Antimony volatilization amount control method based on high-temperature time regulation and control

Abstract

The invention relates to the technical field of monocrystalline silicon drawing, in particular to an antimony volatilization amount control method based on high-temperature time regulation and control, which comprises the following steps: acquiring an antimony volatilization amount threshold value and stage temperature characteristics of each preset temperature control stage; for each temperature control stage, inputting the antimony volatilization amount threshold value and the stage temperature characteristics into a preset temperature control duration evaluation model to obtain the temperature control duration of the temperature control stage; acquiring real-time working conditions of drawing operation in each temperature control stage, and performing volatilization influence analysis on the real-time working conditions to obtain a real-time volatilization rate; on the basis of the real-time volatilization rate and the temperature control duration, the real-time antimony volatilization amount corresponding to the temperature control stage is obtained through calculation; and in response to the condition that the real-time antimony volatilization amount is greater than the antimony volatilization amount threshold value, calculating a volatilization amount overflow value between the two so as to determine a volatilization amount control strategy of the current temperature control stage and / or the subsequent temperature control stage, and executing the strategy. Accurate identification and targeted regulation and control of volatilization amount abnormity are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of single crystal silicon pulling, and in particular to a method for controlling antimony volatilization based on high temperature time regulation. Background Art

[0002] During the single crystal silicon pulling process, antimony, as an important N-type dopant, has a key impact on the resistivity uniformity and crystal quality of single crystal silicon due to its volatilization behavior. Due to its extremely low segregation coefficient and high volatilization constant, the volatilization rate of antimony will fluctuate significantly with changes in parameters such as temperature, furnace pressure, and gas flow rate during different pulling stages such as high-temperature melt, seeding, and equal diameter. If the volatilization amount is not properly controlled, it can easily lead to problems such as excessive resistivity difference between the head and tail of the single crystal silicon rod and reduced minority carrier lifetime, which seriously affect product performance.

[0003] Existing control methods mainly rely on fixed process parameter settings, such as the high-temperature duration range or adjusting single variables such as furnace pressure and argon flow rate; however, due to the lack of a quantitative correlation model between temperature characteristics and antimony volatilization, it is impossible to accurately evaluate the reasonable temperature control time under different temperature characteristics; at the same time, there is a lack of dynamic monitoring and analysis of the real-time working conditions of the pulling operation, making it difficult to adjust the control strategy according to the real-time volatilization rate; when the actual volatilization volume exceeds the preset threshold due to equipment differences, thermal field fluctuations and other factors, the existing methods are unable to promptly identify the volatilization volume overflow and implement targeted regulation, resulting in insufficient control accuracy of the resistivity uniformity of single crystal silicon and limited improvement in product yield. Summary of the Invention

[0004] The present invention provides an antimony volatilization control method based on high-temperature time regulation, which can achieve accurate identification and targeted regulation of volatilization abnormalities and can effectively solve the problems in the background technology.

[0005] In order to achieve the above object, the present invention provides a method for controlling the volatilization amount of antimony based on high temperature time regulation, comprising: Obtaining the antimony volatilization threshold and stage temperature characteristics of each preset temperature control stage; For each temperature control stage, the antimony volatilization threshold and the stage temperature characteristics are input into a preset temperature control duration evaluation model to obtain the temperature control duration of the temperature control stage; Obtaining the real-time working conditions of the drawing operation in each temperature control stage, and performing volatilization impact analysis thereon to obtain the real-time volatilization rate; Based on the real-time volatilization rate and the temperature control time, the real-time antimony volatilization amount corresponding to the temperature control stage is calculated; In response to the real-time antimony volatilization amount being greater than the antimony volatilization amount threshold, a volatilization amount overflow value between the two is calculated to determine and execute a volatilization amount control strategy for the current temperature control stage and / or subsequent temperature control stages.

[0006] In a possible design, obtaining the antimony volatilization threshold and stage temperature characteristics of each preset temperature control stage includes: Obtaining the temperature characteristics of a single crystal silicon pulling process and an antimony-doped raw material, and extracting resistivity characteristics of the single crystal silicon pulling process to obtain resistivity design requirements; According to the single crystal silicon pulling process and the temperature characteristics of the antimony-doped raw material, the pulling process is divided by temperature to obtain multiple temperature control stages; According to the resistivity design requirements, the antimony volatilization threshold and the stage temperature characteristics of each temperature control stage are determined.

