Processing Method, Device, System and Computer Equipment for Semiconductor Thin Film

Abstract

The above-mentioned processing method, device, system and computer equipment for semiconductor thin films determine a first processing model of a reference semiconductor thin film based on a preset thickness; wherein, the substrate wafer of the reference semiconductor thin film is a silicon wafer; determine a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film; wherein, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer; determine a target processing model based on the first processing model and the second processing model; control a chemical vapor deposition process equipment to process the target semiconductor thin film based on the target processing model. The above method obtains a target processing model based on the relationship between the first processing model and the second processing model. Taking the first processing model with high accuracy as a benchmark, the obtained target processing model can improve the accuracy of processing semiconductor thin films with silicon carbide as the substrate wafer and shorten the equipment debugging time, saving the debugging cost.

Description

Technical Field

[0001] This application relates to the field of semiconductor thin film research and development, and particularly to a processing method, device, system, and computer device for semiconductor thin films. Background Art

[0002] When processing semiconductor thin films (such as silicon dioxide thin films, polysilicon thin films, silicon nitride thin films, etc.) using low-pressure chemical vapor deposition (LPCVD) process equipment, the method of processing semiconductor thin films on silicon wafers is already very accurate and mature. Moreover, the film thickness data and cross-section measurement data of the thin films obtained by ellipsometer testing are highly accurate, and the test results are also highly reliable.

[0003] However, in the prior art, using the low-pressure chemical vapor deposition (LPCVD) process equipment and processing method of silicon wafers, for semiconductor thin films processed and prepared on other materials, especially the currently widely used silicon carbide (SiC) material, there is a large difference in the thickness of the semiconductor thin films obtained compared to those on silicon wafers, and the processing accuracy of the semiconductor thin films is low. This is mainly due to the differences in the LPCVD process results caused by the differences in the thermal conductivities of various materials. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a processing method, device, system, and computer device for semiconductor thin films.

[0005] In a first aspect, this application provides a processing method for a semiconductor thin film, the method comprising:

[0006] Determining a first processing model of a reference semiconductor thin film based on a preset thickness;

[0007] Wherein, the substrate wafer of the reference semiconductor thin film is a silicon wafer;

[0008] Determining a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film;

[0009] Wherein, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer;

[0010] Determining a target processing model based on the first processing model and the second processing model;

[0011] Controlling a chemical vapor deposition process equipment to process the target semiconductor thin film based on the target processing model.

[0012] In one of the embodiments, the determining a first processing model of a reference semiconductor thin film based on a preset thickness includes:

[0013] Controlling a chemical vapor deposition process device to process a reference semiconductor thin film based on a preset thickness;

[0014] Obtaining the film refractive index and film thickness of the reference semiconductor thin film;

[0015] Determining a first processing model of the reference semiconductor thin film based on the film refractive index and film thickness of the reference semiconductor thin film.

[0016] In one embodiment, after determining the first processing model of the reference semiconductor thin film based on the preset thickness, it includes:

[0017] Obtaining a first preset number of substrate wafers loaded in the chemical vapor deposition process device for the target semiconductor thin film based on the historical debugging data of the reference semiconductor thin film.

[0018] In one embodiment, the determining the second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film includes:

[0019] Controlling a chemical vapor deposition process device to process the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers;

[0020] Obtaining the film refractive index and film thickness of the target semiconductor thin film;

[0021] Determining the second processing model of the target semiconductor thin film based on the film refractive index and film thickness of the target semiconductor thin film.

[0022] In one embodiment, after determining the second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film, it includes:

[0023] Determining a third processing model based on the preset thickness and a second preset number of substrate wafers;

[0024] The determining the target processing model based on the first processing model and the second processing model includes:

[0025] Determining the target processing model based on the first processing model, the second processing model, and the third processing model.

[0026] In one embodiment, after determining the third processing model based on the preset thickness and the second preset number of substrate wafers, it includes:

[0027] If both the second processing model and the third processing model do not meet the preset conditions, then determining a fourth processing model based on a third preset number of substrate wafers;

[0028] Determining the target processing model based on the first processing model, the second processing model, and the third processing model includes:

[0029] Determining the target processing model based on the first processing model, the second processing model, the third processing model, and the fourth processing model.

[0030] In a second aspect, the present application further provides a processing system for a semiconductor thin film, including a controller and a low-pressure chemical vapor deposition process device. The controller is configured to determine a first processing model of a reference semiconductor thin film based on a preset thickness; wherein, the substrate of the reference semiconductor thin film is a silicon wafer; determining a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film; wherein, the substrate of the target semiconductor thin film is a silicon carbide wafer; determining the target processing model based on the first processing model and the second processing model;

[0031] The controller is further configured to send a control instruction to the low-pressure chemical vapor deposition process device;

[0032] The low-pressure chemical vapor deposition process device is configured to receive the control instruction sent by the controller and process the target semiconductor thin film based on the target processing model.

