Method for improving growth quality of PVT method silicon carbide single crystal
By monitoring and adjusting the temperature gradient and fluctuations during the PVT method for silicon carbide single crystal growth, the problem of poor crystal growth quality was solved, and high-quality, defect-free silicon carbide single crystal growth was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SU ZHOU QING YAN BAN DAO TI KE JI YOU XIAN GONG SI
- Filing Date
- 2026-01-23
- Publication Date
- 2026-04-28
AI Technical Summary
During the PVT method for silicon carbide single crystal growth, the crystal growth quality is affected by temperature gradient and temperature fluctuation, resulting in problems such as high defect and impurity content and poor growth uniformity.
The temperature parameters of the growth chamber are monitored by sensors, the axial temperature gradient and fluctuations are analyzed, corresponding signals and evaluation values are generated, and the temperature gradient and fluctuations are adjusted to ensure that the temperature gradient is reasonable and stable.
This improves the crystallization quality of silicon carbide single crystals, reduces defects, enhances the stability and repeatability of the growth process, and ensures consistency in each batch of production.
Smart Images
Figure CN121931602A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of silicon carbide single crystal growth technology, specifically a method for improving the growth quality of silicon carbide single crystals using the PVT method. Background Technology
[0002] With the rapid development of modern technology, silicon carbide (SiC), as a wide-bandgap semiconductor material, has shown great application potential in many fields such as power electronics, optoelectronics, and radio frequency communications due to its excellent electrical, thermal, and mechanical properties. Physical vapor transport (PVT) is currently one of the mainstream methods for preparing high-quality silicon carbide single crystals. However, in actual growth processes, due to the influence of various factors, it is still difficult to further improve the crystal growth quality. For example, during the PVT method for silicon carbide single crystal growth, temperature gradients and temperature fluctuations lead to defects, high impurity content, and poor growth uniformity in the resulting crystals, all of which reduce the quality of silicon carbide single crystal growth. In the silicon carbide single crystal growth process, the axial temperature gradient is analyzed, and the magnitude and correlation of temperature fluctuations in the axial temperature gradient are analyzed to determine whether the axial temperature gradient of the growth chamber meets the requirements for silicon carbide single crystal growth. This facilitates the precise pre-setting of the temperature gradient, creates ideal conditions for the stable transport and uniform deposition of gaseous substances generated by silicon carbide sublimation, effectively reduces crystal growth defects caused by unreasonable temperature gradients, and significantly improves the crystallization quality of silicon carbide single crystals. Summary of the Invention
[0003] The purpose of this invention is to provide a method for improving the quality of silicon carbide single crystal growth by PVT method, so as to solve at least one of the above-mentioned problems in the prior art.
[0004] In a first aspect, the present invention provides a method for improving the growth quality of silicon carbide single crystals using the PVT method, the specific steps of which are as follows: Step 1: Obtain the temperature parameters of the growth chamber through sensors, and obtain the gradient characterization value by analyzing the axial temperature gradient inside the growth chamber; Step 2: Compare the gradient characterization value with the gradient characterization threshold, and determine whether the axial temperature gradient of the growth chamber is qualified based on the comparison result. If it is qualified, generate a gradient qualification signal. Step 3: Based on the gradient qualified signal, analyze the temperature fluctuation of each temperature monitoring point to obtain the fluctuation evaluation value; compare the fluctuation evaluation value with the fluctuation evaluation threshold, and determine whether the temperature stability of the temperature monitoring point is qualified according to the comparison result. If so, generate a fluctuation stability signal. Step 4: Based on the stable fluctuation signal, analyze the correlation of temperature fluctuations between adjacent monitoring temperature points to obtain a comprehensive correlation evaluation value; Step 5: Compare the comprehensive correlation evaluation value with the comprehensive correlation evaluation threshold. Based on the comparison result, determine whether the axial temperature gradient needs to be adjusted. If so, generate an adjustment signal. Based on the adjustment signal, adjust the axial temperature gradient.
