Preparation method of coating for realizing high absorbance on surface of base material

Abstract

The invention discloses a preparation method of a coating for realizing high absorbance on a substrate surface, which comprises the following steps: designing a PVD (Physical Vapor Deposition) coating structure according to the type of a coating material, and controlling the thickness of the coating to be within a preset range by adjusting deposition parameters; pretreating the carbon nano tube by adopting a high-speed shearing dispersion technology, and measuring the performance of the carbon nano tube dispersion liquid; establishing a coating formula database according to the performance of the carbon nanotube dispersion liquid, and screening solvent types through an orthogonal test; carrying out surface modification on the carbon nano tube by adopting plasma treatment, and measuring the content of functional groups on the surface of the carbon nano tube; the uniformity of the coating is improved in a multi-time coating mode, infrared drying is carried out after each time of coating, and the thickness of the coating is measured; and the surface roughness and hardness of the coating are measured, and the preliminarily screened PVD coating material is obtained.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to a method for preparing a coating with high light absorbance on the surface of a substrate. Background Art

[0002] High absorbance materials are mainly used in camera modules of electronic communication equipment. Traditional micro-arc oxidation surface treatment cannot achieve ideal absorbance. Carbon nanotube all-black materials can solve the problem of high absorbance. However, in the screening of PVD coating materials and the matching research of carbon nanotube coatings, we are faced with a series of interrelated technical challenges.

[0003] First, the thickness and structure of the PVD coating need to be controlled by adjusting the deposition parameters to obtain the best surface properties. At the same time, the dispersion of carbon nanotubes directly affects the uniformity and performance of the coating, so the dispersion process needs to be optimized. In addition, the optimization of the carbon nanotube coating formula involves multiple variables, such as content, aspect ratio and purity, which are closely related to the matching of the PVD coating. During the coating preparation process, the selection of spin coating, spray coating or dip coating process parameters directly affects the coating quality, while multiple coating and drying processes affect the uniformity and thickness of the coating. Most importantly, the interfacial bonding strength between the PVD coating and the carbon nanotube coating determines the overall performance of the composite coating, which may need to be improved by plasma treatment. These issues are intertwined, forming a complex network of technical problems that need to be systematically solved to achieve the preparation of high-performance composite coatings. Summary of the invention

[0004] In order to effectively solve the above technical problems, the present invention provides a method for preparing a coating having high light absorbance on the surface of a substrate, the method comprising:

[0005] Designing the PVD coating structure according to the type of coating material, and controlling the coating thickness within a preset range by adjusting deposition parameters;

[0006] Pretreating the carbon nanotubes by high-speed shear dispersion technology and measuring the performance of the carbon nanotube dispersion;

[0007] Establishing a coating formula database according to the properties of the carbon nanotube dispersion and screening the solvent types through orthogonal experiments;

[0008] Modifying the surface of the carbon nanotubes by plasma treatment, and measuring the content of functional groups on the surface of the carbon nanotubes;

[0009] The coating uniformity is improved by using multiple coating methods, and drying is performed after each coating, and the coating thickness is measured;

[0010] The surface roughness and hardness of the coating were measured to obtain the preliminarily screened PVD coating material.

[0011] Preferably, the PVD coating structure is designed according to the type of coating material, and the coating thickness is controlled within a preset range by adjusting deposition parameters, including:

[0012] Obtain information about the type of coating material and determine the design parameters of the PVD coating structure based on the material properties;

[0013] For different coating materials, select matching deposition parameter combinations from the preset PVD process parameter library;

[0014] The coating material type, coating structure design parameters and deposition parameters are combined and input into the neural network model to predict the coating thickness;

[0015] Determine whether the predicted coating thickness is within a preset range, and if not, adjust the deposition parameters and re-predict the coating thickness;

[0016] When the predicted coating thickness meets the preset range requirements, the PVD coating structure design and deposition parameter combination are determined as the optimal process parameters;

[0017] Apply the optimal process parameters to the PVD equipment to deposit and prepare a coating structure that meets the thickness requirements;

[0018] Scanning electron microscopy and other characterization methods were used to measure the actual thickness of the coating and verify the effectiveness of the optimized PVD process parameters.

