And determining the distribution parameters other than the average range in the semiconductor substrate.

According to the present invention, when ions are implanted into a single-crystal semiconductor substrate through the first amorphous film,
In a recording medium on which an ion implantation simulation program for causing a simulation apparatus to simulate the distribution of implanted ions in the semiconductor substrate by superimposing distribution functions having a plurality of distribution parameters, (film thickness of first amorphous film) × (Average range of the second amorphous film)
/ (Average range of the first amorphous film); and a second amorphous film having the thickness obtained in the step is provided in place of the first amorphous film. A program for causing the simulation device to execute a step of obtaining the distribution parameter other than the average range in the semiconductor substrate is recorded.

According to a ninth aspect of the present invention, the thicknesses T1, T2,
When ions are implanted into a monocrystalline semiconductor substrate through a multilayer film in which amorphous materials D1, D2,..., Dn of Tn are stacked, a distribution function having a plurality of distribution parameters is superimposed. In a recording medium recording an ion implantation simulation program for causing a simulation device to simulate the distribution of implanted ions in the semiconductor substrate,

[Equation 11] And calculating the distribution parameters other than the average range in the semiconductor substrate, assuming that the surface of the semiconductor substrate has an amorphous substance A having a thickness determined in the step. A program to be executed by the simulation device is recorded.

[0027]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the drawings.

FIG. 1 is a flowchart showing a processing flow of an ion implantation simulation method according to an embodiment of the present invention.

In this embodiment, when ions are implanted into a single-crystal semiconductor substrate through an amorphous film, the distribution of the implanted ions in the semiconductor substrate is changed by the first randomly dispersed particles in the semiconductor substrate. And a distribution function represented by a sum of a second distribution of particles by channeling, for example, obtained by superimposing a Pearson function. A plurality of distribution parameters of the distribution function are obtained by determining at least the implantation energy and the amorphous film thickness. In the ion implantation simulation method that depends on the implantation parameters including the first parameter table, the first parameter table is referred to based on a plurality of implantation parameters that determine ion implantation conditions. Obtaining the distribution ratio of the second distribution and the distribution of the second distribution, and based on the distribution ratio and the implantation energy obtained in the previous step. There refers to the second parameter table, characterized by having a step of obtaining a plurality of distribution parameters from the second parameter table.

Further, the simulation apparatus for realizing such a process, when ions are implanted into a single crystalline semiconductor substrate through an amorphous film, changes the distribution of implanted ions in the semiconductor substrate. Is simulated as a superposition of a distribution function represented by a sum of a first distribution of particles randomly scattered and a second distribution of particles by channeling, and a plurality of distribution parameters of the distribution function are at least injection energy and non- In an ion implantation simulation apparatus, which depends on an implantation parameter including a crystalline film thickness, a distribution ratio of a first distribution and a second distribution in the distribution function is determined from a plurality of implantation parameters that determine ion implantation conditions. From the first parameter table for obtaining the distribution ratio and the implantation energy obtained from the first parameter table. Second determining a distribution parameter number
The distribution ratio of the first distribution and the second distribution in the distribution function is obtained from a plurality of injection parameters with reference to the first parameter table, and the distribution ratio is determined with reference to the second parameter table. It is characterized by calculating a plurality of distribution parameters from the injection energy and calculating the distribution function. For example, a CPU serving as a control center performing various processes for executing a program, and a keyboard, a mouse, a light pen, or a flexible It is configured to include a normal computer system including an input device such as a disk device, an external storage device such as a memory device and a disk device, and an output device such as a display device and a printer device. Note that the CPU includes an arithmetic unit that performs processing in a computer language or the like that describes the following processing, and a main storage unit that stores instructions for the processing.

A program for realizing the above-described ion implantation simulation method in the above-described simulation apparatus can be stored in a recording medium. This recording medium is read by a computer system, and the above-described ion implantation simulation method can be realized while controlling a computer by executing a program. Here, the recording medium includes a device that records a program and can be read by a computer, such as a memory device, a magnetic disk device, and an optical disk device.

The main feature of the present invention is that "determining distribution parameters from injection conditions" in the processing flow shown in FIG.
Although the portion of the process step S3, the operation through the entire simulation (100) of the silicon target injection energy E oxide film is formed of thickness T _OX on the crystal surface of the substrate, injection angle theta, [psi, A case where ions are implanted at an implantation amount Q will be described as one embodiment.

