Uniform ink jet printing process for battery UV insulating coating

Abstract

The invention discloses an ink-uniformizing jet printing process for a battery UV insulating coating, which comprises the following steps: adding a first fluorescent marker and a second fluorescent marker in a UV coating material, the two fluorescent markers being capable of performing fluorescence resonance energy transfer to obtain a marked UV coating material; carrying out multi-position spectral characteristic acquisition on the micro-droplets formed by the UV coating material; dynamically tracking the spreading process of the micro-droplets; exciting the coating in the curing process by adopting multi-wavelength exciting light to obtain cross-linking degree distribution data; and carrying out thermoacoustic scanning on the coating. According to the technical scheme, real-time monitoring of cross-linking degree distribution in the curing process of the UV insulating coating can be achieved, the problem of non-uniform cross-linking of the coating can be found in time by monitoring the whole process of micro-droplet formation, spreading and curing in combination with fluorescence spectrum analysis and thermoacoustic detection technologies, and the quality of the coating is improved. And an effective quality control means is provided for ensuring the long-term reliability of the battery insulating coating.

Description

Technical Field

[0001] The present invention relates to the technical field of coating quality monitoring in the battery manufacturing process, and particularly to an ink-jet printing process for uniformizing the ink of a battery UV insulation coating. Background Art

[0002] The ink-jet printing process for uniformizing the ink of a battery UV insulation coating is an advanced battery manufacturing technology. Its core is to form a protective layer with high insulation, high adhesion, and durability on the battery surface. This process uses a precisely controlled ink-jet printing system to uniformly spray a liquid UV coating material in the form of micro-droplets onto the battery surface, and then rapidly cures it under the irradiation of a UV light source to form a protective film. During the curing process, the UV light triggers the formation of chemical bonds between monomer molecules in the coating material, constructing a three-dimensional network structure. This intermolecular chemical bonding process is called crosslinking. Compared with traditional coating processes, the ink-jet printing process for uniformizing the ink has higher coating uniformity and more precise thickness control capabilities.

[0003] In practical applications, due to the complexity of the geometric structure of the battery surface (such as edges, curved surfaces, etc.), there are significant differences in the UV light intensity received by different regions. This light non-uniformity, combined with the complexity of the spreading and curing behavior of micro-droplets during the ink-jet printing process, easily leads to the problem of insufficient crosslinking in local areas of the coating. Existing technologies mainly rely on offline detection methods after curing (such as electrical insulation testing, hardness testing, or solvent resistance testing, etc.) to evaluate the coating quality. These methods cannot reflect the actual crosslinking state of the coating during the curing process in real time. Especially for those regions with uneven crosslinking that are not easily detected in the initial stage, during the long-term use of the battery, the coating in these regions will gradually degrade due to insufficient crosslinking, ultimately leading to local failure of the insulation performance and seriously threatening battery safety. Therefore, there is an urgent need for a method that can monitor the crosslinking degree distribution of the coating in real time and comprehensively during the UV curing process, so as to timely discover and correct this potential quality and safety hazard. Summary of the Invention

[0004] The main purpose of the present invention is to solve the technical problems that the existing ink-jet printing process for uniformizing the ink of a battery UV insulation coating has uneven crosslinking degree distribution of the coating and is difficult to detect in real time.

[0005] The first aspect of the present invention provides an ink-jet printing process for uniformizing the ink of a battery UV insulation coating, and the ink-jet printing process for uniformizing the ink of a battery UV insulation coating includes: Adding a first fluorescent marker and a second fluorescent marker to the UV coating material, where the first fluorescent marker and the second fluorescent marker can undergo fluorescence resonance energy transfer to obtain a marked UV coating material; Collecting the spectral characteristics at multiple positions of the micro-droplets formed by the marked UV coating material to obtain the spectral dynamic characteristic data of the micro-droplets; Dynamically track the spreading process of the micro-droplets based on the spectral dynamic characteristic data to obtain the interface spreading characteristic data; According to the interface spreading characteristic data, use multi-wavelength excitation light to excite the coating during the curing process, obtain the change law of the fluorescence emission spectrum, and obtain the crosslinking degree distribution data of the coating; Perform thermoacoustic scanning on the coating during the curing process according to the crosslinking degree distribution data to obtain the crosslinked network structure characteristics of the coating.

[0006] Preferably, the first fluorescent marker is a hydrophobic-modified pyran fluorescent dye, and the maximum emission wavelength of the pyran fluorescent dye is 460 - 500 nm; the second fluorescent marker is a hydrophobic-modified coumarin derivative, and the maximum emission wavelength of the coumarin derivative is 550 - 600 nm.

[0007] Preferably, add the first fluorescent marker and the second fluorescent marker to the UV coating material, and the first fluorescent marker and the second fluorescent marker can undergo fluorescence resonance energy transfer to obtain the labeled UV coating material, including: Add the first fluorescent marker to the UV coating material at a mass fraction of 0.03 - 0.07%, and add the second fluorescent marker to the UV coating material at a mass fraction of 0.01 - 0.05% to obtain a UV coating material containing fluorescent markers; Perform high-speed shear dispersion on the UV coating material containing fluorescent markers, measure the fluorescence resonance energy transfer efficiency during the dispersion process, and when the change rate of the fluorescence resonance energy transfer efficiency is less than 5%, obtain a uniformly dispersed UV coating material; Adjust the viscosity of the uniformly dispersed UV coating material so that the ratio of the viscosity of the UV coating material to the surface energy of the substrate is between 0.8 - 1.2, and make the average distance between the two fluorescent markers in the UV coating material within the range of 2 - 10 nm to obtain the labeled UV coating material.

[0008] Preferably, perform multi-position spectral characteristic acquisition on the micro-droplets formed by the labeled UV coating material to obtain the spectral dynamic characteristic data of the micro-droplets, including: Collect the morphological parameters of the micro-droplets at the nozzle outlet, the midpoint of flight, and the position before landing. The morphological parameters include the diameter, eccentricity, and surface curvature of the micro-droplets to obtain the morphological dynamic change data of the micro-droplets; Collect the emission spectrum of the first fluorescent marker and the emission spectrum of the second fluorescent marker of the micro-droplets at the nozzle outlet, the midpoint of flight, and the position before landing respectively, and calculate the fluorescence resonance energy transfer efficiency between the two fluorescent markers to obtain the spectral change data of the micro-droplets; Calculate the change rate of the morphological parameters of the micro-droplets between adjacent acquisition positions based on the morphological dynamic change data of the micro-droplets to obtain the flight stability data of the micro-droplets; Analyze the spectral change data of the micro-droplets, calculate the ratio of the emission peak intensity of the first fluorescent marker to the emission peak intensity of the second fluorescent marker, and the spatial change gradient of the fluorescence resonance energy transfer efficiency to obtain the internal component uniformity data of the micro-droplets; Establish a corresponding relationship map between the morphological parameters and the spectral parameters based on the flight stability data and the internal component uniformity data of the micro-droplets to obtain the spectral dynamic characteristic data of the micro-droplets.

