A femtosecond laser nanotexturing method and system for bismuth-tellurium-based thermoelectric materials

Abstract

The present invention relates to the field of femtosecond laser processing technology, and discloses a femtosecond laser nanotexturing processing method and system for bismuth-tellurium-based thermoelectric materials, comprising a multi-dimensional monitoring module and an intelligent control module. The system obtains monitoring data of bismuth-tellurium-based thermoelectric material slices, laser energy monitoring data, and environmental sensing data through the multi-dimensional monitoring module, and classifies and forms data sets. The intelligent control module analyzes the degree of change in the surface temperature of each bismuth-tellurium-based thermoelectric material slice, generates a temperature rise index, and then monitors the roughening effect of each bismuth-tellurium-based thermoelectric material slice in real time, generates a femtosecond data set, and ensures precise control of energy density and scanning speed. The intelligent control module monitors the degree of influence of the processing environment on the femtosecond laser nanotexturing processing in real time, generates an environmental data set, and has high multi-dimensional monitoring accuracy, ensuring processing consistency. The femtosecond laser nanotexturing processing effect is then evaluated, and corresponding processing instructions are output, achieving excellent intelligent control processing effects.

Description

Technical Field

[0001] The present invention relates to the technical field of femtosecond laser processing, and in particular to a femtosecond laser nanotexturing processing method and system for bismuth-tellurium-based thermoelectric materials. Background Art

[0002] Bismuth-telluride-based thermoelectric materials, based on bismuth telluride, are doped with elements such as antimony, selenium, and silver to form alloys or composite materials, effectively optimizing their thermoelectric properties. These materials possess a unique hexagonal crystal structure, and their layered atomic arrangement results in significant anisotropy in their electrical and thermal conductivity. Their thermoelectric performance is primarily determined by the Seebeck coefficient, electrical conductivity, and thermal conductivity; higher values ​​for these parameters indicate improved thermoelectric conversion efficiency. The core advantage of bismuth-telluride-based thermoelectric materials lies in their high thermoelectric conversion efficiency near room temperature, particularly in the field of thermoelectric cooling. For example, they are widely used for local cooling of precision equipment such as laser diodes, infrared detectors, and CCD sensors, as well as for temperature control in portable refrigeration devices such as automotive air conditioners and water dispensers. However, in practical applications, the surface of bismuth-telluride-based thermoelectric materials is too smooth after slicing, resulting in insufficient adhesion when directly electroplated, leading to a weak coating. Therefore, surface roughening is necessary to enhance the adhesion of the coating. Since bismuth-tellurium-based materials are very brittle, traditional sandblasting can easily cause damage, and more gentle surface treatment methods need to be explored.

[0003] At present, traditional femtosecond laser nanotexturing methods for bismuth-tellurium-based thermoelectric materials mostly use thermal light source lasers. Due to the brittle layered crystal structure characteristics of bismuth-tellurium-based thermoelectric materials, high-energy lasers can easily induce microcracks or interlayer separation problems. At the same time, under high-temperature treatment environments, the tellurium and bismuth elements in bismuth-tellurium-based thermoelectric materials are prone to melting and decomposition, resulting in an imbalance in the stoichiometric ratio of the material. Although increasing the particle density and texture depth can improve the surface texturing effect, the texture depth is mainly determined by the laser power. Increasing the power will significantly increase the material temperature, thereby causing defects such as thermal stress accumulation and thermal damage. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a femtosecond laser nanotexturing processing method and system for bismuth-tellurium-based thermoelectric materials, which has the advantages of high multi-dimensional monitoring accuracy and good intelligent control processing effect. It solves the problems of easy delamination and unstable texturing effect in traditional femtosecond laser nanotexturing processing methods for bismuth-tellurium-based thermoelectric materials.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a femtosecond laser nanotexturing method for bismuth-tellurium-based thermoelectric materials, comprising the following steps:

