A method for analyzing the quality of silicon rods used in the production process of photovoltaic silicon wafers.

Abstract

A method for quality analysis of silicon rods in the photovoltaic silicon wafer production process includes the following steps: resistivity testing of the silicon rods to obtain resistivity values; minority carrier lifetime testing of the silicon rods to obtain minority carrier lifetime values; calculation of the ratio between the minority carrier lifetime and resistivity values, referred to as the relative minority carrier lifetime; calculation of the relative minority carrier lifetime values ​​for a group of silicon rod samples; grouping the samples into m groups based on their relative minority carrier lifetime values, and slicing each group; calculating the average relative minority carrier lifetime value for each of the m groups of samples; evaluating the cell efficiency of each of the m groups of silicon wafer samples to obtain the cell conversion efficiency data for the m groups; and performing correlation analysis between the cell conversion efficiency data and the average relative minority carrier lifetime values ​​of the m groups to verify the correlation between the two sets of data. This invention proposes a method for evaluating silicon rod quality using relative minority carrier lifetime, which can eliminate the influence of doping resistivity on minority carrier lifetime.

Description

Technical Field

[0001] This invention belongs to the field of silicon rod quality analysis technology, and specifically relates to a silicon rod quality analysis method used in the photovoltaic silicon wafer production process. Background Technology

[0002] Dislocation density and metal contamination are defects in silicon rods, affecting their minority carrier lifetime and consequently the conversion efficiency of solar cells. Doping resistivity is a parameter for process adjustment. Currently, the segregation coefficients of gallium and phosphorus, the mainstream doping elements, in silicon are relatively small, making it difficult to stably control the resistivity of the product within a single value or a very small resistivity range. Therefore, producing products with different resistivities is inevitable. However, silicon rods with different resistivities will exhibit different minority carrier lifetime performances. How to quickly compare the quality of silicon rods with different minority carrier lifetimes has become a challenge for quality analysts. For example, monocrystalline silicon rod A, with the same doping type, has a tested resistivity of 0.5 Ω·cm and a minority carrier lifetime of 300 μs, while monocrystalline silicon rod B has a tested resistivity of 0.8 Ω·cm and a minority carrier lifetime of 400 μs. Judging solely from the minority carrier lifetime of 400 μs > 300 μs, monocrystalline silicon rod B is superior to monocrystalline silicon rod A. However, in actual cell efficiency, monocrystalline silicon rod A performs better than monocrystalline silicon rod B. The technical problem to be solved by this invention is how to quickly determine the quality of silicon blocks by minority carrier lifetime for silicon rods with different resistivities. Summary of the Invention

[0003] In view of the technical problems existing in the background art, the present invention provides a silicon rod quality analysis method for the photovoltaic silicon wafer production process. The present invention proposes a method for evaluating silicon rod quality using relative minority carrier lifetime, which can eliminate the influence of doping resistivity on minority carrier lifetime.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0005] A method for quality analysis of silicon rods used in the production process of photovoltaic silicon wafers includes the following steps:

[0006] Step 1: Perform resistivity testing on the silicon rod to obtain the resistivity value R;

[0007] Step 2: Perform minority carrier lifetime testing on the silicon rod; minority carrier lifetime value L.

[0008] Step 3: Calculate the ratio of minority carrier lifetime L to resistivity R. The ratio L is obtained. R This is called the relative minority lifetime;

[0009] Step 4: Using the methods described in steps 1-3 above, process a group of silicon rod samples N1, N2, N3...N n The relative minority carrier lifetime value is calculated to obtain the relative minority carrier lifetime L. R1L R2 L R3 ...L Rn ;

[0010] Step 5: Group the samples according to their relative minority carrier lifetime values ​​to obtain m groups of samples. Slice each of the m groups of samples to obtain m groups of silicon wafer samples. Calculate the average relative minority carrier lifetime values ​​L1, L2, L3...L for each of the m groups of samples. m ;

[0011] Step 6: Evaluate the cell efficiency of each of the m groups of silicon wafer samples, and obtain the cell conversion efficiency data F1, F2, F3...Fm for each of the m groups;

[0012] Step 7: Perform correlation analysis on the m sets of battery conversion efficiency data F1, F2, F3...Fm and the m sets of average relative minority carrier lifetime values ​​L1, L2, L3...Lm to verify the correlation between the two sets of data.

