Preparation method and preparation device of piezoelectric sensing film

Abstract

The invention provides a preparation method and a preparation device of a piezoelectric sensing film, which can be applied to the technical field of material science and engineering, and the method comprises the following steps: providing nanoscale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode; the preparation method comprises the following steps: mixing and dispersing nanoscale piezoelectric SiC powder to form a suspension; coating a flexible polymer substrate with the suspension to form a thin film, and preparing an upper electrode on the thin film to form an initial thin film structure; and sequentially carrying out curing treatment and polarization treatment on the initial film structure to obtain the piezoelectric sensing film. Finally, the performance of the piezoelectric sensing film is analyzed in combination with artificial intelligence, and preparation parameters are optimized according to the analysis result. Therefore, the piezoelectric sensing film is prepared by using the stable piezoelectric property of the SiC material in a wide temperature range, and artificial intelligence is combined to carry out performance analysis so as to optimize preparation parameters, so that the repeatability of film preparation is realized, and the performance of the piezoelectric sensing film is improved.

Description

Technical Field

[0001] The present application relates to the field of materials science and engineering technology, and particularly to a preparation method and a preparation device for a piezoelectric sensing thin film. Background Art

[0002] A piezoelectric sensing thin film is a sensor device based on the piezoelectric effect, which realizes measurement by converting physical quantities such as mechanical force, pressure, or vibration into electrical signals. However, with the continuous development of technology, the demand for high-performance piezoelectric sensing materials is increasing day by day.

[0003] Taking piezoelectric ceramics as an example, various materials with piezoelectric sensing functions have become research hotspots in the field of piezoelectric sensing due to their excellent piezoelectric properties, mechanical properties, and chemical stability. However, the piezoelectric properties of traditional piezoelectric ceramic materials decay at high temperatures, and their compatibility with flexible substrates is poor, and it is difficult to improve the preparation process, resulting in poor performance of the prepared piezoelectric sensing thin films.

[0004] Therefore, how to improve the performance of piezoelectric sensing thin films is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0005] Based on the above problems, the present application provides a preparation method and a preparation device for a piezoelectric sensing thin film, which utilize the stable piezoelectric properties of SiC materials in a wide temperature range to prepare piezoelectric sensing thin films, and combine artificial intelligence for performance analysis and then optimize the preparation parameters to achieve the repeatability of thin film preparation and improve the performance of piezoelectric sensing thin films.

[0006] In the first aspect, an embodiment of the present application provides a preparation method for a piezoelectric sensing thin film, including:

[0007] Providing nano-scale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode; the material of the flexible polymer substrate is polyimide or polyether ether ketone;

[0008] Performing a mixing and dispersion treatment on the nano-scale piezoelectric SiC powder to form a suspension;

[0009] Coating the suspension onto the flexible polymer substrate to form a thin film, and preparing an upper electrode on the thin film to form an initial thin film structure;

[0010] Performing a curing treatment on the initial thin film structure, and performing a poling treatment on the initial thin film structure after the curing treatment to obtain a piezoelectric sensing thin film;

[0011] Combining artificial intelligence to analyze the performance of the piezoelectric sensing thin film, and optimizing the preparation parameters according to the analysis results.

[0012] Optionally, the method further includes:

[0013] Providing modified piezoelectric SiC powder doped with 0.2 - 0.5 wt% of Al / Yb;

[0014] Refining the modified piezoelectric SiC powder based on high - energy ball milling method to obtain nanoscale piezoelectric SiC powder with D 50 = 80 ± 20 nm.

[0015] Optionally, the mixing and dispersing treatment of the nanoscale piezoelectric SiC powder to form a suspension includes:

[0016] Mixing the nanoscale piezoelectric SiC powder with an ethanol solution to form a first mixed solution;

[0017] Adding a dispersant and a conductive reinforcing phase to the first mixed solution to form a target mixed solution;

[0018] Performing a dispersion treatment on the target mixed solution based on an ultrasonic - mechanical vibration composite system to form a suspension;

[0019] The ultrasonic frequency of the ultrasonic - mechanical vibration composite system is set to 20 kHz, the vibration frequency is set to 200 Hz, the vibration amplitude is set between 500 - 1000 μm, the acceleration is set between 5 - 10 g, and the vibration time is set to 30 min.

[0020] Optionally, the method further includes:

[0021] Collecting state pictures of the suspension;

[0022] Analyzing the state pictures in combination with the HSV color space vision algorithm to determine the degree of particle dispersion uniformity in the suspension;

[0023] If the degree of particle dispersion uniformity is lower than a preset threshold, an alarm is triggered and the dispersion parameters are adjusted.