[0006] Step 1: Connect the detection device, femtosecond laser, high-resolution spectrometer, and sensor device through the network to obtain monitoring data of the bismuth tellurium-based thermoelectric material slice, laser energy monitoring data, and environmental sensing data, and classify them into slice data sets, laser data sets, and environmental data sets;

[0007] Step 2: Based on the slice data set, analyze the degree of change in the surface temperature of each bismuth-tellurium-based thermoelectric material slice and generate the corresponding temperature rise index ;

[0008] Step 3: Based on the slice data set and laser data set, the texturing effect of each bismuth-tellurium-based thermoelectric material slice is monitored in real time to generate the corresponding femtosecond data set. ;

[0009] Step 4: Set a fixed range of gas content , ambient temperature range , Ambient ventilation range and ambient humidity range , combined with the environmental data set, real-time monitoring of the impact of the processing environment on the femtosecond laser nanotexturing process, and generating the corresponding environmental data set ;

[0010] Step 5: Set a fixed energy threshold and processing threshold , combined with the warming index , femtosecond data set and Environmental Data Group , evaluate the femtosecond laser nanotexturing effect of bismuth-tellurium-based thermoelectric materials and output corresponding processing instructions.

[0011] Preferably, in step 1, the slice data set includes the surface temperature, particle density and texture depth of each bismuth-tellurium-based thermoelectric material slice.

[0012] Preferably, in step 1, the laser data set includes pulse energy, spot area, laser power and scanning speed of the laser energy.

[0013] Preferably, in step 1, the environmental data set includes the inert gas content, temperature, ventilation volume and humidity of the processing environment.

[0014] Preferably, in step 2, the temperature rise index The calculation process is as follows:

[0015] According to the slice data set, the monitoring cycle is counted within, no. Monitoring data of bismuth-tellurium-based thermoelectric material slices, The surface of the bismuth-tellurium-based thermoelectric material slice is provided with monitoring points;

[0016] Based on the sliced ​​dataset, the monitoring period within, no. Bismuth-tellurium-based thermoelectric material slice The surface temperature of each monitoring point is marked as , , to Indicates the The monitoring points are from the first time point to the Surface temperature at a time point;

[0017]

[0018]

[0019] In the formula, Indicates the The average surface temperature of the monitoring points, According to the standard deviation formula, the Bismuth-tellurium-based thermoelectric material slice Temperature rise index at each monitoring point .

[0020] Preferably, in step 3, the femtosecond data set The calculation process is as follows:

[0021] According to the laser data set, the processing When slicing a bismuth-tellurium-based thermoelectric material, the monitoring data of the laser energy is obtained, and the pulse energy of the laser energy is marked as , the spot area of ​​laser energy is marked as , the laser power of the laser energy is marked as , the scanning speed of the laser energy is marked as ;

[0022] According to the slice data set, Bismuth-tellurium-based thermoelectric material slices Among the monitoring points, the maximum single-point surface temperature is marked as , will The particle density of a bismuth-tellurium-based thermoelectric material slice is marked as , will The texture depth of a bismuth-tellurium-based thermoelectric material slice is marked as ;

[0023]

[0024] In the formula, Indicates processing When slicing bismuth tellurium-based thermoelectric materials, the energy density of the laser energy is represents the ratio of particle density to laser power, represents the ratio of texture depth to laser power, It represents the ratio of the maximum single-point surface temperature to the scanning speed. Indicates processing A femtosecond data set of a bismuth-tellurium-based thermoelectric material slice.

[0025] Preferably, in step 4, the environmental data set The calculation process is as follows:

[0026] According to the environmental data set, the processing The environmental sensing data of the bismuth-tellurium-based thermoelectric material during slicing is obtained, and the inert gas content of the processing environment is marked as , mark the temperature of the processing environment as , mark the ventilation volume of the processing environment as , the humidity of the processing environment is marked as ;

[0027]

[0028] In the formula, and Indicates gas content range The lowest and highest values ​​of and Indicates the ambient temperature range The lowest and highest values ​​of and Indicates the ambient ventilation range The lowest and highest values ​​of and Indicates the ambient humidity range The lowest and highest values ​​of Indicates processing Environmental data set for slicing bismuth-tellurium-based thermoelectric materials.