[0005] Secondly, this invention provides a system for improving the quality of silicon carbide single crystal growth using the PVT method, with the following specific modules: Gradient parameter acquisition module: acquires the temperature parameters of the growth chamber through sensors, and obtains the gradient characterization value by analyzing the axial temperature gradient inside the growth chamber; Gradient parameter analysis module: compares the gradient characterization value with the gradient characterization threshold, and determines whether the axial temperature gradient of the growth chamber is qualified based on the comparison result. If it is qualified, a gradient qualification signal is generated. Fluctuation parameter analysis module: Based on the gradient qualified signal, analyze the temperature fluctuation of each temperature monitoring point to obtain the fluctuation evaluation value; compare the fluctuation evaluation value with the fluctuation evaluation threshold, and determine whether the temperature stability of the temperature monitoring point is qualified according to the comparison result. If it is qualified, generate the fluctuation stability signal. Correlation parameter acquisition module: Based on the fluctuation stability signal, analyze the correlation of temperature fluctuations between adjacent monitoring temperature points to obtain a comprehensive correlation evaluation value; Correlation parameter analysis module: compares the comprehensive correlation evaluation value with the comprehensive correlation evaluation threshold, determines whether the axial temperature gradient needs to be adjusted based on the comparison result, and generates an adjustment signal based on the adjustment signal; and adjusts the axial temperature gradient based on the adjustment signal.
[0006] The beneficial effects of this invention are: 1. By monitoring the temperature gradient along the axial direction of the growth chamber, the axial temperature gradient is analyzed to determine whether the temperature difference at all monitoring points along the growth axis is uniform, and the rationality of the axial temperature gradient in the growth chamber is comprehensively analyzed. Under a reasonable axial temperature gradient in the growth chamber, the gaseous substances generated by the sublimation of silicon carbide raw materials can be transported to the seed crystal area at a stable rate and deposited uniformly on the seed crystal surface, so that the crystal grows at a constant speed in the axial direction, which helps to form high-quality, defect-free silicon carbide single crystals.
[0007] 2. Analyzing temperature fluctuations at various temperature monitoring points enables timely capture and correction of temperature gradient deviations, ensuring the entire growth process is conducted within a stable temperature gradient environment; determining whether the axial temperature gradient is acceptable, and analyzing temperature fluctuations at monitoring points when the temperature gradient is acceptable; avoiding quality degradation of PVT-based silicon carbide single crystal growth due to temperature fluctuations; and greatly enhancing the stability and repeatability of the growth process, resulting in highly consistent quality of silicon carbide single crystals produced in each batch.
[0008] 3. By analyzing the correlation of temperature fluctuations between monitoring temperature points, when the correlation is weak, the temperature fluctuations of the monitoring temperature points are adjusted accordingly to keep the axial temperature gradient relatively stable. This ensures that the gaseous material transport force provided by the axial temperature gradient can remain at a relatively stable level during fluctuations. This allows the gaseous material generated by the sublimation of silicon carbide raw materials to move towards the seed crystal area at a relatively stable rate and direction, which is beneficial for forming a uniform deposition on the seed crystal surface, thereby improving the growth quality of silicon carbide single crystals. Attached Figure Description
[0009] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0010] Figure 1 This is a flowchart of a method for improving the growth quality of silicon carbide single crystals using the PVT method, provided in Embodiment 1 of the present invention. Figure 2 This is a flowchart of obtaining gradient characterization values for a method to improve the growth quality of silicon carbide single crystals using the PVT method, provided in Embodiment 2 of the present invention. Figure 3 This is a flowchart of a method for obtaining fluctuation assessment values to improve the growth quality of silicon carbide single crystals using the PVT method, provided in Embodiment 3 of the present invention. Figure 4 This is a flowchart of a method for obtaining a comprehensive correlation evaluation value to improve the growth quality of silicon carbide single crystals using the PVT method, provided in Embodiment 4 of the present invention. Detailed Implementation
[0011] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.