[0033] In a third aspect, the present application further provides a processing device for a semiconductor thin film. The device includes:

[0034] A first processing model determination module, configured to determine a first processing model of a reference semiconductor thin film based on a preset thickness;

[0035] wherein, the substrate of the reference semiconductor thin film is a silicon wafer;

[0036] A second processing model determination module, configured to determine a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film;

[0037] wherein, the substrate of the target semiconductor thin film is a silicon carbide wafer;

[0038] A target processing model determination module, configured to determine the target processing model based on the first processing model and the second processing model;

[0039] A processing module, configured to control a chemical vapor deposition process device to process the target semiconductor thin film based on the target processing model.

[0040] In a fourth aspect, the present application further provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the following steps are implemented:

[0041] Determine a first processing model of a reference semiconductor thin film based on a preset thickness;

[0042] Wherein, the substrate wafer of the reference semiconductor thin film is a silicon wafer;

[0043] Determine a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film;

[0044] Wherein, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer;

[0045] Determine a target processing model based on the first processing model and the second processing model;

[0046] Control a chemical vapor deposition process device to process the target semiconductor thin film based on the target processing model.

[0047] In a fifth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium has a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented:

[0048] Determine a first processing model of a reference semiconductor thin film based on a preset thickness;

[0049] Wherein, the substrate wafer of the reference semiconductor thin film is a silicon wafer;

[0050] Determine a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film;

[0051] Wherein, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer;

[0052] Determine a target processing model based on the first processing model and the second processing model;

[0053] Control a chemical vapor deposition process device to process the target semiconductor thin film based on the target processing model.

[0054] The above-mentioned processing method, device, system and computer equipment for semiconductor thin films determine a first processing model of a reference semiconductor thin film based on a preset thickness; wherein, the substrate wafer of the reference semiconductor thin film is a silicon wafer; determine a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film; wherein, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer; determine a target processing model based on the first processing model and the second processing model; control a chemical vapor deposition process device to process the target semiconductor thin film based on the target processing model. In the above-mentioned processing method for semiconductor thin films, after obtaining the first processing model of the reference semiconductor thin film and the second processing model of the target semiconductor thin film, based on the relationship between the first processing model and the second processing model, taking the first processing model as a benchmark, the target processing model is obtained. Since the first processing model is determined based on the reference semiconductor thin film, the accuracy and credibility of the model are relatively high. Taking the first processing model as a benchmark, the obtained target processing model can improve the accuracy of processing and preparing semiconductor thin films with silicon carbide as the substrate wafer. Also, because the cost of the silicon wafer substrate is low and the process of processing semiconductor thin films with a silicon wafer as the substrate is mature, based on the silicon wafer debugging, not only can the debugging cost be reduced, but also the debugging time can be shortened. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present application or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0056] Figure 1 It is an application environment diagram of the processing method for semiconductor thin films in an embodiment;

[0057] Figure 2 It is a schematic flowchart of the processing method for semiconductor thin films according to an embodiment of the present invention;

[0058] Figure 3 It is a schematic distribution diagram of the substrate wafer and the baffle loaded on the susceptor in an embodiment of the present invention;

[0059] Figure 4 It is a schematic flowchart of the implementation of the processing method for semiconductor thin films according to an embodiment of the present invention;

[0060] Figure 5 It is a schematic structural diagram of the processing system for semiconductor thin films according to an embodiment of the present invention;

[0061] Figure 6Structural block diagram of a semiconductor thin film processing apparatus in an embodiment of the present invention;

[0062] Figure 7 Internal structure diagram of a computer device in an embodiment of the present invention. Detailed implementation manners

[0063] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0064] Semiconductor technology is one of the most complex technologies in the development of human science and technology. Due to the high precision of semiconductor devices, semiconductor thin films are usually prepared and processed using film deposition technology. That is, the deposits on the wafer surface will form a continuous and airtight thin film on the wafer surface. In the semiconductor industry, the thin film deposition process is a common and important process. There are many technologies for depositing thin films on a wafer substrate, which are mainly divided into chemical processes and physical processes. Chemical processes mainly refer to chemical vapor deposition, including atmospheric pressure chemical vapor deposition (APCVD), low pressure chemical vapor deposition (LPCVD), plasma enhanced chemical vapor deposition (PECVD), high density plasma chemical vapor deposition (HDPCVD), electroplating, etc. Physical processes mainly include physical vapor deposition, evaporation, spin coating, etc.

[0065] Low pressure chemical vapor deposition (LPCVD) refers to a chemical vapor deposition reaction in which the operating pressure during the deposition reaction of reaction gases in a reactor is reduced to less than about 133 Pa. When the pressure drops to less than about 133 Pa, the mean free path of molecules and the gas diffusion coefficient increase, accelerating the mass transfer rate of gaseous reactants and by-products, and increasing the reaction rate of forming a thin film. Even when the wafer spacing between parallel and vertically placed wafer substrates is reduced to 5-10 mm, the chemical reaction rate on the surface of the wafer substrate is still relatively high, which creates conditions for upright and densely packed wafer loading and can increase the wafer loading capacity per batch of the process equipment.

[0066] In the prior art, the technical method of processing and preparing semiconductor thin films based on silicon wafer substrates using low pressure chemical vapor deposition (LPCVD) process equipment has been very accurate and mature. However, the processing system for preparing semiconductor thin films based on silicon carbide wafer substrates using low pressure chemical vapor deposition (LPCVD) process equipment is imperfect, resulting in low accuracy in the processing and preparation of semiconductor thin films with silicon carbide as the wafer substrate, directly affecting the R & D efficiency. Therefore, it is very important to improve the accuracy of semiconductor thin film processing.

