Development method of thin film process and semiconductor process equipment

Abstract

The invention discloses a thin film process development method and semiconductor process equipment. The method comprises the following steps: generating a plurality of random experiment groups according to process parameters needing to be adjusted and parameter ranges corresponding to the process parameters; a first process experiment is carried out based on the multiple random experiment groups, multiple corresponding first process results are obtained, the first process results comprise process indexes and first actual values corresponding to the process indexes, and the process indexes comprise process contours; the first actual value corresponding to the process contour is determined according to the thickness measurement values of the film on a plurality of preset routing paths; according to the multiple random experiment groups and the multiple first process results, a corresponding process window is determined, and the process window comprises the target parameter range of the process parameters. The method can be suitable for adjusting the process parameters in a large range, analysis on the process contour is more accurate, the process development period is shortened, process development resources are saved, and the development difficulty is reduced.

Description

Technical Field

[0001] The present application relates to the field of semiconductor technology, and in particular to a thin film process development method and semiconductor process equipment. Background Art

[0002] Plasma-enhanced chemical vapor deposition (PECVD) is a technology that uses glow discharge plasma to dissociate a gaseous source under low vacuum. This is then used to react with the wafer surface for thin film surface pretreatment (such as reduction), or to recombine gaseous ions for thin film deposition. Achieving high-quality thin film deposition and etching requires higher standards for thin film process development. Parameters that can be used to adjust the PECVD process include gas flow rate, RF power, gas pressure, and temperature. Process metrics (i.e., process performance) used to measure film quality include film thickness, in-plane uniformity, refractive index, stress, and process profile. Most of these process metrics can be measured and directly quantified, making it easy to identify univariate trends in these process parameters. However, process profile is more difficult to quantify. It directly affects the local stress distribution of the thin film on the wafer, the effective usable area of ​​the entire wafer, and the yield, ultimately impacting chip production costs.

[0003] In related technologies, process indicators are usually regulated based on single-variable trend experiments. However, the premise of single-variable trend experiments is that, except for the currently changing process parameters, other process parameters are fixed. Therefore, they can only be used to fine-tune process parameters within a small range. In addition, single-variable trend experiments can only be used to characterize quantifiable process indicators. For process profiles that are difficult to quantify, the analysis results are inaccurate. Moreover, after the adjustment of quantifiable process indicators is completed, further adjustments to the process profile will cause the adjusted process indicators to shift or even completely overturn the previous debugging data, greatly extending the process development cycle, wasting process development resources, and increasing the difficulty of development. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a thin film process development method and semiconductor process equipment to solve the problem that the related technology can only be used for fine-tuning of process parameters within a small range, the analysis results of process profiles that are difficult to quantify are inaccurate, the process development cycle is extended, process development resources are wasted, and the development difficulty is increased.

[0005] To achieve the above objectives, the present invention adopts the following technical solutions: In a first aspect, an embodiment of the present application provides a method for developing a thin film process, the method comprising: generating multiple random experimental groups based on process parameters to be adjusted and parameter ranges corresponding to the process parameters; conducting a first process experiment based on the multiple random experimental groups, and obtaining corresponding multiple first process results, the first process results including process indicators and first actual values ​​corresponding to the process indicators, the process indicators including process profiles, the first actual values ​​corresponding to the process profiles being determined based on thickness measurements of the thin film on multiple preset routing paths; determining a corresponding process window based on the multiple random experimental groups and the multiple first process results, the process window including a target parameter range for the process parameters.

[0006] In the second aspect, an embodiment of the present application provides a semiconductor process equipment, comprising: a controller, an RF power supply, a chamber, and a shower head and a base arranged in the chamber, wherein the RF power supply is used to output RF power to the shower head and the base to dissociate the reaction gas in the chamber into plasma, and the controller is arranged in a host computer and / or a slave computer, and the controller includes at least one processor and at least one memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the method described in the first aspect are implemented.