In FIG. 1, first, in step S1, “target...” Reads the target structure formed before the ion implantation step and the ion implantation conditions. Here, the target structure is that an oxide film having a thickness T _OX is formed on the surface of the (100) silicon crystal substrate,
What is necessary is just to be able to refer to the ion implantation conditions.
Thereafter, the injection concentration is calculated. In the analysis model, as in the present embodiment, it is more efficient to calculate for each layer, and it is more efficient to calculate from the surface side layer. Further, in the present embodiment, as a method of applying an analysis model to a multilayer film, for example, a document “H, Ryssel, J. Lorenz and K. Hoff
mann, Appl. Phys., A41, 201 (1986). ''
The nge scaling method is used.

Next, in the "outermost surface layer ..." of step S2, the setting for calculating the outermost surface layer is made. This operation is performed so that the calculation can be performed by the same procedure as that of the second layer on the surface and thereafter. The injection density Q1 for the first layer on the surface is set to the injection density Q, and the layer above the first layer on the surface (this In the embodiment, the effective thickness which does not actually exist but is set for convenience only needs to be set to zero.

Next, "from the injection condition ..." in step S3.
Sets the distribution parameters from the ion implantation conditions. Since the first layer is an amorphous oxide film, the distribution function is one.
It can be expressed by a Pearson function, and the distribution parameter is
R _P , σ, γ, and β. Further, since the distribution shape in the amorphous may depend only on the implantation energy E, the parameter table is small. Step S3 and subsequent steps are called again in this embodiment.

Next, in step S4, "with distribution parameters ...", the distribution parameters obtained in step S3 are determined.
Using the Pearson function, the concentration distribution in the first layer on the surface is calculated. At this time, the value obtained by integrating the concentration from the outermost surface of the first layer to the infinite depth with the same substance becomes equal to the injection amount.

(Equation 12) Is standardized as follows.

Next, in the "lower layer ..." of step S5,
Since there is a lower layer, in step S6 “below the lower layer...”, The amount of implantation into the first layer calculated from the amount of implantation into the entire target is subtracted.

[0038]

(Equation 13) Further, the effective thickness Teff1 of the first layer is calculated. The effective thickness is a dimensionless quantity obtained by dividing the thickness of the layer by the Rp (the above-mentioned average value) of the injection distribution in the layer, and Teff1 is obtained as Teff1 = thickness of the first layer / Rp in the first layer. . Thereafter, the second layer is calculated, and the distribution parameter is determined from the injection conditions again in “injection conditions...” In step S3. Since the second layer is crystalline silicon, the distribution parameters are implantation energy E, implantation angle θ,
求 め る, the injection amount Q, and the surface oxide film thickness T _OX are determined with reference to the thickness. The parameter table in the decision scheme according to the prior art is shown in FIG. 3, but in the present embodiment, the parameter table shown in FIG. 2 is used.

First, in the first parameter table PT1 shown in FIG. 2, five injection condition parameters E, θ,
Distribution ratio r of two Pearson functions based on ψ, Q, T _OX
Ask for. The distribution ratio r is determined, and then the other distribution parameters R _pR , σ _R , γ _R , β _pC , σ _C , γ _C , β _C are the distribution energies obtained from the implantation energy E and the first parameter table PT1. It is determined from the second parameter table PT2 based on the rate r. That is, five injection condition parameters E, θ,
The distribution parameter depending on, Q, T _OX is two Pears
The other distribution parameters R _pR , σ _R , γ _R , β _pC , σ _C , γ _C , and β _C are assumed to depend on the implantation energy E and the distribution ratio r, with only r determining the distribution ratio of the on function. . It has been confirmed by simulation that even if such a dependency is adopted, the difference in the distribution parameters is not so large as to cause a practical problem compared to the conventional dependency using the parameter table shown in FIG. I have. In addition,
The interpolation method from the table values is the same as the conventional one.

Next, in “distribution parameters...” In step S3, the distribution function f2 (z) based on the distribution parameters previously determined with reference to the parameter tables PT1 and PT2.
Is used to calculate the concentration in the second layer. At this time,

F2 (z) = rf2R (z) + (1−r) f2C (z) Since z is a coordinate measurement when the surface is not an oxide film but silicon, coordinate conversion is performed. Then, it is obtained from the following equation.

[0041]

F2 (z) = rf2R (z + Teff1-
1) × R _pR first layer) + (1-r) f2C (z + (te
FF1-1) × but only 2 layers in R _pC) This example of the second layer, if there is a calculation of the third layer, in place of Teff1, effective thickness of the first layer Teff1
And the sum Teff of the effective thickness Teff2 of the second layer. Subsequently, the injection amount was set to Q2 which was obtained by subtracting the injection amount to the first layer from the injection amount to the entire target.

(Equation 16) It is standardized so that Next, "lower layer ..." in step S5 is "end" in step S7 because only two layers are used in this example.