[0024] Optionally, the coating of the suspension onto the flexible polymer substrate to form a film includes:

[0025] Using a spin - coating device to coat the suspension onto the flexible polymer substrate at a dynamically adjusted speed of 800 - 2500 rpm to form a film with a preset target thickness.

[0026] Optionally, the method further includes:

[0027] Collecting film thickness data during the process of coating the suspension onto the flexible polymer substrate;

[0028] Combined with the preset target thickness, the PID controller and the deep learning model are used to jointly analyze the film thickness data to determine the rotation speed correction amount and the compensation control amount;

[0029] Based on the rotation speed correction amount and the compensation control amount, the rotation speed of the spin coating equipment is controlled.

[0030] Optionally, the curing treatment of the initial film structure includes:

[0031] Using a temperature control box, the initial film structure is dried at 80 °C to remove the residual solution in the initial film structure;

[0032] The temperature control box is heated stepwise to 140 °C, and the initial film structure is controlled to be continuously cured in the temperature control box for two hours.

[0033] Optionally, the poling treatment of the initial film structure after the curing treatment includes:

[0034] The initial film structure after the curing treatment is immersed in a silicone oil medium, and a DC electric field of 8 kV / mm is applied between the upper electrode and the lower electrode at an environment of 100 °C for 30 min.

[0035] Optionally, the performance of the piezoelectric sensing film is analyzed by combining artificial intelligence, and the preparation parameters are optimized according to the analysis results, including:

[0036] Perform a piezoelectric-electrical joint test on the piezoelectric sensing film and obtain test data;

[0037] Determine the piezoelectric coefficient of the piezoelectric sensing film;

[0038] Combined with the test data and the piezoelectric coefficient, a relationship model between the piezoelectric performance and the preparation parameters is constructed through the support vector machine algorithm;

[0039] Combined with the reinforcement learning algorithm, the preparation parameters are optimized by using the relationship model.

[0040] In a second aspect, an embodiment of the present application provides a preparation device for a piezoelectric sensing film, including:

[0041] A supply module for providing nanoscale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode; the material of the flexible polymer substrate is polyimide or polyether ether ketone;

[0042] A first processing module for performing a mixing and dispersion treatment on the nanoscale piezoelectric SiC powder to form a suspension;

[0043] A second processing module, configured to coat the suspension onto the flexible polymer substrate to form a thin film, and prepare an upper electrode on the thin film to form an initial thin film structure;

[0044] A third processing module, configured to perform a curing process on the initial thin film structure and perform a polarization process on the cured initial thin film structure to obtain a piezoelectric sensing film;

[0045] An optimization module, configured to analyze the performance of the piezoelectric sensing film by combining artificial intelligence and optimize the preparation parameters according to the analysis results.

[0046] It can be seen from the above technical solutions that compared with the prior art, the present application has the following advantages:

[0047] The present application first provides nanoscale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode. Among them, the material of the flexible polymer substrate is polyimide or polyether ether ketone. Then, the nanoscale piezoelectric SiC powder is subjected to a mixing and dispersion process to form a suspension. The suspension is coated onto the flexible polymer substrate to form a thin film, and an upper electrode is prepared on the thin film to form an initial thin film structure. Finally, the initial thin film structure is subjected to a curing process, and the cured initial thin film structure is subjected to a polarization process to obtain a piezoelectric sensing film. Finally, the performance of the piezoelectric sensing film is analyzed by combining artificial intelligence, and the preparation parameters are optimized according to the analysis results. In this way, the stable piezoelectric performance of the SiC material in a wide temperature range is used to prepare the piezoelectric sensing film, and the performance is analyzed by combining artificial intelligence and then the preparation parameters are optimized, realizing the repeatability of film preparation and improving the performance of the piezoelectric sensing film. Description of the Drawings

[0048] Figure 1 It is a flowchart of a method for preparing a piezoelectric sensing film provided by an embodiment of the present application;

[0049] Figure 2 It is a flowchart of a method for intelligently preparing a piezoelectric sensing film provided by an embodiment of the present application;

[0050] Figure 3 It is a schematic structural diagram of a device for preparing a piezoelectric sensing film provided by an embodiment of the present application. Detailed Embodiments

[0051] As described above, the existing piezoelectric sensing films have problems with poor performance. Specifically, most of the existing piezoelectric sensing films use piezoelectric ceramic materials, but traditional piezoelectric ceramic materials face problems such as attenuation of piezoelectric performance at high temperatures and poor adaptability to flexible substrates, and it is difficult to improve the preparation process, resulting in poor performance of the prepared piezoelectric sensing films.