[0067] The semiconductor thin film processing method provided by the embodiments of the present application can be applied to, for example Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or can be placed on the cloud or other network servers. The user makes the current behavior on the terminal 102, and the terminal 102 transmits the current behavior data to the server 104. The server 104 determines the first processing model of the reference semiconductor thin film based on the preset thickness; wherein, the substrate of the reference semiconductor thin film is a silicon wafer; based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film, determine the second processing model of the target semiconductor thin film; wherein, the substrate of the target semiconductor thin film is a silicon carbide wafer; determine the target processing model based on the first processing model and the second processing model; control the chemical vapor deposition process equipment to process the target semiconductor thin film based on the target processing model. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0068] In one embodiment, as Figure 2 shown, a method for processing a semiconductor thin film is provided. In this embodiment, this method is exemplified by being applied to a terminal. It can be understood that this method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is realized through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0069] Step S201, determine the first processing model of the reference semiconductor thin film based on the preset thickness; wherein, the substrate of the reference semiconductor thin film is a silicon wafer.

[0070] Specifically, the preset thickness refers to the thickness of the thin film that is preset to be generated during the processing and preparation of the semiconductor thin film. The setting of the preset thickness can be realized by adjusting the parameters of the semiconductor thin film processing equipment.

[0071] Specifically, the first processing model can be recognized and run by the semiconductor thin film processing equipment, that is, the semiconductor thin film processing equipment processes the reactants according to the first processing model, and after the processing is completed, a reference semiconductor thin film with a preset thickness is obtained.

[0072] It can be understood that the substrate of the reference semiconductor thin film is a silicon wafer. Therefore, the first processing model is a processing model of a semiconductor thin film with a silicon substrate obtained based on the semiconductor thin film processing equipment and the preset thickness.

[0073] Step S202: Determine a second processing model for the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film; wherein, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer.

[0074] Specifically, the target semiconductor thin film includes a semiconductor thin film processed and prepared using silicon carbide as the substrate wafer.

[0075] Specifically, the substrate wafer (substrate) can directly enter the wafer manufacturing process to produce semiconductor devices, or can undergo epitaxial process processing to produce epitaxial wafers. It is not difficult to understand that the number of substrate wafers is the same as the number of product wafers, and the product is the target semiconductor thin film. Therefore, the first preset number of substrate wafers is also the number of target semiconductor thin films to be presetly generated.

[0076] Specifically, the dummy wafer is also called a fake wafer. During experiments, both the dummy wafer and the substrate wafer are placed in the equipment's crystal boat. The substrate wafer is placed in the middle position of the crystal boat, and the dummy wafers are placed at both ends of the position where the substrate wafer is placed. Its function is to adjust the gas flow in the furnace to improve deposition uniformity.

[0077] It can be understood that the second processing model is the second processing model of the target semiconductor thin film obtained based on the semiconductor thin film processing equipment, the preset thickness, and the first preset number of substrate wafers. The second processing model can be recognized and run by the semiconductor thin film processing equipment. That is, the semiconductor thin film processing equipment processes the reactants according to the second processing model, and after processing, obtains the target semiconductor thin film with the preset thickness and the first preset number of substrate wafers, wherein the substrate wafer of the target semiconductor thin film is a silicon carbide wafer.

[0078] Step S203: Determine a target processing model based on the first processing model and the second processing model.

[0079] Specifically, based on the relationship between the first processing model and the second processing model, take the first processing model as the benchmark to obtain the target processing model. The target processing model can be recognized and run by the semiconductor thin film processing equipment. That is, the semiconductor thin film processing equipment processes the reactants according to the target processing model, and after processing, obtains a target semiconductor thin film with a high degree of coincidence and high accuracy with the preset thickness.

[0080] It can be understood that since the first processing model is determined based on the reference semiconductor thin film, the substrate wafer of the reference semiconductor thin film is a silicon wafer, and the system for processing semiconductor thin films using silicon wafers as substrate wafers is mature. Therefore, the accuracy and credibility of the first processing model are relatively high, so the first processing model is used as the benchmark.

[0081] Step S204, control the chemical vapor deposition process equipment to process the target semiconductor thin film based on the target processing model.

[0082] Specifically, when the chemical vapor deposition process equipment processes the target semiconductor thin film based on the target processing model, a target semiconductor thin film that is very consistent with the preset thickness can be obtained.

[0083] It can be understood that based on the target processing model, the processing time of the chemical vapor deposition process equipment can be adjusted, the processing time is more accurate, and thus the accuracy of the obtained target semiconductor thin film is also higher.

[0084] In the above method for processing a semiconductor thin film, a first processing model of a reference semiconductor thin film is determined based on a preset thickness; wherein, the substrate wafer of the reference semiconductor thin film is a silicon wafer; a second processing model of the target semiconductor thin film is determined based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film; wherein, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer; a target processing model is determined based on the first processing model and the second processing model; control the chemical vapor deposition process equipment to process the target semiconductor thin film based on the target processing model. Since the first processing model is determined based on the reference semiconductor thin film, and the substrate wafer of the reference semiconductor thin film is a silicon wafer, and the system for processing a semiconductor thin film with a silicon wafer as the substrate wafer is mature, the accuracy and credibility of the first processing model are relatively high. Based on the first processing model, the obtained target processing model can improve the accuracy of processing a semiconductor thin film with a silicon carbide wafer as the substrate wafer, shorten the equipment debugging time, and save the debugging cost.