[0007] The embodiment of the present application quantifies the process profile based on the thickness measurements of the film along multiple preset routing paths and incorporates it into a Design of Experiment (DOE) along with other quantifiable process indicators. Each process parameter in the experiment can take values ​​within an adjustable parameter range, making it suitable for adjusting process parameters within a larger range. Furthermore, by quantifying the process profile, which is difficult to control and predict, the analysis of the process profile is more accurate. The quantified process profile is incorporated into the experimental design for unified adjustment along with other quantifiable process indicators, shortening the process development cycle, saving process development resources, and reducing development difficulty. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 It is a schematic diagram of the structure of a typical PECVD equipment; Figure 2 A schematic diagram of the process development process of ODC based on single variable trend in related technologies; Figure 3 A schematic flow chart of a thin film process development method provided in accordance with one embodiment of the present application; Figure 4A film thickness contour map corresponding to a deposition process provided in one embodiment of the present application; Figure 5 A routing diagram of measurement points provided in accordance with an embodiment of the present application; Figure 6 A schematic diagram of process profile types corresponding to positive and negative value combinations of the first profile parameter A1 and the second profile parameter A2 provided in one embodiment of the present application; Figure 7 A schematic diagram of experimental results of an experimental design provided for one embodiment of the present application; Figure 8 A schematic diagram of a process profile obtained during the process verification process provided in one embodiment of the present application; Figure 9 A schematic diagram of the overall process of a thin film process development method provided in another embodiment of the present application. DETAILED DESCRIPTION

[0009] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0010] The terms "first", "second", etc. in this application are used to distinguish similar objects and are not used to describe a specific order or precedence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances so that the embodiments of the present application can be implemented in an order other than those illustrated or described here. In addition, "and / or" in this application represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship. It should be noted that the data involved in this application are all obtained under the premise of obtaining user authorization.

[0011] Plasma-enhanced chemical vapor deposition (PECVD) is a technology that uses glow discharge plasma to dissociate a gaseous source under low vacuum. This is then used to react with the wafer surface for thin-film surface pretreatment (such as reduction), or to recombine gaseous ions for thin-film deposition. PECVD offers fast reaction speeds and low reaction temperatures, making it suitable for most surface pretreatments and dielectric thin-film deposition. It is primarily used for etch-stop layers (ESLs), hard masks (HMs), inter-metal dielectrics (IMDs), and inter-layer dielectrics (ILDs) in semiconductor devices. It has a wide range of applications in fields such as very large-scale integrated circuits, optoelectronic devices, and micro-electro-mechanical systems (MEMS).

[0012] The performance improvements of modern computing and storage devices rely on highly integrated chip manufacturing. The miniaturization of devices and the increase in stacked film layers place higher demands on the reliability, repeatability, stability, and control of thin film process profiles in each process. Achieving high-quality thin film deposition and etching capabilities limits wafer manufacturing throughput, placing higher demands on thin film process development.

[0013] Figure 1 This is a schematic diagram of the structure of a typical PECVD device, such as Figure 1 As shown, reactant gases flow from a gas box 101 through a showerhead 103 at the top of chamber 102 and into chamber 102. Radio frequency (RF) power, driven by an RF power supply 104, is applied to parallel metal plates within chamber 102, consisting of the showerhead 103 and a susceptor 105. This dissociates the reactant gases within chamber 102 and generates capacitively coupled plasma (CCP) 106. To increase the controllability of the thin film surface treatment effect on wafer 107, both high-frequency (HF) and low-frequency (LF) power can be fed simultaneously. A heater 108 controls the temperature of the susceptor 105. A dry pump 109 controls the pressure within chamber 102.

[0014] Process parameters that can be used to adjust the process results in PECVD reactions include gas flow, RF power, gas pressure, and temperature. Process indicators (i.e., process performance) that measure thin film quality include film thickness (THK), within-wafer (WIW) uniformity, refractive index (RI), stress, and process profile. Most of these process indicators can be directly quantified after measurement, making it very easy to identify univariate trends in process parameters. However, the process profile is difficult to quantify. In the field of thin film deposition, the process profile can be considered a contour map of the film thickness, used to measure the thickness distribution of the thin film deposited on the wafer. The process profile directly affects the local stress distribution of the thin film on the wafer, the effective usable area of ​​the entire wafer, and the yield, ultimately affecting the production cost of the chip.

[0015] In related technologies, the process profile and other quantifiable process indicators are regulated based on the Single Value Trend (SVT) experiment. Figure 2 The following is a schematic diagram of the process development flow of oxygen-doped silicon carbide (ODC) based on a single variable trend. Figure 2 As shown, the specific steps include: S201, set a benchmark for all quantifiable process parameters.