[0019] Preferably, the high-speed shear dispersion technology is used to pretreat the carbon nanotubes and the performance of the carbon nanotube dispersion is measured, including:

[0020] Determine the shear rate and dispersion time parameters of the high-speed shear dispersion device according to the initial length and diameter of the carbon nanotubes, and control the shear rate and dispersion time to make the carbon nanotubes reach a preset length and diameter range;

[0021] The carbon nanotubes are added into a preset dispersion medium, and the carbon nanotubes are pretreated by a high-speed shear dispersion technology, so that the carbon nanotubes are evenly dispersed in the dispersion medium by shearing to obtain a carbon nanotube dispersion liquid;

[0022] The particle size distribution of the carbon nanotube dispersion is measured by a dynamic light scattering method, and whether the dispersion uniformity of the carbon nanotubes in the dispersion reaches a preset threshold is determined according to the measurement result;

[0023] If the dispersion uniformity does not reach the preset threshold, the shear speed and dispersion time parameters of the high-speed shear dispersion device are adjusted, and the above steps are repeated until the dispersion uniformity reaches the preset threshold;

[0024] Using a transmission electron microscope to observe the morphology of the carbon nanotube dispersion, measure the length and diameter of the carbon nanotubes, and determine whether the size of the carbon nanotubes is within a preset range;

[0025] If the size of the carbon nanotubes is not within the preset range, adjusting the shear rate and dispersion time parameters of the high-speed shear dispersion device according to the degree of deviation from the preset range, and repeating steps 2 to 5 until the size of the carbon nanotubes is within the preset range;

[0026] The prepared carbon nanotube dispersion is applied to subsequent processes, such as composite material preparation and conductive coating preparation, and the performance of the composite material or coating is tested to verify whether the dispersion performance of the carbon nanotube dispersion meets the application requirements.

[0027] Preferably, the coating uniformity is improved by using multiple coating methods, infrared drying is performed after each coating, and the coating thickness is measured, including:

[0028] An automated coating system is used, which can control the uniformity of the coating and automatically adjust the coating parameters to ensure consistent thickness after each coating;

[0029] Monitor the coating drying process through infrared sensors and adjust the drying temperature and time in real time to optimize the coating drying effect;

[0030] Use machine vision technology to detect the coating in real time, and use image analysis algorithms to identify the uniformity and thickness of the coating. If uneven coating or thickness that does not meet preset standards is detected, the coating parameters are automatically adjusted or the coating process is repeated;

[0031] The data analysis module collects data from the coating and drying process, and uses machine learning algorithms to analyze the relationship between coating quality and process parameters to achieve more accurate process control;

[0032] After integrating these technologies, an integrated control system is used to coordinate each link of coating, drying and inspection to ensure that the final quality of the coating meets industrial application standards.

[0033] Preferably, the measuring of the surface roughness and hardness of the coating to obtain the preliminarily screened PVD coating material comprises:

[0034] First, the surface roughness of the PVD coating was quantified using precision measuring equipment and the resulting data was recorded;

[0035] Measure the hardness of the coating using a hardness testing instrument and also record the measurement results;

[0036] The acquired surface roughness and hardness data are stored in the database to provide data support for subsequent analysis;

[0037] Data analysis software was used to statistically analyze the recorded roughness and hardness data to determine the average roughness and hardness values ​​for each material;

[0038] According to the preset screening criteria, the analysis results are evaluated and the coating materials that meet the criteria are screened out;

[0039] Evaluate the performance of the selected materials and compare other performance parameters to ensure that the comprehensive performance of the materials meets the application requirements;

[0040] Finally, a preferred PVD coating material is obtained.

[0041] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0042] The present invention discloses a method for preparing a coating with high absorbance on the surface of a substrate, which is combined with the pretreatment and surface modification technology of carbon nanotubes to improve the performance of the coating. First, the carbon nanotubes are pretreated by high-speed shear dispersion technology, and the performance of the dispersion liquid is measured. A coating formula database is established based on the performance, and a suitable solvent type is screened by orthogonal test. Subsequently, the carbon nanotubes are surface modified by plasma treatment, and the content of surface functional groups is measured to enhance the binding force between the carbon nanotubes and the coating material. The uniformity of the coating is improved by multiple coating methods, and infrared drying is performed after each coating, and the coating thickness is measured to ensure that it is within a preset range. Finally, the surface roughness and hardness of the coating are measured to obtain a preliminarily screened PVD coating material. The present invention achieves an effective improvement in coating thickness, uniformity and surface performance through the optimization and control of a series of process steps, and ultimately improves the overall performance and application effect of the coating. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 The present invention is a flow chart of a method for preparing a coating having high light absorbance on a substrate surface.