[0007] In a possible design, the calculation formula of the temperature control time evaluation model is: ; in, Indicates the temperature control duration of the i-th temperature control stage; represents the antimony volatilization threshold value in the i-th temperature control stage; represents the process constant of the i-th temperature control stage; represents the stage temperature characteristics of the i-th temperature control stage; represents the activation energy of antimony volatilization; represents the gas constant; Represents a natural constant.

[0008] In a possible design, the real-time working conditions of the pulling operation include furnace pressure, protective gas flow rate and crystal pulling speed.

[0009] In one possible design, the real-time antimony volatilization amount corresponding to the temperature control stage is calculated based on the real-time volatilization rate and the temperature control duration, including: Based on real-time time, the temperature control stage is divided into the period in which the temperature control has occurred and the period in which the temperature control has not occurred; Performing segmented integration on the period of occurrence to calculate the antimony volatilization amount in the period of occurrence; Performing a rolling forecast for the non-occurrence period to calculate the antimony volatilization amount during the non-occurrence period; The antimony volatilization amount during the period in which antimony volatilization has occurred and the antimony volatilization amount during the period in which antimony volatilization has not occurred are summed to obtain the real-time antimony volatilization amount corresponding to the temperature control stage.

[0010] In a possible design, performing segmented integration on the occurred period to calculate the antimony volatilization amount in the occurred period includes: Performing mutation point detection on the real-time operating condition during the period of occurrence to obtain at least one operating condition mutation point; Divide the occurred period into multiple intervals based on the boundary of the operating condition mutation point; In each interval, the volatilization rate of the preset step length is calculated using the preset volatilization impact analysis model to obtain the volatilization rate sequence of the interval; Based on the volatilization rate sequence, the integrated antimony volatilization amount of each interval is calculated, and the antimony volatilization amounts of all intervals are summed up to obtain the antimony volatilization amount of the occurred period.

[0011] In one possible design, the integrated volatility is calculated for each interval using the following formula: ; in, represents the integrated volatility of the ith interval within the period of occurrence; Indicates the preset step size; represents the number of volatilization rate sequences in the i-th interval; represents the kth volatility rate in the volatility rate sequence in the i-th interval.

[0012] In a possible design, when dividing the occurred time period into multiple sub-intervals with the mutation point as the boundary, if the interval between adjacent change points is less than a preset interval threshold, they are merged into the same interval.

[0013] In a possible design, a rolling forecast is performed for the non-occurrence period to calculate the antimony volatilization amount in the non-occurrence period, including: The time series prediction model is used to predict the trend of operating parameters. The input data of the time series prediction model are the operating parameters within the most recent preset time window; the output data are the operating parameters within the future preset time period; Every time the preset time is advanced, the input data is updated with the latest data, and the operating parameters within the future preset time are re-predicted; The above-mentioned time series prediction model is used to make a step-by-step prediction of the volatility during the period when no volatility occurs, and the prediction results are sorted to obtain the working condition parameter prediction sequence; Generate future volatilization rate sequence based on the prediction sequence of operating condition parameters; Based on the future volatilization rate series, calculate the antimony volatilization amount in the period when no volatilization occurs.

[0014] In one possible design, the formula for calculating the antimony volatilization amount during the non-occurrence period is: ; in, represents the amount of antimony volatilization during the period when no volatilization occurs; j represents the amount of data in the future volatilization rate series; represents the kth volatility rate in the future volatility rate sequence; Indicates the preset duration.

[0015] The technical solution of the present invention can achieve the following technical effects: By combining the antimony volatilization threshold and the stage temperature characteristics, the preset temperature control time evaluation model is used to output the precise temperature control time, and a dynamic quantitative association between the temperature characteristics and the antimony volatilization is established, so that the temperature control time is transformed from an empirical setting to a model-driven one; by real-time collection of the pulling operation conditions and analysis of the volatilization impact, the static preset parameters are combined with the dynamic real-time data; the real-time volatilization rate and the temperature control time are linked and calculated to form a dynamic control chain of monitoring, analysis, prediction and adjustment; compared with the existing lag mode of post-detection plus manual adjustment, this method can provide early warning before the volatilization deviates from the threshold, reducing crystal quality defects caused by response delays; by comparing the real-time volatilization amount with the threshold and calculating the overflow, accurate identification and targeted regulation of volatilization abnormalities can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The figure is a logic flow chart of the antimony volatilization amount control method based on high temperature time regulation in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The present application is described below in conjunction with the accompanying drawings.