[0009] Preferably, the analyzing the spectral change data of the micro-droplets, calculating the ratio of the emission peak intensity of the first fluorescent marker to the emission peak intensity of the second fluorescent marker, and the spatial change gradient of the fluorescence resonance energy transfer efficiency to obtain the internal component uniformity data of the micro-droplets includes: Normalize the emission peak intensity of the first fluorescent marker and the emission peak intensity of the second fluorescent marker at three positions of the micro-droplets to obtain the standardized fluorescence intensity data; Calculate the fluorescence intensity ratio at each position based on the standardized fluorescence intensity data, and calculate the change rate of the fluorescence intensity ratio between adjacent positions to obtain the fluorescence intensity spatial distribution data; Perform gradient analysis on the fluorescence resonance energy transfer efficiency at three positions, calculate the correlation coefficient between the fluorescence resonance energy transfer efficiency and the surface curvature of the micro-droplets to obtain the component distribution state data; Calculate the component distribution uniformity coefficient and the uniformity coefficient of variation inside the micro-droplets based on the fluorescence intensity spatial distribution data and the component distribution state data to obtain the internal component uniformity data of the micro-droplets.

[0010] Preferably, the dynamically tracking the spreading process of the micro-droplets based on the spectral dynamic characteristic data to obtain the interface spreading characteristic data includes: Perform time series analysis on the spectral dynamic characteristic data, obtain the initial contact angle and the contact area after the micro-droplets land to obtain the spreading initial state data; Based on the spreading initial state data, track the fluorescence intensity distribution at the edge of the spreading area, calculate the change rate of the spreading radius over time to obtain the spreading kinetics data; Scan the spatial distribution of the first fluorescent marker and the second fluorescent marker in the spreading area, calculate the radial distribution of the fluorescence resonance energy transfer efficiency to obtain the interface interaction uniformity data; Based on the spreading kinetics data and the interface action uniformity data, analyze the spatio-temporal evolution law of the fluorescence resonance energy transfer efficiency in the spreading region, calculate the ratio of the spreading rates in the radial and tangential directions, and obtain the interface spreading characteristic data.

[0011] Preferably, scan the spatial distributions of the first fluorescent marker and the second fluorescent marker in the spreading region, calculate the radial distribution of the fluorescence resonance energy transfer efficiency, and obtain the interface action uniformity data, including: Divide the spreading region into grids at intervals of 0.5 mm, obtain the emission spectra of the first fluorescent marker and the second fluorescent marker at each grid point, and obtain the fluorescence spectrum spatial distribution data; Normalize the fluorescence spectrum spatial distribution data, calculate the fluorescence resonance energy transfer efficiency at each grid point, and obtain the fluorescence resonance energy transfer efficiency distribution map; Perform slice analysis on the fluorescence resonance energy transfer efficiency distribution map along the radial direction, calculate the energy transfer efficiency gradient at different radial positions, and obtain the radial uniformity distribution data; Perform circumferential integration on the radial uniformity distribution data, calculate the coefficient of variation of the energy transfer efficiency at different radii, and obtain the interface action uniformity data.

[0012] Preferably, according to the interface spreading characteristic data, use multi-wavelength excitation light to excite the coating during the curing process, obtain the variation law of the fluorescence emission spectrum, and obtain the crosslinking degree distribution data of the coating, including: Divide the coating region into a central region and an edge region according to the interface spreading characteristic data, and calculate the surface curvature coefficient and the coating thickness distribution coefficient of the two regions to obtain the initial coating morphology characteristic data; According to the initial coating morphology characteristic data, select excitation lights with wavelengths of 350 nm, 380 nm, and 420 nm to perform layered excitation on the coating, and obtain the emission spectra of the second fluorescent marker at different depths to obtain the depth-resolved spectrum data; Analyze the depth-resolved spectrum data, calculate the displacement of the emission peak of the second fluorescent marker at different regions and different depths, and combine the change in the fluorescence resonance energy transfer efficiency to obtain the crosslinking reaction process data; According to the crosslinking reaction process data, calculate the correlation coefficient between the surface curvature coefficient and the crosslinking degree, and the corresponding relationship between the coating thickness distribution coefficient and the crosslinking depth, and obtain the three-dimensional crosslinking degree distribution data; Normalize the three-dimensional crosslinking degree distribution data, calculate the gradient value of the crosslinking degree between adjacent regions and the uniformity coefficient of the crosslinking depth, and obtain the crosslinking degree distribution data of the coating.

[0013] Preferably, the depth-resolved spectral data is analyzed to calculate the displacement of the emission peaks of the second fluorescent label at different regions and depths, and combined with the change in the fluorescence resonance energy transfer efficiency to obtain the crosslinking reaction process data, including: Perform wavelength correction on the emission spectra of the second fluorescent label at different depths, establish a comparison between the baseline spectrum and the reference spectrum before crosslinking, and obtain spectral drift correction data; According to the spectral drift correction data, calculate the displacement of the emission peaks of the second fluorescent label, and perform hierarchical mapping in the depth direction to obtain the depth distribution data of the emission peak displacement; Analyze the change process of the fluorescence resonance energy transfer efficiency during the crosslinking reaction, calculate the change rate of the fluorescence resonance energy transfer efficiency at different regions and depths over time, and obtain the crosslinking microenvironment evolution data; According to the depth distribution data of the emission peak displacement and the crosslinking microenvironment evolution data, analyze the spatial distribution of the crosslinking reaction rate in different regions to obtain the crosslinking reaction process data.

