A dynamic control method of electronic grade polysilicon cleaning process
By monitoring and dynamically adjusting the etching solution parameters in real time, the problem of unstable etching rate in the polycrystalline silicon cleaning process was solved, achieving consistency in product quality and optimization of costs, and improving production efficiency and yield.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 内蒙古大全半导体有限公司
- Filing Date
- 2026-06-22
- Publication Date
- 2026-07-24
AI Technical Summary
In existing polysilicon cleaning processes, the etching rate of the reusable etching solution is unstable due to acid concentration decay, temperature fluctuations, and accumulation of metal impurities. This results in large fluctuations in product quality and poor consistency between batches, affecting production efficiency and yield.
By acquiring the process parameters of the etching solution in real time, the etching rate is calculated using the etching rate prediction formula, and the etching time and cleaning process are dynamically adjusted based on the prediction results, triggering online mixing or acid replacement strategies to ensure the consistency of etching depth and cleanliness.
This achieved stability in etching depth and cleanliness between batches, reduced the consumption of high-purity reagents and the cost of waste acid treatment, and improved production yield and economic benefits.
Smart Images
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Abstract
Description
Technical Field
[0001] This invention relates to the field of polycrystalline silicon technology, and more specifically to a dynamic control method for electronic-grade polycrystalline silicon cleaning processes. Background Technology
[0002] Electronic-grade polysilicon is a fundamental material for manufacturing semiconductor devices, and its surface cleanliness directly affects the performance and yield of subsequent chips. After front-end processes such as pulling and dicing, a damaged layer and metallic impurities form on the surface of the electronic-grade polysilicon core, which must be removed by wet chemical etching. Currently, the mainstream process uses a mixed acid solution of hydrofluoric acid and nitric acid for cleaning.
[0003] During the cleaning process, to meet the ultra-high cleanliness requirements of electronic-grade polycrystalline silicon, the nitric acid and hydrofluoric acid used in the cleaning solution are both ultra-high purity reagents of UP-S or higher grade, which are extremely expensive. To spread the cost of acid replacement as much as possible, the cleaning solution usually needs to be reused to process multiple batches of silicon cores continuously until its cleaning capacity is exhausted before replacement. This reuse method causes the etching solution to age continuously with each batch, the acid concentration to decrease continuously, the metal impurities to accumulate continuously, and the temperature fluctuations to cause the etching rate to show a significant downward trend. Currently, before each cleaning, due to the lack of an effective means to assess the actual etching rate of the current etching solution in real time, operators can only rely on experience to set a fixed etching time according to a fixed etching rate. This extensive control method completely ignores the dynamic impact of acid concentration decay, temperature fluctuations, and metal impurity accumulation on the etching rate. In the early batches where the cleaning solution is highly active, the actual etching rate is much higher than the set value, resulting in over-etching and material waste; while in the later batches where the cleaning solution is aging, the etching rate has decreased significantly, and the fixed etching time cannot achieve the required etching depth, resulting in insufficient etching, damaged layers, and metal impurity residues. This leads to problems such as over-etching in early batches and under-etching in later batches, resulting in large fluctuations and poor consistency in product quality between batches, which seriously restricts the production efficiency and final yield of electronic-grade polysilicon. Summary of the Invention
[0004] To address the aforementioned problems, the present invention aims to provide a dynamic control method for electronic-grade polysilicon cleaning processes. By predicting the real-time etching rate and dynamically adjusting the etching time and cleaning process accordingly, the consistency of product quality and product yield across batches can be ensured.
[0005] This invention is implemented by the following technical solution: A method for dynamically controlling an electronic-grade polysilicon cleaning process includes the following steps: S1: Obtain the process parameters of the etching solution in the current cleaning tank. The process parameters include the concentration of hydrofluoric acid, the concentration of nitric acid, the temperature of the etching solution, and the total concentration of metal impurities in the etching solution. S2: Substitute the process parameters into the etching rate prediction formula to calculate the predicted etching rate; S3: Calculate the required baseline etching time based on the target etching depth and the predicted etching rate; S4: Determine whether the dynamic control conditions are met based on the reference etching time and the total concentration of metal impurities in the etching solution. If they are met, proceed to S5; otherwise, use the etching solution in the current cleaning tank to clean according to the reference etching time. S5: Dynamically regulate the cleaning process according to the dynamic regulation strategy.
[0006] Furthermore, in step S2, the etch rate prediction formula is:
[0007] In the formula: R is the predicted etching rate; R0 is the pre-exponential factor; E a It is the apparent activation energy; T represents the current etching solution temperature; [HF] represents the concentration of hydrofluoric acid in the current etching solution; [HNO3] represents the current concentration of nitric acid in the etching solution; α and β are the reaction orders of HF and HNO3, respectively; k is the impurity suppression coefficient; C imp This represents the total concentration of metallic impurities in the current etching solution.