[0029] Preferably, in step 5, the temperature rise index of any monitoring point of a single bismuth-tellurium-based thermoelectric material slice is When the temperature is greater than or equal to 200°C, it indicates that there is abnormal temperature rise locally and thermal stress accumulation is significant. The laser processing should be stopped immediately and the surface temperature of the bismuth-tellurium-based thermoelectric material slices should be reduced in time.

[0030] Preferably, in step 5, the femtosecond data set In the case of laser energy, the energy density is greater than the energy threshold When the ratio of particle density to laser power decreases with time, it means that the bismuth tellurium-based thermoelectric material slice has been thermally damaged, and the pulse energy should be reduced in time. If the ratio of particle density to laser power decreases with time, it means that the bismuth tellurium-based thermoelectric material slice has been melted and decomposed, and the laser power should be reduced in time. If the ratio of texture depth to laser power decreases with time, it means that the bismuth tellurium-based thermoelectric material slice has been delaminated and cracked, and the laser power should be reduced in time. If the ratio of the maximum single-point surface temperature to the scanning speed is greater than the processing threshold , indicating that the thermal stress accumulation of bismuth tellurium-based thermoelectric material slices is significant, and the scanning speed should be reduced in time. If any value exceeds the interval, it means that the processing environment affects the effect of femtosecond laser nanotexturing. The laser processing should be stopped immediately and the processing environment should be adjusted in time.

[0031] A femtosecond laser nanotexturing processing system for bismuth-tellurium-based thermoelectric materials, comprising a multi-dimensional monitoring module and an intelligent control module;

[0032] The multi-dimensional monitoring module consists of a slice data unit, a processing data unit and a sensor data unit. The slice data unit collects slice data sets through a network connection to a detection device, the processing data unit collects laser data sets through a network connection to a femtosecond laser and a high-resolution spectrometer, and the sensor data unit collects environmental data sets through a network connection to a sensor device.

[0033] The intelligent control module consists of a temperature monitoring unit, a laser monitoring unit, an environmental monitoring unit, and a processing management unit. The temperature monitoring unit analyzes the change in surface temperature of each bismuth-tellurium-based thermoelectric material slice based on the slice data set and generates a corresponding temperature rise index. The laser monitoring unit monitors the roughening effect of each bismuth-tellurium-based thermoelectric material slice in real time based on the slice data set and the laser data set, and generates the corresponding femtosecond data set. The environmental monitoring unit is provided with a fixed range of gas content intervals. , ambient temperature range , Ambient ventilation range and ambient humidity range , combined with the environmental data set, real-time monitoring of the impact of the processing environment on the femtosecond laser nanotexturing process, and generating the corresponding environmental data set The processing management unit is set with a fixed energy threshold and processing threshold , combined with the warming index , femtosecond data set and Environmental Data Group , evaluate the femtosecond laser nanotexturing effect of bismuth-tellurium-based thermoelectric materials and output corresponding processing instructions.

[0034] Compared with the prior art, the present invention provides a femtosecond laser nanotexturing method and system for bismuth-tellurium-based thermoelectric materials, which has the following beneficial effects:

[0035] 1. The present invention connects the detection device, femtosecond laser, high-resolution spectrometer and sensor device through a multi-dimensional monitoring module network to obtain the monitoring data of the bismuth tellurium-based thermoelectric material slice, the monitoring data of the laser energy and the environmental sensing data, and classifies them into slice data sets, laser data sets and environmental data sets. The intelligent control module analyzes the degree of change in the surface temperature of each bismuth tellurium-based thermoelectric material slice based on the slice data sets and generates the corresponding temperature rise index Then, based on the slice data set and laser data set, the texturing effect of each bismuth-tellurium-based thermoelectric material slice is monitored in real time to generate the corresponding femtosecond data set. To ensure precise control of energy density and scanning speed, the intelligent control module is set with a fixed range of gas content intervals. , ambient temperature range , Ambient ventilation range and ambient humidity range , combined with the environmental data set, real-time monitoring of the impact of the processing environment on the femtosecond laser nanotexturing process, and generating the corresponding environmental data set Insufficient inert gas content may cause material oxidation, and excessive humidity may affect laser energy transmission. Multi-dimensional monitoring has high accuracy and ensures processing consistency.