[0044] Figure 2 It is a schematic diagram of a method for preparing a coating having high light absorbance on a substrate surface according to the present invention.

[0045] Figure 3 This is another schematic diagram of a method for preparing a coating having high light absorbance on a substrate surface according to the present invention. DETAILED DESCRIPTION

[0046] In order to further understand the content of the present invention, the present invention is described in detail in conjunction with the accompanying drawings and embodiments. The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are only used to explain the relevant inventions, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the invention are shown in the accompanying drawings.

[0047] Embodiment 1:

[0048] like Figure 1-3 In this embodiment, a method for preparing a coating having high light absorbance on a substrate surface may specifically include:

[0049] Step S101, designing the PVD coating structure according to the type of coating material, and controlling the coating thickness within a preset range by adjusting deposition parameters.

[0050] Obtain information on the type of coating material, and determine the design parameters of the PVD coating structure based on the material properties. For different coating materials, select a matching combination of deposition parameters from the preset PVD process parameter library. Input the type of coating material, coating structure design parameters, and deposition parameter combination into the neural network model to predict the coating thickness. Determine whether the predicted coating thickness is within the preset range. If not, adjust the deposition parameters and re-predict the coating thickness. When the predicted coating thickness meets the preset range requirements, determine the PVD coating structure design and deposition parameter combination as the optimal process parameters. Apply the optimal process parameters to the PVD equipment to deposit and prepare a coating structure that meets the thickness requirements. Use characterization methods such as scanning electron microscopy to measure the actual thickness of the coating and verify the effectiveness of the optimized PVD process parameters.

[0051] Step S102, pre-treating the carbon nanotubes by using a high-speed shear dispersion technique, and measuring the properties of the carbon nanotube dispersion.

[0052] According to the initial length and diameter of the carbon nanotubes, the shear speed and dispersion time parameters of the high-speed shear dispersion device are determined, and the carbon nanotubes are made to reach the preset length and diameter range by controlling the shear speed and dispersion time. The carbon nanotubes are added to the preset dispersion medium, and the carbon nanotubes are pretreated by the high-speed shear dispersion technology. The carbon nanotubes are uniformly dispersed in the dispersion medium by shearing to obtain a carbon nanotube dispersion. The particle size distribution of the carbon nanotube dispersion is measured by dynamic light scattering method, and it is judged whether the dispersion uniformity of the carbon nanotubes in the dispersion reaches the preset threshold value according to the measurement results. If the dispersion uniformity does not reach the preset threshold value, the shear speed and dispersion time parameters of the high-speed shear dispersion device are adjusted, and steps 2 and 3 are repeated until the dispersion uniformity reaches the preset threshold value. The morphology of the carbon nanotube dispersion is observed by a transmission electron microscope, and the length and diameter of the carbon nanotubes are measured to determine whether the size of the carbon nanotubes is within the preset range. If the size of the carbon nanotubes is not within the preset range, the shear speed and dispersion time parameters of the high-speed shear dispersion device are adjusted according to the degree of deviation from the preset range, and steps 2 to 5 are repeated until the size of the carbon nanotubes is within the preset range. The prepared carbon nanotube dispersion is applied to subsequent processes, such as composite material preparation, conductive coating preparation, etc., and the performance of the composite material or coating is tested to verify whether the dispersion performance of the carbon nanotube dispersion meets the application requirements.

[0053] Step S103, establishing a coating formula database according to the properties of the carbon nanotube dispersion, and screening solvent types through orthogonal experiments.

[0054] According to the performance parameters of the carbon nanotube dispersion, a coating formula database is established, and the corresponding relationship between the performance parameters of the carbon nanotube dispersion and the coating formula is recorded in the database. For the coating formula in the database, an orthogonal test method is used, with the solvent type as the independent variable and the coating performance as the dependent variable, to conduct multiple groups of orthogonal tests. Through machine learning algorithms such as support vector machines or neural networks, the orthogonal test data is trained to obtain the association model between the solvent type and the coating performance. According to the established association model, the performance of the coating under different solvent types is predicted, and the combination of solvent types with the best performance is screened out. The selected optimal solvent type combination is matched with the performance parameters of the carbon nanotube dispersion, and the corresponding optimal coating formula is queried in the database. If the matching optimal formula cannot be queried in the database, a new coating formula is generated by optimizing the optimal solvent type combination through genetic algorithm. The generated new formula is added to the database, and the corresponding relationship between the performance of the carbon nanotube dispersion and the coating formula is continuously improved and expanded, providing a reference for subsequent formula design.