[0016] Subsequent single-variable trend experiments will be adjusted based on this, and the specific settings can be as follows: the flow rate of tetramethylsilane (Si(CH3)4, abbreviated as 4MS) is set to 100-800 standard cubic centimeter per minute (sccm), for example, 300 sccm; the flow rate of CO2 is set to 1000-8000 sccm, for example, 2000 sccm; the pressure is set to 1-7 torr, for example, 5 torr; the high frequency (HF) power is set to 100-800 watts (W), for example, 300 W; the low frequency (LF) power is set to 100-800 W, for example, 300 W.

[0017] S202: A certain quantifiable process parameter is adjusted within a range of ±5 to 20%, while other quantifiable process parameters remain unchanged.

[0018] For example, for 4MS, the flow gradient is set to 100 sccm-200 sccm-300 sccm-400 sccm-500 sccm, and the other process parameters remain unchanged, and five groups of process experiments are performed.

[0019] S203: Collect process indicators corresponding to the quantifiable process parameter changes.

[0020] For example, two types of process indicators, film uniformity (Non-uniformity%, abbreviated as NU%) and refractive index, corresponding to the five groups of experiments in S202, are collected to check the correlation between the 4MS process parameters and the film uniformity and refractive index.

[0021] S204: traverse all quantifiable process parameters. Repeat steps S202-S203. After the traversal is completed, proceed to step S205.

[0022] S205 , summarizing the univariate trends of all quantifiable process parameters.

[0023] S206 , referring to the single variable trend, searching for process parameters that meet the process indicators.

[0024] For example, the process indicators are required to meet the following conditions: film uniformity is less than 3%; the refractive index is in the range of 1.2~1.7, and the process parameters that meet the above process indicators are sought.

[0025] S207 , reviewing the process parameters that may affect the process profile, fine-tuning the process parameters based on this, and measuring whether they affect the adjusted process indicators.

[0026] For example, if review reveals that adjusting the pressure can control the process profile, and the process profile can transition from a thick center with thin edges (∧-shaped profile) to a thin center with thick edges (∨-shaped profile), the pressure is fine-tuned. If other process indicators remain unchanged after the process profile adjustment, then the process profile and other process indicators meet the requirements, and step S208 is executed. If other process indicators change after the process profile adjustment, steps S206-S207 are repeated until the process profile adjustment is complete and other process indicators remain unchanged.

[0027] S208, complete process development.

[0028] In the above scheme, quantifiable process indicators such as film uniformity and refractive index can be correlated with process parameters through single-variable trend experiments. For example, when the 4MS flow rate is within the range of 100-500 sccm, the film refractive index will increase monotonically. However, the premise of this single-variable trend experiment is that, apart from the currently changing process parameter (such as the 4MS flow rate), other process parameters (such as CO2 flow rate and pressure) are fixed. If process parameters such as CO2 flow rate and pressure change, the magnitude and even trend of the film refractive index will change when the 4MS flow rate varies within the range of 100-500 sccm. Therefore, the above scheme can only be used for fine-tuning process parameters within a small range.

[0029] Furthermore, single-variable trend experiments can only characterize quantifiable process indicators, such as film uniformity and refractive index. For process profiles that are difficult to quantify, the analysis results are inaccurate. Furthermore, adjusting the process profile after adjustments to quantifiable process indicators have been made can cause the adjusted process indicators to shift, or even completely overturn the previously adjusted data. This significantly prolongs the process development cycle, wastes process development resources, and increases development difficulty.

[0030] To this end, this application proposes a process development method for the joint regulation of process profile and other quantifiable process indicators.

[0031] The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0032] Figure 3 A schematic diagram of a thin film process development method provided in one embodiment of the present application. Figure 3 As shown, the thin film process development method of the embodiment of the present application may specifically include the following steps: S301: Generate multiple random experimental groups according to the process parameters to be adjusted and the parameter ranges corresponding to the process parameters.

[0033] In an embodiment of the present application, the execution entity of the thin film process development method of the embodiment of the present application is a controller in a semiconductor process equipment (such as a PECVD equipment), and the controller can be set in the host computer and / or the slave computer of the semiconductor process equipment.

[0034] The process parameters that require adjustment are those used to adjust the process results for the current semiconductor process equipment. These parameters may include, but are not limited to, gas flow rate, RF power, gas pressure, and temperature. The parameter range corresponding to the process parameter is the adjustable parameter range within which the process parameter can take values. The parameter range includes an upper parameter limit and a lower parameter limit.

[0035] Taking oxygen-doped silicon carbide film ODC as an example, the parameter ranges of the process parameters that need to be adjusted can be set as follows: the flow rate of 4MS is set to 100~800sccm; the flow rate of CO2 is set to 1000~8000sccm; the pressure is set to 1~7torr; the high-frequency power is set to 100~800W; and the low-frequency power is set to 100~800W.