[0052] To solve the above problems, an embodiment of the present application provides a method for preparing a piezoelectric sensing film, including: First, providing nanoscale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode. Among them, the material of the flexible polymer substrate is polyimide or polyether ether ketone. Then, the nanoscale piezoelectric SiC powder is subjected to a mixing and dispersion treatment to form a suspension. The suspension is coated on the flexible polymer substrate to form a film, and an upper electrode is prepared on the film to form an initial film structure. Finally, the initial film structure is cured, and the cured initial film structure is polarized to obtain the piezoelectric sensing film.

[0053] In this way, by utilizing the stable piezoelectric properties of the SiC material in a wide temperature range, a piezoelectric sensing film is prepared, improving the performance of the piezoelectric sensing film.

[0054] It should be noted that a method and a preparation device for preparing a piezoelectric sensing film provided by the present application can be applied to the field of materials science and engineering technology. The above is only an example and does not limit the application field of the method and the preparation device for preparing a piezoelectric sensing film provided by the present application.

[0055] In order to make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0056] Figure 1 It is a flowchart of a method for preparing a piezoelectric sensing film provided by an embodiment of the present application. Combining Figure 1 As shown, a method for preparing a piezoelectric sensing film provided by an embodiment of the present application may include:

[0057] S101: Providing nanoscale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode; the material of the flexible polymer substrate is polyimide or polyether ether ketone.

[0058] In practical applications, the SiC powder required for preparing the piezoelectric sensing film needs to be nanoscale. D 50= 80 ± 20 nm. Meanwhile, for application scenarios in a wide temperature range from room temperature to 500 °C, the substrate material required for preparing the piezoelectric sensing thin film is selected as a flexible polymer material such as polyimide (PI) or polyetheretherketone (PEEK). Then, a gold (Au) thin film with a thickness of about 100 nm is deposited on the flexible polymer substrate as the lower electrode based on the magnetron sputtering technology. Among them, the sputtering power can be set to 150 W, and the temperature of the flexible polymer substrate during sputtering needs to be ≤ 120 °C.

[0059] In addition, since the preparation methods of nanoscale piezoelectric SiC powder are not the same, an embodiment of the present application can illustrate one possible preparation method.

[0060] In one case, the method further includes:

[0061] Providing modified piezoelectric SiC powder doped with 0.2 - 0.5 wt% of Al / Yb;

[0062] Based on high-energy ball milling method, refining the modified piezoelectric SiC powder to obtain nanoscale piezoelectric SiC powder with D 50 = 80 ± 20 nm.

[0063] In practical applications, the high-energy ball milling method is a technology that realizes material preparation and modification through mechanochemistry, and can induce physical or chemical reactions by using high-intensity mechanical energy. The nanoscale piezoelectric SiC powder provided in this application is obtained by refining the modified piezoelectric SiC powder doped with 0.2 - 0.5 wt% of Al / Yb elements through the high-energy ball milling method. Among them, the rotation speed corresponding to the high-energy ball milling method is set to 120 rpm, and the ball-to-powder ratio is set to 10:1.

[0064] S102: Perform mixing and dispersion treatment on the nanoscale piezoelectric SiC powder to form a suspension.

[0065] In practical applications, a suspension refers to a heterogeneous mixture formed by dispersing nanoscale piezoelectric SiC powder particles in a solution. Therefore, the nanoscale piezoelectric SiC powder needs to be first mixed with a solvent, and then the uniform distribution of solid particles is achieved through physical dispersion or chemical dispersion.

[0066] In addition, since the methods for preparing suspensions are not the same, an embodiment of the present application can illustrate one possible preparation method.

[0067] In one case, the mixing and dispersion treatment of the nanoscale piezoelectric SiC powder to form a suspension includes:

[0068] Mix the nanoscale piezoelectric SiC powder with an ethanol solution to form a first mixed solution;

[0069] A dispersant and a conductive enhancing phase are added to the first mixed solution to form a target mixed solution;

[0070] Based on an ultrasonic-mechanical vibration composite system, the target mixed solution is dispersed to form a suspension;

[0071] The ultrasonic frequency of the ultrasonic-mechanical vibration composite system is set to 20 kHz, the vibration frequency is set to 200 Hz, the vibration amplitude is set between 500 and 1000 μm, the acceleration is set between 5 and 10 g, and the vibration time is set to 30 min.