[0055] Step S104: performing surface modification on the carbon nanotubes by plasma treatment, and measuring the content of functional groups on the surface of the carbon nanotubes.

[0056] According to the surface properties and chemical structure of carbon nanotubes, suitable plasma treatment technology and process parameters are determined. Carbon nanotubes are placed in a plasma reaction chamber, reaction gases are introduced, and parameters such as radio frequency power, pressure, and treatment time are adjusted to modify the surface of carbon nanotubes. Characterization methods such as X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR) are used to analyze the changes in the surface chemical structure of carbon nanotubes and determine the types and quantities of functional groups. The effects of plasma treatment on the physical properties of carbon nanotubes, such as thermal stability and crystallinity, are evaluated by means of thermogravimetric analysis (TGA) and Raman spectroscopy. According to the measurement results of the functional group content, the modification effect of plasma treatment is judged and the process parameters are optimized to obtain ideal surface properties. The modified carbon nanotubes are applied to composite materials, electrode materials, catalysts and other fields to evaluate their performance improvement effects and provide guidance for material applications. A mathematical model between plasma treatment process parameters and carbon nanotube surface properties is established, and machine learning algorithms such as support vector machines (SVM) and artificial neural networks (ANN) are used to achieve process optimization and performance prediction.

[0057] Step S105, using multiple coating methods to improve the uniformity of the coating, performing infrared drying after each coating, and measuring the coating thickness.

[0058] An automated coating system is used that can control the uniformity of the coating and automatically adjust the coating parameters to ensure consistent thickness after each coating. The coating drying process is monitored by infrared sensors, and the drying temperature and time are adjusted in real time to optimize the drying effect of the coating. The coating is inspected in real time using machine vision technology, and the uniformity and thickness of the coating are identified through image analysis algorithms. If uneven coating or thickness does not meet the preset standards is detected, the coating parameters are automatically adjusted or the coating process is repeated. Data from the coating and drying processes are collected through a data analysis module, and the relationship between coating quality and process parameters is analyzed using a machine learning algorithm to achieve more accurate process control. After integrating these technologies, an integrated control system is used to coordinate the various links of coating, drying, and inspection to ensure that the final quality of the coating meets industrial application standards.

[0059] Step S106, measuring the surface roughness and hardness of the coating to obtain the preliminarily screened PVD coating material.

[0060] First, the surface roughness of the PVD coating is quantified using precision measuring equipment and the obtained data is recorded. The hardness of the coating is measured using a hardness tester, and the measurement results are also recorded. The acquired surface roughness and hardness data are stored in a database to provide data support for subsequent analysis. The recorded roughness and hardness data are statistically analyzed using data analysis software to determine the average roughness and hardness values ​​of each material. According to the preset screening criteria, the analysis results are evaluated to screen out coating materials that meet the standards. The screened materials are evaluated for performance and compared with other performance parameters to ensure that the comprehensive performance of the material meets the application requirements. Finally, the preferred PVD coating material is obtained to provide a scientific basis for production and application.

[0061] Embodiment 2:

[0062] The invention discloses a method for preparing a coating with high light absorbance on a substrate surface, comprising: obtaining a metal or plastic substrate, and plating aluminum on the surface of the substrate to obtain an aluminum-plated substrate; placing the aluminum-plated substrate in a femtosecond laser processing device, and using a femtosecond laser to roughen the surface of the aluminum-plated substrate to obtain an aluminum-plated substrate with a super surface structure; transferring the aluminum-plated substrate with the super surface structure to a PVD deposition device, and using a PVD method to deposit a carbon nanotube coating on the surface of the aluminum-plated substrate with the super surface structure under inert atmosphere conditions to obtain a carbon nanotube-coated aluminum-plated substrate; transferring the carbon nanotube-coated aluminum-plated substrate from the PVD deposition device to obtain a substrate with a high light absorbance coating.