[0085] In one embodiment, the determining the first processing model of the reference semiconductor thin film based on the preset thickness includes:

[0086] Control the chemical vapor deposition process equipment to process the reference semiconductor thin film based on the preset thickness;

[0087] Obtain the film refractive index and film thickness of the reference semiconductor thin film;

[0088] Based on the film refractive index and film thickness of the reference semiconductor thin film, determine the first processing model of the reference semiconductor thin film.

[0089] Specifically, the reference semiconductor thin film refers to a semiconductor thin film processed with a silicon wafer as the substrate wafer.

[0090] Specifically, the chemical vapor deposition process equipment, also known as LPCVD (Low Pressure Chemical Vapor Deposition) equipment, can achieve the reaction and deposition of gaseous compounds on the substrate surface under low-pressure conditions to form a stable solid thin film. Due to the low working pressure, the mean free path and diffusion coefficient of gas molecules are large. Therefore, a dense loading method can be adopted to improve productivity, and a thin film deposition layer with good uniformity can be obtained on the substrate surface. The LPCVD low-pressure chemical vapor deposition equipment is used for the preparation of various thin films such as Poly-Si, Si3N4, SiO2, phosphosilicate glass, borophosphosilicate glass, amorphous silicon, and refractory metal silicides, and is widely used in the production processes of semiconductor integrated circuits, electronic power, optoelectronics, and MEMS industries.

[0091] Specifically, the control of the chemical vapor deposition process equipment to process the reference semiconductor thin film based on a preset thickness means controlling the LPCVD low-pressure chemical vapor deposition equipment to process the silicon wafer substrate to generate a reference semiconductor thin film with a preset thickness.

[0092] Specifically, the film refractive index and film thickness of the reference semiconductor thin film can be measured by an ellipsometer. Among them, an ellipsometer is an optical measurement instrument used to detect film thickness, optical constants, and material microstructures. Due to its high measurement accuracy, it is suitable for ultra-thin films, has no contact with the sample, does not damage the sample, and does not require a vacuum; it is mainly divided into: fully automatic spectroscopic ellipsometer, imaging ellipsometer (imaging ellipse polarization technology), laser single-wavelength ellipsometer, etc., which will not be listed one by one here.

[0093] Specifically, determining the first processing model of the reference semiconductor thin film based on the film refractive index and film thickness of the reference semiconductor thin film means: comparing the actually measured film refractive index and film thickness of the reference semiconductor thin film with the preset thickness, and adjusting the processing model of the process equipment at the preset thickness based on the actually measured film refractive index and film thickness to obtain the first processing model of the reference semiconductor thin film.

[0094] In the above embodiment, by accurately obtaining the film refractive index and film thickness of the actually processed reference semiconductor thin film, and adjusting the processing model of the process equipment at the preset thickness based on the actually measured film refractive index and film thickness, the accuracy of the obtained first processing model is greatly improved.

[0095] In one embodiment, after determining the first processing model of the reference semiconductor thin film based on the preset thickness, it includes:

[0096] Obtaining the first preset number of substrate wafers of the target semiconductor thin film loaded in the chemical vapor deposition process equipment based on the historical debugging data of the reference semiconductor thin film.

[0097] Specifically, the historical debugging data of the reference semiconductor thin film can be pre-stored in the chemical vapor deposition process equipment, or can be stored in the cloud and the historical data can be called according to the actual situation, which will not be listed one by one here.

[0098] Specifically, based on the historical debugging data of the reference semiconductor thin film, the full furnace loading quantity A of the chemical vapor deposition process equipment can be determined. The full furnace loading quantity is the maximum total quantity including all the semiconductor thin film pieces that can be loaded. Based on the full furnace loading quantity A, the maximum processing throughput B of the product pieces that meet the uniformity requirement can be determined, where A is greater than B; from the corresponding placement positions of the maximum processing throughput B of the product pieces, the optimal processing position of the furnace tube of the chemical vapor deposition process equipment can be determined and defined as the processing position of the product pieces; the central position of the processing position of the product pieces is called the position in the furnace.

[0099] It can be understood that since the number of substrate pieces is the same as the number of product pieces, the maximum number of the first preset substrate pieces of the target semiconductor thin film is B at most and 1 at least; correspondingly, the minimum number of dummy pieces C = A - B, and the maximum number of dummy pieces D = A - 1.

[0100] Among them, referring to Figure 3 as shown, the Figure 3 is a schematic diagram of the distribution of substrate pieces and dummy pieces loaded on the susceptor. The dummy pieces are also called dummy wafers and are placed at both ends of the substrate piece placement positions, and their function is to adjust the gas flow in the furnace to improve the deposition uniformity.

[0101] In the above embodiment, based on the historical debugging data of the reference semiconductor thin film, the maximum processing throughput of the product pieces that meet the uniformity requirement can be accurately determined. The number of substrate pieces is the same as the number of product pieces. The maximum processing throughput is also the maximum number of the first preset substrate pieces, and then the range of the first preset substrate pieces can be accurately determined.