[0018] like Figure 1 As shown, the method for controlling the volatilization amount of antimony based on high temperature time regulation of the present invention specifically includes the following steps: Step S100, obtaining the antimony volatilization threshold and stage temperature characteristics of each preset temperature control stage; Step S200: For each temperature control stage, input the antimony volatilization threshold and the stage temperature characteristics into a preset temperature control duration evaluation model to obtain the temperature control duration of the temperature control stage, where the temperature control duration represents the duration of maintaining the stage temperature characteristics in the temperature control stage; Step S300: obtaining the real-time working conditions of the drawing operation in each temperature control stage, and performing volatilization impact analysis on the working conditions to obtain the real-time volatilization rate; Step S400: Calculating the real-time antimony volatilization amount corresponding to the temperature control stage based on the real-time volatilization rate and the temperature control duration; Step S500: In response to the real-time antimony volatilization amount being greater than the antimony volatilization amount threshold, a volatilization amount overflow value between the two is calculated to determine and execute a volatilization amount control strategy for the current temperature control stage and / or subsequent temperature control stages.

[0019] In this embodiment, by combining the antimony volatilization threshold with the stage temperature characteristics, a preset temperature control duration evaluation model is used to output a precise temperature control duration. This changes the existing extensive model of fixed process parameters combined with single variable adjustment to establish a dynamic quantitative association between temperature characteristics and antimony volatilization. This shifts the temperature control duration from being empirically set to being model-driven. For example, in the high-temperature melt stage, the model can automatically calculate the optimal holding time based on the real-time temperature curve to ensure doping uniformity while avoiding excessive volatilization, thus solving the problem of blind temperature control caused by the lack of quantitative association. By collecting the working conditions of the drawing operation in real time and analyzing the impact of volatilization, the static preset parameters are combined with the dynamic real-time data. The existing method only relies on preset thresholds and cannot cope with unexpected situations such as equipment differences or thermal field fluctuations. For example, when the argon flow rate fluctuates due to equipment aging in a certain batch of drawing, it can identify and adjust the temperature control time in real time to avoid the overflow of volatilization caused by the failure to capture the equipment differences. The real-time volatilization rate and the temperature control time are linked to form a dynamic control chain of monitoring, analysis, prediction and adjustment. Compared with the existing hysteresis mode of post-detection plus manual adjustment, this method can provide early warning before the volatilization volume deviates from the threshold, reducing crystal quality defects caused by response delays. By comparing real-time volatile volume with the threshold and calculating the overflow, accurate identification and targeted regulation of volatile volume anomalies can be achieved. Existing methods lack quantitative evaluation of overflows and often adopt a one-size-fits-all adjustment approach, which may exacerbate volatile imbalances in other stages. This method dynamically selects a control strategy based on the overflow size and stage characteristics, avoiding the limitations of single variable adjustment. For example, if the volatile volume exceeds the threshold due to excessively high temperature in the seeding stage, the overflow can be compensated by reducing the heating rate in the equal diameter stage, rather than blindly extending the high-temperature time, thereby balancing the volatile volume distribution in each stage. Quantitative overflow calculation and multi-stage strategies work together to form an adaptive control network. Each stage is no longer an independent control unit, but instead forms a global optimization mechanism through overflow transmission.

[0020] In some embodiments of the present invention, step S100 is specifically implemented as follows: Step S110, obtaining the temperature characteristics of the single crystal silicon pulling process and the antimony-doped raw material, and extracting the resistivity characteristics of the single crystal silicon pulling process to obtain the resistivity design requirements, specifically; Step S111: Obtaining the temperature characteristics of the single crystal silicon pulling process. The single crystal silicon pulling process involves multiple stages, including high-temperature melting, seeding, equalizing, and finishing. Each stage has specific temperature requirements. For example, in the high-temperature melting stage, the silicon material needs to be heated to approximately 1420°C to completely melt it. In the seeding stage, the temperature will be slightly lowered to ensure stable growth of the crystal. In the equalizing stage, the temperature needs to be precisely controlled to maintain uniform crystal growth. The above temperature characteristics are basic parameters of the single crystal silicon pulling process and can be obtained through process documents or actual measurement data. Step S112: Obtain the temperature characteristics of the antimony-doped raw material. Antimony, as an N-type dopant, will volatilize at high temperatures. Its volatilization rate is closely related to temperature. Generally, the higher the temperature, the faster the antimony volatilization rate. Obtain the volatilization characteristic curve of antimony at different temperatures through experiments or literature data; Step S113: Resistivity feature extraction. Based on the specifications of the single crystal silicon product, such as the target resistivity range and uniformity requirements of the N-type silicon wafer, key indicators for resistivity design are extracted, such as the head-to-tail resistivity difference threshold and the resistivity fluctuation range of the whole rod. In combination with industry standards or customer needs, the resistivity design requirements are converted into control targets for the antimony volatilization amount. For example, the total volatilization amount must be controlled within a set ratio of the initial doping amount to ensure that the final resistivity meets the standard.