[0014] Preferably, the coating during the curing process is subjected to thermoacoustic scanning according to the crosslinking degree distribution data to obtain the crosslinked network structure characteristics of the coating, including: Determine the sampling point distribution of the thermoacoustic scanning according to the crosslinking degree distribution data, perform thermoacoustic response detection on the coating surface, and obtain the frequency, amplitude, and phase parameters of the acoustic signal to obtain the acoustic response data of the coating; Perform frequency domain analysis on the acoustic response data, calculate the spatial distribution of the sound velocity and sound attenuation coefficient in different regions, and correlate with the crosslinking degree distribution to obtain the elastic modulus distribution data; Analyze the spatial structure characteristics of the crosslinked network according to the elastic modulus distribution data, calculate the elastic modulus gradient and network connectivity parameters between adjacent regions, and obtain the crosslinked network structure characteristics of the coating.

[0015] The present invention constructs a smart material system with spectral response characteristics by adding two fluorescent markers capable of fluorescence resonance energy transfer to UV coating materials, which not only makes the coating material itself an information carrier, but also cleverly utilizes the high sensitivity response characteristics of the fluorescence resonance energy transfer effect to microenvironment changes. After the labeled coating material forms microdroplets, the spectral characteristics are collected at multiple key positions such as the nozzle outlet, the midpoint of flight and before landing, and the dynamic change data of the microdroplets from formation to the whole process of flight can be obtained. These spectral dynamic characteristic data contain key information such as the morphology and component uniformity of the microdroplets, providing a basis for subsequent analysis. Next, the microdroplet spreading process is tracked using these spectral dynamic characteristic data, and the interface spreading characteristic data can be accurately obtained by analyzing the fluorescence intensity distribution at the spreading edge and the spatial variation of the fluorescence resonance energy transfer efficiency, which reflects the interaction between the coating and the battery surface. In the curing stage, the method selectively uses multi-wavelength excitation light to excite the coating based on the aforementioned interface spreading characteristic data. Since light of different wavelengths has different penetration depths in the coating, cross-linking information of different depths can be obtained. By analyzing the change law of the fluorescence emission spectrum, especially the displacement of the emission peak of the second fluorescent marker, the cross-linking distribution data of the coating can be accurately calculated. Finally, the cured coating is thermally scanned based on these cross-linking distribution data. The thermoacoustic signal is extremely sensitive to the changes in the internal microstructure of the coating. By analyzing the relationship between the acoustic response and the cross-linking degree, the cross-linking network structure characteristics of the coating can be determined, thereby comprehensively evaluating the coating quality. This whole process monitoring method from micro-droplet formation, flight, spreading to curing breaks through the limitations of traditional offline detection, and can capture the cross-linking degree differences in different areas of the battery surface due to the complexity of the geometric structure and uneven UV light in real time, providing a precise quality control method for the uniform inkjet printing process, and effectively solving the technical problem that the uneven distribution of the cross-linking degree of the coating cannot be detected in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0017] Figure 1 Schematic diagram of an embodiment of a uniform ink jet printing process for a battery UV insulating coating in an embodiment of the present invention.

[0018] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.

[0020] It should be noted that if there are directional indications (such as up, down, left, right, front, back,...) involved in the embodiments of the present invention, then the directional indications are only used to explain the relative positional relationship and movement conditions between components in a certain specific posture (as shown in the accompanying drawings). If this specific posture changes, the directional indications will also change accordingly.

[0021] In addition, the descriptions involving "first", "second", etc. in the present invention are only for descriptive purposes, and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In addition, "and / or" throughout the text includes three scenarios. Taking A and / or B as an example, it includes the technical solution of A, the technical solution of B, and the technical solution that both A and B are satisfied at the same time. In addition, the technical solutions between the various embodiments can be combined with each other, which must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention.

[0022] An embodiment of the present application provides a uniform inkjet printing process for a battery UV insulation coating. Figure 1 FIG. is a flowchart of a uniform inkjet printing process for a battery UV insulation coating provided by an embodiment of the present application. In this embodiment, the method includes: Please refer to Figure 1 , adding a first fluorescent marker and a second fluorescent marker to the UV coating material, and the first fluorescent marker and the second fluorescent marker can undergo fluorescence resonance energy transfer to obtain a labeled UV coating material; In an embodiment of the present invention, the first fluorescent marker is a hydrophobic modified pyran fluorescent dye, and the maximum emission wavelength of the pyran fluorescent dye is 460 - 500 nm; the second fluorescent marker is a hydrophobic modified coumarin derivative, and the maximum emission wavelength of the coumarin derivative is 550 - 600 nm.

[0023] Specifically, the UV coating material is mainly composed of acrylate monomers, epoxy resin monomers or polyurethane monomers. These materials usually have a hydrophobic backbone structure and initiate a cross-linking reaction through a photoinitiator under UV light to form a three-dimensional network structure. The selection of a hydrophobic modified pyran-based fluorescent dye as the first fluorescent marker is due to its chemical compatibility with the UV coating material. The hydrophobic modification enables the fluorescent dye to be uniformly dispersed in the coating material without affecting the basic properties of the coating. At the same time, the pyran-based dye has a high sensitivity response to changes in physical parameters of the microenvironment (such as viscosity and surface tension), and can accurately reflect the rheological properties of micro-droplets. Limiting its maximum emission wavelength within the range of 460 - 500 nm is for two reasons. On the one hand, the fluorescence signal in this wavelength region is not easily interfered by ambient light and has high detection sensitivity. On the other hand, this wavelength is exactly within the absorption band of the second fluorescent marker, providing ideal conditions for fluorescence resonance energy transfer. The selection of a hydrophobic modified coumarin derivative as the second fluorescent marker is due to its sensitivity to changes in the chemical microenvironment (especially the polarity change during the cross-linking reaction). The coumarin molecular structure contains groups that can interact with the active functional groups in the UV coating material, enabling it to keenly capture the microenvironment changes during the cross-linking process. Setting its maximum emission wavelength in the range of 550 - 600 nm not only forms an obvious spectral separation from the first fluorescent marker, facilitating the simultaneous monitoring of the two fluorescence signals, but more importantly, the fluorescence emission peak position of the coumarin derivative in this wavelength range will undergo an obvious blue shift as the cross-linking degree increases, providing an intuitive spectral index for the cross-linking degree. In addition, the approximately 100 nm gap between the emission wavelengths of the two fluorescent markers ensures an efficient fluorescence resonance energy transfer effect, enabling the system to have extremely high detection sensitivity to subtle changes during the flight and spreading of micro-droplets, laying a foundation for the real-time and accurate monitoring of the cross-linking degree distribution.