[0036] According to the process parameters to be adjusted and the corresponding parameter ranges, random experimental groups are generated. The specific generation process can be as follows: each process parameter is taken as a value in at least one of the following ways: each process parameter is taken as the corresponding parameter upper limit and parameter lower limit, each process parameter is taken as the center value of the corresponding parameter range, and one process parameter is taken as the corresponding parameter upper limit and parameter lower limit, and the remaining process parameters are taken as the center value of the corresponding parameter range to generate multiple regular experimental groups; multiple regular experimental groups are randomly arranged to generate multiple random experimental groups.

[0037] Based on the logic of response surface design, a response relationship can be established between process parameters and process outcomes. This response relationship generally takes the form of a surface or curve and can be represented using surface or curve models. These models include, but are not limited to, central composite design (CCD), Box-Behnken design, spherical design, and cubic region design.

[0038] As a feasible implementation method, multiple randomized experimental groups can be prepared in JMP commercial software based on the logic of response surface design. Assuming that there are N process parameters to be adjusted, for example, the above example includes 5 process parameters to be adjusted (4MS flow rate, CO2 flow rate, pressure, high frequency power and low frequency power), if a central composite design model is used, a total of 2 N End point test, that is, each process parameter takes the upper limit and lower limit of the parameter for experiment; 2*N axis center point test, that is, one process parameter takes the upper limit or lower limit of the parameter, and the other N-1 process parameters take the center value of their corresponding parameter range; and add 3 individual center point tests, that is, N process parameters take the center value of their corresponding parameter range, and repeat 3 times, for a total of 2 N +2*N +3 experimental groups, because these experimental groups are arranged in a regular order, they are recorded as regular experimental groups. When N is 5, there are 2 5 +2*5+3=45 regular experimental groups. JMP commercial software shuffles and rearranges these 45 regular experimental groups to generate 45 random experimental groups with random orders. Subsequently, 45 experiments need to be conducted according to the random order given by the software to minimize the errors caused by human-designed experimental order.

[0039] It's important to note that the central composite design model is primarily used to evaluate binomial designs. The addition of center points allows the model to be optimized based on previous or subsequent experiments. That is, when a new experiment is added, the corresponding experimental data can be recombined with the previous 45 experiments to construct the model. The Box-Behnken design model typically has fewer design points and is less accurate at the extreme values ​​of the independent variable. It is therefore more suitable for scenarios where experimental costs are reduced.

[0040] S302, conducting a first process experiment based on multiple random experimental groups, and obtaining corresponding multiple first process results, the first process results including process indicators and first actual values ​​corresponding to the process indicators, the process indicators including process profiles, and the first actual values ​​corresponding to the process profiles are determined based on thickness measurement values ​​of the film on multiple preset routing paths.

[0041] In this embodiment of the present application, the first process experiment is performed sequentially according to the order of the multiple (e.g., 45 in the above example) randomized experimental groups generated in step S301, and a first process result corresponding to each randomized experimental group is obtained. The first process result includes at least one process indicator and a first actual value corresponding to each process indicator.

[0042] Among them, the process indicators included in the first process result include at least a process profile. The first actual value corresponding to the process profile cannot be obtained by measurement, but can be obtained by calculation, that is, the first actual value corresponding to the process profile is a calculated value, which can be determined based on the thickness measurement value of the film on multiple preset routing paths. Other quantifiable process indicators, such as film thickness, in-plane uniformity, refractive index, and stress, can be obtained by measurement. For example, the film uniformity, refractive index, and two profile parameters A1 and A2 corresponding to the process profile corresponding to each random experimental group are obtained.

[0043] The embodiment of the present application defines a universal process profile measurement standard and designs two quantization parameters (a first profile parameter A1 and a second profile parameter A2) to quantify the process profile and visualize the characteristics of the process profile.

[0044] The process profile can be fitted through the routing diagram of the measurement point data to obtain the contour map of the process profile, such as Figure 4 Shown are the film thickness contour plots corresponding to the deposition process.

[0045] The preset multiple routing paths may specifically include three circular paths with the same center and different radii, wherein the three circular paths include a first circular path a1, a second circular path a2, and a third circular path a3, each of which has a radius increasing in sequence. Figure 5The routing diagram of the measurement points is shown, where the inner circle a1, the second outer circle a2 and the outermost circle a3 correspond to the first circular path a1, the second circular path a2 and the third circular path a3 respectively.