[0021] Step S120: Divide the pulling process by temperature based on the single crystal silicon pulling process and the temperature characteristics of the antimony-doped raw material to obtain multiple temperature control stages; combine the temperature characteristics of the single crystal silicon pulling process and the volatilization characteristics of antimony obtained in step S110 to divide the pulling process into multiple temperature control stages; for example, based on the temperature range, the pulling process can be divided into the following stages: High-temperature melting stage: The temperature range is 1400℃~1450℃. The main purpose of this stage is to completely melt the silicon material. The volatilization rate of antimony is relatively high in this stage. Seeding stage: The temperature range is 1350℃~1400℃. The temperature in this stage is slightly lower to ensure the stable growth of crystals and the volatilization rate of antimony is relatively reduced. Isodiametric stage: The temperature range is 1300℃~1350℃. The temperature in this stage needs to be precisely controlled to maintain uniform crystal growth and a relatively stable volatilization rate of antimony. Finishing stage: The temperature range is 1250℃~1300℃. In this stage, the temperature is further lowered to complete the finishing work of the crystal, and the volatilization rate of antimony is low; By dividing the drawing process into multiple temperature-controlled stages, the amount of antimony volatilization can be controlled more finely. In each stage, a corresponding temperature control strategy can be formulated based on the temperature characteristics and the volatilization characteristics of antimony, thereby improving the uniformity of the resistivity of single crystal silicon and the crystal quality.

[0022] Step S130: Determine the antimony volatilization threshold and stage temperature characteristics for each temperature control stage based on the resistivity design requirements. Allocate the total allowable volatilization amount to each temperature control stage through reverse engineering based on the resistivity design requirements determined in step S110. For example, assuming that the resistivity difference between the head and tail of the single crystal silicon rod is required to be ≤5%, calculate the maximum allowable volatilization amount for each stage based on the relationship between doping concentration and resistivity. For example, the allowable volatilization amount for the high-temperature melt stage is 60% of the total volatilization amount, and the allowable volatilization amount for the constant diameter stage is 30%. Based on the volatilization rate characteristics of each stage, such as the high-temperature stage volatilization rate, differentiated thresholds are set: because the volatilization amount has a greater impact on the total doping concentration, the threshold value for the high-temperature stage is more stringent, while the threshold value for the low-temperature stage is relatively loose. In step S120, the drawing process has been divided into multiple temperature control stages, each stage has its own specific temperature range and temperature change law; for example, in the high-temperature melt stage, the temperature range is 1400℃~1450℃, and the temperature change law may be first quickly heating up to 1450℃, and then slowly cooling down to 1400℃ and maintaining for a period of time; in the seeding stage, the temperature range is 1350℃~1400℃, and the temperature change law may be slowly cooling down from 1400℃ to 1350℃ and maintaining stability, etc.; the stage temperature characteristics are set for each temperature control stage, and any one or more of the target temperature value, temperature fluctuation range and heating / cooling rate are coupled.

[0023] In some embodiments of the present invention, the antimony volatilization threshold and stage temperature characteristics of each temperature control stage are obtained in step S100. Then, for each temperature control stage, the temperature control duration is calculated using a temperature control duration evaluation model. The temperature control duration evaluation model quantifies the relationship between temperature, volatilization, and time through a specific formula to achieve accurate temperature control duration calculation. Specifically, the calculation formula of the temperature control duration evaluation model is: ; in, represents the temperature control duration of the i-th temperature control stage, that is, the time during which the specific temperature characteristics are maintained in this temperature control stage. It is the control parameter output by the temperature control duration evaluation model; The antimony volatilization threshold value in the i-th temperature control stage is determined in step S130 according to the resistivity design requirements and represents the maximum antimony volatilization amount allowed in this temperature control stage; It represents the process constant of the i-th temperature control stage, reflecting the comprehensive influence of other process conditions on the volatilization rate except temperature in this stage. It is determined by the previous process calibration. Without considering the influence of temperature on the volatilization rate, Used to determine the basic volatilization rate, its physical meaning is the basic volatilization amount per unit time; represents the stage temperature characteristics of the i-th temperature control stage; It represents the activation energy of antimony volatilization, a physical quantity that characterizes the difficulty of antimony volatilization. It is determined by the material properties and reflects the energy barrier of the volatilization process. Represents the gas constant, a universal physical constant, used as a conversion factor in the formula relating temperature to energy; Represents a natural constant.