[0012] Example 1 like Figure 1 As shown in the figure, an embodiment of the present invention provides a method for improving the growth quality of silicon carbide single crystals using the PVT method, which specifically includes the following steps: S1: Raw material optimization; A multi-stage purification process is adopted. First, a chemical leaching method is used to select specific reagents to react with silicon carbide raw materials to transform impurities into soluble compounds. After multiple washings, high-temperature vacuum distillation technology is combined to remove volatile impurities, ensuring the purity of the raw materials and strictly controlling the impurity concentration. S2: Fine temperature control; The optimal temperature gradient is preset using a built-in thermophysical model based on the crystal growth direction, expected size, and raw material characteristics. During growth, high-precision thermocouples at multiple locations are used to monitor the growth and the power of the heating elements is adjusted using a feedback system to ensure a smooth temperature decrease. At the same time, a high-precision temperature controller with adaptive compensation function is used, and its built-in intelligent sensor can detect interference factors to ensure a stable thermal environment. S3: Precise air pressure control; Precise gas pressure control refers to the use of an ultra-precise vacuum pressure control system, which automatically and precisely regulates the chamber gas pressure during the growth and sublimation stages, and finely adjusts the gas pressure during the deposition stage based on the concentration of gaseous substances and the deposition rate to ensure gas transport. At the same time, a multi-channel gas precision delivery device is designed to introduce inert or doped gases and use a high-precision mass flow controller combined with a built-in algorithm to precisely adjust the gas ratio. S4: Seed crystal treatment; Based on the seed crystal screening system, seed crystals are screened by surface roughness and crystal structure integrity to select those with low dislocation density and high flatness. Improved chemical mechanical polishing process, new polishing fluid and optimized parameters are used to remove the damaged layer and impurities to ensure atomic-level flatness of the seed crystal surface. During installation, laser interference precision alignment technology is used to ensure that the seed crystal is precisely aligned with the hot axis and airflow field. In the PVT process for growing silicon carbide single crystals, the axial temperature gradient and temperature fluctuations affect the growth quality of silicon carbide single crystals. This study analyzes and adjusts the axial temperature gradient, and analyzes and adjusts the temperature fluctuations accordingly. By adjusting both the axial temperature gradient and temperature fluctuations, the growth quality of silicon carbide single crystals can be improved.
[0013] Example 2 like Figure 2 As shown in the figure, an embodiment of the present invention provides a method for improving the growth quality of silicon carbide single crystals using the PVT method, which specifically includes the following steps: Step 1: Obtain the temperature parameters of the growth chamber through sensors, and obtain the gradient characterization value by analyzing the axial temperature gradient inside the growth chamber; It should be noted that the axial temperature gradient represents the temperature gradient from the bottom to the top of the growth chamber; In the PVT method for silicon carbide single crystal growth, silicon carbide raw materials sublimate at high temperatures to produce gaseous substances; the temperature gradient provides the driving force and direction for the transport of gaseous substances from the raw material area to the seed crystal area; the axial temperature gradient in the growth chamber will affect the growth quality of silicon carbide single crystals in the PVT method. Therefore, the influence of the axial temperature gradient in the growth chamber on the growth quality of silicon carbide single crystals by PVT method is analyzed, specifically; In the growth chamber, several temperature monitoring points are evenly selected from bottom to top along the growth axis; the area between two temperature monitoring points is called the axial sub-region. It should be noted that the temperature gradient along the growth axis from bottom to top is the axial temperature gradient; Acquire the temperature value of each temperature monitoring point and record it as the monitoring temperature value; take the absolute value of the difference between the monitoring temperature values of two adjacent temperature monitoring points to obtain the monitoring point temperature difference. Sum the temperature differences at all monitoring points and take the average value. The average temperature difference ratio is obtained by processing the ratio of the temperature difference at each monitoring point to the average temperature difference at each monitoring point. Calculate the variance of the temperature mean difference ratio to obtain the temperature difference variance value, denoted as FC; It should be noted that the temperature difference variance is the variance of the temperature mean difference ratio, which indicates the degree of deviation of the temperature mean difference ratio from the temperature mean difference at the monitoring point. The smaller the temperature difference variance, the smaller the degree of deviation of the temperature mean difference ratio from the temperature mean difference at the monitoring point. The temperature difference at the monitoring point is compared with the temperature difference threshold at the monitoring point. If the temperature difference at the monitoring point is greater than the temperature difference threshold at the monitoring point, the corresponding temperature monitoring point is marked as a deviation monitoring point; otherwise, no marking is made on the temperature monitoring point. Obtain the number of deviation monitoring points, and calculate the ratio of the number of deviation monitoring points to the total number of temperature monitoring points to obtain the deviation point ratio, which is marked as SL; The temperature difference variance value FC and the ratio of the number of deviation points SL are processed using the formula. The gradient characterization value BZ is obtained; where a1 and a2 are preset scaling coefficients. It should be noted that