[0013] Step 8: Calculate the correlation coefficient r. A correlation coefficient r ≥ 0.931 and a high relative minority carrier lifetime value indicate that the silicon rod is of excellent quality.

[0014] In a preferred embodiment, step 1 involves using eddy current attenuation or a four-probe method to test the resistivity of the silicon rod.

[0015] In the preferred embodiment, step 2 involves using the quasi-steady-state photoconductivity attenuation method to test the minority carrier lifetime.

[0016] In the preferred embodiment, in steps 7-8, the Minitab software is used to analyze the conversion efficiency data F1, F2, F3...Fm of m groups of batteries and the average relative minority carrier lifetime values ​​L1, L2, L3...Lm of m groups. m The correlation between the two sets of data was analyzed, and a Pearson correlation coefficient distribution diagram was obtained. When the p-value is <0.05, the correlation coefficient r ≥0.931, and the relative minority carrier lifetime value is high, it indicates that the silicon rod is of superior quality.

[0017] This patent can achieve the following beneficial effects:

[0018] This invention proposes a method for evaluating the quality of silicon rods using relative minority carrier lifetime. This method can eliminate the influence of doping resistivity on minority carrier lifetime. The relative minority carrier lifetime reflects the dislocation density and metal contamination of the silicon rod, thereby judging the quality of the silicon rod and providing intuitive guidance for production processes and the use of polycrystalline silicon. Attached Figure Description

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0020] Figure 1This is a Pearson correlation diagram of the relative minority carrier lifetime and battery conversion efficiency of the present invention. Detailed Implementation

[0021] The minority carrier lifetime of a silicon rod is affected by dislocations, metallic impurities, and doping resistivity. Currently, the minority carrier lifetime can reflect the quality of the silicon rod, while doping resistivity has a relatively small impact on efficiency. Different customers may use different battery manufacturing processes for products with different resistivities. However, doping resistivity has a significant impact on the minority carrier lifetime value, masking the influence of dislocations, metallic impurities, etc., on the performance of the silicon rod. While the minority carrier lifetime can currently reflect the quality of a silicon rod, consider this scenario: Monocrystalline silicon rod A, with the same doping type, has a resistivity of 0.5 Ω·cm and a minority carrier lifetime of 300 μs, while monocrystalline silicon rod B has a resistivity of 0.8 Ω·cm and a minority carrier lifetime of 400 μs. Judging solely from the difference in minority carrier lifetime (400 μs > 300 μs), monocrystalline silicon rod B is superior to monocrystalline silicon rod A. However, in actual battery efficiency, monocrystalline silicon rod A performs better than monocrystalline silicon rod B. Therefore, the minority carrier lifetime value alone cannot accurately determine the overall performance.

[0022] This invention proposes a method for evaluating the quality of silicon rods using relative minority carrier lifetime. This method can eliminate the influence of doping resistivity on minority carrier lifetime. The relative minority carrier lifetime reflects the dislocation density and metal contamination of the silicon rod, thereby judging the quality of the silicon rod and providing intuitive guidance for production processes and the use of polycrystalline silicon.

[0023] Preferred solutions include Figure 1 As shown, a method for analyzing the quality of silicon rods used in the production process of photovoltaic silicon wafers includes the following steps:

[0024] Step 1: Perform resistivity testing on the silicon rod to obtain the resistivity value R;

[0025] The resistivity of silicon rods is tested using either the eddy current decay method or a four-probe method.

[0026] Step 2: Perform minority carrier lifetime testing on the silicon rod; minority carrier lifetime value L.

[0027] Minority carrier lifetime was tested using the quasi-steady-state photoconductivity attenuation method.