[0008] Furthermore, the pre-exponential factor R0 and the apparent activation energy E a The methods for determining the reaction order α of HF, the reaction order β of HNO3, and the impurity inhibition coefficient k are as follows: S21. Record the etching thickness data of silicon samples under multiple sets of different experimental conditions, including hydrofluoric acid concentration, nitric acid concentration, temperature of etching solution and total concentration of metal impurities in etching solution. S22: Calculate the actual etching rate R under each experimental condition based on the etching thickness data of the silicon sample and the corresponding etching time; S23: Using the actual etching rate R as the training set, substitute the data from multiple sets of experimental conditions and the corresponding silicon sample etching thickness data into the etching rate prediction formula, and obtain the pre-exponential factor R0 and the apparent activation energy E through regression analysis. aThe values of the reaction order α of HF, the reaction order β of HNO3, and the impurity inhibition coefficient k.
[0009] Furthermore, in step S21, the formula for calculating the etching thickness of the silicon sample is: H=(M2-M1)÷ρ÷(6×L 2 ) Where M1 and M2 are the masses of the sample before and after etching, respectively, ρ is the density of silicon, and L is the side length of the sample.
[0010] Furthermore, the total concentration of metallic impurities in the etching solution is expressed in ppm as iron equivalent.
[0011] Furthermore, Pre-exponential factor R0 = 2.47 × 10 6 μm / min; Apparent activation energy E a =42.3kJ / mol; The reaction order of HF is α = 0.68; The reaction order of HNO3 is β = 0.42; Impurity suppression coefficient k = 0.0025 ppm -1 .
[0012] Furthermore, in S4, the dynamic control condition is: The total concentration of metal impurities in the etching solution is greater than or equal to the preset first metal impurity concentration threshold.
[0013] Furthermore, in S5, the dynamic control strategy is as follows: If the preset first metal impurity concentration threshold is less than or equal to the total metal impurity concentration in the etching solution and less than the preset second metal impurity concentration threshold, and the preset second metal impurity concentration threshold is greater than the preset first metal impurity concentration threshold, an online doping strategy is executed: fresh high-purity mixed acid is added to the cleaning tank to dilute the metal impurity concentration and increase the acid concentration. The total metal impurity concentration in the doped etching solution after adding fresh high-purity mixed acid is measured to see if it meets the dynamic control conditions. If it does, the addition of fresh high-purity mixed acid continues until the dynamic control conditions are no longer met. After that, the new etching time is recalculated according to the etching rate prediction formula using the parameters of the doped etching solution, and cleaning is performed according to the new etching time. If the total concentration of metal impurities in the etching solution is greater than or equal to the preset second metal impurity concentration threshold, an acid replacement strategy is implemented: the etching solution in the current cleaning tank is stopped, and fresh high-purity mixed acid is used to perform the cleaning process.
[0014] Furthermore, in the online blending strategy, the volume ratio of fresh high-purity mixed acid added to the cleaning tank to the etching solution in the current cleaning tank is 1:4.
[0015] Advantages of this invention: This invention overcomes the shortcomings of traditional fixed-duration cleaning methods that ignore the effects of acid concentration decay, temperature fluctuations, and metal impurity accumulation by acquiring the process parameters of the etching solution in real time and calculating the current etching rate using an etching rate prediction formula. This effectively avoids over-etching in early batches and under-etching in later batches, significantly improving the consistency of etching depth and surface cleanliness between batches. Furthermore, this invention intelligently triggers online dosing or acid replacement strategies based on the total concentration of metal impurities, maximizing the service life of the etching solution while ensuring cleaning quality. This reduces the consumption of high-purity reagents and the cost of waste acid treatment, achieving refined, low-cost, and highly stable control of the electronic-grade polycrystalline silicon cleaning process, significantly improving production yield and economic benefits. Detailed Implementation
[0016] The technical solutions in the embodiments of the present invention will be clearly and completely described below. 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 are within the scope of protection of the present invention.
[0017] Example 1 A dynamic control method for an electronic-grade polysilicon cleaning process is used to regulate the cleaning batch in a normally functioning cleaning tank, comprising the following steps: S1: Obtain the process parameters of the etching solution in the current cleaning tank. Specifically, the concentration of hydrofluoric acid [HF] is 3.8 mol / L, the concentration of nitric acid [HNO3] is 7.2 mol / L, the temperature of the etching solution is T = 298 K, and the total concentration of metallic impurities in the etching solution is C. imp =65ppb; S2: Substituting the above process parameters into the etching rate prediction formula, the predicted etching rate is calculated to be R = 0.463 μm / min; S3: Calculate the etched height of the sample by dividing the weight reduction after cleaning (during the cleaning process) by the density, and then by the surface area of the sample. This height is 6.0 μm, which is the target etching depth. Based on the target etching depth D... target =6.0μm and the predicted etching rate, calculate the required baseline etching time t base =778 seconds; S4: Due to C imp =65ppb, which is lower than the preset first metal impurity concentration threshold of 155ppb, and does not meet the dynamic control conditions. Therefore, the system determines that the etching solution in the current cleaning tank is in a normal state and does not trigger the dynamic control strategy. It then uses the etching solution in the current cleaning tank according to the calculated baseline etching time t.base The cleaning process takes 778 seconds. The PLC-controlled robotic arm immerses the silicon core in the etching solution in the cleaning tank, and removes it after 778 seconds.