[0036] 2. The present invention sets a fixed energy threshold through the intelligent control module and processing threshold , combined with the warming index , femtosecond data set and Environmental Data Group , evaluate the femtosecond laser nanotexturing treatment effect of bismuth tellurium-based thermoelectric materials, and output corresponding processing instructions, accurately optimize the surface morphology of bismuth tellurium-based thermoelectric materials, ensure the thermoelectric conversion efficiency of the materials, improve the material performance, reduce the scrap rate, and achieve excellent intelligent control processing effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a step diagram of the method of the present invention;

[0038] Figure 2 This is a flow chart of the system of the present invention. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0040] Traditional femtosecond laser nanotexturing methods for bismuth-tellurium-based thermoelectric materials mostly use thermal light source lasers. Since bismuth-tellurium-based thermoelectric materials have brittle layered crystal structures, high-energy lasers can easily induce microcracks or interlayer separation. At the same time, under high-temperature processing environments, the tellurium and bismuth elements in bismuth-tellurium-based thermoelectric materials are prone to melting and decomposition, resulting in an imbalance in the stoichiometric ratio of the material. Although increasing the particle density and texture depth can improve the surface roughening effect, the texture depth is mainly determined by the laser power. Increasing the power will significantly increase the material temperature, which in turn causes defects such as thermal stress accumulation and thermal damage. Therefore, a femtosecond laser nanotexturing method and system for bismuth-tellurium-based thermoelectric materials are provided. Please refer to Figure 1-Figure 2 A femtosecond laser nanotexturing method for bismuth-tellurium-based thermoelectric materials comprises the following steps:

[0041] Step 1: Connect the detection device, femtosecond laser, high-resolution spectrometer, and sensor device through the network to obtain monitoring data of the bismuth tellurium-based thermoelectric material slice, laser energy monitoring data, and environmental sensing data, and classify them into slice data sets, laser data sets, and environmental data sets;

[0042] The slice data set includes the surface temperature, grain density, and texture depth of each bismuth-tellurium-based thermoelectric material slice;

[0043] The laser data set includes the pulse energy, spot area, laser power, and scanning speed of the laser energy;

[0044] The environmental data set includes the inert gas content, temperature, ventilation rate, and humidity of the processing environment;

[0045] Step 2: Based on the slice data set, analyze the degree of change in the surface temperature of each bismuth-tellurium-based thermoelectric material slice and generate the corresponding temperature rise index ;

[0046] Warming Index The calculation process is as follows:

[0047] According to the slice data set, the monitoring cycle is counted within, no. Monitoring data of bismuth-tellurium-based thermoelectric material slices, The surface of the bismuth-tellurium-based thermoelectric material slice is provided with monitoring points;

[0048] Based on the sliced ​​dataset, the monitoring period within, no. Bismuth-tellurium-based thermoelectric material slice The surface temperature of each monitoring point is marked as , , to Indicates the The monitoring points are from the first time point to the Surface temperature at a time point;

[0049]

[0050]

[0051] In the formula, Indicates the The average surface temperature of the monitoring points, According to the standard deviation formula, the Bismuth-tellurium-based thermoelectric material slice Temperature rise index at each monitoring point , real-time monitoring of temperature fluctuations. The higher the value, the more significant the accumulation of local thermal stress.