[0072] In practical applications, nanoscale piezoelectric SiC powder is used as the solute, and an ethanol solution is used as the solvent. The two are mixed in a certain proportion (to form the first mixed solution). For a certain stability, the general solid-phase volume concentration range is 10%-35%. Too low will cause the solute to settle too fast, and too high will cause the viscosity to be too high and lose fluidity. Then, 0.5 wt% polyvinyl alcohol dispersant and 0.3 wt% carboxylated carbon nanotubes (CNTs) are added to the first mixed solution as the conductive enhancing phase (to form the target mixed solution). The ultrasonic-mechanical vibration composite system is a synergistic technology that combines the high-frequency vibration of ultrasonic waves with traditional mechanical vibration. It can enhance the dispersion effect through the resonance effect, and then effectively construct a three-dimensional network structure and form a stable suspension. Specifically, during the process of preparing the suspension using the ultrasonic-mechanical vibration composite system, the preparation parameters are generally set as follows: the ultrasonic frequency is 20 kHz, the vibration frequency is 200 Hz, the vibration amplitude is 500-1000 μm, the acceleration is 5-10 g, and the treatment duration is 30 min.

[0073] In addition, since the methods for judging whether the suspension meets the standards are not the same, the embodiments of the present application can illustrate a possible judgment method.

[0074] In one case, the method further includes:

[0075] Collecting a state picture of the suspension;

[0076] Combining the HSV color space vision algorithm to analyze the state picture to determine the degree of uniform dispersion of the particles in the suspension;

[0077] If the degree of uniform dispersion of the particles is lower than a preset threshold, an alarm is triggered and the dispersion parameters are adjusted.

[0078] In practical applications, the uniformity of the suspension is generally indirectly evaluated through multiple parameters, such as particle size distribution, zeta potential, viscosity, sedimentation rate, etc. The state of the suspension can be photographed in real time by devices such as industrial high-definition cameras, and then the degree of particle dispersion in the suspension can be analyzed by combining the HSV color space vision algorithm to identify precipitation or stratification. HSV is a color model centered on human perception and is widely used in computer vision for color segmentation, object recognition, and image enhancement. By decoupling color and brightness, it significantly improves the robustness of color-related vision tasks. The edge computing device processes 1 frame of image per second, combines the HSV color space vision algorithm to decouple the color and brightness of the state image, and then determines the degree of particle dispersion in the current suspension by identifying precipitation or stratification, or even by determining the particle size distribution in the state image. In addition, the stability of the suspension can be detected by a Zeta potentiometer. Generally, for a suspension in a stable state, its potential value should be stable around -35 mV, and the sedimentation rate should not be greater than 3% within 24 hours. The preset threshold for the degree of particle dispersion uniformity can be set according to indicators such as the standard deviation (reflecting the deviation degree of particle size from the average value) or the dispersity parameter, such as 90% or 95%, etc. When it is monitored that the degree of particle dispersion uniformity corresponding to the current suspension is lower than the preset threshold, an audible and visual alarm is triggered, and the operator is reminded to adjust and optimize the ultrasonic dispersion parameters (preparation parameters involved in the ultrasonic-mechanical vibration composite system during the mixing and dispersion process of nano-scale piezoelectric SiC powder, including ultrasonic frequency, vibration frequency, vibration amplitude, acceleration, and processing duration, etc.).

[0079] S103: Coat the suspension on the flexible polymer substrate to form a thin film, and prepare a top electrode on the thin film to form an initial thin film structure.

[0080] In practical applications, the prepared suspension is uniformly coated on a flexible polymer substrate to form a thin film. After the coating is completed, a gold (Au) thin film with a thickness of about 100 nm is immediately deposited on the surface of the thin film based on the magnetron sputtering process as the top electrode, and its sputtering power can also be selected as 150 W.

[0081] In addition, since the coating methods are not the same, the embodiments of the present application can illustrate one possible coating method.

[0082] In one case, the coating of the suspension on the flexible polymer substrate to form a thin film includes:

[0083] Using a spin coater, the suspension is coated on the flexible polymer substrate at a dynamically adjustable rotation speed of 800 - 2500 rpm to form a thin film with a preset target thickness.

[0084] In practical applications, to ensure the uniform coating of the suspension, the present application uses a spin-coating device to spin-coat the suspension on a flexible polymer substrate at a dynamically adjustable speed of 800 - 2500 rpm, achieving a high-precision film formation with a thickness of 20 ± 0.5 μm (preset target thickness).

[0085] In addition, since the ways of controlling the rotation speed are not the same, the embodiments of the present application can illustrate one possible control method.

[0086] In one case, the method further includes:

[0087] Collecting film thickness data during the process of coating the suspension onto the flexible polymer substrate;

[0088] Combining with the preset target thickness, using a PID controller and a deep learning model to perform collaborative analysis on the film thickness data to determine the rotation speed correction amount and the compensation control amount;

[0089] Controlling the rotation speed of the spin-coating device based on the rotation speed correction amount and the compensation control amount.