the gradient characterization value represents the suitability of the axial temperature gradient in the growth chamber; the larger the gradient characterization value, the more beneficial it is to improving the growth quality of silicon carbide single crystals by the PVT method. Step 2: Compare the gradient characterization value with the gradient characterization threshold, and determine whether the axial temperature gradient of the growth chamber is qualified based on the comparison result. If it is qualified, generate a gradient qualification signal. The gradient representation value is compared with the gradient representation threshold. The comparison process is as follows: If the gradient characterization value is greater than or equal to the gradient characterization threshold, a gradient qualification signal is generated, indicating that the axial temperature gradient of the growth chamber is qualified. If the gradient characterization value is less than the gradient characterization threshold, a gradient failure signal is generated, indicating that the axial temperature gradient of the growth chamber is unqualified. Based on the gradient non-compliance signal, the axial temperature gradient of the growth chamber is adjusted until the gradient characterization value is greater than the gradient characterization threshold. The technical solution of this invention is as follows: by monitoring the temperature of the axial temperature gradient in the growth chamber, analyzing the axial temperature gradient, calculating the variance of the temperature difference at the monitoring points, determining whether the temperature difference at all monitoring points on the growth axis is uniform, and calculating the proportion of temperature differences at the monitoring points that deviate from the threshold, the rationality of the axial temperature gradient in the growth chamber is comprehensively analyzed; under a reasonable axial temperature gradient in the growth chamber, the gaseous substances generated by the sublimation of silicon carbide raw materials can be transported to the seed crystal region at a stable rate and uniformly deposited on the surface of the seed crystal, so that the crystal grows at a constant speed in the axial direction, which helps to form high-quality, defect-free silicon carbide single crystals.
[0014] Example 3 like Figure 3 As shown in the figure, an embodiment of the present invention provides a method for improving the growth quality of silicon carbide single crystals using the PVT method, which specifically includes the following steps: Step 3: Based on the gradient qualified signal, analyze the temperature fluctuation of each temperature monitoring point to obtain the fluctuation evaluation value; compare the fluctuation evaluation value with the fluctuation evaluation threshold, and determine whether the temperature stability of the temperature monitoring point is qualified according to the comparison result. If so, generate a fluctuation stability signal. Within the monitoring period, analyze the temperature fluctuations at the monitored temperature points, specifically; The monitoring temperature points of the axial temperature gradient in the growth chamber are denoted as T1, T2, ..., Tn; The monitoring period is divided into m monitoring time points, and the monitoring temperature value of monitoring temperature point Ti is recorded at each monitoring time point; A two-dimensional coordinate system is constructed with the monitored temperature value as the Y-axis and the monitored time point as the X-axis. The monitored temperature values of each monitoring temperature point are marked and connected in the two-dimensional coordinate system to obtain the temperature fluctuation curve. By comparing and analyzing the temperature fluctuation curve with historical temperature fluctuation curves, the stability of the temperature fluctuation curve can be determined. The non-overlapping portion of the temperature fluctuation curve and the historical temperature fluctuation curve is marked as a non-overlapping curve segment; the maximum temperature difference between the temperature fluctuation curve and the historical temperature fluctuation curve within the non-overlapping curve segment is obtained, thus obtaining the maximum temperature difference value; the monitoring temperature values of monitoring temperature point Ti at each monitoring time point are summed and averaged to obtain the periodic temperature average value; the maximum temperature difference value is ratioed to the periodic temperature average value to obtain the maximum temperature difference ratio, marked as WC; The ratio of the duration of the non-overlapping curve segment to the total duration of the temperature fluctuation curve is processed to obtain the non-overlapping time segment ratio, which is denoted as SD. The maximum temperature difference ratio (WC) and the non-overlapping time period ratio (SD) were processed using the formula. The fluctuation assessment value PG is obtained; where b1 and b2 are preset proportional coefficients. The volatility assessment value is compared with the volatility assessment threshold. The comparison process is as follows: If the fluctuation assessment value is less than the fluctuation assessment threshold, the temperature fluctuation is determined to be stable, and a fluctuation stability signal is generated. If the fluctuation assessment value is greater than or equal to the fluctuation assessment threshold, the temperature fluctuation is determined to be unstable, and an unstable fluctuation signal is generated; the temperature of the monitoring temperature point Ti is adjusted until the fluctuation assessment value meets the standard. The technical solution of this invention is as follows: Based on the gradient qualified signal, the temperature fluctuation of each temperature monitoring point is analyzed to obtain the fluctuation evaluation value; the fluctuation evaluation value is compared with the fluctuation evaluation threshold, and the temperature stability of the temperature monitoring point is judged according to the comparison result. If it is not qualified, the temperature of the monitoring temperature point is adjusted accordingly; under the condition that the temperature gradient is qualified, the temperature fluctuation of the monitoring temperature point is analyzed; to avoid the quality degradation of PVT silicon carbide single crystal growth caused by temperature fluctuation during the PVT method silicon carbide single crystal growth process.