[0052] Step 3: Based on the slice data set and laser data set, the texturing effect of each bismuth-tellurium-based thermoelectric material slice is monitored in real time to generate the corresponding femtosecond data set. ;

[0053] Femtosecond data set The calculation process is as follows:

[0054] According to the laser data set, the processing When slicing a bismuth-tellurium-based thermoelectric material, the monitoring data of the laser energy is obtained, and the pulse energy of the laser energy is marked as , the spot area of ​​laser energy is marked as , the laser power of the laser energy is marked as , the scanning speed of the laser energy is marked as ;

[0055] According to the slice data set, Bismuth-tellurium-based thermoelectric material slices Among the monitoring points, the maximum single-point surface temperature is marked as , will The particle density of a bismuth-tellurium-based thermoelectric material slice is marked as , will The texture depth of a bismuth-tellurium-based thermoelectric material slice is marked as ;

[0056]

[0057] In the formula, Indicates processing When slicing bismuth-tellurium-based thermoelectric materials, the energy density of the laser energy directly reflects the energy input of the laser to the material. Too high a density can easily lead to ablation. represents the ratio of particle density to laser power, represents the ratio of texture depth to laser power, It represents the ratio of the maximum single-point surface temperature to the scanning speed. Indicates processing A femtosecond data set of bismuth-tellurium-based thermoelectric materials sliced ​​to ensure precise control of energy density and scanning speed;

[0058] Step 4: Set a fixed range of gas content , ambient temperature range , Ambient ventilation range and ambient humidity range , combined with the environmental data set, real-time monitoring of the impact of the processing environment on the femtosecond laser nanotexturing process, and generating the corresponding environmental data set ;

[0059] Environmental Data Group The calculation process is as follows:

[0060] According to the environmental data set, the processing The environmental sensing data of the bismuth-tellurium-based thermoelectric material during slicing is obtained, and the inert gas content of the processing environment is marked as , mark the temperature of the processing environment as , mark the ventilation volume of the processing environment as , the humidity of the processing environment is marked as ;

[0061]

[0062] In the formula, and Indicates gas content range The lowest and highest values ​​of and Indicates the ambient temperature range The lowest and highest values ​​of and Indicates the ambient ventilation range The lowest and highest values ​​of and Indicates the ambient humidity range The lowest and highest values ​​of Indicates processing The environmental data set for slicing bismuth-tellurium-based thermoelectric materials was obtained. Insufficient inert gas content may cause material oxidation, and excessive humidity may affect laser energy transmission. Multi-dimensional monitoring with high accuracy ensures processing consistency.

[0063] Step 5: Set a fixed energy threshold and processing threshold , combined with the warming index , femtosecond data set and Environmental Data Group , evaluate the femtosecond laser nanotexturing effect of bismuth-tellurium-based thermoelectric materials and output corresponding processing instructions;

[0064] Temperature rise index of any monitoring point of a single bismuth-tellurium-based thermoelectric material slice When the temperature is greater than or equal to 200°C, it indicates that there is an abnormal temperature rise in a certain area and the thermal stress accumulation is significant. The laser processing should be stopped immediately and the surface temperature of the bismuth-tellurium-based thermoelectric material slice should be reduced in time.

[0065] Femtosecond data set In the case of laser energy, the energy density is greater than the energy threshold When the ratio of particle density to laser power decreases with time, it means that the bismuth tellurium-based thermoelectric material slice has been thermally damaged, and the pulse energy should be reduced in time. If the ratio of particle density to laser power decreases with time, it means that the bismuth tellurium-based thermoelectric material slice has been melted and decomposed, and the laser power should be reduced in time. If the ratio of texture depth to laser power decreases with time, it means that the bismuth tellurium-based thermoelectric material slice has been delaminated and cracked, and the laser power should be reduced in time. If the ratio of the maximum single-point surface temperature to the scanning speed is greater than the processing threshold , indicating that the thermal stress accumulation of bismuth-tellurium-based thermoelectric material slices is significant, and the scanning speed should be reduced in time. Environmental data group If any value exceeds the interval, it means that the processing environment affects the effect of femtosecond laser nanotexturing. The laser processing should be stopped immediately and the processing environment should be adjusted in time to accurately optimize the surface morphology of the bismuth-tellurium-based thermoelectric material, thereby ensuring the thermoelectric conversion efficiency of the material, improving the material performance, and reducing the scrap rate.