[0024] In one embodiment of the present invention, adding the first fluorescent marker and the second fluorescent marker to the UV coating material, where the first fluorescent marker and the second fluorescent marker can undergo fluorescence resonance energy transfer, to obtain a labeled UV coating material, including: Adding the first fluorescent marker to the UV coating material at a mass fraction of 0.03 - 0.07%, and adding the second fluorescent marker to the UV coating material at a mass fraction of 0.01 - 0.05% to obtain a UV coating material containing fluorescent markers; Performing high-speed shear dispersion on the UV coating material containing fluorescent markers, measuring the fluorescence resonance energy transfer efficiency during the dispersion process, and when the change rate of the fluorescence resonance energy transfer efficiency is less than 5%, obtaining a uniformly dispersed UV coating material; Adjust the viscosity of the uniformly dispersed UV coating material so that the ratio of the viscosity of the UV coating material to the surface energy of the substrate is between 0.8 and 1.2, and the average distance between the two fluorescent markers in the UV coating material is in the range of 2-10 nm, to obtain the labeled UV coating material.

[0025] The following specifically describes the steps involved in the above embodiments: The implementation process of adding the first fluorescent marker at a mass fraction of 0.03-0.07% and the second fluorescent marker at a mass fraction of 0.01-0.05% to the UV coating material is as follows: First, prepare a hydrophobic modified pyran-based fluorescent dye (the first fluorescent marker) and a coumarin derivative (the second fluorescent marker), and use a high-precision electronic balance (accuracy 0.0001 g) to weigh the corresponding masses respectively, and then add the two fluorescent markers to the UV coating substrate. The setting of the addition concentration range is based on two factors: one is to ensure sufficient detection sensitivity, and 0.03% is the lower limit concentration for fluorescence detection; the other is to avoid the fluorescence quenching effect. When the concentration exceeds 0.07%, the distance between fluorescent molecules is too close, which will cause self-quenching and reduce the detection accuracy. The concentration of the second fluorescent marker is slightly lower because the molar extinction coefficient of coumarin compounds is usually higher than that of pyran-based dyes, and sufficient signal intensity can be obtained at a lower concentration.

[0026] The specific implementation process of high-speed shear dispersion of the UV coating material containing fluorescent markers is: Place the coated material containing the markers in a high-speed disperser (such as an IKA T25 digital disperser), set the initial rotation speed to 5000 rpm, increase it by 2000 rpm every 5 minutes until it reaches 13000 rpm. During the dispersion process, use a fluorescence spectrometer (such as an Edinburgh FS5) to take samples and measure every 5 minutes, and record the emission intensity of the first fluorescent marker at 480 nm, the emission intensity of the second fluorescent marker at 580 nm, and the emission intensity of the second fluorescent marker under the excitation conditions of the first fluorescent marker respectively.

[0027] It should be noted that fluorescence resonance energy transfer (FRET) is a physical phenomenon that occurs between two fluorescent molecules. Its essence is a non-radiative energy transfer process. In this process, the donor fluorescent molecule in the excited state (such as the first fluorescent label) does not release energy by emitting photons, but directly transfers the energy to the acceptor molecule (such as the second fluorescent label) within an appropriate distance, causing the acceptor molecule to be excited and emit fluorescence. The occurrence of FRET requires several key conditions: First, the emission spectrum of the donor and the absorption spectrum of the acceptor must have sufficient overlap; second, the distance between the two fluorescent molecules usually needs to be in the range of 2 - 10 nanometers; third, the transition dipole moment directions of the donor and acceptor molecules need to have an appropriate relative orientation. The FRET efficiency is inversely proportional to the sixth power of the distance between the two molecules, so it is extremely sensitive to distance changes and can accurately reflect the microenvironment changes at the nanoscale. In the detection of the battery UV insulation coating, by using the high sensitivity of the FRET efficiency to molecular distance and microenvironment changes, the dispersion state of the fluorescent labels in the coating material and the microscopic structure changes during the cross-linking process can be accurately monitored, providing a direct and sensitive spectral index for evaluating the coating uniformity and cross-linking degree distribution.

[0028] The calculation formula for the fluorescence resonance energy transfer (FRET) efficiency is: E = 1 - (FDA / FD), where FDA is the fluorescence intensity in the presence of the acceptor for the donor, and FD is the fluorescence intensity when only the donor is present. When the change rate of the FRET efficiency measured three times continuously is less than 5%, it indicates that the two fluorescent labels have reached a stable dispersion state, and the dispersion process is completed at this time.

[0029] The implementation process of adjusting the viscosity of the uniformly dispersed UV coating material is as follows: Use a rotational viscometer (such as Brookfield DV2T) to measure the viscosity of the coating material, and at the same time use a contact angle measuring instrument (such as Krüss DSA100) to measure the surface energy of the battery substrate. According to the measurement results, adjust the viscosity by adding an appropriate amount of diluent (such as propylene glycol methyl ether acetate) or thickener (such as fumed silica) to control the ratio of viscosity to surface energy between 0.8 - 1.2. The setting of this ratio range is based on hydrodynamic theory and experimental verification: when the ratio is less than 0.8, the coating spreads too fast on the substrate surface, resulting in uneven thickness; when the ratio is higher than 1.2, the spreading is insufficient, resulting in incomplete coverage. During the viscosity adjustment process, the average distance of the fluorescent labels is monitored by a dynamic light scattering instrument (such as Malvern Zetasizer) to ensure that the distance between the two labels is maintained within the range of 2 - 10 nm. This distance range is the best condition for the occurrence of the FRET effect. Being too close will cause quenching, and being too far will result in low FRET efficiency and affect the detection sensitivity.

[0030] Please continue to refer to Figure 1 and collect the multi-position spectral characteristics of the micro-droplets formed by the marked UV coating material to obtain the spectral dynamic characteristic data of the micro-droplets; In one embodiment of the present invention, the collecting of the multi-position spectral characteristics of the micro-droplets formed by the marked UV coating material to obtain the spectral dynamic characteristic data of the micro-droplets includes: Collect the morphological parameters of the micro-droplets at the nozzle outlet, the midpoint of flight, and the position before landing. The morphological parameters include the diameter, eccentricity, and surface curvature of the micro-droplets to obtain the morphological dynamic change data of the micro-droplets; Collect the emission spectra of the first fluorescent marker and the emission spectra of the second fluorescent marker of the micro-droplets at the nozzle outlet, the midpoint of flight, and the position before landing respectively, and calculate the fluorescence resonance energy transfer efficiency between the two fluorescent markers to obtain the spectral change data of the micro-droplets; According to the morphological dynamic change data of the micro-droplets, calculate the change rate of the morphological parameters between adjacent acquisition positions of the micro-droplets to obtain the flight stability data of the micro-droplets; Analyze the spectral change data of the micro-droplets, calculate the ratio of the emission peak intensity of the first fluorescent marker to the emission peak intensity of the second fluorescent marker, and the spatial change gradient of the fluorescence resonance energy transfer efficiency to obtain the internal component uniformity data of the micro-droplets; According to the flight stability data and the internal component uniformity data of the micro-droplets, establish a corresponding relationship map of the morphological parameters and the spectral parameters to obtain the spectral dynamic characteristic data of the micro-droplets.