[0090] In practical applications, intelligent technologies can be combined to monitor the film coating situation in real time, and the rotation speed of the spin-coating device can be dynamically adjusted according to the coating situation, so as to achieve high-precision film formation. Specifically, during the spin-coating process, a laser interferometer with an accuracy of 0.1 μm can be introduced to collect film thickness data in real time and synchronously transmit it to the PID controller and the deep learning model for collaborative analysis. Among them, the PID controller can dynamically calculate the rotation speed correction amount based on the film thickness deviation, so as to achieve a linear and fast response. And the deep learning model pre-trained with historical data can predict non-linear perturbations (such as edge effects, solvent evaporation fluctuations, etc.) through time series features and output the compensation control amount. Furthermore, the weights of the rotation speed correction amount and the compensation control amount can be adaptively adjusted according to the film thickness fluctuation degree, and the rotation speed can be controlled within the range of 800 - 2500 rpm through dynamic feedback. In this way, the CV value of the film thickness can be reduced by more than 40% compared with the traditional coating method, and then a high-precision film formation with a thickness of 20 ± 0.5 μm can be achieved.

[0091] S104: Performing a curing treatment on the initial film structure and performing a polarization treatment on the cured initial film structure to obtain a piezoelectric sensing film.

[0092] In practical applications, it is necessary to first perform a curing treatment on the flexible SiC composite material film coated with electrodes to remove the residual solvent and form a stable connection between SiC particles. After the curing is completed, the flexible SiC composite material film coated with electrodes is continuously polarized to promote the internal electric domains of SiC particles to flip and be oriented along the electric field direction, generating piezoelectric properties, thereby obtaining a wide-temperature flexible SiC composite material piezoelectric sensing film.

[0093] In addition, since the curing methods are not all the same, embodiments of the present application may illustrate one possible curing method.

[0094] In one case, the curing process of the initial film structure includes:

[0095] Using a temperature-controlled oven, the initial film structure is dried at 80°C to remove the residual solution in the initial film structure;

[0096] The temperature-controlled oven is heated stepwise to 140°C, and the initial film structure is controlled to be continuously cured in the temperature-controlled oven for two hours.

[0097] In practical applications, the curing process refers to transforming a material from a liquid or semi-liquid state to a solid state through physical or chemical methods. Specifically, the suspension coated on the flexible substrate is not in a solid state, and there may still be ethanol solvent in it. Therefore, the flexible SiC composite film (initial film structure) coated with electrodes can be placed in a programmable temperature-controlled oven. First, it is pre-dried at 80°C for 1 hour to remove the residual solvent, and then the temperature of the programmable temperature-controlled oven is heated stepwise to 140°C for 2 hours of curing, so as to form stable connections between SiC particles.

[0098] In addition, since the polarization methods are not all the same, embodiments of the present application may illustrate one possible polarization method.

[0099] In one case, the polarization process of the initial film structure after the curing process includes:

[0100] The initial film structure after the curing process is immersed in a silicone oil medium, and a DC electric field of 8 kV / mm is applied between the upper electrode and the lower electrode at an environment temperature of 100°C for 30 min.

[0101] In practical applications, the polarization process refers to the phenomenon that the internal dipoles of a material are oriented by an electric field, a magnetic field or mechanical stress, thereby generating macroscopic polarization. In the present application, the initial film structure after curing can be immersed in a silicone oil medium. At an environment temperature of 100°C, a DC electric field of 8 kV / mm is applied between the upper electrode and the lower electrode, and polarization is carried out continuously for 30 min, so as to promote the internal electric domains of SiC particles to flip and be oriented along the electric field direction, generating piezoelectric properties and obtaining a piezoelectric sensing film.

[0102] S105: Analyze the performance of the piezoelectric sensing film in combination with artificial intelligence, and optimize the preparation parameters according to the analysis results.

[0103] In practical applications, artificial intelligence can be introduced during the preparation process of the piezoelectric sensing film. By analyzing the piezoelectric properties of the piezoelectric sensing film and combining the relationship between the piezoelectric properties and the preparation parameters, the preparation parameters can be optimized and adjusted, thus achieving precise control of the preparation process and improving the repeatability of film preparation.

[0104] In addition, since the methods for ensuring film performance are not the same, embodiments of the present application can illustrate one possible way to ensure film performance.

[0105] In one case, S105: Analyze the performance of the piezoelectric sensing film in combination with artificial intelligence, and optimize the preparation parameters according to the analysis results, specifically including:

[0106] Conduct piezoelectric-electrical joint tests on the piezoelectric sensing film and obtain test data;

[0107] Determine the piezoelectric coefficient of the piezoelectric sensing film;

[0108] Combine the test data and the piezoelectric coefficient to construct a relationship model between piezoelectric performance and preparation parameters through the support vector machine algorithm;

[0109] Combine the reinforcement learning algorithm and use the relationship model to optimize the preparation parameters.