[0046] It's important to note that since semiconductor deposition equipment hardware is generally centrosymmetric, customer requirements and process development requirements generally also require centrosymmetric process profiles. The routing design here is primarily based on commonly encountered process profiles, including sufficiently complex W-shaped and M-shaped profiles. Designing three concentric circles is sufficient for characterization.

[0047] The first actual value corresponding to the process profile includes a first profile parameter actual value A1 and a second profile parameter actual value A2.

[0048] The actual value A1 of the first profile parameter can be determined based on the thickness measurement values ​​of the film on the first circular path a1 and the second circular path a2. Specifically, it can be calculated using the following formula: A1=(a2-a1) / (a2+a1)(1) Wherein, A1 is the actual value of the first profile parameter, a1 is the average value of the thickness measurement values ​​of the film on the first circular path, and a2 is the average value of the thickness measurement values ​​of the film on the second circular path.

[0049] The actual value A2 of the second profile parameter can be determined based on the thickness measurement values ​​of the film on the second circular path a2 and the third circular path a3. Specifically, it can be calculated using the following formula: A2=(a2-a3) / (a2+a3)(2) Wherein, A2 is the actual value of the second profile parameter, a2 is the average value of the thickness measurement values ​​of the film on the second circular path, and a3 is the average value of the thickness measurement values ​​of the film on the third circular path.

[0050] It should be noted that in the above formulas (1) and (2), in addition to calculating the difference between the two path thickness measurements, it is also necessary to divide by the sum of the two path thickness measurements. This is because even for the same process conditions, there is a need to change the overall film thickness by adjusting the deposition time, etc. Therefore, in the process of measuring the process profile, the relative proportion of the film thickness in different regions is more important. For example, if only the difference of 1nm is measured for a film with a thickness of 100nm and a film with a thickness of 1000nm, the trend of the process profile is actually different. The film with a thickness of 1000nm is definitely flatter than the film with a thickness of 100nm. On the other hand, by dividing by the sum of the two path thickness measurements, the profile parameters can be controlled within ±1, which is convenient for subsequent calculations.

[0051] According to the above two profile parameters, the corresponding relationship between the process profile and the profile parameters can be calculated: M type is thin in the inner circle, thick in the second outer circle, and thin in the outermost circle; W type is thick in the inner circle, thin in the second outer circle, and thick in the outermost circle; ∨ type is gradually thickening from the inner circle to the outermost circle; ∧ type is gradually thinning from the inner circle to the outermost circle. Figure 6 The figure shows the process profile types corresponding to combinations of positive and negative values ​​of the first profile parameter A1 and the second profile parameter A2, where "+" indicates a positive value and "-" indicates a negative value. The closer the absolute values ​​of |A1| and |A2| are to 1, the steeper the film; the closer the absolute values ​​of |A1| and |A2| are to 0, the flatter the film. In summary, by defining the values ​​of the first profile parameter A1 and the second profile parameter A2, the corresponding process profile can be defined.

[0052] It should be noted here that if there are customer customization requirements, routing paths of the profile parameters can be appropriately added, such as appropriate eccentricity, etc., and a set of routing paths with mutually perpendicular diameters can be added and introduced into the profile parameters.

[0053] S303 : Determine a corresponding process window according to the multiple random experimental groups and the multiple first process results, where the process window includes a target parameter range of the process parameter.

[0054] In the embodiments of the present application, the process window is the parameter range corresponding to the process parameters that meets the preset process requirements (i.e., the target process result), which is recorded as the target parameter range. The target process result includes the process indicators and the range of expected values ​​corresponding to the process indicators. For example, it is required that the film uniformity is less than 3%, the refractive index is within the range of 1.2-1.7, the first profile parameter A1 is within the range of -0.6-0.2, and the second profile parameter A2 is within the range of -0.3-0.1, i.e., a W-shaped process profile.

[0055] As a feasible implementation, this step can predict the process window by generating a process model and predicting based on the process model. Specifically, the following steps may be included: generating a corresponding process model based on multiple randomized experimental groups and multiple first process results; and determining the corresponding process window based on the process model and preset target process results.

[0056] Among them, the above-mentioned step of "generating a corresponding process model based on multiple random experimental groups and multiple first process results" may specifically include the following steps: generating a process model by fitting based on multiple random experimental groups and multiple first process results using the least squares method.