[0063] The method of roughening the surface of the aluminum-plated substrate by using a femtosecond laser comprises: adjusting the spot diameter of the femtosecond laser to 20-200 microns, adjusting the repetition frequency of the femtosecond laser to 100-2000 kHz, adjusting the scanning speed of the femtosecond laser to 100-2000 mm / s, scanning the surface of the aluminum-plated substrate to obtain an aluminum-plated substrate with a super surface structure; 3. The preparation method according to claim 1 is characterized in that the method of depositing a carbon nanotube coating on the surface of the aluminum-plated substrate with a super surface structure by using a PVD method comprises: placing a graphite rod and a nickel-cobalt alloy rod as raw materials in a deposition chamber of a PVD deposition device, evacuating to 5×10-3Pa, and introducing Argon gas is heated to 0.5-2Pa, a graphite rod and a nickel-cobalt alloy rod are used as cathodes, the aluminum-plated substrate with a super surface structure is used as an anode, a negative bias voltage of 200-500V is applied between the two electrodes, and a carbon nanotube coating is deposited on the surface of the aluminum-plated substrate with a super surface structure; the thickness of the carbon nanotube coating is 50-500nm; 5. The preparation method according to any one of claims 1 to 4, characterized in that the inert atmosphere is an argon atmosphere; 6. The preparation method according to claim 1, characterized in that the substrate is an aluminum alloy substrate or a polyethylene terephthalate substrate; 7. The preparation method according to claim 1, characterized in that the thickness of the aluminum plating is 50-200nm.

[0064] Select a suitable metal or plastic substrate and determine the appropriate aluminum plating method based on its physical and chemical properties. Use physical vapor deposition (PVD) technology to plate a layer of aluminum on the surface of the substrate, and optimize the uniformity and adhesion of the aluminum layer by controlling the deposition parameters. Obtain the aluminum-plated substrate and use a femtosecond laser to create an ultrafine structure on the aluminum surface to increase the surface roughness and specific surface area. After creating the ultrafine structure, immediately transfer the aluminum-plated substrate to an oxygen-free environment to avoid oxidation reactions that affect material properties. Use PVD technology to deposit carbon nanotubes in an oxygen-free environment, and adjust the deposition parameters to control the density and distribution of carbon nanotubes. Use a specific chemical vapor deposition (CVD) process to form an additional functional coating on the carbon nanotubes to improve absorbance and durability. Heat treat the coating to optimize the structure and performance of the coating by controlling temperature and time. Perform surface and performance tests on the treated coating, and confirm that the absorbance reaches the expected effect through spectral analysis. Adjust the parameters in the previous steps based on the test results to finely control the final performance of the coating and ensure the consistency and reliability of each batch of products. Aluminum alloy or ABS plastic was selected as the substrate. According to its melting point, conductivity and surface energy, magnetron sputtering was used to plate aluminum on the surface. The thickness of the aluminum layer was controlled to be around 100nm by adjusting the sputtering power to 200W, the argon flow rate to 50sccm and the substrate temperature to 100°C to ensure uniformity and adhesion. A femtosecond laser with a wavelength of 800nm, a pulse width of 100fs and a repetition frequency of 1kHz was used to scan the aluminum surface to form a micro-nanostructure array with a period of 500nm and an aspect ratio of 5:1. After laser processing, the sample was immediately transferred to a PVD chamber with a vacuum degree of 10-6Pa to avoid oxidation of the aluminum surface. Carbon nanotube arrays were deposited at 800℃ by electron beam evaporation of carbon source, with a carbon source evaporation rate of 0.2nm / s and a deposition time of 30min, forming a carbon tube array with a height of 5μm and a density of 109 / cm2. Then, a 20nm thick silicon carbide coating was deposited at 600°C in an acetylene atmosphere through a CVD process to further improve the absorbance. Finally, in a nitrogen environment, the temperature was raised to 400°C at a rate of 5°C / min and kept warm for 2h to optimize the coating structure. The reflectivity in the 300-2500nm band was tested using a UV-visible-near infrared spectrometer, and the calculated average absorbance was over 99.5%. According to the spectral test results, the laser processing parameters, carbon tube deposition conditions and heat treatment system were adjusted to achieve fine control of coating performance, ensure consistency between batches, and control the absorbance error within 0.1%.