In the above-described embodiment, the parameter table necessary for obtaining the distribution parameter from the injection condition parameter is similar to that described in the prior art.
If ten injection condition parameters are prepared and ten injection condition parameters are used to express the distribution ratio r dependency, the number of elements becomes 100,800. This is about one-ninth of the prior art, the memory used is drastically reduced, and the handling and maintenance of the table can be performed very easily.

Next, one embodiment of the invention according to claim 4, 5, 6, 7, 8 or 9 will be described.

This embodiment is applied to a case where a film other than an oxide film, for example, a nitride film or the like is formed on the surface of a semiconductor substrate, or a case where a multilayer film of an oxide film and a nitride film is laminated. It is.

The algorithm of the whole simulation is
The feature of this embodiment is the same as that of the embodiment described above. When the distribution ratio r of the distribution parameter is determined by the oxide film thickness T _ox , the thickness of the film other than the oxide film is determined by using the following equation. _Is converted to a film thickness T _OX ′ equivalent to an oxide film.

[0046]

Tox '= Thickness of applicable film × Rp in oxide film /
Rp in applicable film Further, even if the above method is extended, even when a multilayer film of an oxide film and a nitride film is formed on a semiconductor substrate by lamination,
The following formula can be used to convert a nitride film into a film thickness equivalent to an oxide film.

[0047]

(Equation 18) These conversion processes are performed in the processing steps shown in step S3 in the flowchart shown in FIG. 1, and are executed by the calculation means included in the CPU in the simulation apparatus.

In the above embodiment, a resist film functioning as a resist is also included, and the film may function as a film functioning as an insulating film other than the oxide film.

In this embodiment, even when a film not registered in the parameter table is formed on the semiconductor substrate, the film is distributed from the parameter table by converting the film into the registered film. Parameters can be easily obtained. In other words, it is not necessary to prepare a parameter table that can be applied to other films such as a nitride film only by creating a parameter table based on the implantation parameters of the oxide film, for example. Thereby, the same effect as in the above-described embodiment can be obtained. In addition, even when a multilayer film including different types of films is stacked on a semiconductor substrate, it is possible to cope with the above in the same manner as described above, and the same effect can be obtained.

In all of the above embodiments, the distribution function is not limited to the Pearson function, but has a Gaussian distribution,
The same effect can be obtained by using the distribution function of the joint half-Gaussian distribution or the superposition of the distribution function of the Gaussian distribution.

[0051]

As described above, according to the first, second or third aspect of the present invention, the distribution ratio of the distribution function is obtained from the injection parameters with reference to the first parameter table.
Since the distribution parameters are obtained based on the distribution ratio and the implantation energy with reference to the second parameter table, the parameter table is reduced in size as compared with the related art, and the memory for storing the parameter table is reduced in size.
Further, management and management of the parameter table are facilitated.

According to the invention as defined in claim 4, 5, 6, 7, 8, or 9, the film thickness of the film formed on the semiconductor substrate is converted to the film thickness of another type of film and the distribution parameter is calculated. Is obtained, the distribution parameter can be easily obtained even for a film not in the parameter table or a multilayer film including films of different types.

[Brief description of the drawings]

FIG. 1 is a flowchart showing a processing flow of an ion implantation simulation method according to an embodiment of the present invention.

FIG. 2 is a diagram showing a first parameter table and a second parameter table.

FIG. 3 is a diagram showing a conventional parameter table.

[Explanation of symbols]

 PT1 first parameter table PT2 second parameter table

Claims (9)