[0110] In practical applications, the present application can conduct piezoelectric-electrical joint tests on the polarized flexible SiC composite film (piezoelectric sensing film) to obtain test data, and measure the piezoelectric coefficient d using the Berlincourt method. 33 . Then, analyze the test data through the support vector machine (SVM) algorithm to establish a relationship model between piezoelectric performance and preparation parameters (including drying and curing temperature, piezoelectric layer film thickness, SiC particle size, Al / Yb doping amount, polarization electric field strength, etc.), and construct an SVM regression model based on the RBF kernel function. In this model, the parameter C = 10 and γ = 0.1. Furthermore, take the value of the piezoelectric coefficient d 33 and the preparation parameters, etc. as the input of the model, and combine the reinforcement learning algorithm to dynamically optimize the spin coating speed and polarization conditions (ambient temperature, DC electric field applied between the upper and lower electrodes, and polarization duration, etc.). In this way, after three iterations of optimization, the piezoelectric coefficient d 33 value of the piezoelectric sensing film can be increased by 15-20% during the overall preparation process, thereby enhancing the piezoelectric response sensitivity and realizing the intelligent mapping between the preparation process parameters and the piezoelectric performance. Finally, synchronize the optimized parameters to the production line through the industrial Internet of Things platform to achieve closed-loop control of the preparation process and large-scale stable output.

[0111] Figure 2The flowchart of a method for intelligently preparing a piezoelectric sensing film provided by an embodiment of the present application. In combination with Figure 2 As shown, the present application first prepares raw materials, including a flexible polymer substrate and refining the SiC raw material powder. Then, the refined SiC powder is used to prepare a suspension, and the dispersion uniformity is monitored by an algorithm during the preparation process; an electrode is sputtered on the flexible polymer substrate. Next, the suspension is spin-coated into a film on the flexible polymer substrate with the sputtered electrode, and the rotation speed is synergistically regulated by PID + deep learning during the film-forming process, so that the CV value of the film thickness is reduced by more than 40% compared with the traditional method, realizing high-precision film formation of 20 ± 0.5 μm. Then, the formed film structure (initial film structure) is cured and polarized in sequence to obtain a piezoelectric sensing film. In addition, the present application also introduces performance testing, and combines the "process parameter - piezoelectric performance" intelligent mapping model (the relationship model between piezoelectric performance and preparation parameters) to perform feedback optimization of the preparation parameters, and synchronizes the optimized parameters to the production line through the industrial Internet of Things platform to realize the closed-loop control and large-scale stable output of the preparation process.

[0112] In summary, the present application first provides nanoscale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode. Among them, the material of the flexible polymer substrate is polyimide or polyetheretherketone. Then, the nanoscale piezoelectric SiC powder is subjected to mixing and dispersion treatment to form a suspension. The suspension is coated on the flexible polymer substrate to form a film, and an upper electrode is prepared on the film to form an initial film structure. Finally, the initial film structure is cured, and the cured initial film structure is polarized to obtain a piezoelectric sensing film. In this way, the stable piezoelectric performance of the SiC material in a wide temperature range is utilized to prepare a piezoelectric sensing film, thereby improving the performance of the piezoelectric sensing film. In addition, through the continuous cycle of data acquisition - model training - parameter optimization, the present application effectively establishes a correlation model of "preparation parameters - macroscopic performance", ensuring that the film performance is stably optimized, and can support large-scale stable production.

[0113] Figure 3 The structural schematic diagram of a preparation device for a piezoelectric sensing film provided by an embodiment of the present application. In combination with Figure 3 As shown, the preparation device 300 for a piezoelectric sensing film provided by an embodiment of the present application includes:

[0114] A supply module 301, configured to provide nanoscale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode; the material of the flexible polymer substrate is polyimide or polyetheretherketone;

[0115] A first processing module 302, configured to perform mixing and dispersion treatment on the nanoscale piezoelectric SiC powder to form a suspension;

[0116] The second processing module 303 is configured to coat the suspension onto the flexible polymer substrate to form a thin film, and prepare an upper electrode on the thin film to form an initial thin film structure;

[0117] The third processing module 304 is configured to perform a curing process on the initial thin film structure, and perform a polarization process on the cured initial thin film structure to obtain a piezoelectric sensing thin film;

[0118] The optimization module 305 is configured to analyze the performance of the piezoelectric sensing thin film in combination with artificial intelligence, and optimize the preparation parameters according to the analysis results.