[0065] According to the material and shape of the substrate surface, a uniform aluminum film is plated on the substrate surface by physical vapor deposition to obtain an aluminum-plated substrate. The aluminum-plated substrate is placed in a femtosecond laser processing device with precise control of power and scanning speed. By setting appropriate laser parameters, the surface of the aluminum-plated substrate is roughened to obtain an aluminum-plated substrate with a specific super surface structure. The aluminum-plated substrate after roughening is transferred to a vacuum chamber and evacuated to a specified pressure to avoid contact between the substrate surface and oxygen to prevent oxidation of the aluminum layer. In a vacuum environment, the carbon source material is heated and vaporized by a physical vapor deposition method, and a uniform carbon nanotube coating is deposited on the surface of the aluminum-plated substrate after roughening by controlling the deposition time and rate. According to the growth mechanism of carbon nanotubes, the temperature, pressure and other parameters in the deposition process are adjusted to ensure that the carbon nanotubes grow vertically in an oriented manner to form a dense array structure. The morphology and orientation of the carbon nanotube coating are observed by scanning electron microscopy to determine whether the coating quality meets the requirements of ultra-black materials. If not, return to step 4 to adjust the deposition parameters. The prepared samples are taken out of the vacuum chamber, and their reflectivity in the visible-near infrared band is measured by optical testing methods to obtain the material's light absorption performance data. Based on the test results, the interface quality of the carbon nanotube coating and the aluminum-plated substrate is evaluated to determine whether there are problems such as insufficient adhesion and coating shedding, and to determine the optimization direction of the process parameters. The performance of samples prepared under different substrates, laser texturing parameters, and carbon nanotube deposition conditions is compared to screen out the optimal process route and form a technical solution for mass production of ultra-black surfaces with high light absorption.

[0066] A layer of aluminum is deposited on the surface of a metal or plastic substrate using physical vapor deposition (PVD) technology. The surface of the aluminum-coated substrate is roughened and a femtosecond laser is used to create a super surface structure. The aluminum-coated substrate with the super surface structure is transferred to a PVD deposition device. An inert atmosphere is created in the PVD deposition device to exclude the presence of oxygen. Under inert atmosphere conditions, the PVD device is started and the parameters are adjusted to accommodate the deposition of carbon nanotubes. A carbon nanotube coating is deposited on the surface of the aluminum-coated substrate with the super surface structure by a PVD method. The deposition process of the carbon nanotubes is monitored and the PVD parameters are adjusted to optimize the coating quality. After the deposition of the carbon nanotube coating is completed, the PVD device is turned off and the substrate is removed from the device. The aluminum-coated substrate coated with carbon nanotubes is post-processed, including cleaning and drying, to stabilize the coating structure.

[0067] Aluminum is plated on the surface of a metal or plastic substrate by physical vapor deposition (PVD) technology, and the coating thickness is set to 5 microns. The aluminum plating parameters are 200 degrees Celsius and 0.5 Pa. Then, the surface of the aluminum-plated substrate is roughened by a femtosecond laser, and the laser parameters are set to a pulse width of 200 femtoseconds and an energy density of 0.5 joules / square centimeter to form a nanoscale rough surface structure. The treated substrate is transferred to a PVD deposition device, and an inert atmosphere composed of argon gas is created in the device, and the gas pressure is maintained at 1 Pa. The PVD device is started and the deposition rate is adjusted to 2 microns / hour to accommodate the deposition of carbon nanotubes. The carbon nanotube coating is deposited on the surface of the aluminum-plated substrate with a super surface structure by the PVD method, and the monitoring system automatically adjusts the power and deposition time to ensure that the carbon nanotubes are evenly distributed. During the deposition process, the growth of carbon nanotubes is monitored in real time by a scanning electron microscope (SEM), and the image data is analyzed to optimize the PVD parameters. After the deposition of the carbon nanotube coating is completed, the PVD device is automatically turned off, and the substrate is removed from the device by a robotic arm. Finally, the carbon nanotube-coated aluminum substrate is subjected to an automated cleaning and drying process, using high-purity nitrogen purging and infrared heating technology with the temperature controlled at 50 degrees Celsius to stabilize the coating structure and remove surface impurities.

[0068] Determine the type of substrate, select metal or plastic material as the coating substrate, and record the physical and chemical properties of the substrate. Clean the substrate surface to remove surface impurities and oxide layers, and use a combination of ultrasonic cleaning and plasma cleaning to ensure that the surface cleanliness meets the coating requirements. Plate a layer of aluminum on the surface of the cleaned substrate, use magnetron sputtering or electron beam evaporation technology to control the thickness and uniformity of the aluminum coating, and record the thickness and surface roughness data of the aluminum coating.

