JP2000331952A - Method and device for ion implantation - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method and a device for implantation wherein, when simulation for impurity at ion implantation is performed with an analytic function, an simulation which is appropriate even at a low energy is realized, with dose-loss considered, for appropriate ion implantation. SOLUTION: An analytic function is used to simulate an impurity concentration at ion-implantation, and ion is implanted based on it. Here, the relation between a dose amount and the amount of ion to be implanted is acquired for each implantation energy, and this relation ship is substituted for the analytic function. Related to an ion implantation device, a simulator which uses the analytic function to simulate an impurity concentration at ion implantation, and an ion implanter which implants ion based on that, are provided. The simulator substitutes a function of the relationship between the dose amount and the amount of ion which is implanted for each implantation energy for the analytic function for simulation.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] The present invention relates to an ion implantation method and an ion implantation apparatus. INDUSTRIAL APPLICABILITY The present invention can be used for an ion implantation technique in a semiconductor manufacturing process or the like. According to the present invention, an ion implantation technique considering a dose loss phenomenon is provided.

[0002]

2. Description of the Related Art In a semiconductor manufacturing process and the like, a technique of introducing impurity ions into a silicon substrate or the like as a material by an ion implantation method is widely used in order to form a desired impurity distribution in silicon or the like.

[0003] With the recent miniaturization of devices, there is an increasing demand for limiting the distribution of impurities to the surface as close as possible. For this reason, impurities are brought closer to the surface,
There is a need for a technique for distributing at higher concentrations. As a result, a reduction in ion implantation energy is required, and the implantation energy has been significantly reduced.

However, a phenomenon is observed in which, due to a decrease in the implantation energy, the ion implantation amount actually implanted into the ion-implanted material becomes smaller than the dose amount (total amount of impurity implantation given, also referred to as dose). this is,
It is considered that the ion beam is bounced off the surface of the ion implantation material such as a silicon substrate, and only a part of the ion beam to be implanted enters the ion implantation material (substrate). This phenomenon is called dose loss.

On the other hand, for ion implantation, a simulation technique relating to the impurity concentration is known (Japanese Patent Application No. 7-245275). As such a simulation technique, typically, a calculation method by a Monte Carlo method, an analysis function (Pearson function, Gaussian function, etc.)
There is a calculation method using. However, in the prior art, it is difficult to perform a simulation in consideration of the dose loss phenomenon. In particular, in the case of a technique of performing a simulation using a model using an analysis function, it is difficult to capture a dose loss phenomenon. For example, Dual Pearson (Dual
A simulation using an analysis model based on a (Piason) distribution is known. In this model, the impurity distribution is created by multiplying the normalized dual Pearson distribution by the dose (total impurity). Therefore, it is difficult to immediately take in the above-mentioned dose loss phenomenon.

Hereinafter, the problem of the above-described dose loss will be further described with reference to the drawings. The following description is based on an example in which the ion-implanted material is a silicon substrate.

It is known that the impurity implanted by the ion implantation process has a distorted bell-shaped distribution as indicated by reference numeral 6 in FIG. 6 in the silicon substrate. FIG.
Medium, vertical axis is impurity concentration, horizontal axis is substrate (ion implanted material)
Of depth. The reference numeral 5 at the depth = 0 indicates the surface of the substrate (here, silicon) (the same applies to FIGS. 7 and 8).

It is known that the position of the peak of the bell-shaped distribution is substantially proportional to the energy of ion implantation. On the other hand, recent miniaturization of elements has required that the distribution of impurities in the silicon substrate be limited to the vicinity of the surface as shown by reference numeral 7 in FIG.

The simplest way to realize such a distribution shape is to lower the implantation energy of impurity ions. As shown in FIG. 8, when the implantation energy indicated by the reference numeral 81 is low, the impurity distribution is limited to the surface, and when the implantation energy is increased, the position of the peak of the impurity distribution shifts to the inside as indicated by the reference numeral 82. This is because when the implantation energy is high, the impurity distribution comes to a deep position as indicated by reference numeral 83.

However, there is an inevitable problem in reducing the implantation energy of the impurity ions.
The reason is that the implantation energy decreases and the coherence deteriorates, so that it cannot enter the substrate from the silicon surface,
This is a problem of dose loss that only a part of the dose is implanted. The above-described problem of the dose loss becomes important when the implantation energy of the impurity ions is reduced as described above.

[0011] FIGS. 3 to 5, respectively BF ₂ 0.
A sample implanted into a silicon substrate at an implantation energy of 5 keV, 1.0 keV, and 2.5 keV at a dose of 4.0E14 was measured by SIMS (Secondary I).
on Mass Spectrometry) shows the measured data and the corresponding simulation results. The symbol II in each figure is the result of a simulation by a conventional method (which will be described in detail later). When this is compared with the actual SIMS measurement data indicated by reference numeral III, the measurement data III and the simulation result II when the implantation energy is 2.5 keV (FIG. 5) show a good agreement. However, the injection energy is 1.0 ke
In the case of V (FIG. 4) and in the case of 0.5 keV (FIG. 3), the measured data clearly shows the phenomenon of dose loss.