[0028] Step 3: Calculate the ratio of minority carrier lifetime L to resistivity R. The ratio L is obtained. R This is called the relative minority lifetime;

[0029] Step 4: Using the methods described in steps 1-3 above, process a group of silicon rod samples N1, N2, N3...N n The relative minority carrier lifetime value is calculated to obtain the relative minority carrier lifetime L. R1 L R2 L R3 ...LRn ;

[0030] Step 5: Group the samples according to their relative minority carrier lifetime values ​​to obtain m groups of samples. Slice each of the m groups of samples to obtain m groups of silicon wafer samples. Calculate the average relative minority carrier lifetime values ​​L1, L2, L3...L for each of the m groups of samples. m ;

[0031] Step 6: Evaluate the cell efficiency of each of the m groups of silicon wafer samples, and obtain the cell conversion efficiency data F1, F2, F3...Fm for each of the m groups;

[0032] Step 7: Perform correlation analysis on the m sets of battery conversion efficiency data F1, F2, F3...Fm and the m sets of average relative minority carrier lifetime values ​​L1, L2, L3...Lm to verify the correlation between the two sets of data.

[0033] Step 8: Calculate the correlation coefficient r. A correlation coefficient r ≥ 0.931 and a high relative minority carrier lifetime value indicate that the silicon rod is of excellent quality.

[0034] The correlation between the conversion efficiency data F1, F2, F3...Fm of m groups of cells and the average relative minority carrier lifetime values ​​L1, L2, L3...Lm of m groups was analyzed using Minitab software, and a Pearson correlation coefficient distribution chart was obtained. When the p value is <0.05, the correlation coefficient r is ≥0.931, and the relative minority carrier lifetime value is high, it indicates that the silicon rod is of excellent quality.

[0035] The correlation coefficient, first designed by statistician Carl Pearson, is a statistical indicator used to study the degree of linear correlation between variables. Correlation is a non-deterministic relationship, and the correlation coefficient measures the strength of this linear relationship. The simple correlation coefficient, also called the correlation coefficient or linear correlation coefficient, is generally represented by the letter 'r' and is used to measure the linear relationship between two variables. The calculation formula is:

[0036]

[0037] Where Cov(X,Y) is the covariance of X and Y, Var[X] is the variance of X, and Var[Y] is the variance of Y.

[0038] The correlation coefficient ranges from -1 to 1. A correlation coefficient of -1 indicates a perfect negative correlation, meaning the returns of the two assets move in completely opposite directions and at completely opposite magnitudes. A correlation coefficient of +1 indicates a perfect positive correlation, meaning the returns of the two assets move in exactly the same direction and at completely opposite magnitudes. A correlation coefficient of 0 indicates no correlation. The absolute value of r ranges from 0 to 1. Generally speaking, the closer r is to 1, the stronger the correlation between x and y; conversely, the closer r is to 0, the weaker the correlation between x and y.

[0039] This procedure is used to determine the correlation between the relative minority carrier lifetime L and the quality of silicon rods. The higher the relative minority carrier lifetime L, the better the quality of the silicon rods. The statistical significance of the P-value is an estimation method for the degree of truthfulness of the result (that it can represent the population).

[0040] The p-value, in professional terms, is a decreasing indicator of the reliability of a result. The larger the p-value, the less reliable we are in considering the association between variables in the sample as a reliable indicator of the association between variables in the population. The p-value represents the probability of error in considering an observation as valid, or representative of the population. In scientific fields, a p-value ≤ 0.05 is considered the boundary of statistical significance, but this level of significance still includes a fairly high probability of error. A result of 0.05 ≥ p > 0.01 is considered statistically significant, while 0.01 ≥ p is considered highly statistically significant.

[0041] When using relative minority carrier lifetime to evaluate silicon rods, the same minority carrier lifetime measurement method should be used, and the doping type of the silicon rods should be the same. Relative minority carrier lifetime can be used to evaluate polycrystalline silicon rods as well as monocrystalline silicon rods.

[0042] The minority carrier lifetime of silicon ingots is affected by dislocations in the silicon rod, metallic impurities, and doping resistivity. While doping resistivity has a relatively small impact on efficiency, and different customers may use different battery manufacturing processes for products with different resistivities, doping resistivity has a significant impact on the minority carrier lifetime value, masking the influence of dislocations and metallic impurities on the silicon rod's performance. By using relative minority carrier lifetime (the ratio of measured minority carrier lifetime value to resistivity), the influence of doping resistivity on minority carrier lifetime can be eliminated, allowing for a rapid assessment of the silicon rod's quality.