[0069] The aluminum-plated surface is roughened, and a femtosecond laser is used for super-surface processing. The laser power, pulse frequency and scanning path are set to generate micro-nano structures, and the surface morphology data after roughening is recorded. The roughened substrate is sent to the PVD deposition device, and the vacuum degree and deposition parameters are set to ensure that the atmosphere in the device is oxygen-free, and prepare for the deposition of carbon nanotubes. In the PVD deposition device, physical vapor deposition technology is used to deposit carbon nanotubes, and the deposition temperature, time and gas flow are adjusted. The pressure and temperature changes during the deposition process are monitored, and the deposition parameters and coating thickness data are recorded. After the deposition is completed, the aluminum-plated substrate coated with carbon nanotubes is removed from the PVD deposition device by an automated robotic arm to ensure that the substrate does not contact oxygen during the transfer process, and the transfer time and environmental conditions data are recorded. The surface absorbance of the removed substrate is tested, and the absorbance of different bands is measured using a spectrometer to determine the high light absorption performance of the coating, and the absorbance test results are recorded. According to the absorbance test results, the deposition process parameters are optimized and adjusted. If the absorbance does not meet the expected standards, the PVD deposition parameters and the carbon nanotube coating thickness are readjusted, and steps 5 to 8 are repeated until a coating substrate that meets the high absorbance requirements is obtained.

[0070] First, metal aluminum was selected as the coating substrate, and its chemical composition was determined by X-ray fluorescence spectrometer, which mainly contained 99.5% Al. Then, ultrasonic cleaning was performed at a frequency of 40kHz for 10 minutes, and then plasma cleaning was performed at a power of 100W for 5 minutes. The surface was observed using a scanning electron microscope to confirm that the cleanliness reached Ra<0.1μm. Then, an electron beam evaporation coating device was used to deposit a 500nm thick aluminum layer on the surface of the substrate, and the surface roughness Ra=10nm was measured using an atomic force microscope. Subsequently, a femtosecond laser with a wavelength of 1030nm, a pulse width of 300fs, and a repetition frequency of 100kHz was used at 0.1J / cm 2 The aluminum-plated surface was textured with an energy density of 50 μm and a scanning interval of 50 μm, and a periodic micro-nano structure was obtained by observation under a laser scanning electron microscope. The textured substrate was transferred to the PVD deposition chamber, acetylene gas was introduced, and carbon nanotubes were deposited at a rate of 1 nm / s for 30 minutes. A quartz crystal oscillator was used to monitor the deposition rate and thickness in real time. After the deposition was completed, the substrate was taken out of the chamber by a robotic arm under argon protection. Finally, a UV-VisN IR spectrophotometer was used to test the reflectivity of the substrate. The average reflectivity in the 200-2500 nm band was less than 0.5%, meeting the high absorbance requirement. If the reflectivity exceeds 1%, return to the PVD deposition step, adjust the deposition time of the carbon nanotubes to 45 minutes, and retest the reflectivity until it meets the standard.

[0071] The above is only a specific implementation method of this specification. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the system, module and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. It should be understood that the protection scope of this specification is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this specification, and these modifications or replacements should be covered within the protection scope of this specification.

Claims

1. A method for preparing a coating having high light absorbance on a substrate surface, characterized in that: The method comprises: Designing the PVD coating structure according to the type of coating material, and controlling the coating thickness within a preset range by adjusting deposition parameters; Pretreating the carbon nanotubes by high-speed shear dispersion technology and measuring the performance of the carbon nanotube dispersion; Establishing a coating formula database according to the properties of the carbon nanotube dispersion and screening the solvent types through orthogonal experiments; Modifying the surface of the carbon nanotubes by plasma treatment, and measuring the content of functional groups on the surface of the carbon nanotubes; The coating uniformity is improved by using multiple coating methods, infrared drying is performed after each coating, and the coating thickness is measured; The surface roughness and hardness of the coating were measured to obtain the preliminarily screened PVD coating material.