[0015] Example 4 like Figure 4 As shown in the figure, an embodiment of the present invention provides a method for improving the growth quality of silicon carbide single crystals using the PVT method, which specifically includes the following steps: Step 4: Based on the stable fluctuation signal, analyze the correlation of temperature fluctuations between adjacent monitoring temperature points to obtain a comprehensive correlation evaluation value; Obtain the correlation of temperature fluctuations between two adjacent monitoring temperature points; specifically; Obtain the rising wave period, falling wave period, and stable period of the temperature fluctuation curve between the monitoring temperature point Ti and the adjacent monitoring temperature point T(i+1); It should be noted that the rising period refers to the time when the temperature fluctuation curve rises, the falling period refers to the time when the temperature fluctuation curve falls, and the stable period refers to the time when the temperature fluctuation curve remains stable. The overlap between the wave rise period of monitoring temperature point Ti and the wave rise period of the adjacent monitoring temperature point T(i+1) is analyzed to obtain the overlap duration between the wave rise period of monitoring temperature point Ti and the wave rise period of the adjacent monitoring temperature point T(i+1). The overlap duration is then compared with the wave rise period duration of monitoring temperature point Ti to obtain the wave rise overlap. Similarly, the overlap between the wave fall period and the steady period is analyzed to obtain the wave fall overlap and the steady period overlap, respectively. The steady period overlap is denoted as PD. During the rise phase of the temperature fluctuation curve at monitoring temperature point Ti, obtain the maximum and minimum values of the monitored temperature at monitoring temperature point Ti; calculate the difference between the maximum and minimum values to obtain the temperature difference during the rise phase; and calculate the ratio of the temperature difference during the rise phase to the duration of the rise phase to obtain the temperature rise rate during the rise phase. Similarly, obtain the temperature fall rate during the fall phase, as well as the temperature rise rate and fall rate during the rise phase for adjacent monitoring temperature points T(i+1). The rise rate ratio is obtained by comparing the rise rate of the temperature fluctuation curve at monitoring temperature point Ti with the rise rate of the temperature fluctuation curve at the adjacent monitoring temperature point T(i+1); similarly, the fall rate ratio is obtained. The wave rise correlation evaluation value is obtained by weighting and summing the wave rise overlap and wave rise rate ratio between the monitoring temperature point Ti and the adjacent monitoring temperature point T(i+1); similarly, the wave fall correlation evaluation value is obtained by weighting and summing the wave fall overlap and wave fall rate ratio. The rise-fall correlation evaluation value is multiplied by the fall-fall correlation evaluation value to obtain the rise-fall correlation value, which is denoted as SJ. The stability overlap PD and the rise / fall correlation value SJ are processed using the formula. The comprehensive correlation evaluation value ZH is obtained, where c1 and c2 are preset proportional coefficients; It should be noted that the comprehensive correlation evaluation value represents the correlation between the temperature fluctuation of the monitoring temperature point Ti and the adjacent monitoring temperature point T(i+1). The larger the comprehensive correlation evaluation value, the stronger the correlation between the temperature fluctuation of the monitoring temperature point Ti and the adjacent monitoring temperature point T(i+1). Step 5: Compare the comprehensive correlation evaluation value with the comprehensive correlation evaluation threshold. Based on the comparison result, determine whether the axial temperature gradient needs to be adjusted. If so, generate an adjustment signal. Based on the adjustment signal, adjust the axial temperature gradient. The comprehensive correlation assessment value is compared with the comprehensive correlation assessment threshold. The comparison process is as follows: If the comprehensive correlation evaluation value is less than the comprehensive correlation evaluation threshold, an adjustment signal is generated, and it is determined that the correlation between the monitoring temperature point Ti and the adjacent monitoring temperature point T(i+1) is weak. The monitoring temperature point Ti and the adjacent monitoring temperature point T(i+1) are recorded as a non-correlated temperature group. If the comprehensive correlation evaluation value is greater than or equal to the comprehensive correlation evaluation threshold, a correlation signal is generated, and it is determined that the monitoring temperature point Ti is strongly correlated with the adjacent monitoring temperature point T(i+1). The monitoring temperature point Ti and the adjacent monitoring temperature point T(i+1) are recorded as