CN-122022036-A - Passivation process parameter determination and passivation process control method for discharge cavity

CN122022036ACN 122022036 ACN122022036 ACN 122022036ACN-122022036-A

Abstract

The application provides a passivation process parameter determination and a passivation process control method of a discharge cavity, which relate to the technical field of semiconductors, wherein the method comprises the steps of obtaining a plurality of groups of passivation experiment parameters of the discharge cavity, wherein the plurality of groups of passivation experiment parameters of the discharge cavity are experiment parameters obtained by adopting a plurality of groups of different passivation process parameters to carry out passivation treatment on the same type of discharge cavity, and the passivation experiment parameters of the discharge cavity comprise the passivation process parameters and predicted service life data corresponding to performance test data of the corresponding discharge cavity after the passivation treatment; and according to the passivation experimental parameters of the multiple groups of discharge chambers, determining the passivation technological parameter corresponding to the highest predicted service life data as the optimal passivation technological parameter of the same type of discharge chamber by adopting a pre-training model. The application improves the renewing efficiency of the discharge cavity and the reliability of the renewing cavity.

Inventors

ZHANG QI
FU YOUYIN
ZHU QINGNA

Assignees

新毅东科技股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260126

Claims (10)

1. A method for determining passivation process parameters of a discharge chamber, the method comprising: obtaining a plurality of groups of discharge cavity passivation experimental parameters, wherein the plurality of groups of discharge cavity passivation experimental parameters are experimental parameters obtained by adopting a plurality of groups of different passivation technological parameters to carry out passivation treatment on the same type of discharge cavity, and the discharge cavity passivation experimental parameters comprise the passivation technological parameters and predicted service life data corresponding to performance test data of the corresponding discharge cavity after passivation treatment; and according to a plurality of groups of passivation experimental parameters of the discharge cavity, determining the passivation technological parameter corresponding to the highest predicted service life data as the optimal passivation technological parameter of the same type of discharge cavity by adopting a pre-training model.
2. The method according to claim 1, wherein the pre-training model is a multiple regression model, and the determining, according to the multiple sets of passivation experimental parameters of the discharge chamber, the passivation process parameter corresponding to the highest predicted service life data as the optimal passivation process parameter of the similar discharge chamber by using the pre-training model includes: And according to a plurality of groups of passivation experimental parameters of the discharge cavities, adopting the multiple regression model to analyze, and determining the optimal passivation technological parameters of the similar discharge cavities.
3. The method according to claim 1, wherein the pre-training model is a machine learning model, and the determining, according to the sets of passivation experimental parameters of the discharge chambers, the passivation process parameter corresponding to the highest predicted service life data as the optimal passivation process parameter of the similar discharge chamber by using the pre-training model includes: and according to a plurality of groups of passivation experimental parameters of the discharge cavities, analyzing by adopting the machine learning model to obtain the optimal passivation technological parameters of the similar discharge cavities.
4. The method of claim 1, wherein the passivation process parameters include passivation temperature data, passivation pressure data, passivation gas mixture ratio data, discharge frequency data, discharge voltage data, gas agitation rate data; According to a plurality of groups of passivation experimental parameters of the discharge cavity, a pre-training model is adopted to determine the passivation technological parameter corresponding to the highest predicted service life data as the optimal passivation technological parameter of the same type of discharge cavity, and the method comprises the following steps: And determining a group of passivation process parameters corresponding to the highest predicted service life data as optimal passivation process parameters of the same type of discharge cavity by adopting the pre-training model according to a plurality of groups of passivation experiment parameters of the discharge cavity, wherein the optimal passivation process parameters comprise optimal passivation temperature data, optimal passivation pressure data, optimal passivation gas mixing proportion data, optimal discharge frequency data, optimal discharge voltage data and optimal gas stirring rate data.
5. The method according to claim 1, wherein the method further comprises: receiving optimal passivation technological parameters, current performance test data and corresponding predicted service life data sent by a control module; Generating a process report according to the optimal passivation process parameters, the current performance test data, the corresponding predicted service life data and a plurality of groups of passivation experiment parameters of the discharge cavity, wherein the process report comprises a process parameter curve, performance test data and optimization process information.
6. A method for controlling a passivation process of a discharge chamber, the method comprising: The method comprises the steps of obtaining optimal passivation process parameters of a target discharge cavity sent by an upper computer, wherein the optimal passivation process parameters are determined by the upper computer according to a passivation process parameter determination method of the discharge cavity; And controlling passivation process equipment to execute process operation on the target discharge cavity to be treated according to the optimal passivation process parameters.
7. The method of claim 6, wherein the optimal passivation process parameters include optimal passivation temperature data, optimal passivation pressure data, optimal passivation gas mixture ratio data, optimal discharge frequency data, optimal discharge voltage data, optimal gas agitation rate data; The passivation process equipment comprises a high-voltage power supply, a pulse converter, a cooling device, an air inlet device and a gas stirring controller, wherein the process operation of the passivation process equipment on the target discharge cavity to be treated is controlled according to the optimal passivation process parameters, and the method comprises the following steps: Determining the opening degree of a cooling regulating valve in the cooling equipment by adopting a preset feedforward coefficient and a first proportional-derivative integral algorithm according to the optimal passivation temperature data, so that the temperature data in the target discharge cavity is the optimal passivation temperature data; Determining the mixed gas charging proportion in the air inlet equipment according to the optimal passivation gas mixing proportion, so that the gas mixing proportion data in the target type discharge cavity is the optimal gas mixing proportion; Determining the opening degree of a slow charging regulating valve in the air inlet equipment by adopting a second proportional-differential integral algorithm according to the optimal passivation pressure data, so that the pressure data in the target discharge cavity is the optimal passivation pressure data; determining high-voltage control parameters, duty ratio and delay time of the pulse converter of the high-voltage power supply according to the optimal discharge frequency data and the optimal discharge voltage data, so that the discharge frequency data in the target type discharge cavity is the optimal discharge frequency data and the discharge voltage data in the target type discharge cavity is the optimal discharge voltage data; Determining the stirring rate of the gas stirring controller according to the optimal gas stirring rate data, so that the gas stirring rate data in the target type discharge cavity is the optimal gas stirring rate data; And controlling passivation process equipment to execute process operation on the target class discharge cavity to be processed according to the optimal passivation temperature data, the optimal passivation pressure data, the optimal passivation gas mixing proportion data, the optimal discharge frequency data, the optimal discharge voltage data and the optimal gas stirring rate data.
8. The method of claim 6, wherein the method further comprises: After the passivation process of the target class discharge cavity is executed, current performance test data and corresponding predicted service life data of the process operation executed by the target class discharge cavity are obtained; And sending the optimal passivation process parameters, the current performance test data and the corresponding predicted service life data to the upper computer, so that the upper computer updates the pre-training model according to the optimal passivation process parameters, the current performance test data and the corresponding predicted service life data.
9. The upper computer device is characterized by comprising a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the upper computer device is operated, the processor executes the machine-readable instructions to perform the steps of the passivation process parameter determining method of the discharge cavity according to any one of claims 1 to 5.
10. The passivation process control system is characterized by at least comprising a control module and passivation process equipment, wherein the control module is connected with the upper computer equipment and the passivation process equipment and is used for executing the steps of the discharge cavity passivation process control method according to any one of claims 6-8.