2. The method for preparing a coating having high light absorbance on a substrate surface according to claim 1, characterized in that: The step of designing the PVD coating structure according to the type of coating material and controlling the coating thickness within a preset range by adjusting deposition parameters includes: Obtain information about the type of coating material and determine the design parameters of the PVD coating structure based on the material properties; For different coating materials, select matching deposition parameter combinations from the preset PVD process parameter library; The coating material type, coating structure design parameters and deposition parameters are combined and input into the neural network model to predict the coating thickness; Determine whether the predicted coating thickness is within a preset range, and if not, adjust the deposition parameters and re-predict the coating thickness; When the predicted coating thickness meets the preset range requirements, the PVD coating structure design and deposition parameter combination are determined as the optimal process parameters; Apply the optimal process parameters to the PVD equipment to deposit and prepare a coating structure that meets the thickness requirements; Scanning electron microscopy was used to measure the actual thickness of the coating and verify the effectiveness of the optimized PVD process parameters.

3. The method for preparing a coating having high light absorbance on a substrate surface according to claim 1, characterized in that: The method of pretreating the carbon nanotubes by using a high-speed shear dispersion technique and measuring the properties of the carbon nanotube dispersion comprises: Determine the shear rate and dispersion time parameters of the high-speed shear dispersion device according to the initial length and diameter of the carbon nanotubes, and control the shear rate and dispersion time to make the carbon nanotubes reach a preset length and diameter range; The carbon nanotubes are added into a preset dispersion medium, and the carbon nanotubes are pretreated by a high-speed shear dispersion technology, so that the carbon nanotubes are evenly dispersed in the dispersion medium by shearing to obtain a carbon nanotube dispersion liquid; The particle size distribution of the carbon nanotube dispersion is measured by a dynamic light scattering method, and whether the dispersion uniformity of the carbon nanotubes in the dispersion reaches a preset threshold is determined according to the measurement result; If the dispersion uniformity does not reach the preset threshold, the shear speed and dispersion time parameters of the high-speed shear dispersion device are adjusted, and the above steps are repeated until the dispersion uniformity reaches the preset threshold; Using a transmission electron microscope to observe the morphology of the carbon nanotube dispersion, measure the length and diameter of the carbon nanotubes, and determine whether the size of the carbon nanotubes is within a preset range; If the size of the carbon nanotubes is not within the preset range, adjusting the shear rate and dispersion time parameters of the high-speed shear dispersion device according to the degree of deviation from the preset range, and repeating steps 2 to 5 until the size of the carbon nanotubes is within the preset range; The prepared carbon nanotube dispersion is applied to subsequent processes, composite material preparation and conductive coating preparation, and the performance of the composite material or coating is tested to verify whether the dispersion performance of the carbon nanotube dispersion meets the application requirements.

4. The method for preparing a coating having high light absorbance on a substrate surface according to claim 1, characterized in that: The method of using multiple coatings to improve the uniformity of the coating, performing infrared drying after each coating, and measuring the thickness of the coating comprises: An automated coating system is used, which can control the uniformity of the coating and automatically adjust the coating parameters to ensure consistent thickness after each coating; Monitor the coating drying process through infrared sensors and adjust the drying temperature and time in real time to optimize the coating drying effect; Use machine vision technology to detect the coating in real time, and use image analysis algorithms to identify the uniformity and thickness of the coating. If uneven coating or thickness that does not meet preset standards is detected, the coating parameters are automatically adjusted or the coating process is repeated; The data analysis module collects data from the coating and drying process, and uses machine learning algorithms to analyze the relationship between coating quality and process parameters to achieve more accurate process control; After integrating these technologies, an integrated control system is used to coordinate each link of coating, drying and inspection to ensure that the final quality of the coating meets industrial application standards.

5. The method for preparing a coating having high light absorbance on a substrate surface according to claim 1, characterized in that: The method of measuring the surface roughness and hardness of the coating to obtain the preliminarily screened PVD coating material comprises: First, the surface roughness of the PVD coating was quantified using precision measuring equipment and the resulting data was recorded; Measure the hardness of the coating using a hardness testing instrument and also record the measurement results; The acquired surface roughness and hardness data are stored in the database to provide data support for subsequent analysis; Data analysis software was used to statistically analyze the recorded roughness and hardness data to determine the average roughness and hardness values ​​for each material; According to the preset screening criteria, the analysis results are evaluated and the coating materials that meet the criteria are screened out; Evaluate the performance of the selected materials and compare other performance parameters to ensure that the comprehensive performance of the materials meets the application requirements; Finally, a preferred PVD coating material is obtained.

Images