[0102] In another embodiment, the determining the second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate pieces of the target semiconductor thin film includes:

[0103] Controlling the chemical vapor deposition process equipment to process the target semiconductor thin film based on the preset thickness and the first preset number of substrate pieces;

[0104] Obtaining the film refractive index and film thickness of the target semiconductor thin film;

[0105] Based on the film refractive index and film thickness of the target semiconductor thin film, determining the second processing model of the target semiconductor thin film.

[0106] Specifically, the control of the chemical vapor deposition process equipment to process the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers means controlling the LPCVD (Low Pressure Chemical Vapor Deposition) equipment to process the substrate wafers to generate the target semiconductor thin film with the preset thickness and the number of the first preset substrate wafers. Among them, the substrate wafers are made of silicon carbide material, the first preset number of substrate wafers is consistent with the number of product wafers to be produced, and the target semiconductor thin film refers to the semiconductor thin film generated with the silicon carbide material as the substrate wafer.

[0107] Specifically, the film refractive index and film thickness of the target semiconductor thin film can be measured by an ellipsometer. Among them, an ellipsometer is an optical measurement instrument used to detect film thickness, optical constants, and material microstructure.

[0108] Specifically, determining the first processing model of the reference semiconductor thin film based on the film refractive index and film thickness of the target semiconductor thin film means: comparing the actually measured film refractive index and film thickness of the target semiconductor thin film with the preset thickness, and adjusting the processing model of the process equipment at the preset thickness based on the actually measured film refractive index and film thickness to obtain the second processing model of the target semiconductor thin film.

[0109] In the above embodiment, by accurately obtaining the film refractive index, film thickness, and preset thickness of the actually processed target semiconductor thin film, and adjusting the processing model of the process equipment at the preset thickness based on the actually measured film refractive index and film thickness, the second processing model of the target semiconductor thin film with higher accuracy is obtained.

[0110] In one embodiment, after determining the second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film, it includes:

[0111] Determining the third processing model based on the preset thickness and the second preset number of substrate wafers;

[0112] The determination of the target processing model based on the first processing model and the second processing model includes:

[0113] Determining the target processing model based on the first processing model, the second processing model, and the third processing model.

[0114] Specifically, the number of substrate wafers is consistent with the number of product wafers. Therefore, when the required number of product wafers changes, the processing model will also change correspondingly.

[0115] It can be understood that when the accuracy of the second processing model cannot meet the R & D requirements, a third processing model can be obtained based on the preset thickness and the second preset number of substrate wafers, and then the final target processing model can be determined based on the first processing model, the second processing model, and the third processing model.

[0116] Exemplarily, generally, the first preset number of substrate wafers is generally 1, that is, the corresponding second processing model refers to the processing model for generating a target semiconductor thin film with a preset thickness. Since the product base generated by the second processing model is small, the accuracy and credibility of the model are not high. Therefore, another second preset number of substrate wafers can be found, and a third processing model is determined based on the preset thickness and the second preset number of substrate wafers. The second preset number of substrate wafers generally adopts the maximum processing throughput value B of the product wafers that meet the uniformity requirements.

[0117] Specifically, the determining the third processing model based on the preset thickness and the second preset number of substrate wafers includes:

[0118] Controlling the chemical vapor deposition process equipment to process the target semiconductor thin film based on the preset thickness and the second preset number of substrate wafers;

[0119] Obtaining the film refractive index and film thickness of the target semiconductor thin film;

[0120] Based on the film refractive index and film thickness of the target semiconductor thin film, determining the third processing model of the target semiconductor thin film.

[0121] Specifically, the determining the target processing model based on the first processing model, the second processing model, and the third processing model includes:

[0122] Based on the relationship between the first processing model and the second processing model and the third processing model, taking the first processing model as a benchmark to obtain the target processing model. The specific process is as follows:

[0123] Based on the first processing model and the second processing model, determining the deviation coefficient a;

[0124] Based on the first processing model and the third processing model, determining the deviation coefficient b;

[0125] Based on the deviation coefficient a and the deviation coefficient b, determining the target deviation coefficient c;

[0126] Among them, the target deviation coefficient c can be the mean value after adding a and b, or the corresponding relationship between c and a, b can be determined according to actual needs, which will not be elaborated here.

[0127] Exemplarily, when the preset thickness is the same, the thickness of the reference semiconductor thin film obtained based on the first processing model is TH1; the thickness of the target semiconductor thin film obtained based on the second processing model is TH2; the thickness of the target semiconductor thin film obtained based on the third processing model is TH3. The deviation coefficient a can be represented by the ratio relationship between TH1 and TH2, and the deviation coefficient b can be represented by the ratio relationship between TH1 and TH3.

[0128] In the above embodiment, the third processing model is determined based on the preset thickness and the second preset number of substrate wafers, and the target processing model is determined based on the first processing model, the second processing model, and the third processing model. Due to the increase in model comparison, the obtained target processing model is more accurate and has higher credibility, and it also shortens the equipment debugging time and saves the debugging cost.