[0018] After cleaning, the actual etching depth was measured to be 5.95 μm, with a relative error of 0.83% compared to the target etching depth of 6.0 μm, and the surface metallic impurities Fe < 5 × 10⁻⁶. 9 atoms / cm 2 It fully meets electronic-grade requirements. The system did not trigger dynamic control strategies, and the cleaning task was efficiently completed using waste acid without the need to replenish fresh high-purity mixed acid after replacement.
[0019] Example 2 A dynamic control method for an electronic-grade polysilicon cleaning process is used to regulate a cleaning tank with a high accumulation of impurities. The method includes the following steps: S1: Obtain the process parameters of the etching solution in the current cleaning tank. Specifically, the concentration of hydrofluoric acid [HF] = 4.5 mol / L, the concentration of nitric acid [HNO3] = 8.6 mol / L, the temperature of the etching solution T = 298 K, and the total concentration of metallic impurities C in the etching solution. imp =185ppb; S2: Substituting the above process parameters into the etching rate prediction formula, the predicted etching rate is calculated to be R = 0.349 μm / min; S3: Based on the target etching depth D target =6.0μm and the predicted etching rate, calculate the required baseline etching time t base =1031 seconds; S4: Due to C imp =185ppb, which is higher than the preset first metal impurity concentration threshold of 155ppb, and meets the dynamic control conditions. Therefore, the system judges that the current state of the etching solution in the cleaning tank is abnormal and triggers the dynamic control strategy. S5: Due to C imp =185ppb, between the preset first metal impurity concentration threshold of 155ppb and the preset second metal impurity concentration threshold of 200ppb. If the current etching solution is used for cleaning, simply extending the etching time may cause surface roughness and uncontrollable defects. Therefore, an online doping strategy is implemented: fresh high-purity mixed acid is added to the cleaning tank at a volume ratio of 1:4 to dilute the metal impurity concentration and increase the acid concentration. The concentration of HF in the fresh high-purity mixed acid is 6.0mol / L, and the concentration of HNO3 is 11.0mol / L. After doping, the parameters of the new etching solution measured by the sensor are approximately [HF]=4.8mol / L, [HNO3]=9.08mol / L, C imp≈150 ppb, lower than the preset first metal impurity concentration threshold of 155 ppb. R was recalculated. new The etching rate is approximately 0.437 μm / min. Based on the new etching rate, the new etching time is calculated to be 824 seconds. Therefore, the modified etching solution is used for cleaning according to the calculated new etching time of 824 seconds. The PLC-controlled robot arm immerses the silicon core in the etching solution in the cleaning tank and removes it after 824 seconds.
[0020] After cleaning, the actual etching depth was measured to be 6.08 μm, with a relative error of 1.3% compared to the target etching depth of 6.0 μm, and the surface metallic impurities Fe < 6 × 10⁻⁶. 9 atoms / cm 2 It fully meets electronic-grade requirements. By triggering a dynamic control strategy, the system replenishes a certain amount of fresh, high-purity mixed acid and then uses the mixed etching solution to complete the cleaning task, saving a batch of acid that was about to be scrapped and preventing product spoilage.
[0021] Comparative Example 1 The cleaning process in Example 2 was controlled using traditional control methods, specifically as follows: The process parameters of the etching solution in the cleaning tank are: hydrofluoric acid concentration [HF] = 4.5 mol / L, nitric acid concentration [HNO3] = 8.6 mol / L, etching solution temperature T = 298 K, and total concentration of metallic impurities in the etching solution C. imp =185ppb; Using traditional methods, only the acid concentration is monitored to determine if it is within acceptable limits. The operator sets the etching time to 554 seconds based on an empirical formula.
[0022] After cleaning, testing revealed that the etching depth was only 3.91 μm, far below the target value of 6.0 μm, and the surface Fe impurities reached as high as 3.2 × 10¹. 0 atoms / cm 2 The product is scrapped.