[0057] Specifically, the process parameters of multiple randomized experimental groups and the corresponding multiple first process results are entered into JMP commercial software. Numerical fitting, such as the least squares method, is performed to identify highly influential factors, which may include combinations of linear, quadratic, or even quintic terms. A model to be fitted (e.g., a model based on a multivariate quadratic regression equation) is designed and a process model that meets the requirements is fitted. Specifically, to obtain the optimal model, the confidence level of each candidate process model generated during the fitting process is calculated. The candidate process model with a confidence level equal to or greater than a preset confidence threshold is determined as the final process model. Model confidence can be measured using the model's predicted R-squared, which is set to fall within the range of 0.9 to 1. R-squared is a statistic in the regression numerator that measures the model's fit to the data.

[0058] The above step of "determining the corresponding process window based on the process model and the preset target process results" can be simply understood as follows: if the process parameter is defined as the independent variable X of the equation corresponding to the process model, and the process result is defined as the dependent variable Y of the equation, then by entering the desired range of Y in the process model, a range of X will be obtained. The range of X is the process window.

[0059] For example, Figure 7 The experimental results of the experimental design are shown. The confidence R square of the process model is 0.983258, which confirms that the confidence of the process model meets the requirements. Figure 7 The white area indicated by the middle cross represents the process window that meets process requirements. Specifically, when the high-frequency (HF) power is set to 200W, the pressure is set to 2 torr, and the 4MS flow rate is set to 190 sccm, the low-frequency (LF) power ranges from 187 to 240W, and the CO2 flow rate ranges from 4780 to 6000 sccm. These meet the target process results: film uniformity (NU%) <3%, refractive index (RI) between 1.2 and 1.7, the first profile parameter A1 between -0.6 and -0.2, and the second profile parameter A2 between -0.3 and -0.1, representing a W-shaped process profile.

[0060] Furthermore, after the above step S303 of "determining the corresponding process window based on multiple random experimental groups and multiple first process results", the thin film process development method of the embodiment of the present application may also include the following verification step: performing process verification on the process model based on the process window.

[0061] Furthermore, the above-mentioned step of "performing process verification on the process model based on the process window" may specifically include the following steps: conducting a second process experiment based on the target parameters of the process parameters, and obtaining a corresponding second process result, the target parameters are within the target parameter range, and the second process result includes the process indicators and the second actual values ​​corresponding to the process indicators; based on the second process result and the target process result, performing process verification on the process model, and the target process result includes the process indicators and the range of expected values ​​corresponding to the process indicators.

[0062] Specifically, according to Figure 7 The second process experiment was conducted with the process parameters at the middle cross position: the high frequency (HF) power was set to 200W, the pressure was set to 2 torr, the 4MS flow rate was set to 190 sccm, the low frequency (LF) power was set to 220W, and the CO2 flow rate was set to 5500 sccm. The second process results obtained were a film uniformity (NU%) of 1.744% and a refractive index (RI) of 1.65. The process profile is shown in Figure 1. Figure 8 As shown, it presents a W-shape, which meets the preset target process results: the film uniformity (NU%) is required to be <3%, the refractive index (RI) is within the range of 1.2~1.7, and the W-shaped process profile verifies the accuracy and reliability of the experimental design.

[0063] To clearly illustrate the development method of the thin film process of the embodiment of the present application, the following is combined with Figure 9 The overall process of the thin film process development method of the embodiment of the present application is described in detail. Figure 9 As shown, the thin film process development method of the embodiment of the present application may specifically include the following steps: S901, determining a target process result, where the target process result includes a process indicator and a range of expected values ​​corresponding to the process indicator.

[0064] S902: Determine the process parameters to be adjusted and the corresponding parameter ranges.

[0065] S903, based on the logic of response surface design, generates multiple randomized experimental groups.

[0066] S904: Perform a first process experiment based on multiple random experimental groups, and obtain corresponding multiple first process results.

[0067] S905 , generating a process model with a confidence level that meets requirements by fitting using a least squares method according to the multiple random experimental groups and the multiple first process results.

[0068] S906: Predict the process window based on the process model and the preset target process result.

[0069] S907: Perform process verification on the process model based on the process window.