[0129] In one embodiment, after determining the third processing model based on the preset thickness and the second preset number of substrate wafers, it includes:

[0130] If both the second processing model and the third processing model do not meet the preset conditions, then a fourth processing model is determined based on the third preset number of substrate wafers;

[0131] The determining of the target processing model based on the first processing model, the second processing model, and the third processing model includes:

[0132] Determining the target processing model based on the first processing model, the second processing model, the third processing model, and the fourth processing model.

[0133] Specifically, when both the second processing model and the third processing model cannot meet the preset conditions, then a fourth processing model needs to be determined based on the third preset number of substrate wafers.

[0134] The preset condition refers to that the actual thickness of the target semiconductor thin film processed based on the first processing model and the second processing model is less than one-half of the preset thickness, which is specifically expressed by the following formula (1):

[0135]

[0136] When the preset conditions are not met, then a fourth processing model is determined based on the third preset number of substrate wafers; when the preset conditions are met, there is no need to determine the fourth processing model. In other embodiments, the content of the preset conditions can be determined according to the actual situation, which will not be elaborated here one by one.

[0137] Specifically, the determining of the target processing model based on the first processing model, the second processing model, the third processing model, and the fourth processing model includes:

[0138] Based on the relationship between the first processing model and the second, third, and fourth processing models, taking the first processing model as the reference, the target processing model is obtained. The specific process is as follows:

[0139] Based on the first processing model and the second processing model, the deviation coefficient a is determined;

[0140] Based on the first processing model and the third processing model, the deviation coefficient b is determined;

[0141] Based on the first processing model and the fourth processing model, the deviation coefficient d is determined;

[0142] Based on the deviation coefficient a, the deviation coefficient b, and the deviation coefficient d, the target deviation coefficient c is determined;

[0143] Among them, the target deviation coefficient c can be the average value after adding a, b, and d, or the corresponding relationship between c and a, b, d can be determined according to actual requirements, which will not be elaborated here.

[0144] Exemplarily, under the condition of the same preset thickness, the thickness of the reference semiconductor thin film obtained based on the first processing model is TH1; the thickness of the target semiconductor thin film obtained based on the second processing model is TH2; the thickness of the target semiconductor thin film obtained based on the third processing model is TH3, and the thickness of the target semiconductor thin film obtained based on the third processing model is TH4. The deviation coefficient a can be represented by the ratio relationship between TH1 and TH2, the deviation coefficient b can be represented by the ratio relationship between TH1 and TH3, and the deviation coefficient d can be represented by the ratio relationship between TH1 and TH4.

[0145] In the above embodiment, by determining whether the second processing model and the third processing model meet the preset conditions, when they do not meet the preset conditions, the fourth processing model is determined based on the third preset number of substrate wafers, and then the target processing model is determined based on the first, second, third, and fourth processing models, which can effectively correct the problem of low accuracy of the second and third processing models, improve the accuracy and credibility of the finally generated target processing model, shorten the equipment debugging time, and save the debugging cost.

[0146] In one embodiment, refer to Figure 4 as shown Figure 4 is a schematic flowchart of the implementation of the processing method of the semiconductor thin film.

[0147] Step 1, load the silicon wafer and run the target menu T, measure the refractive index and film thickness of the thin film using an ellipsometer, and establish a model of the silicon wafer.

[0148] Step 2: Based on the stable debugging data of the silicon wafers, determine the full-furnace loading quantity A of this machine tool, determine the maximum processing throughput B of the product wafers that meet the uniformity requirements and their placement positions, and thus define the minimum number of dummy wafers C = A - B, and the maximum number of dummy wafers D = A - 1;

[0149] Step 3: Debug the target menu T suitable for the processing of silicon carbide (SiC) wafers, and establish the corresponding model 1:

[0150] Run the target menu T using 1 silicon carbide (SiC) substrate wafer + the number of silicon dummy wafers D. Place the silicon carbide (SiC) wafer in the center. After the furnace is unloaded, use an ellipsometer to measure the film thickness and refractive index of the deposited film on the silicon carbide (SiC) wafer, and establish the SiC wafer processing model 1;

[0151] Step 4: Debug the target menu T suitable for the processing of silicon carbide (SiC) wafers, and establish the corresponding model 2:

[0152] Run the target menu T using the number of silicon carbide (SiC) substrate wafers B + the number of silicon dummy wafers C. After the furnace is unloaded, use an ellipsometer to measure the film thickness and refractive index of the deposited film on the silicon carbide (SiC) wafer, and establish the silicon carbide (SIC) wafer processing model 2;

[0153] Step 5: According to the results of model 1 and model 2, determine whether other models need to be established;

[0154] Step 6: According to the results of Steps 1 to 5, fit the deviation coefficient between the processing of silicon carbide (SiC) wafers and silicon wafers, and establish the final model of the target menu T for processing silicon carbide (SiC) wafers based on silicon dummy wafers.