[0023] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A method for dynamically controlling an electronic-grade polycrystalline silicon cleaning process, characterized in that, Includes the following steps: S1: Obtain the process parameters of the etching solution in the current cleaning tank. The process parameters include the concentration of hydrofluoric acid, the concentration of nitric acid, the temperature of the etching solution, and the total concentration of metal impurities in the etching solution. S2: Substitute the process parameters into the etching rate prediction formula to calculate the predicted etching rate; S3: Calculate the required baseline etching time based on the target etching depth and the predicted etching rate; S4: Determine whether the dynamic control conditions are met based on the reference etching time and the total concentration of metal impurities in the etching solution. If they are met, proceed to S5; otherwise, use the etching solution in the current cleaning tank to clean according to the reference etching time. S5: Dynamically regulate the cleaning process according to the dynamic regulation strategy.
2. The dynamic control method for an electronic-grade polycrystalline silicon cleaning process according to claim 1, characterized in that, In step S2, the etching rate prediction formula is: In the formula: R is the predicted etching rate; R0 is the pre-exponential factor; E a It is the apparent activation energy; T represents the current etching solution temperature, expressed in Kelvin. [HF] represents the current concentration of hydrofluoric acid in the etching solution; [HNO3] represents the current concentration of nitric acid in the etching solution; α and β are the reaction orders of HF and HNO3, respectively; k is the impurity suppression coefficient; C imp This represents the total concentration of metallic impurities in the current etching solution.
3. The dynamic control method for an electronic-grade polycrystalline silicon cleaning process according to claim 2, characterized in that, The pre-exponential factor R0, the apparent activation energy E a The methods for determining the reaction order α of HF, the reaction order β of HNO3, and the impurity inhibition coefficient k are as follows: S21. Record the etching thickness data of silicon samples under multiple sets of different experimental conditions, including hydrofluoric acid concentration, nitric acid concentration, temperature of etching solution and total concentration of metal impurities in etching solution. S22: Calculate the actual etching rate R under each experimental condition based on the etching thickness data of the silicon sample and the corresponding etching time; S23: Using the actual etching rate R as the training set, substitute the data from multiple sets of experimental conditions and the corresponding silicon sample etching thickness data into the etching rate prediction formula, and obtain the pre-exponential factor R0 and the apparent activation energy E through regression analysis. a The values of the reaction order α of HF, the reaction order β of HNO3, and the impurity inhibition coefficient k.
4. The dynamic control method for an electronic-grade polycrystalline silicon cleaning process according to claim 3, characterized in that, In step S21, the formula for calculating the etching thickness of the silicon sample is: H=(M2-M1)÷ρ÷(6×L 2 ) Where M1 and M2 are the masses of the sample before and after etching, respectively, ρ is the density of silicon, and L is the side length of the sample.
5. A dynamic control method for an electronic-grade polycrystalline silicon cleaning process according to claim 1 or 3, characterized in that, The total concentration of metallic impurities in the etching solution is expressed in ppm as iron equivalent.
6. A dynamic control method for an electronic-grade polycrystalline silicon cleaning process according to claim 1 or 3, characterized in that, Pre-exponential factor R0 = 2.47 × 10 6 μm / min; Apparent activation energy E a =42.3kJ / mol; The reaction order of HF is α = 0.68; The reaction order of HNO3 is β = 0.42; Impurity suppression coefficient k = 0.0025 ppm -1 .
7. The dynamic control method for an electronic-grade polycrystalline silicon cleaning process according to claim 1, characterized in that, In S4, the dynamic control condition is: The total concentration of metal impurities in the etching solution is greater than or equal to the preset first metal impurity concentration threshold.
8. The dynamic control method for an electronic-grade polycrystalline silicon cleaning process according to claim 7, characterized in that, In S5, the dynamic control strategy is as follows: If the preset first metal impurity concentration threshold is less than the total metal impurity concentration in the etching solution and the preset second metal impurity concentration threshold is greater than the preset first metal impurity concentration threshold, an online doping strategy is executed: fresh high-purity mixed acid is added to the cleaning tank, and the total metal impurity concentration in the doped etching solution after adding fresh high-purity mixed acid is measured to see if the dynamic control conditions are met. If they are met, the addition of fresh high-purity mixed acid continues until the dynamic control conditions are no longer met. Then, the new etching time was recalculated using the parameters of the mixed etching solution according to the etching rate prediction formula, and cleaning was performed according to the new etching time. If the total concentration of metal impurities in the etching solution is greater than or equal to the preset second metal impurity concentration threshold, an acid replacement strategy is implemented: the etching solution in the current cleaning tank is stopped, and fresh high-purity mixed acid is used to perform the cleaning process.
9. The dynamic control method for an electronic-grade polycrystalline silicon cleaning process according to claim 8, characterized in that, In the online blending strategy, the volume ratio of fresh high-purity mixed acid added to the cleaning tank to the etching solution in the current cleaning tank is 1:4.