[0024] The above formula establishes a strong correlation between temperature and volatilization rate through the exponential term, that is, the higher the temperature, the higher the exponential term. The larger the value of , the larger the denominator, resulting in a shorter temperature control time. This indicates that in the high temperature stage, the antimony volatilization rate is fast and the time required to reach the volatilization threshold is shorter; on the contrary, it increases in the low temperature stage, which is in line with the physical law of antimony volatilization.

[0025] In this embodiment, the calculated temperature control time will be used to guide the actual drawing process to ensure that the volatilization amount of antimony is precisely controlled in each temperature control stage; the temperature control time is calculated based on the preset antimony volatilization amount threshold and temperature characteristics, which can help the operator control the temperature more accurately during the drawing process to avoid excessive or insufficient volatilization of antimony.

[0026] In some embodiments of the present invention, during the single crystal silicon pulling process, real-time operating data related to the antimony volatilization rate covers multiple aspects and needs to be accurately collected by various sensors. It should be noted that the real-time operating conditions of the pulling operation do not include temperature conditions, because the temperature is controlled according to the stage temperature characteristics determined in step S130. Therefore, the real-time operating conditions of the pulling operation include: Furnace pressure: The pressure inside the furnace is obtained in real time through a pressure sensor. Changes in furnace pressure affect the motion of gas molecules and their interaction with antimony, which in turn affects the volatilization of antimony. For example, excessively high furnace pressure may inhibit the volatilization of antimony, while excessively low furnace pressure may accelerate its volatilization. Gas flow rate: Use a flow meter to accurately measure the flow rate of shielding gas and other gases that may participate in the reaction entering the furnace. Changes in gas flow rate will change the gas environment in the furnace, affecting the diffusion and volatilization process of antimony atoms. For example, appropriately increasing the argon flow rate may dilute other components in the furnace that may inhibit antimony volatilization to a certain extent, thereby affecting the volatilization rate of antimony. Crystal pulling speed: The control system of the crystal pulling equipment can provide real-time feedback on the crystal pulling speed information. Different crystal pulling speeds will cause the state of the silicon melt surface to change, thereby affecting the concentration distribution and volatilization of antimony on the melt surface. A faster crystal pulling speed may cause the melt surface to update faster, affecting the accumulation and volatilization of antimony atoms.

[0027] Furthermore, the collected original real-time operating condition data may have problems such as noise interference and data anomalies, and preprocessing is required to improve the accuracy and reliability of the data; specifically, for continuously changing analog signal data such as furnace pressure and gas flow, digital filtering algorithms are used to remove high-frequency noise and smooth the data curve so that the data can better reflect the actual operating condition changes; outliers in the data are identified through statistical analysis methods or threshold judgments based on historical data; for outliers that obviously deviate from the normal range, methods such as elimination and interpolation can be used according to the specific situation to ensure the accuracy of subsequent analysis.

[0028] Furthermore, based on the collected and preprocessed real-time operating data, a volatilization impact analysis model was established to evaluate the impact of various factors on the antimony volatilization rate. Taking into account the complex nonlinear relationship between the various influencing factors, a neural network model was constructed with furnace pressure, gas flow rate, and crystal pulling speed as input layer nodes and the antimony volatilization rate as the output layer node. The network was trained using a small amount of training sample data, and the weights and thresholds were adjusted to achieve an approximate assessment of the antimony volatilization rate. Specifically, a large amount of historical data under different working conditions is collected, including furnace pressure, gas flow, crystal pulling speed and the corresponding antimony volatilization rate measurement values; the volatilization impact analysis model automatically extracts the complex nonlinear relationship between input parameters (furnace pressure, gas flow, crystal pulling speed) and output parameters (antimony volatilization rate) by learning from a large amount of historical data; for example, a certain combination of furnace pressure and gas flow has a specific influence pattern on the antimony volatilization rate, which is difficult to accurately describe with a simple mathematical formula, but the neural network can capture this relationship by learning the patterns in the data; the activation function is used to realize the nonlinear mapping from input to output, so that the model can handle the complex interactions between the input parameters and more accurately reflect the changing law of the antimony volatilization rate in actual conditions.