[0031] The following is a specific description of the steps involved in the above embodiments: The implementation process of collecting the morphological parameters of micro-droplets at the nozzle exit, mid-flight point, and pre-landing position is as follows: A high-speed imaging system (Photron FASTCAM SA-Z) is used in combination with a long-distance microscope. Imaging regions are set at three key positions to capture the instantaneous images of micro-droplets. Edge extraction and contour fitting are performed on the acquired droplet images through image processing software to calculate the diameter (maximum diameter), eccentricity (the ratio of the longest axis to the shortest axis), and surface curvature (fitting a quadratic surface through edge points) of the micro-droplets. For example, in the common ink-jet printing process, micro-droplets usually appear approximately spherical at the nozzle exit, with an eccentricity close to 1.0; during flight, they gradually deform under the influence of air resistance, and the eccentricity may increase to 1.2 - 1.5; at the pre-landing position, due to the action of gravity and surface tension, the droplet morphology will change further. By comparing the morphological parameters at the three positions, dynamic change data of the micro-droplet morphology are formed. The sophistication of this step lies in: choosing three positions instead of more is based on the analysis of the key nodes of the droplet flight trajectory, which can capture the main changes and avoid data redundancy; the introduction of the eccentricity and surface curvature parameters is aimed at the sensitivity of the battery UV insulation coating to the deformation history of the droplet, and these parameters are directly related to the internal hydrodynamics characteristics of the droplet.

[0032] The implementation method of collecting the fluorescence spectra of micro-droplets at three positions is as follows: A fluorescence spectral imaging system (Princeton Instruments IsoPlane-320) is used in combination with a pulsed laser, synchronized with the high-speed imaging system, to perform fluorescence excitation on the same micro-droplet. A laser with a wavelength of 365 nm is used to excite the first fluorescent label and a laser with a wavelength of 470 nm is used to excite the second fluorescent label respectively, and their emission spectra are recorded; at the same time, under the condition of only being excited by 365 nm, the emission intensity of the second fluorescent label at about 580 nm is measured to calculate the fluorescence resonance energy transfer efficiency. The calculation formula is: FRET efficiency = (Ia - Ib × fd) / Ia, where Ia is the emission intensity obtained by directly exciting the acceptor, Ib is the emission intensity obtained through FRET, and fd is the spectral correction factor. For the micro-droplets of the battery insulation coating, the change in FRET efficiency reflects the change in the spatial relationship of the fluorescent labels inside the droplet, and further indicates the dynamic redistribution of the coating components during flight. The uniqueness of this step design is that by measuring the change in the real-time FRET efficiency during the flight of the micro-droplet, the internal microscopic reorganization process of the droplet that cannot be monitored by traditional methods can be captured, which is crucial for judging the coating uniformity.

[0033] The specific method for calculating the flight stability data of micro-droplets is as follows: Based on the morphological dynamic change data, a three-dimensional parameter space including the diameter change rate (ΔD / D), eccentricity change rate (Δε / ε), and surface curvature change rate (ΔC / C) is established. For each pair of adjacent acquisition positions (nozzle exit - mid-flight and mid-flight - before landing), calculate the magnitude and direction of the change rate vector to form the flight stability index. For example, for micro-droplets under standard conditions, the diameter change rate is usually within the range of ±5%; the eccentricity change rate is within the range of +10% to +20%; the surface curvature change rate is related to the droplet size and flight speed. Through the comprehensive analysis of these change rates, it is possible to determine whether there are abnormal fluctuations or unstable factors during the flight of micro-droplets. This calculation method expands the change rate of a single parameter into a comprehensive analysis of a multi-dimensional parameter space, avoiding one-sided judgments that may result from only focusing on a single index.

[0034] The specific steps for analyzing the internal component uniformity of micro-droplets are as follows: First, calculate the ratio of the emission peak intensities of the first fluorescent marker to the second fluorescent marker (R = I1 / I2) at each measurement position to form the spatial distribution data of R values; then calculate the spatial gradient of the FRET efficiency (∇EFRET) to characterize the change trend of the FRET efficiency inside the droplet. Through the combined analysis of these two sets of data, it is possible to determine the distribution state of the internal components of the micro-droplet. For example, in the ideal case of completely uniform components, the R value should remain constant throughout the droplet, while the FRET gradient is close to zero; in actual droplets, there are usually differences between the edge region and the central region, and by quantitatively analyzing the degree of this difference, the component uniformity can be evaluated. This analysis method uses two complementary indicators, the fluorescence ratio and the FRET gradient, to analyze both the macroscopic distribution of components and capture the microscopic changes at the molecular scale.

[0035] The method for establishing the mapping relationship diagram between morphological parameters and spectral parameters is as follows: Take the morphological parameters (diameter, eccentricity, surface curvature) of the micro-droplet as the abscissa and the spectral parameters (R value, FRET efficiency) as the ordinate to construct a multi-dimensional parameter space. Through visualization methods such as scatter plots and contour maps, present the mapping relationship between the two types of parameters. For example, it can be found that there is a specific functional relationship between the eccentricity and the FRET efficiency, indicating the internal connection between the degree of droplet deformation and the internal molecular rearrangement. This mapping relationship diagram intuitively shows the correlation between the physical morphology of the micro-droplet and its internal chemical composition, providing an intuitive basis for comprehensively evaluating the quality of the micro-droplet. The establishment process of this diagram takes into account the unique properties of the micro-droplets with battery coatings: the coating quality not only depends on the appearance morphology of the droplets but is also closely related to the internal molecular distribution, and this correlation is often overlooked in traditional detection methods.