[0119] As an implementation manner, for how to obtain nanoscale piezoelectric SiC powder, the preparation device 300 of the piezoelectric sensing thin film further includes: a fourth processing module;

[0120] The fourth processing module is configured to provide modified piezoelectric SiC powder doped with 0.2 - 0.5 wt% of Al / Yb;

[0121] Based on the high-energy ball milling method, refine the modified piezoelectric SiC powder to obtain nanoscale piezoelectric SiC powder with D 50 = 80 ± 20 nm.

[0122] As an implementation manner, for how to prepare the suspension, the first processing module 302 is specifically configured to:

[0123] Mix the nanoscale piezoelectric SiC powder with an ethanol solution to form a first mixed solution;

[0124] Add a dispersant and a conductive reinforcing phase to the first mixed solution to form a target mixed solution;

[0125] Based on an ultrasonic-mechanical vibration composite system, perform a dispersion process on the target mixed solution to form a suspension;

[0126] The ultrasonic frequency of the ultrasonic-mechanical vibration composite system is set to 20 kHz, the vibration frequency is set to 200 Hz, the vibration amplitude is set between 500 - 1000 μm, the acceleration is set between 5 - 10 g, and the vibration time is set to 30 min.

[0127] As an implementation manner, for how to determine whether the suspension meets the standard, the preparation device 300 of the piezoelectric sensing thin film further includes: a monitoring module;

[0128] The monitoring module is configured to collect state pictures of the suspension;

[0129] Analyze the state pictures in combination with the HSV color space vision algorithm to determine the degree of uniform dispersion of the particles in the suspension;

[0130] If the degree of uniform dispersion of the particles is lower than a preset threshold, an alarm is triggered and the dispersion parameters are adjusted.

[0131] As an implementation manner, for how to coat the suspension on the flexible polymer substrate, the above-mentioned second processing module 303 is specifically configured to:

[0132] Using a spin coater, coat the suspension on the flexible polymer substrate at a dynamically adjustable speed of 800 - 2500 rpm to form a thin film with a preset target thickness.

[0133] As an implementation manner, for how to control the rotation speed, the preparation device 300 of the piezoelectric sensing film further includes: a control module;

[0134] The control module is configured to collect thin film thickness data during the process of coating the suspension on the flexible polymer substrate;

[0135] Combined with the preset target thickness, use a PID controller and a deep learning model to perform collaborative analysis on the thin film thickness data to determine the rotation speed correction amount and the compensation control amount;

[0136] Control the rotation speed of the spin coater based on the rotation speed correction amount and the compensation control amount.

[0137] As an implementation manner, for how to cure the initial thin film structure, the above-mentioned third processing module 304 is specifically configured to:

[0138] Use a temperature control box to perform a drying process on the initial thin film structure at 80°C to remove the residual solution in the initial thin film structure;

[0139] Gradually increase the temperature of the temperature control box to 140°C, and control the initial thin film structure to continue to cure in the temperature control box for two hours.

[0140] As an implementation manner, for how to polarize the initial thin film structure after the curing process, the above-mentioned third processing module 304 is specifically configured to:

[0141] Immerse the initial thin film structure after the curing process in a silicone oil medium, and apply a DC electric field of 8 kV / mm between the upper electrode and the lower electrode at an environment temperature of 100°C for 30 min.

[0142] As an implementation manner, for how to perform performance testing, the above-mentioned optimization module 305 is specifically configured to:

[0143] Perform a piezoelectric-electrical joint test on the piezoelectric sensing film and obtain test data;

[0144] Determine the piezoelectric coefficient of the piezoelectric sensing film;

[0145] Combine the test data and the piezoelectric coefficient, and construct a relationship model between the piezoelectric performance and the preparation parameters through the support vector machine algorithm;

[0146] Combine the reinforcement learning algorithm and use the relationship model to optimize the preparation parameters.

[0147] In summary, this application first provides nanoscale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode. Among them, the material of the flexible polymer substrate is polyimide or polyether ether ketone. Then, the nanoscale piezoelectric SiC powder is mixed and dispersed to form a suspension. The suspension is coated on the flexible polymer substrate to form a film, and an upper electrode is prepared on the film to form an initial film structure. Finally, the initial film structure is cured, and the cured initial film structure is polarized to obtain a piezoelectric sensing film. In this way, by utilizing the stable piezoelectric performance of the SiC material in a wide temperature range, a piezoelectric sensing film is prepared, improving the performance of the piezoelectric sensing film. In addition, this application effectively establishes an association model of "preparation parameters - macroscopic performance" through a continuous cycle of data acquisition - model training - parameter optimization, ensuring that the film performance is stably optimized and can support large-scale stable production.