[0029] In some embodiments of the present invention, since the volatilization rate may change dynamically over time in actual production, such as due to furnace pressure fluctuations, gas flow adjustment, etc., it is necessary to adopt a segmented integration combined with a rolling prediction method to divide the temperature control stage into a period in which the volatilization has occurred and a period in which the volatilization has not occurred, and calculate the volatilization amount separately and then sum them up.

[0030] Perform segmented integration for the period of occurrence and calculate the antimony volatilization amount during the period of occurrence. The specific implementation is as follows: The sliding window variance analysis method is used to detect mutation points in real-time operating condition data such as furnace pressure, gas flow, and crystal pulling speed. If the furnace pressure drops suddenly and exceeds the threshold, it is determined to be a condition mutation point. The mutation point is used as the boundary to divide the occurred period into multiple sub-intervals. If the interval between adjacent change points is less than 5 seconds, they are merged into the same interval. In each interval, the volatility impact analysis model of step S300 is called to calculate the volatility rate of a preset step length to obtain the volatility rate sequence of the interval; Calculate the integrated volatility for each interval using the following formula: ; in, represents the integrated volatility of the ith interval within the period of occurrence; Indicates the preset step size; represents the number of volatilization rate sequences in the i-th interval; represents the kth volatility rate in the volatility rate sequence in the i-th interval; The formula for calculating the antimony volatilization amount during the period of occurrence is:

[0031] in, It represents the amount of antimony volatilization during the period of occurrence, and n represents the number of intervals.

[0032] Volatility is predicted for periods where no emissions have occurred. A time series prediction model is used to predict the trend of operating parameters. The input data for the time series prediction model is the operating parameters for the last 60 seconds. The output data is the operating parameters for a preset future duration, namely, furnace pressure, gas flow rate, and crystal pulling speed. Each time the preset duration is advanced, the input window is updated with the latest data, and the operating parameters for the preset future duration are re-predicted. The above-mentioned time series prediction model is used to make a step-by-step prediction of the volatility during the period when no volatility occurs, and the prediction results are sorted to obtain the working condition parameter prediction sequence; Input the operating condition parameter prediction sequence into the neural network model of step S300 to output the future volatilization rate sequence; The calculation formula for the antimony volatilization amount during the period without antimony volatilization is: ; in, represents the amount of antimony volatilization during the period when no volatilization occurs; j represents the amount of data in the future volatilization rate series; represents the kth volatility rate in the future volatility rate sequence; Indicates the preset duration.

[0033] The calculation formula for the real-time antimony volatilization amount during the temperature control stage is: ; in, Indicates the real-time antimony volatilization amount during the temperature control stage.

[0034] In this embodiment, a piecewise integration method combined with a rolling prediction method is used to divide the temperature control stage into a period where antimony volatilization has occurred and a period where antimony volatilization has not occurred. The antimony volatilization amount is calculated and predicted separately, allowing for a more accurate assessment of the actual antimony volatilization amount in each temperature control stage. A sliding window variance analysis method is used to detect operating condition mutation points in the period where antimony volatilization has occurred, and a volatilization impact analysis model is used to calculate the volatilization rate sequence within each interval, thereby more accurately calculating the antimony volatilization amount that has occurred. During the period where antimony volatilization has not occurred, a time series prediction model is used to predict the operating condition parameter trends, and a neural network model is used to output the future volatilization rate sequence, thereby predicting the antimony volatilization amount that has not occurred, thereby improving the prediction accuracy of the antimony volatilization amount. Due to the use of a rolling prediction method, the input window is updated with the latest data every time a preset time period is advanced. This method can respond to changes in operating condition parameters during the production process in real time, and promptly adjust the predictions of volatilization amount and future operating conditions. This allows the control strategy of the production process to more closely match the actual operating conditions and enhance the adaptability of the production process to various changes.

[0035] In some embodiments of the present invention, when the real-time antimony volatilization amount is greater than the antimony volatilization amount threshold, the difference between the two, i.e., the volatilization amount overflow, is calculated; based on the size of the volatilization amount overflow and the situation in the current drawing stage, a corresponding control strategy is determined; the control strategy includes adjusting the parameters of the current temperature control stage, and if the current temperature control stage cannot completely eliminate the impact of the volatilization amount overflow, or in order to avoid further exceeding the volatilization amount in the subsequent stage, it is necessary to adjust the process parameters of the subsequent temperature control stage.