[0036] In one embodiment of the present invention, the spectral change data of the microdroplets is analyzed to calculate the ratio of the emission peak intensity of the first fluorescent marker to the emission peak intensity of the second fluorescent marker, and the spatial change gradient of the fluorescence resonance energy transfer efficiency, so as to obtain the internal component uniformity data of the microdroplets, including: Normalize the emission peak intensities of the first fluorescent marker and the second fluorescent marker at three positions of the microdroplets to obtain normalized fluorescence intensity data; According to the normalized fluorescence intensity data, calculate the fluorescence intensity ratio at each position, and calculate the change rate of the fluorescence intensity ratio between adjacent positions to obtain the fluorescence intensity spatial distribution data; Perform gradient analysis on the fluorescence resonance energy transfer efficiency at three positions, and calculate the correlation coefficient between the fluorescence resonance energy transfer efficiency and the surface curvature of the microdroplets to obtain the component distribution state data; According to the fluorescence intensity spatial distribution data and the component distribution state data, calculate the component distribution uniformity coefficient and the uniformity variation coefficient inside the microdroplets to obtain the internal component uniformity data of the microdroplets.

[0037] The following specifically describes the steps involved in the above embodiment: The specific method for normalizing the emission peak intensities of the first fluorescent marker and the second fluorescent marker at three positions of the microdroplets is as follows: Use spectral analysis software (such as OriginPro) to process the original fluorescence spectrum data. First, subtract the background signal, and then integrate the emission peak of the first fluorescent marker (pyran dye) near 480 nm and the emission peak of the second fluorescent marker (coumarin derivative) near 580 nm to obtain the peak area values. Divide the peak area at each position by the maximum peak area value measured at that position to obtain the normalized intensity value (ranging from 0 to 1). The normalization process eliminates the systematic errors caused by different measurement conditions (such as excitation light intensity, detector sensitivity, etc.), making the data at different positions comparable. During the ink-jet printing of the battery UV insulation coating, the microdroplets undergo deformation and internal reorganization from the nozzle outlet to before landing. The normalization process ensures the consistency of the spectral data during this dynamic process.

[0038] The specific steps for calculating the fluorescence intensity ratio and its change rate based on the standardized fluorescence intensity data are as follows: For each position (the nozzle exit, the midpoint of flight, and the position before landing), calculate the ratio of the normalized intensities of the first fluorescence marker to the second fluorescence marker, \(R = I1 / I2\), to obtain the \(R\) values (\(R1\), \(R2\), \(R3\)) at the three positions. Then calculate the change rate of the ratio between adjacent positions: the change rate \(\Delta R12=(R2 - R1) / R1\times100\%\) from the nozzle exit to the midpoint of flight, and the change rate \(\Delta R23=(R3 - R2) / R2\times100\%\) from the midpoint of flight to the position before landing. These change rates form the fluorescence intensity spatial distribution data, which intuitively reflects the dynamic changes in the internal component distribution of the microdroplet during flight. For example, in an ideal and uniform microdroplet, \(\Delta R12\) and \(\Delta R23\) should be close to zero; while in an actual battery coating microdroplet, due to the effects of surface tension and gravity, a change rate of about 5% is often observed, indicating a slight component redistribution inside the microdroplet. The sophistication of this step lies in: choosing the ratio rather than the absolute intensity for analysis, so that the result is not affected by the change in the volume of the microdroplet; calculating the change rate rather than the absolute difference, which makes the data of microdroplets of different sizes comparable.

[0039] The method for performing a gradient analysis on the fluorescence resonance energy transfer efficiency at the three positions is as follows: First, obtain the FRET efficiencies (\(E1\), \(E2\), \(E3\)) at the three positions from the previous step, and then calculate the FRET efficiency gradients between the positions: \(G12=(E2 - E1) / d12\), \(G23=(E3 - E2) / d23\), where \(d12\) and \(d23\) are the distances between adjacent positions respectively. Then, using the Pearson correlation analysis method, calculate the correlation coefficient between the FRET efficiency and the surface curvature (\(C1\), \(C2\), \(C3\)) of the microdroplet: \(r = cov(E,C) / [\sigma(E)\times\sigma(C)]\), where \(cov\) is the covariance and \(\sigma\) is the standard deviation. The range of the correlation coefficient is between -1 and 1, and the closer the absolute value is to 1, the stronger the correlation. This analysis reveals the relationship between the degree of microdroplet deformation and the internal molecular rearrangement, constituting the component distribution state data. For example, during the ink-jet printing of a battery UV insulation coating, the correlation coefficient between the FRET efficiency and the surface curvature is usually in the range of 0.6 - 0.8, indicating that the change in the microdroplet morphology does indeed cause a change in the internal molecular spatial relationship. This analysis method establishes a quantitative relationship between the macroscopic morphological characteristics and the microscopic molecular distribution of the microdroplet, providing a new dimension for evaluating the quality of the microdroplet.

[0040] The method for calculating the uniformity coefficient and the coefficient of variation of uniformity of the internal components of a micro-droplet is as follows: Based on the spatial distribution data of fluorescence intensity, calculate the uniformity coefficient H = 1 - |ΔR12| / 100% - |ΔR23| / 100%. The closer the H value is to 1, the more uniform the distribution of the internal components of the micro-droplet; based on the data of the component distribution state, calculate the coefficient of variation of uniformity V = |r|×(1 - min(E1, E2, E3) / max(E1, E2, E3)). The closer the V value is to 0, the more stable the distribution of the internal components of the micro-droplet. Finally, combine H and V to form a two-dimensional evaluation index to obtain the data of the internal component uniformity of the micro-droplet. In the application of the battery UV insulating coating, an ideal micro-droplet should have an H value close to 1 and a V value close to 0, indicating that the distribution of its internal components is uniform and stable. This calculation method comprehensively considers two complementary dimensions, namely the absolute uniformity (H) and the relative stability (V) of the component distribution, making the evaluation results more comprehensive and objective. Especially for the ink-jet printing process on the surface of a battery with a complex shape, this multi-dimensional evaluation can effectively identify those micro-droplets that seem uniform on the surface but have potential internal instabilities, improving the accuracy of coating quality control.

[0041] Please continue to refer to Figure 1 , and dynamically track the spreading process of the micro-droplet according to the spectral dynamic characteristic data to obtain the data of the interface spreading characteristics; In an embodiment of the present invention, the dynamically tracking the spreading process of the micro-droplet according to the spectral dynamic characteristic data to obtain the data of the interface spreading characteristics includes: Perform time series analysis on the spectral dynamic characteristic data, obtain the initial contact angle and contact area after the micro-droplet lands, and obtain the data of the initial spreading state; According to the data of the initial spreading state, track the fluorescence intensity distribution at the edge of the spreading region, calculate the change rate of the spreading radius with time, and obtain the spreading kinetics data; Scan the spatial distribution of the first fluorescent marker and the second fluorescent marker in the spreading region, calculate the radial distribution of the fluorescence resonance energy transfer efficiency, and obtain the data of the interface action uniformity; According to the spreading kinetics data and the data of the interface action uniformity, analyze the spatio-temporal evolution law of the fluorescence resonance energy transfer efficiency in the spreading region, calculate the ratio of the spreading rates in the radial and tangential directions, and obtain the data of the interface spreading characteristics.