[0066] A femtosecond laser nanotexturing processing system for bismuth-tellurium-based thermoelectric materials, comprising a multi-dimensional monitoring module and an intelligent control module;

[0067] The multi-dimensional monitoring module consists of a slicing data unit, a processing data unit, and a sensing data unit. The slicing data unit collects slicing data sets through a network connection to a detection device. The processing data unit collects laser data sets through a network connection to a femtosecond laser and a high-resolution spectrometer. The sensing data unit collects environmental data sets through a network connection to a sensing device.

[0068] The intelligent control module consists of a temperature monitoring unit, a laser monitoring unit, an environmental monitoring unit, and a processing management unit. The temperature monitoring unit analyzes the surface temperature change of each bismuth-tellurium-based thermoelectric material slice based on the slice data set and generates a corresponding temperature rise index. The laser monitoring unit monitors the roughening effect of each bismuth-tellurium-based thermoelectric material slice in real time based on the slice data set and the laser data set, and generates the corresponding femtosecond data set. , the environmental monitoring unit is set with a fixed range of gas content intervals , ambient temperature range , Ambient ventilation range and ambient humidity range , combined with the environmental data set, real-time monitoring of the impact of the processing environment on the femtosecond laser nanotexturing process, and generating the corresponding environmental data set , multi-dimensional monitoring with high accuracy, the processing management unit is set with a fixed energy threshold and processing threshold , combined with the warming index , femtosecond data set and Environmental Data Group , evaluate the femtosecond laser nanotexturing treatment effect of bismuth tellurium-based thermoelectric materials, and output corresponding processing instructions, with intelligent control and good processing effect.

[0069] Example 1:

[0070] In this experiment, a bismuth-tellurium-based thermoelectric material slice with five monitoring points was selected as the experimental object. The monitoring points were distributed at the center and four corners of the material. After testing, the surface temperature of the central monitoring point of the material was 245℃, 247℃, 120℃, 48℃ and 46℃ respectively within 5 minutes. The temperature rise index of the central monitoring point was 245℃, 247℃, 120℃, 48℃ and 46℃ respectively. The calculation process is as follows:

[0071]

[0072]

[0073] In the formula, Represents the average value of the surface temperature of the central monitoring point. According to the standard deviation formula, the temperature rise index of the central monitoring point of the bismuth tellurium-based thermoelectric material slice is calculated. Approximately , it is judged that the temperature rise index of the monitoring point at the center of the bismuth-tellurium-based thermoelectric material slice is The temperature did not reach 200°C, and there was no abnormal temperature rise at the central monitoring point, so laser processing could continue.

[0074] Example 2:

[0075] In this experiment, a femtosecond laser with a spot area of ​​2cm² was selected as the experimental object. After testing, the pulse energy of the laser energy was 10J, the laser power was 5W, the scanning speed was 10mm / s, the maximum single-point surface temperature of the tellurium-based thermoelectric material slice was 80℃, the particle density was 4 particles / cm³, and the texture depth was 0.5mm. The femtosecond data set when processing the bismuth-tellurium-based thermoelectric material slice was obtained. The calculation process is as follows:

[0076]

[0077] In the formula, J / cm² represents the energy density of the laser energy when processing the bismuth-tellurium-based thermoelectric material slice. Particles / (cm³·W) represents the ratio of particle density to laser power. mm / W represents the ratio of texture depth to laser power. ℃ / (mm / s) represents the ratio of the maximum single-point surface temperature to the scanning speed, energy threshold Set to 1J / cm², processing threshold The speed is set to 10℃ / (mm / s). It is judged that when processing the bismuth-tellurium-based thermoelectric material slice, the energy density of the laser energy is greater than the energy threshold. , indicating that the bismuth-tellurium-based thermoelectric material slice has suffered thermal damage and the pulse energy should be reduced in time.