[0148] The above description of the disclosed embodiments enables those skilled in the art to implement or use this application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application will not be limited to the embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A preparation method of a piezoelectric sensing thin film, characterized in that, The method includes: Providing nanoscale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode; the material of the flexible polymer substrate is polyimide or polyether ether ketone; Performing a mixing and dispersion treatment on the nanoscale piezoelectric SiC powder to form a suspension; Coating the suspension onto the flexible polymer substrate to form a thin film, and preparing an upper electrode on the thin film to form an initial thin film structure; Performing a curing treatment on the initial thin film structure, and performing a poling treatment on the initial thin film structure after the curing treatment to obtain a piezoelectric sensing thin film; Combining artificial intelligence to analyze the performance of the piezoelectric sensing thin film, and optimizing the preparation parameters according to the analysis results.

2. The method according to claim 1, characterized in that, The method further includes: Providing modified piezoelectric SiC powder doped with 0.2 - 0.5 wt% of Al / Yb; The refined treatment of the modified piezoelectric SiC powder is carried out by high-energy ball milling to obtain nanoscale piezoelectric SiC powder with D 50 = 80 ± 20 nm.

3. The method according to claim 1, characterized in that, The performing a mixing and dispersion treatment on the nanoscale piezoelectric SiC powder to form a suspension includes: Mixing the nanoscale piezoelectric SiC powder with an ethanol solution to form a first mixed solution; Adding a dispersant and a conductive enhancing phase to the first mixed solution to form a target mixed solution; Performing a dispersion treatment on the target mixed solution based on an ultrasonic-mechanical vibration composite system to form a suspension; The ultrasonic frequency of the ultrasonic-mechanical vibration composite system is set to 20 kHz, the vibration frequency is set to 200 Hz, the vibration amplitude is set between 500 - 1000 μm, the acceleration is set between 5 - 10 g, and the vibration time is set to 30 min.

4. The method according to claim 3, wherein The method further includes: Collecting state pictures of the suspension; Combining the HSV color space vision algorithm to analyze the state pictures to determine the degree of uniform dispersion of particles in the suspension; If the degree of uniform dispersion of the particles is lower than a preset threshold, triggering an alarm and adjusting the dispersion parameters.

5. The method according to claim 1, wherein The coating the suspension onto the flexible polymer substrate to form a thin film includes: Using a spin coater to coat the suspension onto the flexible polymer substrate at a dynamically adjustable speed of 800 - 2500 rpm to form a thin film with a preset target thickness.

6. The method according to claim 5, wherein The method further includes: Collecting thin film thickness data during the process of coating the suspension onto the flexible polymer substrate; Combining the preset target thickness, using a PID controller and a deep learning model to perform a collaborative analysis on the thin film thickness data to determine a rotation speed correction amount and a compensation control amount; Controlling the rotation speed of the spin coater based on the rotation speed correction amount and the compensation control amount.

7. The method according to claim 1, characterized in that The performing a curing treatment on the initial thin film structure includes: Using a temperature control box to perform a drying treatment on the initial thin film structure at 80°C to remove the residual solution in the initial thin film structure; Raising the temperature of the temperature control box stepwise to 140°C, and controlling the initial thin film structure to be continuously cured in the temperature control box for two hours.

8. The method according to claim 1, wherein The performing a poling treatment on the initial thin film structure after the curing treatment includes: Immersing the initial thin film structure after the curing treatment in a silicone oil medium, and applying a DC electric field of 8 kV / mm between the upper electrode and the lower electrode in an environment of 100°C for 30 min.

9. The method according to claim 1, characterized in that Analyze the performance of the piezoelectric sensing film by combining artificial intelligence, and optimize the preparation parameters according to the analysis results, including: Conduct piezoelectric-electrical joint tests on the piezoelectric sensing film and obtain test data; Determine the piezoelectric coefficient of the piezoelectric sensing film; Combine the test data and the piezoelectric coefficient, and construct a relationship model between the piezoelectric performance and the preparation parameters through the support vector machine algorithm; Combine the reinforcement learning algorithm and use the relationship model to optimize the preparation parameters.

10. A preparation device for a piezoelectric sensing thin film, characterized in that, Including: A supply module for providing nanoscale piezoelectric SiC powder and a flexible polymer substrate deposited with a lower electrode; the material of the flexible polymer substrate is polyimide or polyether ether ketone; A first processing module for performing a mixing and dispersion process on the nanoscale piezoelectric SiC powder to form a suspension; A second processing module for coating the suspension onto the flexible polymer substrate to form a film, and preparing an upper electrode on the film to form an initial film structure; A third processing module for curing the initial film structure and polarizing the cured initial film structure to obtain a piezoelectric sensing film; An optimization module for analyzing the performance of the piezoelectric sensing film by combining artificial intelligence and optimizing the preparation parameters according to the analysis results.

Images