[0070] In summary, the thin film process development method of the embodiment of the present application quantifies the process profile based on the thickness measurement value of the thin film on multiple preset routing paths, and adds the experimental design at the same time with other quantifiable process indicators. In the experiment, each process parameter can take values ​​within the adjustable parameter range, so it is suitable for adjusting the process parameters within a large range, enhancing the flexibility and reliability of process parameter adjustment. In addition, by quantifying the process profile that is difficult to control and predict, the analysis of the process profile is more accurate, matching the profile requirements of the front-end or back-end thin film deposition and etching process. The quantified process profile is added to the experimental design at the same time with other quantifiable process indicators for unified adjustment, shortening the process development cycle, saving process development resources, and reducing the development difficulty. The process profile is quantified based on three circular paths with the same center and different radii, which can simply and accurately characterize various common process profiles. When determining the quantified profile parameters, in addition to calculating the difference between the thickness measurement values ​​of the two paths, it is also necessary to divide by the sum of the thickness measurement values ​​of the two paths. By measuring the relative proportion of the film thickness in different regions, the process profile can be better characterized. In addition, the profile parameters can be controlled within ±1, which is convenient for subsequent calculations.

[0071] The present application also provides a semiconductor process equipment. Figure 1 As shown, the semiconductor process equipment includes: a controller ( Figure 1 ), an RF power supply 104, a chamber 102, and a shower head 103 and a base 105 arranged in the chamber 102, the RF power supply 104 is used to output RF power to the shower head 103 and the base 105 to dissociate the reaction gas in the chamber 102 into plasma 106, and a controller is set in the upper computer and / or the lower computer. The controller includes at least one processor and at least one memory. The memory stores a computer program. When the computer program is executed by the processor, the steps of the embodiment of the development method of any of the above-mentioned thin film processes are implemented.

[0072] The semiconductor process equipment of the embodiment of the present application quantifies the process profile based on the thickness measurement values ​​of the thin film on multiple preset routing paths, and adds it to the experimental design at the same time with other quantifiable process indicators. In the experiment, each process parameter can take values ​​within the adjustable parameter range, so it is suitable for adjusting the process parameters within a large range, enhancing the flexibility and reliability of process parameter adjustment. In addition, by quantifying the process profile that is difficult to control and predict, the analysis of the process profile is more accurate and matches the profile requirements of the front-end or back-end thin film deposition and etching processes. The quantified process profile is added to the experimental design at the same time with other quantifiable process indicators for unified adjustment, shortening the process development cycle, saving process development resources, and reducing development difficulty. The process profile is quantified based on three circular paths with the same center and different radii, which can simply and accurately characterize various common process profiles. When determining the quantified profile parameters, in addition to calculating the difference between the thickness measurement values ​​of the two paths, it is also necessary to divide it by the sum of the thickness measurement values ​​of the two paths. By measuring the relative proportion of the film thickness in different regions, the process profile can be better characterized. In addition, the profile parameters can be controlled within ±1, which facilitates subsequent calculations.

[0073] An embodiment of the present application also proposes a readable storage medium, on which one or more computer programs are stored. The one or more computer programs include instructions. When the program or instructions are executed by a processor in a semiconductor process equipment that includes multiple application programs, the processor in the semiconductor process equipment can execute the various processes of the above-mentioned thin film process development method embodiment, and is specifically used to execute the steps of any of the above-mentioned thin film process development method embodiments.

[0074] The readable storage medium of the embodiment of the present application quantifies the process profile based on the thickness measurement value of the thin film on multiple preset routing paths, and adds the experimental design at the same time with other quantifiable process indicators. In the experiment, each process parameter can take values ​​within the adjustable parameter range, so it is suitable for adjusting the process parameters within a larger range, enhancing the flexibility and reliability of the process parameter adjustment. In addition, by quantifying the process profile that is difficult to control and predict, the analysis of the process profile is more accurate, matching the profile requirements of the front-end or back-end thin film deposition and etching process. The quantified process profile is added to the experimental design at the same time with other quantifiable process indicators for unified adjustment, shortening the process development cycle, saving process development resources, and reducing the development difficulty. The process profile is quantified based on three circular paths with the same center and different radii, which can simply and accurately characterize various common process profiles. When determining the quantified profile parameters, in addition to calculating the difference between the thickness measurement values ​​of the two paths, it is also necessary to divide by the sum of the thickness measurement values ​​of the two paths. By measuring the relative proportion of the film thickness in different regions, the process profile can be better characterized. In addition, the profile parameters can be controlled within ±1, which is convenient for subsequent calculations.