[0155] It should be understood that although the various steps in the flowcharts involved in the above-described embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0156] In another embodiment, the embodiment of the present application also provides a semiconductor thin film processing system for implementing the semiconductor thin film processing method involved above. As Figure 5As shown, a processing system for a semiconductor thin film is provided, including a controller and a low-pressure chemical vapor deposition process device. The controller is used to determine a first processing model of a reference semiconductor thin film based on a preset thickness. Among them, the substrate of the reference semiconductor thin film is a silicon wafer. Based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film, determine a second processing model of the target semiconductor thin film. Among them, the substrate of the target semiconductor thin film is a silicon carbide wafer. Determine a target processing model based on the first processing model and the second processing model.

[0157] The controller is further used to send a control instruction to the low-pressure chemical vapor deposition process device.

[0158] The low-pressure chemical vapor deposition process device is used to receive the control instruction sent by the controller and process the target semiconductor thin film based on the target processing model.

[0159] Specifically, when the controller controls the low-pressure chemical vapor deposition process device, a direct control method can be adopted. For example, by directly issuing an instruction to the low-pressure chemical vapor deposition process device, the low-pressure chemical vapor deposition process device processes the thin film after receiving the instruction. Or an indirect control method can be used. For example, by directly issuing an instruction to the switch of the circuit connected to the low-pressure chemical vapor deposition process device, by controlling the closing and opening of the switch, and then controlling the startup of the low-pressure chemical vapor deposition process device. In other embodiments, the low-pressure chemical vapor deposition process device can also be controlled by other means, which will not be elaborated here one by one.

[0160] In the above embodiment, a dedicated processing system for a semiconductor thin film is provided. Through the controller and the low-pressure chemical vapor deposition process device, the target semiconductor thin film can be processed more accurately.

[0161] Based on the same inventive concept, an embodiment of the present application also provides a processing device for a semiconductor thin film for implementing the above-mentioned processing method of the semiconductor thin film. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the following processing device for a semiconductor thin film can refer to the limitations on the processing method of the semiconductor thin film in the above text, and will not be elaborated here.

[0162] In one embodiment, as Figure 6 shown, a processing device for a semiconductor thin film is provided, including: a first processing model determination module 610, a second processing model determination module 620, a target processing model determination module 630, and a processing module 640, where:

[0163] The first processing model determination module 610 is configured to determine a first processing model of a reference semiconductor thin film based on a preset thickness, where a substrate wafer of the reference semiconductor thin film is a silicon wafer.

[0164] The first processing model determination module 610 is further configured to control a chemical vapor deposition process device to process the reference semiconductor thin film based on the preset thickness; obtain a film refractive index and a film thickness of the reference semiconductor thin film; and determine the first processing model of the reference semiconductor thin film based on the film refractive index and the film thickness of the reference semiconductor thin film.

[0165] The second processing model determination module 620 is configured to determine a second processing model of the target semiconductor thin film based on the preset thickness and a first preset number of substrate wafers of the target semiconductor thin film.

[0166] The second processing model determination module 620 is further configured to control a chemical vapor deposition process device to process the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers; obtain a film refractive index and a film thickness of the target semiconductor thin film; and determine the second processing model of the target semiconductor thin film based on the film refractive index and the film thickness of the target semiconductor thin film, where a substrate wafer of the target semiconductor thin film is a silicon carbide wafer.

[0167] The target processing model determination module 630 is configured to determine a target processing model based on the first processing model and the second processing model.

[0168] The processing module 640 is configured to control a chemical vapor deposition process device to process the target semiconductor thin film based on the target processing model.

[0169] The processing device for a semiconductor thin film further includes: a substrate wafer determination module, a third processing model determination module, and a fourth processing model determination module.

[0170] The substrate wafer determination module is configured to obtain a first preset number of substrate wafers of the target semiconductor thin film loaded in the chemical vapor deposition process device based on historical debugging data of the reference semiconductor thin film.

[0171] The third processing model determination module is configured to determine a third processing model based on the preset thickness and a second preset number of substrate wafers; the determining the target processing model based on the first processing model and the second processing model includes: determining the target processing model based on the first processing model, the second processing model, and the third processing model.

[0172] A fourth processing model determination module, configured to determine a fourth processing model based on a third preset number of substrate films if neither the second processing model nor the third processing model meets a preset condition; determining a target processing model based on the first processing model, the second processing model, and the third processing model includes: determining a target processing model based on the first processing model, the second processing model, the third processing model, and the fourth processing model.

[0173] Each module in the above semiconductor thin film processing apparatus can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or stored in a memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0174] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as Figure 7 shown. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner. The wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a semiconductor thin film processing apparatus. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse, etc.

[0175] Those skilled in the art can understand that Figure 7 the structure shown in

[0176] merely represents a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0177] Determine a first processing model of a reference semiconductor thin film based on a preset thickness;

[0178] Among them, the substrate wafer of the reference semiconductor thin film is a silicon wafer;

[0179] Determine a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film, where the substrate wafer of the target semiconductor thin film is a silicon carbide wafer.

[0180] Determine a target processing model based on the first processing model and the second processing model;

[0181] Control the chemical vapor deposition process equipment to process the target semiconductor thin film based on the target processing model.

[0182] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0183] Determine a first processing model of a reference semiconductor thin film based on a preset thickness;

[0184] Among them, the substrate wafer of the reference semiconductor thin film is a silicon wafer;

[0185] Determine a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film;

[0186] Among them, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer;

[0187] Determine a target processing model based on the first processing model and the second processing model;

[0188] Control the chemical vapor deposition process equipment to process the target semiconductor thin film based on the target processing model.

