CN111534804A - Magnetron sputtering process parameter optimization method based on improved grey correlation model - Google Patents

Magnetron sputtering process parameter optimization method based on improved grey correlation model Download PDF

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CN111534804A
CN111534804A CN202010549140.XA CN202010549140A CN111534804A CN 111534804 A CN111534804 A CN 111534804A CN 202010549140 A CN202010549140 A CN 202010549140A CN 111534804 A CN111534804 A CN 111534804A
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magnetron sputtering
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潘俊杰
陈功
侯东东
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Changzhou Lemeng Pressure Vessel Co ltd
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    • C—CHEMISTRY; METALLURGY
    • C23—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; CHEMICAL SURFACE TREATMENT; DIFFUSION TREATMENT OF METALLIC MATERIAL; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL; INHIBITING CORROSION OF METALLIC MATERIAL OR INCRUSTATION IN GENERAL
    • C23C—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; SURFACE TREATMENT OF METALLIC MATERIAL BY DIFFUSION INTO THE SURFACE, BY CHEMICAL CONVERSION OR SUBSTITUTION; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL
    • C23C14/00—Coating by vacuum evaporation, by sputtering or by ion implantation of the coating forming material
    • C23C14/22—Coating by vacuum evaporation, by sputtering or by ion implantation of the coating forming material characterised by the process of coating
    • C23C14/34—Sputtering
    • C23C14/35—Sputtering by application of a magnetic field, e.g. magnetron sputtering
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Abstract

The invention discloses a magnetron sputtering process parameter optimization method based on an improved grey correlation model, which is characterized in that the improved grey correlation model is adopted to obtain the influence of magnetron sputtering process parameters on the performance of a film layer, and the influence of different magnetron sputtering processes on the thickness and the optical transmittance of the film layer is obtained through analyzing the relation among various performance indexes and the structure of a coating film tissue, so that the magnetron sputtering process parameters are optimized. Aiming at the defects of analysis of the traditional grey correlation model, the invention considers the weight of absolute position difference and the weight of change rate difference between data, constructs and improves the grey correlation model, obtains the optimal parameter value through experiments, and can more accurately provide the degree of the influence of the process parameter on the film thickness and the transmittance compared with the traditional method, thereby realizing the optimization of the magnetron sputtering process parameter.