[0075] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0076] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0077] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0078] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0079] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0080] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of action steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0081] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0082] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0083] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0084] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0085] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0086] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0087] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for developing a thin film process, characterized in that: include: generating a plurality of random experimental groups according to the process parameters to be adjusted and the parameter ranges corresponding to the process parameters; performing a first process experiment based on the plurality of random experimental groups and obtaining a corresponding plurality of first process results, wherein the first process results include a process indicator and a first actual value corresponding to the process indicator, wherein the process indicator includes a process profile, and the first actual value corresponding to the process profile is determined based on thickness measurements of the film along a plurality of preset routing paths; A corresponding process window is determined according to the multiple random experimental groups and the multiple first process results, where the process window includes a target parameter range of the process parameter.

2. The method according to claim 1, characterized in that The plurality of routing paths include three circular paths having the same center and different radii.

3. The method according to claim 2, characterized in that The three circular paths include a first circular path, a second circular path, and a third circular path with successively increasing radii; the first actual value corresponding to the process profile includes a first profile parameter actual value and a second profile parameter actual value; The actual value of the first profile parameter is determined based on thickness measurements of the film along the first circular path and the second circular path; The actual value of the second profile parameter is determined based on thickness measurements of the film on the second circular path and the third circular path.

4. The method according to claim 3, characterized in that The actual value of the first profile parameter is calculated by the following formula: A1=(a2-a1) / (a2+a1); Wherein, A1 is the actual value of the first profile parameter, a1 is the average value of the thickness measurement values ​​of the film on the first circular path, and a2 is the average value of the thickness measurement values ​​of the film on the second circular path; The actual value of the second profile parameter is calculated by the following formula: A2=(a2-a3) / (a2+a3); Wherein, A2 is the actual value of the second profile parameter, a2 is the average value of the thickness measurement values ​​of the film on the second circular path, and a3 is the average value of the thickness measurement values ​​of the film on the third circular path.

5. The method according to claim 1, wherein The parameter range includes a parameter upper limit and a parameter lower limit. The multiple random experimental groups are generated according to the process parameters to be adjusted and the parameter ranges corresponding to the process parameters, including: The process parameters are each taken as a value in at least one of the following ways: each process parameter is taken as a value of the corresponding parameter upper limit and parameter lower limit, each process parameter is taken as a value of the center value of the corresponding parameter range, or one process parameter is taken as a value of the corresponding parameter upper limit and parameter lower limit, and the remaining process parameters are taken as the center value of the corresponding parameter range, to generate multiple regular experimental groups; The multiple regular experimental groups are randomly arranged to generate the multiple random experimental groups.

6. The method according to claim 1, characterized in that The determining corresponding process windows according to the multiple random experimental groups and the multiple first process results includes: generating corresponding process models according to the multiple random experimental groups and the multiple first process results; The corresponding process window is determined according to the process model and a preset target process result, where the target process result includes the process indicator and a range of expected values ​​corresponding to the process indicator.

7. The method according to claim 6, characterized in that Generating corresponding process models according to the multiple random experimental groups and the multiple first process results includes: The process model is generated by fitting using a least squares method according to the multiple random experimental groups and the multiple first process results.

8. The method according to claim 7, characterized in that Before determining the corresponding process window according to the process model and the preset target process result, the method further includes: Calculate the confidence level of each candidate process model generated during the fitting process; The candidate process model with a confidence equal to or greater than a preset confidence threshold is determined as the process model.

9. The method according to claim 1, characterized in that After determining corresponding process windows according to the plurality of random experimental groups and the plurality of first process results, the method further includes: Process validation is performed on the process model based on the process window.

10. The method according to claim 9, characterized in that The performing process verification on the process model based on the process window includes: performing a second process experiment based on the target parameter of the process parameter and obtaining a corresponding second process result, wherein the target parameter is within the target parameter range, and the second process result includes the process indicator and a second actual value corresponding to the process indicator; The process model is subjected to process verification according to the second process result and a target process result, wherein the target process result includes the process index and a range of expected values ​​corresponding to the process index.

11. A semiconductor process equipment, characterized in that: include: A controller, a radio frequency power supply, a chamber, and a shower head and a base arranged in the chamber, wherein the radio frequency power supply is used to output radio frequency power to the shower head and the base to dissociate the reaction gas in the chamber into plasma, the controller is arranged in a host computer and / or a slave computer, the controller includes at least one processor and at least one memory, the memory stores a computer program, and when the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 10 are implemented.

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