[Claims] When ions are implanted into a single-crystal semiconductor substrate through an amorphous film, the distribution of the implanted ions in the semiconductor substrate is changed by a first randomly dispersed particle in the semiconductor substrate. Determined as a superposition of a distribution function represented by the sum of the distribution and the second distribution of particles by channeling,
In the ion implantation simulation method, it is assumed that the plurality of distribution parameters of the distribution function depend on implantation parameters including at least implantation energy and an amorphous film thickness. A first parameter table based on the first parameter table, and calculating a distribution ratio of a first distribution and a second distribution in the distribution function from the first parameter table; A second step of referring to a second parameter table based on the obtained distribution ratio and the implantation energy, and obtaining the plurality of distribution parameters from the second parameter table. 2. When ions are implanted into a single-crystal semiconductor substrate through an amorphous film, the distribution of the implanted ions in the semiconductor substrate is changed by first scattering by particles randomly scattered in the semiconductor substrate. The simulation is performed as a superposition of a distribution function represented by a sum of a distribution and a second distribution of particles by channeling, and a plurality of distribution parameters of the distribution function include an implantation parameter including at least an implantation energy and an amorphous film thickness. A first parameter table for obtaining a distribution ratio of a first distribution and a second distribution in the distribution function from the plurality of implantation parameters for determining ion implantation conditions; A second step of obtaining the plurality of distribution parameters from the distribution ratio and the implantation energy obtained in the first parameter table; Comprising a parameter table, determining a distribution ratio of a first distribution and a second distribution in the distribution function from the plurality of injection parameters with reference to the first parameter table, and referring to the second parameter table. An ion implantation simulation apparatus, wherein the plurality of distribution parameters are obtained from a distribution ratio and an implantation energy to calculate the distribution function. 3. When ions are implanted into a single-crystal semiconductor substrate through an amorphous film, the distribution of the implanted ions in the semiconductor substrate is changed by a first randomly dispersed particle in the semiconductor substrate. The simulation is simulated as a superposition of a distribution function represented by the sum of the distribution and the second distribution of the particles by channeling, and a plurality of distribution parameters of the distribution function include at least the implantation energy and the amorphous film thickness. A recording medium storing an ion implantation simulation program which is assumed to be dependent on an implantation parameter including: a first parameter table based on the plurality of implantation parameters for determining ion implantation conditions; A first step of obtaining a distribution ratio of a first distribution and a second distribution in the distribution function from a table Referring to a second parameter table based on the distribution ratio and the implantation energy determined in the first step, and determining the plurality of distribution parameters from the second parameter table by the simulation apparatus. A recording medium on which an ion implantation simulation program is recorded. 4. When ions are implanted into a single-crystal semiconductor substrate through a first amorphous film, the distribution of the implanted ions in the semiconductor substrate is superimposed by superposing distribution functions having a plurality of distribution parameters. In the ion implantation simulation method for simulating, in place of the first amorphous film, (film thickness of first amorphous film) × (average range of second amorphous film) / (first amorphous film) Ion distribution simulation, wherein the distribution parameters other than the average range in the semiconductor substrate are obtained assuming that there is a second amorphous film having a film thickness obtained by (average range of the amorphous film). Method. 5. When ions are implanted into a single crystalline semiconductor substrate through a multilayer film in which amorphous materials D1, D2,..., Dn having thicknesses T1, T2,. In the ion implantation simulation method for simulating the distribution of implanted ions in the semiconductor substrate by superimposing a distribution function having the following distribution parameters, the surface of the semiconductor substrate has a surface thickness of Wherein the distribution parameter other than the average range in the semiconductor substrate is determined assuming that there is an amorphous substance A represented by the following formula: 6. When ions are implanted into a single-crystal semiconductor substrate through a first amorphous film, the distribution of implanted ions in the semiconductor substrate is superimposed by superimposing distribution functions having a plurality of distribution parameters. In the ion implantation simulation apparatus to be simulated, (the thickness of the first amorphous film) × (the average range of the second amorphous film) / (the average range of the first amorphous film) is calculated. Computing means for performing the above operation, except that there is a second amorphous film having a thickness obtained by the computing means in place of the first amorphous film. An ion implantation simulation apparatus for determining a distribution parameter. 7. When ions are implanted into a single-crystal semiconductor substrate through a multilayer film in which amorphous materials D1, D2,..., Dn having thicknesses T1, T2,. An ion implantation simulation apparatus for simulating the distribution of implanted ions in the semiconductor substrate by superimposing distribution functions having the following distribution parameters: Calculating means for calculating the distribution parameters other than the average range in the semiconductor substrate, assuming that the surface of the semiconductor substrate has an amorphous substance A having a thickness determined by the calculating means. An ion implantation simulation apparatus characterized in that: 8. When ions are implanted into a single-crystal semiconductor substrate through a first amorphous film, the distribution of the implanted ions in the semiconductor substrate is superimposed by superposing distribution functions having a plurality of distribution parameters. In a recording medium on which an ion implantation simulation program to be simulated by a simulation apparatus is recorded, (film thickness of first amorphous film) × (average range of second amorphous film) / (first amorphous film) Calculating the average range of the film, and assuming that there is a second amorphous film having the thickness obtained in the step in place of the first amorphous film, A recording medium recording an ion implantation simulation program, wherein a program for causing the simulation apparatus to execute the step of obtaining the distribution parameter other than the range is recorded. . 9. When ions are implanted into a single-crystal semiconductor substrate through a multilayer film in which amorphous materials D1, D2,..., Dn having thicknesses T1, T2,. In a recording medium storing an ion implantation simulation program for causing a simulation device to simulate the distribution of implanted ions in the semiconductor substrate by superimposing distribution functions having the following distribution parameters: Calculating the distribution parameters other than the average range in the semiconductor substrate, assuming that the surface of the semiconductor substrate has an amorphous substance A having a thickness determined in the step. A recording medium on which an ion implantation simulation program is recorded, wherein a program to be executed by a simulation device is recorded.