[0078] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A femtosecond laser nanotexturing method for bismuth-tellurium-based thermoelectric materials, characterized in that: The following steps are involved: Step 1: Connect the detection device, femtosecond laser, high-resolution spectrometer, and sensor device through the network to obtain monitoring data of the bismuth tellurium-based thermoelectric material slice, laser energy monitoring data, and environmental sensing data, and classify them into slice data sets, laser data sets, and environmental data sets; Step 2: Based on the slice data set, analyze the degree of change in the surface temperature of each bismuth-tellurium-based thermoelectric material slice and generate the corresponding temperature rise index ; Step 3: Based on the slice data set and laser data set, the texturing effect of each bismuth-tellurium-based thermoelectric material slice is monitored in real time to generate the corresponding femtosecond data set. ; Femtosecond data set The calculation process is as follows: According to the laser data set, the processing When slicing a bismuth-tellurium-based thermoelectric material, the monitoring data of the laser energy is obtained, and the pulse energy of the laser energy is marked as , the spot area of ​​laser energy is marked as , the laser power of the laser energy is marked as , the scanning speed of the laser energy is marked as ; According to the slice data set, Bismuth-tellurium-based thermoelectric material slices Among the monitoring points, the maximum single-point surface temperature is marked as , will The particle density of a bismuth-tellurium-based thermoelectric material slice is marked as , will The texture depth of a bismuth-tellurium-based thermoelectric material slice is marked as ; In the formula, Indicates processing When slicing bismuth tellurium-based thermoelectric materials, the energy density of the laser energy is represents the ratio of particle density to laser power, represents the ratio of texture depth to laser power, It represents the ratio of the maximum single-point surface temperature to the scanning speed. Indicates processing A femtosecond data set of bismuth-tellurium-based thermoelectric materials sliced; Step 4: Set a fixed range of gas content , ambient temperature range , Ambient ventilation range and ambient humidity range , combined with the environmental data set, real-time monitoring of the impact of the processing environment on the femtosecond laser nanotexturing process, and generating the corresponding environmental data set ; Step 5: Set a fixed energy threshold and processing threshold , combined with the warming index , femtosecond data set and Environmental Data Group , evaluate the femtosecond laser nanotexturing effect of bismuth-tellurium-based thermoelectric materials and output corresponding processing instructions; Femtosecond data set In the case of laser energy, the energy density is greater than the energy threshold When the ratio of particle density to laser power decreases with time, it means that the bismuth tellurium-based thermoelectric material slice has been thermally damaged, and the pulse energy should be reduced in time. If the ratio of particle density to laser power decreases with time, it means that the bismuth tellurium-based thermoelectric material slice has been melted and decomposed, and the laser power should be reduced in time. If the ratio of texture depth to laser power decreases with time, it means that the bismuth tellurium-based thermoelectric material slice has been delaminated and cracked, and the laser power should be reduced in time. If the ratio of the maximum single-point surface temperature to the scanning speed is greater than the processing threshold , indicating that the thermal stress accumulation of bismuth tellurium-based thermoelectric material slices is significant, and the scanning speed should be reduced in time. If any value exceeds the interval, it means that the processing environment affects the effect of femtosecond laser nanotexturing. The laser processing should be stopped immediately and the processing environment should be adjusted in time.

2. The femtosecond laser nanotexturing method for bismuth-tellurium-based thermoelectric materials according to claim 1, characterized in that: In the step 1, the slice data set includes the surface temperature, particle density and texture depth of each bismuth-tellurium-based thermoelectric material slice.

3. The femtosecond laser nanotexturing method for bismuth-tellurium-based thermoelectric materials according to claim 2, characterized in that: In step 1, the laser data set includes the pulse energy, spot area, laser power and scanning speed of the laser energy.