[0012]

SUMMARY OF THE INVENTION The present invention has been made in view of the above-mentioned problems of the prior art, and has been made in consideration of a dose loss in performing a simulation relating to an impurity concentration in ion implantation using an analysis function. Therefore, an object of the present invention is to provide an ion implantation method and an ion implantation apparatus capable of performing appropriate simulation even in a region where ion implantation energy is low, and achieving proper ion implantation based on the simulation.

[0013]

According to the ion implantation method of the present invention, a simulation relating to the impurity concentration in the ion implantation is performed using an analysis function, and the ion implantation is performed based on the simulation result. The relationship between the dose of implantation and the amount of ion implantation to be implanted into the ion-implanted material is obtained for each implantation energy, and the relationship is introduced as a coefficient into the above analysis function to perform a simulation. is there.

An ion implantation apparatus according to the present invention includes a simulator for simulating the concentration of impurities in ion implantation using an analysis function, and an ion implanter for performing ion implantation based on the simulation result. In the apparatus, the simulator simulates the relationship between the dose of ion implantation and the amount of ion implantation to be implanted into the ion-implanted material by introducing coefficients obtained for each implantation energy into the analysis function. It is characterized by being.

According to the present invention, the effect of the dose loss is expressed by a coefficient, and the simulation is performed by introducing the effect into the analysis function. Therefore, the simulation in consideration of the dose loss can be performed, and thus, appropriate ion implantation can be realized. In particular, in the case of ion implantation at a low implantation energy required in recent years, the effect of the dose loss is large, so that it can be said that such ion implantation is particularly effective.

[0016]

Embodiments of the present invention will be further described below. Needless to say, the present invention is not limited to the illustrated embodiment.

As described above, as described with reference to FIGS. 3 to 5, the effect of the dose loss has a relationship with the implantation energy. Therefore, here, in order to estimate such a dose loss, the set dose is multiplied by a coefficient and reduced, and the measured dose is observed in accordance with the actually measured data. This coefficient is obtained for each implantation energy by comparing the measured data. Ratio in Table 1 below corresponds to this coefficient.

[0018]

[Table 1]

That is, as shown in Table 1 above, when the implantation energy is 2.5 keV, the dose (Samp in the table)
If le Oose is 4.0E14, the simulation value (Simulation Dose) may also be 4.0E14, so the coefficient (indicated by Ratio) is 1.0. However, the injection energy is 1.0k
In the case of eV, the dose amount (Sample Dos in the table)
If e) is 4.0E14, the simulation value needs to be 3.0E14 and the coefficient is 0.75 in order to match the measured value as described above. Similarly, when the implantation energy is 0.5 keV, the coefficient is about 0.523.
9

Simulation results obtained by introducing the coefficients as parameters of the analysis function are shown by reference numeral I in FIGS. As shown in FIG. 3, the simulation result I in which the present invention is implemented is in good agreement with the actually measured value III even when the implantation energy is as low as 0.5 keV. As shown in FIGS. 4 and 5, when the implantation energy is 1.0 keV,
In the case of eV, the degree of matching is even higher. Specifically, the simulation result I is obtained by introducing the above-mentioned coefficient as one of the parameters of the analysis function described below, and emphasizing the impurity distribution in the vicinity of the surface so as to avoid discontinuity and mismatch. Each parameter is set and a function formula is determined and derived.

That is, in this embodiment, a function obtained by combining the first and second functions at a predetermined ratio is used as the analysis function. In particular, a dual Pearson function obtained by combining the first and second Pearson functions at a predetermined ratio is used.

As described above, in order to capture the effect of the dose loss, a simulation may be performed by multiplying the set dose by a coefficient corresponding to the implantation energy. On the other hand, in the ion implantation simulation, the impurity distribution after implantation is expressed by an analysis function such as a dual Pearson distribution, and parameters of the analysis function according to the ion implantation conditions such as implantation energy and dose are tabulated. Accordingly, the table is read out from the table and interpolated as necessary. Therefore, in this embodiment, when the dual Pearson function is used, the table is loaded with the above coefficients to carry out.

The Pearson distribution is a general term for a distribution function p (x) satisfying the following differential equation (1), and has four parameters (a, c0, c1, c2). These parameters are associated with physical quantities in the following relational expressions (2) to (6).

[0024]

(Equation 1)

This distribution function is widely used in a simulation of an ion implantation process in a semiconductor device manufacturing process.

In actual ion implantation, a distribution having two peaks, relatively shallow and deep, is obtained in the profile.
A dual Pearson distribution combining two Pearson distributions is used. This is also used in this example.

The dual Pearson distribution is defined by the following equation (7) using two Pearson distributions f (x) and g (x).

[0028]

(Equation 2)

Usually, a Pearson distribution f (x) having a peak at a shallow position is defined as a first Pearson distribution, and a Pearson distribution g (x) having a peak at a deep position is defined as a first Pearson distribution.