[0042] The following specifically describes the steps involved in the above embodiment: The implementation method for obtaining the initial spreading state data by performing time series analysis on the spectral dynamic characteristic data is as follows: The moment of micro-droplet landing is imaged in real time through a high-speed confocal microscope system (such as Leica SP8), with the frame rate set at 1000 frames per second, while recording the fluorescence signal and bright-field images. The contact contour between the micro-droplet and the battery surface is extracted from the sequence of bright-field images, and the initial contact angle (the angle between the micro-droplet edge and the substrate surface) and the contact area are measured. The contact angle is obtained by fitting the droplet contour curve and calculating the tangent angle, and the contact area is converted into the actual area by calculating the number of pixels in the contact region and combining with the calibration coefficient. For example, for the UV insulating coating of the battery, the initial contact angle is usually in the range of 30° - 60°, and this range is related to the viscosity and surface tension characteristics of the coating material. A smaller contact angle (such as 30°) indicates good wettability of the coating material on the battery surface, which is conducive to forming a uniform coating; while a larger contact angle (such as 60°) may lead to insufficient spreading. This analysis method analyzes the entire process of the micro-droplet from flight to landing as a continuum, uses the previously obtained spectral dynamic characteristic data to predict the micro-droplet landing behavior, and compares it with the actual observation results, improving the accuracy of spreading behavior prediction.

[0043] The specific method for tracking the fluorescence intensity distribution at the edge of the spreading region based on the initial spreading state data is as follows: After the micro-droplet lands, the spreading region is scanned every 10 milliseconds using a fluorescence confocal scanning system, and the fluorescence intensity distribution maps of the first fluorescent marker and the second fluorescent marker are recorded. The edge of the spreading region is extracted through image processing software (such as ImageJ), and the spreading radius R is defined as the radius of the equivalent circular area. Then, the change rate dR / dt of R with respect to time t is calculated, and the R-t curve and the dR / dt-t curve are plotted to form the spreading kinetic data. In the inkjet printing process of the UV insulating coating on the battery, an ideal spreading process should exhibit the characteristics of being fast first and then slow: in the initial stage (the first 20 milliseconds), the spreading rate is relatively high (about 0.5 - 1.0 mm / s), and then it gradually decreases and tends to be stable. This spreading kinetic characteristic ensures that the coating material can fully cover the battery surface without excessive diffusion, especially for complex-shaped regions such as the battery edges. By tracking the fluorescence intensity distribution rather than simply the droplet contour, this method can simultaneously monitor the movement of the liquid front and the redistribution of components during the spreading process, providing more microscopic information for understanding the interaction between the battery surface and the coating material.

[0044] The implementation method for scanning the spatial distribution of fluorescent markers in the spreading area is as follows: Use a high-resolution confocal microscope to perform an XY-plane scan on the spreading area, set the scanning step size to 10 micrometers, and record the fluorescence intensity images of the first fluorescent marker (excitation wavelength 365 nm, emission wavelength 480 nm) and the second fluorescent marker (under FRET conditions, excitation wavelength 365 nm, emission wavelength 580 nm) respectively. Through the FRET efficiency calculation formula E = 1 - (FDA / FD), generate the FRET efficiency distribution map of the entire spreading area. Then, with the spreading center as the origin, extract the FRET efficiency values along different radial directions (take a radial line every 15°), calculate the average value and standard deviation of the FRET efficiency on each radial line, form the radial FRET efficiency distribution data, and constitute the interface interaction uniformity data. In the application of the battery UV insulating coating, a uniform and ideal spreading should show that the difference in FRET efficiency in each radial direction is less than 10%, and the standard deviation is less than 0.05. This scanning method can sensitively detect the local interface interaction differences caused by the non-uniform microstructure of the battery surface (such as small scratches, oxidation areas, etc.) during the spreading process through the radial distribution characteristics of FRET efficiency, and these differences directly affect the adhesion and long-term stability of the coating.

[0045] The specific steps for analyzing the spatio-temporal evolution law of the fluorescence resonance energy transfer efficiency in the spreading area are as follows: Combine the aforementioned spreading kinetic data with the interface interaction uniformity data to construct a four-dimensional data set (x, y, t, E) of the FRET efficiency varying with time and spatial position. Generate the spatio-temporal evolution map of the FRET efficiency through data visualization software (such as MATLAB), and analyze the time characteristics and spatial characteristics of the FRET efficiency change in different regions. Calculate the radial spreading rate Vr (the spreading speed along the radius direction) and the tangential spreading rate Vθ (the spreading speed perpendicular to the radius direction), and calculate the ratio Vr / Vθ between the two to form the interface spreading characteristic data. In the inkjet printing process of the battery UV insulating coating, an ideal spreading process should show that the ratio of Vr / Vθ is in the range of 1.0 - 1.2, indicating that the spreading process is close to isotropic and is conducive to forming a uniform coating. When the ratio is too large (>1.5), it indicates that there is an obvious directionality in the spreading, which may lead to uneven coating thickness; while when the ratio is too small (<0.8), it may indicate that there are obstacles on the substrate surface hindering the radial spreading. This analysis method can not only evaluate the macroscopic uniformity of the spreading through the spatio-temporal evolution law of the FRET efficiency, but also reveal the dynamic process of the microscopic interaction between the coating material and the battery surface, providing a scientific basis for optimizing the coating formulation and printing parameters.

[0046] In an embodiment of the present invention, scanning the spatial distribution of the first fluorescent marker and the second fluorescent marker in the spreading area, calculating the radial distribution of the fluorescence resonance energy transfer efficiency, and obtaining the interface interaction uniformity data include: The spreading area is meshed at an interval of 0.5 mm, and the emission spectra of the first and second fluorescent markers at each grid point are obtained to obtain the spatial distribution data of the fluorescence spectra; The spatial distribution data of the fluorescence spectra is normalized, and the fluorescence resonance energy transfer efficiency at each grid point is calculated to obtain a fluorescence resonance energy transfer efficiency distribution map; The fluorescence resonance energy transfer efficiency distribution map is sliced along the radial direction, and the energy transfer efficiency gradient at different radial positions is calculated to obtain the radial uniformity distribution data; The radial uniformity distribution data is integrated circumferentially, and the coefficient of variation of the energy transfer efficiency at different radii is calculated to obtain the interface action uniformity data.