[0036] Strategies for adjusting parameters in the current temperature control phase include: Temperature adjustment: If the temperature has a significant impact on the antimony volatilization rate and the current temperature is within the adjustable range, the temperature can be appropriately lowered to slow down the antimony volatilization rate. For example, during the high-temperature melting stage, if the temperature is slightly higher than the set value and the volatilization overflow is large, the temperature can be lowered by 5-10°C. However, it should be noted that the temperature adjustment should not affect the melting effect of the silicon material. Furnace pressure adjustment: Based on the relationship between furnace pressure and antimony volatilization rate, the furnace pressure can be appropriately increased to suppress antimony volatilization. For example, if the furnace pressure is lower than the normal range, resulting in excessive volatilization, the furnace pressure can be slowly increased to an appropriate level. However, excessive furnace pressure should be avoided to prevent adverse effects on equipment and crystal growth. Gas flow adjustment: Increase or decrease the flow of protective gas to change the gas environment in the furnace, thereby affecting the volatilization of antimony; for example, when it is found that the overflow of volatilization is caused by insufficient gas flow, the argon flow can be appropriately increased, but it must be ensured that the change in gas flow does not cause instability in the thermal field.

[0037] Strategies for adjusting parameters in subsequent temperature control phases include: Temperature control time: Based on the volatility overflow in the current stage, the possible volatility in the subsequent stages is predicted, and the temperature control time in the subsequent stages is adjusted accordingly. For example, if the volatility overflow in the current stage is large, the temperature control time in the subsequent equal diameter stage may need to be shortened to ensure that the total volatility of antimony in the entire drawing process is within a reasonable range. Temperature setting: Optimize the temperature setting in subsequent stages to better control the volatilization of antimony. For example, in the seeding stage, if the volatilization in the previous stage is too much, the temperature setting value of the seeding stage can be appropriately lowered, but the stable growth of the crystal must be ensured. Other parameters: Based on actual conditions, other parameters such as furnace pressure and gas flow rate in subsequent stages are adjusted to achieve precise control of antimony volatilization.

[0038] After determining the control strategy, the adjustment parameters should be sent to the control system of the crystal pulling equipment in a timely manner to ensure that the equipment operates according to the new parameters; in the process of implementing the control strategy, the real-time operating data and changes in the antimony volatilization rate should be closely monitored, and the control strategy should be further adjusted according to the actual situation to ensure that the antimony volatilization amount is always under control.

[0039] In this embodiment, the parameters of the current and subsequent stages are flexibly adjusted based on the overflow value of the volatilization volume, achieving a highly targeted approach. During the current temperature control stage, excessive antimony volatilization is promptly suppressed by adjusting the temperature, furnace pressure, and gas flow rate. Simultaneously, to prevent further volatilization exceeding the specified limit in subsequent stages, parameters such as the temperature control duration and temperature are optimized in subsequent temperature control stages. This allows for comprehensive control of the volatilization volume, avoiding the drawbacks of traditional methods of lagging overflow control. This allows for precise control of the antimony volatilization volume, effectively reducing the resistivity difference between the head and tail of the single crystal silicon, and improving crystal quality and product yield.

[0040] Certain steps in the above method embodiments may be equivalently replaced with other possible steps. Alternatively, certain steps in the method embodiments may be optional and may be deleted in certain usage scenarios. Alternatively, other possible steps may be added to the method embodiments. Furthermore, the various method embodiments may be implemented separately or in combination.

[0041] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for controlling antimony volatilization based on high temperature time regulation, characterized in that: include: Obtaining the antimony volatilization threshold and stage temperature characteristics of each preset temperature control stage; For each temperature control stage, the antimony volatilization threshold and the stage temperature characteristics are input into a preset temperature control duration evaluation model to obtain the temperature control duration of the temperature control stage; Obtaining the real-time working conditions of the drawing operation in each temperature control stage, and performing volatilization impact analysis thereon to obtain the real-time volatilization rate; Based on the real-time volatilization rate and the temperature control time, the real-time antimony volatilization amount corresponding to the temperature control stage is calculated; In response to the real-time antimony volatilization amount being greater than the antimony volatilization amount threshold, a volatilization amount overflow value between the two is calculated to determine and execute a volatilization amount control strategy for the current temperature control stage and / or subsequent temperature control stages.