Description

Magnetron sputtering process parameter optimization method based on improved grey correlation model
Technical Field
The invention relates to the technical field of magnetron sputtering processes, in particular to a magnetron sputtering process parameter optimization method based on an improved ash correlation model.
Background
In recent years, magnesium alloys have attracted attention due to their excellent properties, and have been widely used in the fields of land vehicles, aerospace, 3C products, and the like. However, magnesium alloys have poor hardness and corrosion resistance properties, which severely limit their wide application. Improving the surface properties of magnesium alloys is an important issue in the development and research of magnesium alloys. Among the various surface technologies mainly adopted at present, magnetron sputtering is considered to be one of the best methods for preparing surface coatings due to the advantages of good film quality, high density and purity, environmental friendliness and the like.
The magnetron sputtering technology has made an important progress in the research of the sputtering mechanism on the surface of the solid target, the influence of unbalanced magnetron sputtering and pulse magnetron sputtering on the deposited coating, and so on, and at present, many researchers at home and abroad research the influence of the process parameters on different sub-coatings and develop a series of deposition process processes according to different materials.
However, data in the process of the magnetron sputtering technology is limited, the gray scale of the existing data is large, and due to human reasons, many data appear several times and greatly fall, and a typical distribution rule does not exist. Therefore, it is often difficult to work with mathematical statistics. The grey correlation analysis method proposed by the grey system theory is not limited by the limitations, and the analysis method makes up for the defects caused by the system analysis by using a mathematical statistics method. The grey correlation analysis can extract main factors, main characteristics and differences among the factors influencing the system from incomplete information, and find main characteristics and main influencing factors. However, the existing grey correlation analysis method only emphasizes the absolute position difference between sequences, does not consider the difference of the change rate between the sequences, and has certain defects.
Disclosure of Invention
The invention provides a magnetron sputtering process parameter optimization method based on an improved grey correlation model, which is used for researching the influence of a magnetron sputtering main process on the performance of a film layer, analyzing the relation condition possibly existing among various performance indexes, and analyzing the reason that the magnetron sputtering main process influences the thickness and the optical transmittance of the film layer through analyzing the structure of a coated film.
In order to achieve the purpose, the invention adopts the technical scheme that:
the magnetron sputtering process parameter optimization method based on the improved grey correlation model comprises the steps of obtaining the influence of magnetron sputtering process parameters on the performance of a film layer by adopting the improved grey correlation model, obtaining the influence of different magnetron sputtering processes on the thickness and the optical transmittance of the film layer through analyzing the relation among performance indexes and the structure of a coated film, and further optimizing the magnetron sputtering process parameters; the method comprises the following steps:
step 1: constructing the following grey correlation degree improvement model:
Figure BDA0002541873880000021
step 2: constructing magnetron sputtering technological parameters;
the magnetron sputtering process parameters comprise a background vacuum pressure value in the cavity, a volume flow of argon, a volume flow of oxygen, an air pressure value, a voltage value, a current value, a cathode temperature, a substrate temperature, a process temperature, a deposition time and a pre-sputtering time, and corresponding output values of different process parameters after magnetron sputtering are the transmittance and the thickness of the film;
and step 3: changing lambda1、λ2、λ3The values seek the optimal model parameters.
Further, the step 1 comprises:
step 1.1: improved ash correlation coefficient (x)0(k),xi(k))：
Figure BDA0002541873880000022
In the formula, λ1,λ2,…λk-1> 0 and lambda1+λ2+…+λk-1＝1，λ1As a weight for absolute position differences, λ2,…λk-1ξ is the absolute position difference discrimination coefficient, η, as the weight of the rate of change difference1,…ηk-2Respectively, first order to k-2 order rate of changeAn identification coefficient of the difference;
Δx0i(k)＝x0(k)-xi(k) is a sequence x0(k) And xi(k) Absolute position difference at point k;
Figure BDA0002541873880000023
the difference in the variation of the first order sequence, in turn,
Figure BDA0002541873880000024
difference in variance for k-2 order sequences;
Figure BDA0002541873880000025
the rate of change of the first order sequence, in turn,
Figure BDA0002541873880000026
is the rate of change of the k-2 order sequence; the above-mentioned i is 0,1,2, …, n, k is 2,3, …, m.
Step 1.2: and calculating the grey correlation degree to obtain a grey correlation improved model.
Further, the parameter value is ξ1Taken as 0.5, η2,…ηk-2＝0。λ1+λ2+λ31 and λ4＝λ5＝…λk-10,1, … 11, 1, … N; at this time:
Figure BDA0002541873880000031
Figure BDA0002541873880000032
furthermore, an improved grey correlation model is constructed by considering the weight of the absolute position difference and the weight of the change rate difference between the data, and the optimal parameter value is obtained through experiments.
Further, the step 2 includes the influence of the magnetron sputtering process on the transmittance and the influence of the magnetron sputtering process on the film thickness.
The invention has the following effective effects:
the invention overcomes the defects of integrity and normalization of the existing grey correlation analysis method and provides an improved grey correlation method for integrating absolute position difference and change rate difference. Aiming at the technology of preparing the aluminum nitride film on the surface of the magnesium alloy substrate by the magnetron sputtering technology, the invention respectively researches the influence of the main magnetron sputtering technology on the film performance by adopting an improved grey correlation analysis method, analyzes the possible relation condition among various performance indexes, and mainly analyzes the reason that the main magnetron sputtering technology influences the film hardness and the corrosion resistance by analyzing the film organization structure.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
Aiming at the problems that the existing grey correlation analysis method only emphasizes the absolute position difference between sequences, does not consider the difference of change rates between the sequences and has poor optimization effect, the invention provides a magnetron sputtering process parameter optimization method based on an improved grey correlation model as shown in figure 1.
The method of the invention is concretely as follows:
step 1: construction of improved grey correlation model
Step 1.1: improved ash correlation coefficient (x)0(k),xi(k))：
Figure BDA0002541873880000033
In the formula, λ1,λ2,…λk-1> 0 and lambda1+λ2+…+λk-1＝1，λ1As a weight for absolute position differences, λ2,…λk-1Weight for rate of change difference ξ is absolute position difference discrimination coefficient, η1,…ηk-2Respectively, the identification coefficients of the first order to k-2 order rate of change differences. Typically, these several parameters may be taken to be 0.5.
Δx0i(k)＝x0(k)-xi(k) Is a sequence x0(k) And xi(k) Absolute position difference at point k.
Figure BDA0002541873880000041
The difference in the variation of the first order sequence, in turn,
Figure BDA0002541873880000042
the difference in the variance of the k-2 order sequence.
Figure BDA0002541873880000043
The rate of change of the first order sequence, in turn,
Figure BDA0002541873880000044
is the rate of change of the k-2 order sequence. The above-mentioned i is 0,1,2, …, n, k is 2,3, …, m.
|Δx0i(k) The smaller the | is, the more closely the two sequence curves are at the moment.
Figure BDA0002541873880000045
The smaller the curve is, the more the development speeds of the two sequence curves at the moment tend to be the same; while
Figure BDA0002541873880000046
The smaller the rate of change of the development rate, the more the same the rate of change of the development rate.
Step 1.2: calculating the grey correlation degree:
Figure BDA0002541873880000047
then the model is a gray association refined model.
Step 2: establishing magnetron sputtering process parameters
Establishing magnetron sputtering process parameters, namely the process parameters influencing the transmittance and the film thickness are as follows:
the vacuum pressure value of the inner background of the cavity, the volume flow of argon, the volume flow of oxygen, the pressure value of air pressure, the voltage value, the current value, the cathode temperature, the substrate temperature, the process temperature, the deposition time and the pre-sputtering time are 11 items. The corresponding output values of 11 different technological parameters after magnetron sputtering are 2 items of transmittance and film thickness of the film. There are N groups of the above data.
The method aims to research the influence of different processes on the transmittance and the thickness of the film and find out the main process parameter factors influencing the transmittance and the thickness of the film.
By analysis, the following parameters are taken in ξ1Taken as 0.5, η2,…ηk-2＝0。λ1+λ2+λ31 and λ4＝λ5＝…λk-10,1, … 11(11 process parameters), 1, … N (N groups of data) satisfy the calculation requirements. At this time
Figure BDA0002541873880000051
Figure BDA0002541873880000052
Step 2.1 study of the influence of the magnetron sputtering process on transmittance
x0(k) A transmission N }is a transmission 1, a transmission 2
x1(k) A background vacuum pressure value N }, · a background vacuum pressure value 1, a background vacuum pressure value 2
x2(k) A volume flow of argon N }
x3(k) The volumetric flow rate N of oxygen is }
x4(k) An atmospheric pressure value N }is set to { atmospheric pressure value 1
x5(k) A voltage value N }is set to { voltage value 1
x6(k) Current value N }is set to { current value 1
x7(k) A cathode temperature N }is set to be equal to a cathode temperature 1
x8(k) Substrate temperature N }
x9(k) The temperature of the process is 1,... Process temperature N }
x10(k) Deposition time N }
x11(k) A pre-sputtering time N }is set to { pre-sputtering time 1
Step 2.2 study of the influence of the magnetron sputtering process on the film thickness
x0(k) Thin film thickness N }, { thin film thickness 1, thin film thickness 2
xi(k) I 1, … 11 same as step 2.1
And step 3: changing lambda1、λ2、λ3Value-seeking optimal model parameters
For seeking optimum parameters for improving the model, respectively changing λ1、λ2、λ3The experimental results are as follows:
TABLE 1 influence of some Process parameters on film thickness
Figure BDA0002541873880000053
Figure BDA0002541873880000061
TABLE 2 influence of some process parameters on transmittance
Figure BDA0002541873880000062
The numbers 1 to 7 represent the influence degree of the process parameters on the film thickness and the transmittance from high to low (i.e. the sequence of the coefficients for improving the gray correlation model from large to small), and the analysis is carried out by the following tables 1 and 2, wherein the lambda is1＝0.9λ2＝0.1λ3When 0, the other parameters are ranked for correct influence degree and the original grey correlation model analysis is wrong.
In conclusion, aiming at the defects of the analysis of the traditional grey correlation model, the invention considers the weight of the absolute position difference and the weight of the change rate difference between data, constructs the improved grey correlation model, obtains the optimal parameter value through experiments, can more accurately provide the degree of the influence of the process parameter on the film thickness and the transmittance compared with the traditional method, and further realizes the optimization of the magnetron sputtering process parameter.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the present invention. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (5)