The dual Pearson distribution has four parameters for each of the two Pearson distributions and a total α of the ratio α of the two functions.
Requires two parameters. As an example of a table describing these parameters, a part of a table used for TSUPREM-4, which is one of simulation software, is shown in FIG.
Shown in This corresponds to the parameter table of the analytic function used to obtain the simulation result of the prior art, which is indicated by reference numeral II in FIGS.

This table is based on the dual Pearson model. One injection energy corresponds to three rows of data and includes nine parameters of the dual Pearson model.

That is, the reading of this table is based on the RP,
In DRP, GAMMA, BETA, LDRP, 6.0000E-04, 5.1000E-04, 1.3 in the fourth row
40, 5.000, 1.0600E-02 and 2
RP2, DRP2, GAMMA2, BETA2 on the line
In LDRP2, 2.50000003,1.0 in the fourth row
000E-03, 0.000, 3.000, 1.060
0E-02 corresponds to the FRACTION (ND
OSE times. ) Corresponds to 0.9950 in the sixth row. Hereinafter, the same applies to each item.

In the present embodiment, the above table shows
The dose coefficient according to the implantation energy described above is added. An example is shown in FIG. This is the DOSE-DIM (see the third line) in the conventional example shown in FIG.
The above coefficient is taken in. 1-3
Regarding reading of data corresponding to each item in the row, the same items as those in FIG. 2 are the same as described above. As shown in FIG. 1, when the ion implantation energy is 0.5 keV, the parameter of the newly introduced DOSE-DIM is 0.5239 as indicated by reference numeral 1. When the ion implantation energy is 1.0 keV, it is 0.75 as indicated by reference numeral 2. 2.5 ion implantation energy
At the time of keV, as indicated by reference numeral 3, it is 1.0. When the ion implantation energy is 5.0 keV, it is 1.0 as indicated by reference numeral 3. This corresponds to the coefficients shown in Table 1 above.

As described above, by using the newly added dose coefficient, it is possible to incorporate the effect of the dose loss in the low energy ion implantation into the simulation.

As described above, regarding the phenomenon of the dose loss that cannot be reproduced by the conventional ion implantation simulation, in the present embodiment, the effect of the dose loss is expressed by a coefficient, and parameters for that are shown in a table of ion implantation parameters. The addition enables simulation taking into account the dose loss.

In the present embodiment, appropriate ion implantation can be realized based on the above. That is, here
As described above, a simulator for performing a simulation regarding the impurity concentration in the ion implantation using the analysis function is provided. Based on the simulation result,
Preferable results were obtained by ion implantation with an ion implanter. In particular, in order to obtain a miniaturized element, in order to limit the distribution of impurities to very close to the surface, when performing ion implantation with significantly reduced ion implantation energy,
Good results were obtained.

[0037]

According to the ion implantation method and the ion implantation apparatus of the present invention, it is possible to realize a simulation in consideration of a dose loss in performing a simulation relating to an impurity concentration in an ion implantation using an analysis function. Simulation can be performed even in a region where the ion implantation is low, and the effect that proper ion implantation can be achieved based on the simulation can be obtained.

[Brief description of the drawings]

FIG. 1 is a diagram for explaining an embodiment of the present invention.

FIG. 2 is a diagram for explaining a conventional technique.

FIG. 3 is a diagram showing a comparison between a simulation result of application of the present invention when the ion implantation energy is 0.5 keV, a conventional simulation result, and actual measurement data.

FIG. 4 is a diagram showing a comparison between a simulation result of applying the present invention when ion implantation energy is 1.0 keV, a conventional simulation result, and actual measurement data.

FIG. 5 is a diagram showing a comparison between a simulation result of applying the present invention, a conventional simulation result, and actual measurement data when the ion implantation energy is 2.5 keV.

FIG. 6 is a diagram for explaining a conventional technique.

FIG. 7 is a diagram for explaining a conventional technique.

FIG. 8 is a diagram for explaining a conventional technique.

[Explanation of symbols]

1 coefficient (in the case of ion implantation energy of 0.5 keV), 2 coefficient (ion implantation energy of 1.0 keV)
V), 3... Coefficient (ion implantation energy 2.
(In the case of 5 keV), 3 ... coefficient (in the case of ion implantation energy of 5.0 keV).

Claims (4)

[Claims] 1. An ion implantation method for simulating the concentration of an impurity in ion implantation using an analytical function, and performing ion implantation based on the simulation result. A method for obtaining a relationship with the ion implantation amount for each implantation energy, and introducing the relationship as a coefficient into the analysis function to perform a simulation. 2. The ion implantation method according to claim 1, wherein the analysis function is a function obtained by combining the first and second functions at a predetermined ratio. 3. The ion implantation method according to claim 2, wherein the analysis function is a dual Pearson function obtained by combining the first and second Pearson functions at a predetermined ratio. 4. An ion implantation apparatus comprising: a simulator for performing a simulation relating to an impurity concentration in ion implantation using an analysis function; and an ion implantation machine for performing ion implantation based on the simulation result. A relationship between the dose amount of the ion implanted material to be implanted into the ion implanted material is obtained by introducing a coefficient obtained for each implantation energy into the analysis function, and performing a simulation. Infusion device.