[0189] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data that have been authorized by the user or fully authorized by all parties.

[0190] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0191] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0192] The above-described embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A processing method for a semiconductor thin film, characterized in that, Including: Determining a first processing model of a reference semiconductor thin film based on a preset thickness; Wherein, the substrate wafer of the reference semiconductor thin film is a silicon wafer; Determining a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film; Wherein, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer; Determining a target processing model based on the first processing model and the second processing model; Controlling a chemical vapor deposition process device to process the target semiconductor thin film based on the target processing model; The determining the first processing model of the reference semiconductor thin film based on the preset thickness includes: controlling a chemical vapor deposition process device to process the reference semiconductor thin film based on the preset thickness; obtaining the film refractive index and film thickness of the reference semiconductor thin film; determining the first processing model of the reference semiconductor thin film based on the film refractive index and film thickness of the reference semiconductor thin film; The determining the second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film includes: controlling a chemical vapor deposition process device to process the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers; obtaining the film refractive index and film thickness of the target semiconductor thin film; determining the second processing model of the target semiconductor thin film based on the film refractive index and film thickness of the target semiconductor thin film; The first processing model, the second processing model, and the target processing model can be recognized and run by a semiconductor thin film processing process device.

2. The processing method for a semiconductor thin film according to claim 1, characterized in that, After determining the first processing model of the reference semiconductor thin film based on the preset thickness, it includes: Obtaining the first preset number of substrate wafers of the target semiconductor thin film loaded in the chemical vapor deposition process device based on the historical debugging data of the reference semiconductor thin film.

3. The processing method for a semiconductor thin film according to claim 1, characterized in that, After determining the second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film, it includes: Determining a third processing model based on the preset thickness and the second preset number of substrate wafers; The determining the target processing model based on the first processing model and the second processing model includes: Determining the target processing model based on the first processing model, the second processing model, and the third processing model.

4. The processing method for a semiconductor thin film according to claim 3, characterized in that, After determining the third processing model based on the preset thickness and the second preset number of substrate wafers, it includes: If both the second processing model and the third processing model do not meet the preset conditions, determining a fourth processing model based on the third preset number of substrate wafers; The determining the target processing model based on the first processing model, the second processing model, and the third processing model includes: Determining the target processing model based on the first processing model, the second processing model, the third processing model, and the fourth processing model.

5. A processing system for a semiconductor thin film, comprising a controller and a low-pressure chemical vapor deposition process device, wherein the controller is used to determine a first processing model of a reference semiconductor thin film based on a preset thickness; wherein, The substrate wafer of the reference semiconductor thin film is a silicon wafer; Determining the second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film; wherein, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer; determining the target processing model based on the first processing model and the second processing model; The controller is further configured to send a control instruction to the low-pressure chemical vapor deposition process equipment; The low-pressure chemical vapor deposition process equipment is configured to receive the control instruction sent by the controller and process the target semiconductor thin film based on the target processing model; The first processing model for determining the reference semiconductor thin film based on the preset thickness includes: controlling the chemical vapor deposition process equipment to process the reference semiconductor thin film based on the preset thickness; obtaining the film refractive index and film thickness of the reference semiconductor thin film; and determining the first processing model of the reference semiconductor thin film based on the film refractive index and film thickness of the reference semiconductor thin film; The second processing model for determining the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film includes: controlling the chemical vapor deposition process equipment to process the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers; obtaining the film refractive index and film thickness of the target semiconductor thin film; and determining the second processing model of the target semiconductor thin film based on the film refractive index and film thickness of the target semiconductor thin film; The first processing model, the second processing model, and the target processing model can be recognized and run by the semiconductor thin film processing equipment.

6. A processing device for a semiconductor thin film, characterized in that, The device includes: A first processing model determination module, configured to determine a first processing model of a reference semiconductor thin film based on a preset thickness; Wherein, the substrate wafer of the reference semiconductor thin film is a silicon wafer; A second processing model determination module, configured to determine a second processing model of the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film; Wherein, the substrate wafer of the target semiconductor thin film is a silicon carbide wafer; A target processing model determination module, configured to determine a target processing model based on the first processing model and the second processing model; A processing module, configured to control the chemical vapor deposition process equipment to process the target semiconductor thin film based on the target processing model; The first processing model for determining the reference semiconductor thin film based on the preset thickness includes: controlling the chemical vapor deposition process equipment to process the reference semiconductor thin film based on the preset thickness; obtaining the film refractive index and film thickness of the reference semiconductor thin film; and determining the first processing model of the reference semiconductor thin film based on the film refractive index and film thickness of the reference semiconductor thin film; The second processing model for determining the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers of the target semiconductor thin film includes: controlling the chemical vapor deposition process equipment to process the target semiconductor thin film based on the preset thickness and the first preset number of substrate wafers; obtaining the film refractive index and film thickness of the target semiconductor thin film; and determining the second processing model of the target semiconductor thin film based on the film refractive index and film thickness of the target semiconductor thin film; The first processing model, the second processing model, and the target processing model can be recognized and run by the semiconductor thin film processing equipment.

7. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

8. A computer-readable storage medium, having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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