the correlated temperature group. For example, there are n monitoring temperature points T1, T2, ..., Tn, where T1 and T2 form one monitoring temperature point group, and T2 and T3 form another monitoring temperature point group; there are n monitoring temperature points, and a total of (n-1) monitoring temperature point groups. Temperature adjustment is performed on the axial temperature gradient based on the adjustment signal; Obtain the number of non-associated temperature groups and determine whether the number of non-associated temperature groups is odd or even; if the number of non-associated temperature groups is odd, adjust all monitoring temperature points after the corresponding non-associated temperature group. For example, in a total of (n-1) groups of monitoring temperature points, only monitoring temperature point Ti and its adjacent monitoring temperature point T(i+1) are non-correlated temperature groups. This indicates that monitoring temperature points T1, T2, ..., Ti are strongly correlated, and monitoring temperature points T(i+1), T(i+2), ..., Tn are also strongly correlated. However, since monitoring temperature point Ti and monitoring temperature point T(i+1) are weakly correlated, this indicates that the overall temperature fluctuation of monitoring temperature points T1, T2, ..., Ti and monitoring temperature points T(i+1), T(i+2), ..., Tn deviates. Therefore, temperature fluctuation adjustments are made for monitoring temperature points T(i+1), T(i+2), ..., Tn. If the number of non-associated temperature groups is even, analyze whether the non-associated temperature groups are connected; if they are connected, perform comprehensive temperature adjustment on the two connected non-associated temperature groups; if they are not connected, the processing method is the same as that for non-associated temperature groups with an odd number of groups. For example, in a total of (n-1) groups of monitoring temperature points, monitoring temperature point Ti and its adjacent monitoring temperature point T(i+1) are non-associated temperature groups, and monitoring temperature point T(i+1) and its adjacent monitoring temperature point T(i+2) are also non-associated temperature groups; then temperature fluctuation adjustment is performed on monitoring temperature point T(i+1). The technical solution of this invention is as follows: Based on the results of temperature fluctuation adjustment, the comprehensive correlation evaluation value of each monitoring temperature point is calculated, the temperature fluctuation correlation between monitoring temperature points is analyzed, and when the temperature fluctuation correlation between monitoring temperature points is weak, the corresponding temperature fluctuation adjustment is performed on the monitoring temperature points to keep the axial temperature gradient relatively stable, so that the gas phase material transport force provided by the axial temperature gradient can still be maintained at a relatively stable level during the fluctuation process; so that the gas phase material generated by the sublimation of silicon carbide raw material can move towards the seed crystal area at a relatively stable rate and direction, which is conducive to forming a uniform deposition on the seed crystal surface, thereby improving the growth quality of silicon carbide single crystal.
[0016] Example 5 This invention provides a system for improving the quality of silicon carbide single crystal growth using the PVT method, which specifically includes the following modules: Gradient parameter acquisition module: acquires the temperature parameters of the growth chamber through sensors, and obtains the gradient characterization value by analyzing the axial temperature gradient inside the growth chamber; Gradient parameter analysis module: compares the gradient characterization value with the gradient characterization threshold, and determines whether the axial temperature gradient of the growth chamber is qualified based on the comparison result. If it is qualified, a gradient qualification signal is generated. Fluctuation parameter analysis module: Based on the gradient qualified signal, analyze the temperature fluctuation of each temperature monitoring point to obtain the fluctuation evaluation value; compare the fluctuation evaluation value with the fluctuation evaluation threshold, and determine whether the temperature stability of the temperature monitoring point is qualified according to the comparison result. If it is qualified, generate the fluctuation stability signal. Correlation parameter acquisition module: Based on the fluctuation stability signal, analyze the correlation of temperature fluctuations between adjacent monitoring temperature points to obtain a comprehensive correlation evaluation value; Correlation parameter analysis module: compares the comprehensive correlation evaluation value with the comprehensive correlation evaluation threshold, determines whether the axial temperature gradient needs to be adjusted based on the comparison result, and generates an adjustment signal based on the adjustment signal; and adjusts the axial temperature gradient based on the adjustment signal.