1. The magnetron sputtering process parameter optimization method based on the improved grey correlation model is characterized by comprising the following steps: the method comprises the following steps of obtaining the influence of magnetron sputtering process parameters on the performance of a film layer by adopting an improved grey correlation model, obtaining the influence of different magnetron sputtering processes on the thickness and the optical transmittance of the film layer by analyzing the relation among various performance indexes and the structure of a coated film tissue, and further optimizing the magnetron sputtering process parameters; the method comprises the following steps:
step 1: constructing the following grey correlation degree improvement model:
Figure FDA0002541873870000011
step 2: constructing magnetron sputtering technological parameters;
the magnetron sputtering process parameters comprise a background vacuum pressure value in the cavity, a volume flow of argon, a volume flow of oxygen, an air pressure value, a voltage value, a current value, a cathode temperature, a substrate temperature, a process temperature, a deposition time and a pre-sputtering time, and corresponding output values of different process parameters after magnetron sputtering are the transmittance and the thickness of the film;
and step 3: changing lambda1、λ2、λ3The values seek the optimal model parameters.
2. The magnetron sputtering process parameter optimization method based on the improved ash correlation model according to claim 1, characterized in that: the step 1 comprises the following steps:
step 1.1: improved ash correlation coefficient (x)0(k),xi(k))：
Figure FDA0002541873870000012
In the formula, λ1,λ2,…λk-1> 0 and lambda1+λ2+…+λk-1＝1，λ1As a weight for absolute position differences, λ2,…λk-1ξ is the absolute position difference discrimination coefficient, η, as the weight of the rate of change difference1,…ηk-2Identification coefficients of the first order to k-2 order rate of change difference respectively;
Δx0i(k)＝x0(k)-xi(k) is a sequence x0(k) And xi(k) Absolute position difference at point k;
Figure FDA0002541873870000013
the difference in the variation of the first order sequence, in turn,
Figure FDA0002541873870000014
difference in variance for k-2 order sequences;
Figure FDA0002541873870000015
the rate of change of the first order sequence, in turn,
Figure FDA0002541873870000016
is the rate of change of the k-2 order sequence; the above-mentioned i is 0,1,2, …, n, k is 2,3, …, m.
Step 1.2: and calculating the grey correlation degree to obtain a grey correlation improved model.
3. The magnetron sputtering process parameter optimization method based on the improved gray correlation model as claimed in claim 2, wherein the parameter value is ξ1Taken as 0.5, η2,…ηk-2＝0。λ1+λ2+λ31 and λ4＝λ5＝…λk-10,1, … 11, 1, … N; at this time:
Figure FDA0002541873870000021
Figure FDA0002541873870000022
4. the magnetron sputtering process parameter optimization method based on the improved ash correlation model according to claim 1, characterized in that:
and (4) considering the weight of the absolute position difference and the weight of the change rate difference between the data, constructing an improved grey correlation model, and obtaining the optimal parameter value through experiments.
5. The magnetron sputtering process parameter optimization method based on the improved ash correlation model according to claim 1, characterized in that: and the step 2 comprises the influence of the magnetron sputtering process on the transmittance and the influence of the magnetron sputtering process on the thickness of the film.
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CN114237322A (en) * 2021-12-21 2022-03-25 杭州千岛湖啤酒有限公司 Draught beer barrel outer wall heat sensing monitoring and rejecting system and method
CN115449771A (en) * 2022-09-21 2022-12-09 华中科技大学 Mold coating generation method, apparatus, device, storage medium, and program product
CN116641035A (en) * 2023-07-26 2023-08-25 南京诺源医疗器械有限公司 Film coating method for laparoscopic optical piece

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