2. The method for controlling antimony volatilization based on high temperature time regulation according to claim 1, characterized in that: Obtain the antimony volatilization threshold and stage temperature characteristics of each preset temperature control stage, including: Obtaining the temperature characteristics of a single crystal silicon pulling process and an antimony-doped raw material, and extracting resistivity characteristics of the single crystal silicon pulling process to obtain resistivity design requirements; According to the single crystal silicon pulling process and the temperature characteristics of the antimony-doped raw material, the pulling process is divided by temperature to obtain multiple temperature control stages; According to the resistivity design requirements, the antimony volatilization threshold and the stage temperature characteristics of each temperature control stage are determined.

3. The method for controlling antimony volatilization based on high temperature time regulation according to claim 2, characterized in that: The calculation formula of the temperature control time evaluation model is: ； in, Indicates the temperature control duration of the i-th temperature control stage; represents the antimony volatilization threshold value in the i-th temperature control stage; represents the process constant of the i-th temperature control stage; represents the stage temperature characteristics of the i-th temperature control stage; represents the activation energy of antimony volatilization; represents the gas constant; Represents a natural constant.

4. The method for controlling antimony volatilization based on high temperature time regulation according to claim 1, characterized in that: The real-time working conditions of the pulling operation include furnace pressure, protective gas flow rate and crystal pulling speed.

5. The method for controlling the volatilization amount of antimony based on high temperature time regulation according to claim 4, characterized in that: Based on the real-time volatilization rate and the temperature control time, the real-time antimony volatilization amount corresponding to the temperature control stage is calculated, including: Based on real-time time, the temperature control stage is divided into the period in which the temperature control has occurred and the period in which the temperature control has not occurred; Performing segmented integration on the period of occurrence to calculate the antimony volatilization amount in the period of occurrence; Performing a rolling forecast for the non-occurrence period to calculate the antimony volatilization amount during the non-occurrence period; The antimony volatilization amount during the period in which antimony volatilization has occurred and the antimony volatilization amount during the period in which antimony volatilization has not occurred are summed to obtain the real-time antimony volatilization amount corresponding to the temperature control stage.

6. The method for controlling antimony volatilization based on high temperature time regulation according to claim 5, characterized in that: Performing segmented integration on the period of occurrence to calculate the antimony volatilization amount of the period of occurrence, including: Performing mutation point detection on the real-time operating condition during the period of occurrence to obtain at least one operating condition mutation point; Divide the occurred period into multiple intervals based on the boundary of the operating condition mutation point; In each interval, the volatilization rate of the preset step length is calculated using the preset volatilization impact analysis model to obtain the volatilization rate sequence of the interval; Based on the volatilization rate sequence, the integrated antimony volatilization amount of each interval is calculated, and the antimony volatilization amounts of all intervals are summed up to obtain the antimony volatilization amount of the occurred period.

7. The method for controlling antimony volatilization based on high temperature time regulation according to claim 6, characterized in that: Calculate the integrated volatility for each interval using the following formula: ； in, represents the integrated volatility of the ith interval within the period of occurrence; Indicates the preset step size; represents the number of volatilization rate sequences in the i-th interval; represents the kth volatility rate in the volatility rate sequence in the i-th interval.

8. The method for controlling antimony volatilization based on high temperature time regulation according to claim 6, characterized in that: In the process of dividing the occurred period into multiple sub-intervals with the mutation point as the boundary, if the interval between adjacent change points is less than the preset interval threshold, they are merged into the same interval.

9. The method for controlling antimony volatilization based on high temperature time regulation according to claim 7, characterized in that: Perform rolling forecasts for the non-occurrence period and calculate the antimony volatilization amount during the non-occurrence period, including: The time series prediction model is used to predict the trend of operating parameters. The input data of the time series prediction model are the operating parameters within the most recent preset time window; the output data are the operating parameters within the future preset time period; Every time the preset time is advanced, the input data is updated with the latest data, and the operating parameters within the future preset time are re-predicted; The above-mentioned time series prediction model is used to make a step-by-step prediction of the volatility during the period when no volatility occurs, and the prediction results are sorted to obtain the working condition parameter prediction sequence; Generate future volatilization rate sequence based on the prediction sequence of operating condition parameters; Based on the future volatilization rate series, calculate the antimony volatilization amount in the period when no volatilization occurs.

10. The method for controlling the volatilization amount of antimony based on high temperature time regulation according to claim 9, characterized in that: The formula for calculating the antimony volatilization amount during the period without antimony volatilization is: ； in, represents the amount of antimony volatilization during the period when no volatilization occurs; j represents the amount of data in the future volatilization rate series; represents the kth volatility rate in the future volatility rate sequence; Indicates the preset duration.

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