[0017] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.
Claims
1. A method for improving the quality of silicon carbide single crystal growth using the PVT method, characterized in that, Includes the following steps: Raw material optimization, precise temperature control, accurate air pressure management, and seed crystal processing; In the PVT method for silicon carbide single crystal growth, the axial temperature gradient and temperature fluctuations affect the growth quality of the silicon carbide single crystal. This study analyzes and adjusts the axial temperature gradient, and simultaneously analyzes and adjusts temperature fluctuations. By adjusting both the axial temperature gradient and temperature fluctuations, the growth quality of the silicon carbide single crystal can be improved. The steps are as follows: Step 1: Obtain the temperature parameters of the growth chamber through sensors, and obtain the gradient characterization value by analyzing the axial temperature gradient inside the growth chamber; Step 2: Compare the gradient characterization value with the gradient characterization threshold, and determine whether the axial temperature gradient of the growth chamber is qualified based on the comparison result. If it is qualified, generate a gradient qualification signal. Step 3: Based on the gradient qualified signal, analyze the temperature fluctuation of each temperature monitoring point to obtain the fluctuation evaluation value; compare the fluctuation evaluation value with the fluctuation evaluation threshold, and determine whether the temperature stability of the temperature monitoring point is qualified according to the comparison result. If it is qualified, generate a fluctuation stability signal. Step 4: Based on the stable fluctuation signal, analyze the correlation of temperature fluctuations between adjacent monitoring temperature points to obtain a comprehensive correlation evaluation value; Step 5: Compare the comprehensive correlation evaluation value with the comprehensive correlation evaluation threshold. Based on the comparison result, determine whether the axial temperature gradient needs to be adjusted. If so, generate an adjustment signal. Based on the adjustment signal, adjust the axial temperature gradient.
2. The method for improving the quality of silicon carbide single crystal growth by PVT method according to claim 1, characterized in that, The gradient representation value is obtained as follows: The temperature values at the temperature monitoring points were analyzed to obtain the temperature variance value FC; The deviation monitoring points are analyzed to obtain the deviation monitoring point SL; The temperature difference variance value FC and the ratio of the number of deviation points SL are processed using the formula. The gradient representation value BZ is obtained; where a1 and a2 are preset scaling coefficients.
3. The method for improving the quality of silicon carbide single crystal growth by PVT method according to claim 2, characterized in that, The method for obtaining the temperature difference variance value is as follows: In the growth chamber, several temperature monitoring points are evenly selected from bottom to top along the growth axis; Acquire the temperature value of each temperature monitoring point and record it as the monitoring temperature value; take the absolute value of the difference between the monitoring temperature values of two adjacent temperature monitoring points to obtain the monitoring point temperature difference. Sum the temperature differences at all monitoring points and take the average value. The average temperature difference ratio is obtained by processing the ratio of the temperature difference at each monitoring point to the average temperature difference at each monitoring point. Calculate the variance of the temperature mean difference ratio to obtain the temperature difference variance value, denoted as FC.
4. The method for improving the quality of silicon carbide single crystal growth by PVT method according to claim 2, characterized in that, The method for obtaining the ratio of deviation points is as follows: The temperature difference at the monitoring point is compared with the temperature difference threshold at the monitoring point. If the temperature difference at the monitoring point is greater than the temperature difference threshold at the monitoring point, the corresponding temperature monitoring point is marked as a deviation monitoring point. Obtain the number of deviation monitoring points, and then calculate the ratio of the number of deviation monitoring points to the total number of temperature monitoring points to obtain the deviation point ratio, which is denoted as SL.
5. The method for improving the quality of silicon carbide single crystal growth by PVT method according to claim 1, characterized in that, The method for obtaining the fluctuation stabilization signal is as follows: By analyzing the temperature fluctuation curve and the historical temperature fluctuation curve, the maximum temperature difference ratio WC was obtained. Analysis of non-overlapping curve segments yields the non-overlapping time period ratio (SD). The maximum temperature difference ratio (WC) and the non-overlapping time period ratio (SD) were processed using the formula. The fluctuation assessment value PG is obtained; where b1 and b2 are preset proportional coefficients.