4. The femtosecond laser nanotexturing method for bismuth-tellurium-based thermoelectric materials according to claim 3, characterized in that: In step 1, the environmental data set includes the inert gas content, temperature, ventilation volume and humidity of the processing environment.

5. The femtosecond laser nanotexturing method for bismuth-tellurium-based thermoelectric materials according to claim 4, characterized in that: In the step 2, the temperature rise index The calculation process is as follows: According to the slice data set, the monitoring cycle is counted within, no. Monitoring data of bismuth-tellurium-based thermoelectric material slices, The surface of the bismuth-tellurium-based thermoelectric material slice is provided with monitoring points; Based on the sliced ​​dataset, the monitoring period within, no. Bismuth-tellurium-based thermoelectric material slice The surface temperature of each monitoring point is marked as , , to Indicates the The monitoring points are from the first time point to the Surface temperature at a time point; In the formula, Indicates the The average surface temperature of the monitoring points, According to the standard deviation formula, the Bismuth-tellurium-based thermoelectric material slice Temperature rise index at each monitoring point .

6. The femtosecond laser nanotexturing method for bismuth-tellurium-based thermoelectric materials according to claim 5, characterized in that: In step 4, the environmental data set The calculation process is as follows: According to the environmental data set, the processing The environmental sensing data of the bismuth-tellurium-based thermoelectric material during slicing is obtained, and the inert gas content of the processing environment is marked as , mark the temperature of the processing environment as , mark the ventilation volume of the processing environment as , the humidity of the processing environment is marked as ; In the formula, and Indicates gas content range The lowest and highest values ​​of and Indicates the ambient temperature range The lowest and highest values ​​of and Indicates the ambient ventilation range The lowest and highest values ​​of and Indicates the ambient humidity range The lowest and highest values ​​of Indicates processing Environmental data set for slicing bismuth-tellurium-based thermoelectric materials.

7. The femtosecond laser nanotexturing method for bismuth-tellurium-based thermoelectric materials according to claim 6, characterized in that: In step 5, the temperature rise index of any monitoring point of a single bismuth-tellurium-based thermoelectric material slice is When the temperature is greater than or equal to 200°C, it indicates that there is abnormal temperature rise locally and thermal stress accumulation is significant. The laser processing should be stopped immediately and the surface temperature of the bismuth-tellurium-based thermoelectric material slices should be reduced in time.

8. A femtosecond laser nanotexturing system for bismuth-tellurium-based thermoelectric materials, applied to a femtosecond laser nanotexturing method for bismuth-tellurium-based thermoelectric materials according to any one of claims 1 to 7, characterized in that: Including multi-dimensional monitoring module and intelligent control module; The multi-dimensional monitoring module consists of a slice data unit, a processing data unit and a sensor data unit. The slice data unit collects slice data sets through a network connection to a detection device, the processing data unit collects laser data sets through a network connection to a femtosecond laser and a high-resolution spectrometer, and the sensor data unit collects environmental data sets through a network connection to a sensor device. The intelligent control module consists of a temperature monitoring unit, a laser monitoring unit, an environmental monitoring unit, and a processing management unit. The temperature monitoring unit analyzes the change in surface temperature of each bismuth-tellurium-based thermoelectric material slice based on the slice data set and generates a corresponding temperature rise index. The laser monitoring unit monitors the roughening effect of each bismuth-tellurium-based thermoelectric material slice in real time based on the slice data set and the laser data set, and generates the corresponding femtosecond data set. The environmental monitoring unit is provided with a fixed range of gas content intervals. , ambient temperature range , Ambient ventilation range and ambient humidity range , combined with the environmental data set, real-time monitoring of the impact of the processing environment on the femtosecond laser nanotexturing process, and generating the corresponding environmental data set The processing management unit is set with a fixed energy threshold and processing threshold , combined with the warming index , femtosecond data set and Environmental Data Group , evaluate the femtosecond laser nanotexturing effect of bismuth-tellurium-based thermoelectric materials and output corresponding processing instructions.

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