Description

Passivation process parameter determination and passivation process control method for discharge cavity Technical Field The application relates to the technical field of semiconductors, in particular to a passivation process parameter determination and a passivation process control method for a discharge cavity. Background In the high-tech fields of semiconductor manufacturing, plasma etching, thin film deposition, high-power lasers and the like, a discharge cavity is used as a key component for generating stable plasma or realizing gas discharge, and the internal surface state of the discharge cavity directly influences the process consistency, the operation stability and the service life of equipment. To suppress sputtering of the metal material of the inner wall of the chamber, reduce adhesion of reaction by-products, and improve insulating properties, passivation treatment is generally performed on the discharge chamber before the apparatus is started or after maintenance. Currently, passivation parameters of the discharge chamber are set according to an empirical formula or a fixed process template. Specifically, an operator typically selects a preset passivation procedure to execute according to a standard process flow manual provided by an equipment manufacturer, and performs surface treatment on the chamber wall under fixed flow, radio frequency power, treatment time and chamber pressure conditions using a specific gas. However, depending on manual experience or a mode of fixing a template, the method is difficult to adapt to different equipment ageing degrees, chamber pollution conditions and variable process requirements, so that the passivation effect is unstable, the problems of excessive passivation or insufficient passivation are easy to occur, and efficient, accurate and self-adaptive target passivation is difficult to realize. Disclosure of Invention The application aims to provide a passivation process parameter determination and a passivation process control method for a discharge cavity aiming at the defects in the prior art so as to improve the renovation efficiency of the discharge cavity and the reliability of a renovated cavity. In order to achieve the above purpose, the technical scheme adopted by the embodiment of the application is as follows: in a first aspect, an embodiment of the present application provides a method for determining passivation process parameters of a discharge chamber, where the method includes: obtaining a plurality of groups of discharge cavity passivation experimental parameters, wherein the plurality of groups of discharge cavity passivation experimental parameters are experimental parameters obtained by adopting a plurality of groups of different passivation technological parameters to carry out passivation treatment on the same type of discharge cavity, and the discharge cavity passivation experimental parameters comprise the passivation technological parameters and predicted service life data corresponding to performance test data of the corresponding discharge cavity after passivation treatment; and according to a plurality of groups of passivation experimental parameters of the discharge cavity, determining the passivation technological parameter corresponding to the highest predicted service life data as the optimal passivation technological parameter of the same type of discharge cavity by adopting a pre-training model. Optionally, the pre-training model is a multiple regression model, and according to a plurality of groups of passivation experimental parameters of the discharge cavity, determining a passivation process parameter corresponding to the highest predicted service life data as an optimal passivation process parameter of the similar discharge cavity by adopting the pre-training model includes: And according to a plurality of groups of passivation experimental parameters of the discharge cavities, adopting the multiple regression model to analyze, and determining the optimal passivation technological parameters of the similar discharge cavities. Optionally, the pre-training model is a machine learning model, and according to a plurality of groups of passivation experimental parameters of the discharge cavity, determining a passivation process parameter corresponding to the highest predicted service life data as an optimal passivation process parameter of the similar discharge cavity by adopting the pre-training model includes: and according to a plurality of groups of passivation experimental parameters of the discharge cavities, analyzing by adopting the machine learning model to obtain the optimal passivation technological parameters of the similar discharge cavities. Optionally, the passivation process parameters comprise passivation temperature data, passivation pressure data, passivation gas mixing proportion data, discharge frequency data, discharge voltage data and gas stirring rate data; According to a plurality of groups of passiva