6. The method for improving the quality of silicon carbide single crystal growth by PVT method according to claim 5, characterized in that, The maximum temperature difference ratio is obtained as follows: The monitoring temperature points of the axial temperature gradient in the growth chamber are denoted as T1, T2, ..., Tn; The monitoring period is divided into m monitoring time points, and the monitoring temperature value of monitoring temperature point Ti is recorded at each monitoring time point; By constructing an XY two-dimensional coordinate system, the monitored temperature values of each monitoring temperature point are marked and connected in the XY two-dimensional coordinate system to obtain the temperature fluctuation curve; The non-overlapping portion of the temperature fluctuation curve and the historical temperature fluctuation curve is marked as a non-overlapping curve segment; the maximum temperature difference between the temperature fluctuation curve and the historical temperature fluctuation curve within the non-overlapping curve segment is obtained, thus obtaining the maximum temperature difference value; the monitoring temperature values of monitoring temperature point Ti at each monitoring time point are summed and averaged to obtain the periodic temperature average value; the maximum temperature difference value is ratioed to the periodic temperature average value to obtain the maximum temperature difference ratio, marked as WC.
7. The method for improving the quality of silicon carbide single crystal growth by PVT method according to claim 5, characterized in that, The method for obtaining the non-overlapping time period ratio is as follows: The ratio of the duration corresponding to the non-overlapping curve segment to the total duration of the temperature fluctuation curve is processed to obtain the non-overlapping time segment ratio, which is denoted as SD.
8. The method for improving the quality of silicon carbide single crystal growth by PVT method according to claim 1, characterized in that, The method for obtaining the comprehensive correlation evaluation value is as follows: By comparing and analyzing the temperature fluctuation curves of adjacent monitoring temperature points, the stability overlap (PD) is obtained. The rise and fall periods of the temperature fluctuation curves at adjacent monitoring temperature points are analyzed to obtain the rise-fall correlation value SJ. The stability overlap PD and the rise / fall correlation value SJ are processed using the formula. The comprehensive correlation evaluation value ZH is obtained, where c1 and c2 are preset proportional coefficients.
9. A method for improving the quality of silicon carbide single crystal growth by PVT method according to claim 8, characterized in that, The method for obtaining the smooth overlap is as follows: Obtain the rising wave period, falling wave period, and stable period of the temperature fluctuation curve between the monitoring temperature point Ti and the adjacent monitoring temperature point T(i+1); The overlap between the rise period of the monitoring temperature point Ti and the steady period of the adjacent monitoring temperature point T(i+1) is analyzed to obtain the overlap duration between the steady period of the monitoring temperature point Ti and the steady period of the adjacent monitoring temperature point T(i+1). The overlap duration is then compared with the steady period duration of the monitoring temperature point Ti to obtain the steady overlap degree, which is denoted as PD.
10. A method for improving the quality of silicon carbide single crystal growth by PVT method according to claim 8, characterized in that, The method for obtaining the elevation / decrease correlation value is as follows: During the rise period of the temperature fluctuation curve at monitoring temperature point Ti, obtain the maximum and minimum values of the monitored temperature at monitoring temperature point Ti; calculate the difference between the maximum and minimum values of the monitored temperature to obtain the temperature difference during the rise period; calculate the ratio of the temperature difference during the rise period to the duration of the rise period to obtain the temperature rise rate during the rise period; similarly, obtain the temperature rise rate during the rise period of adjacent monitoring temperature points T(i+1). The rise rate ratio is obtained by comparing the rise rate during the rise period of the temperature fluctuation curve at monitoring temperature point Ti with the rise rate during the rise period of the adjacent monitoring temperature point T(i+1). The wave rise correlation evaluation value is obtained by weighting and summing the wave rise overlap and wave rise rate ratio between the monitoring temperature point Ti and the adjacent monitoring temperature point T(i+1); the wave fall correlation evaluation value is obtained in the same way. The rise-fall correlation evaluation value is multiplied by the fall-fall correlation evaluation value to obtain the rise-fall correlation value, which is denoted as SJ.