[0043] Example 1: For purchased silicon rods, the relative minority carrier lifetime can be used for acceptance testing. For example, the resistivity of single crystal silicon rod A is 0.5 Ω·cm, the minority carrier lifetime test value is 300 μs, and the relative minority carrier lifetime value is 600. The resistivity of silicon block B is 0.8 Ω·cm, the minority carrier lifetime test value is 400 μs, and the relative minority carrier lifetime value is 500. The relative minority carrier lifetime value of silicon block A (600) is greater than that of silicon block B (500), so the quality of silicon block A is better than that of silicon block B.

[0044] Example 2: When using the same quality of polysilicon, the production process of silicon rods can be evaluated using relative minority carrier lifetime to guide the optimization of silicon rod production process.

[0045] Example 3: When the silicon rod production process is the same, the relative minority carrier lifetime can be used to evaluate the quality of polycrystalline silicon material produced from silicon rods, and to guide the classification of polycrystalline silicon material quality.

[0046] The above embodiments are merely preferred technical solutions of the present invention and should not be considered as limitations on the present invention. The scope of protection of the present invention should be limited to the technical solutions described in the claims, including equivalent substitutions of the technical features described in the claims. That is, equivalent substitutions and improvements within this scope are also within the scope of protection of the present invention.

Claims

1. A method for analyzing the quality of silicon rods used in the production process of photovoltaic silicon wafers, characterized in that... Includes the following steps: Step 1: Perform resistivity testing on the silicon rod to obtain the resistivity value R; Step 2: Perform minority carrier lifetime testing on the silicon rod to obtain the minority carrier lifetime value L; Step 3: Calculate the ratio of minority carrier lifetime L to resistivity R. The ratio L is obtained. R This is called the relative minority lifetime; Step 4: Using the methods described in steps 1-3 above, process a group of silicon rod samples N1, N2, N3...N n The relative minority carrier lifetime value is calculated to obtain the relative minority carrier lifetime L. R1 L R2 L R3 ...L Rn ; Step 5: Group the samples according to the relative minority carrier lifetime values ​​to obtain m groups of samples. Slice each of the m groups of samples to obtain m groups of silicon wafer samples. The average relative minority carrier lifetime values ​​L1, L2, L3...L for each of the m groups of samples were calculated. m ; Step 6: Evaluate the cell efficiency of each of the m groups of silicon wafer samples to obtain the cell conversion efficiency data F1, F2, F3...Fm for each of the m groups; Step 7: Perform correlation analysis on the m sets of battery conversion efficiency data F1, F2, F3...Fm and the m sets of average relative minority carrier lifetime values ​​L1, L2, L3...Lm to verify the correlation between the two sets of data. Step 8: Calculate the correlation coefficient r. A correlation coefficient r ≥ 0.931 and a high relative minority carrier lifetime value indicate that the silicon rod is of excellent quality.

2. The method for analyzing the quality of silicon rods in the photovoltaic silicon wafer production process according to claim 1, characterized in that: In step 1, the resistivity of the silicon rod is tested using the eddy current decay method or a four-probe method.

3. The method for analyzing the quality of silicon rods in the photovoltaic silicon wafer production process according to claim 1, characterized in that: In step 2, the minority carrier lifetime is tested using the quasi-steady-state photoconductivity attenuation method.

4. The method for analyzing the quality of silicon rods in the photovoltaic silicon wafer production process according to claim 1, characterized in that: In steps 7-8, the Minitab software is used to analyze the conversion efficiency data F1, F2, F3...Fm of the m groups of cells and the average relative minority carrier lifetime values ​​L1, L2, L3...Lm of the m groups. m The correlation between the two sets of data was analyzed, and a Pearson correlation coefficient distribution diagram was obtained. When the p-value is <0.05, the correlation coefficient r ≥0.931, and the relative minority carrier lifetime value is high, it indicates that the silicon rod is of superior quality.

Images