[0047] The following specifically describes the steps involved in the above embodiments: The specific implementation of obtaining the spatial distribution data of the fluorescence spectra by meshing the spreading area at an interval of 0.5 mm is as follows: A motorized precision stage (such as Prior ProScan III) carrying a confocal fluorescence spectrometer (such as Horiba LabRAM HR Evolution) is used to perform spectral scanning on the spreading area. First, the outer boundary of the spreading area is determined, then a Cartesian coordinate system is established within this area, and it is divided into regular grids at an equal interval of 0.5 mm. At each grid intersection, a 365 nm wavelength laser is used to excite the first fluorescent marker, and the emission spectrum in the range of 460 - 500 nm is collected; a 470 nm wavelength laser is used to excite the second fluorescent marker, and the emission spectrum in the range of 550 - 600 nm is collected. The selection of an interval of 0.5 mm is based on the balance consideration of the typical spreading diameter (about 5 - 10 mm) of the micro-droplets of the battery UV insulating coating and the required detection accuracy. If the interval is too large (>1 mm), the spatial resolution will be insufficient to capture local non-uniformities; if the interval is too small (<0.1 mm), the data volume will be too large and the scanning time will be prolonged, possibly missing the dynamic process of spreading. In special areas such as the corners of the battery, the interval can be appropriately reduced to 0.3 mm to improve the local resolution. After the scanning is completed, the emission spectrum data of the two fluorescent markers at each grid point is integrated into a three-dimensional data set (x, y, λ) to form the spatial distribution data of the fluorescence spectra.

[0048] The implementation method for calculating the fluorescence resonance energy transfer (FRET) efficiency by normalizing the spatial distribution data of fluorescence spectra is as follows: Use spectral data processing software (such as OriginPro) to perform background subtraction and intensity normalization on the fluorescence spectra of each grid point. Define the maximum emission intensity of the first fluorescent label (donor) under the condition of only the donor present as FD, and define the donor emission intensity measured at the same position under the conditions of both the donor and acceptor present as FDA. Calculate the energy transfer efficiency of each grid point according to the FRET efficiency calculation formula E = 1 - (FDA / FD). To ensure the accuracy of the calculation results, factors such as spectral overlap and spectral leakage of the instrument need to be corrected. Rearrange the calculated FRET efficiency values according to the spatial coordinates of the grid points, and use false color display technology (such as blue indicating low FRET efficiency and red indicating high FRET efficiency) to generate a two-dimensional FRET efficiency distribution map. In the application of the battery UV insulation coating, the FRET efficiency in the uniformly well-spread area is usually in the range of 0.4 - 0.6, and the spatial variation is gentle; while in the poorly spread area, it shows that the FRET efficiency is abnormally high (>0.7) or low (<0.3), and the distribution is uneven. This normalization process eliminates systematic errors caused by factors such as excitation light intensity fluctuations and detector sensitivity changes, making the FRET efficiency data at different positions comparable.

[0049] The method for slicing and analyzing the FRET efficiency distribution map along the radial direction is as follows: Take the spreading center as the origin, set radial sampling lines, and take 24 radial lines (covering 360°) at an angular interval of 15° from the center outwards. Extract the FRET efficiency data along each radial line, and calculate the FRET efficiency gradient along the radial direction, that is, the ratio of the change in FRET efficiency between adjacent points to the distance (ΔE / Δr). For the battery UV insulation coating, an ideal spread should show that the absolute value of the radial FRET efficiency gradient is less than 0.1 / mm, indicating that the coating maintains good component uniformity during the spreading process. An overly large gradient (>0.2 / mm) often means that phase separation or non-uniform migration of the coating components occurs during the spreading process, which will directly affect the crosslinking uniformity during the subsequent UV curing process. After calculating the FRET efficiency gradients on the 24 radial lines respectively, construct a three-dimensional data set of gradient - angle - radius to form radial uniformity distribution data. This slicing analysis method selects radial slicing instead of simple XY grid analysis, which is more in line with the physical nature of droplet spreading (expanding from the center outwards) and can directly reflect the radial characteristics of component migration during the spreading process.

[0050] The implementation method of circumferential integration for radially uniformly distributed data is as follows: Group the FRET efficiency gradient data on the aforementioned 24 radial lines according to the radial distance. Specifically, starting from the spreading center, set a concentric ring every 0.5 mm, and conduct statistical analysis on the FRET efficiency gradient values within each concentric ring. Calculate the average value (μ), standard deviation (σ), and coefficient of variation (CV = σ / μ) of the gradient values within each ring. The coefficient of variation is the ratio of the standard deviation to the average value, reflecting the relative dispersion degree of the data, independent of the data dimension, and facilitating comparison between different regions. Here, the "circumferential integration" is actually a statistical aggregation of data at different angular positions at the same radius. For the uniform spreading of the battery UV insulation coating, the coefficient of variation of the inner ring (near the central region) is usually less than 0.1, indicating uniform spreading in the central region; while the coefficient of variation of the outer ring (near the edge region) is slightly larger, but should be controlled within 0.2 to ensure the spreading quality of the edge region. By analyzing the distribution characteristics of the coefficient of variation of the FRET efficiency gradient at different radii, the interface interaction uniformity data is constituted. This circumferential integration method decouples and analyzes the angular and radial characteristics of micro-droplet spreading, and can distinguish the angular non-uniformity caused by local property non-uniformity of the battery surface (such as surface energy, roughness, etc.) from the radial non-uniformity caused by the spreading dynamics itself, providing a more accurate evaluation basis for the spreading quality of the battery UV insulation coating.

[0051] Please continue to refer to Figure 1 , according to the interface spreading characteristic data, use multi-wavelength excitation light to excite the coating during the curing process, obtain the change rule of the fluorescence emission spectrum, and obtain the crosslinking degree distribution data of the coating; In an embodiment of the present invention, the step of using multi-wavelength excitation light to excite the coating during the curing process according to the interface spreading characteristic data, obtaining the change rule of the fluorescence emission spectrum, and obtaining the crosslinking degree distribution data of the coating includes: Divide the coating area into a central region and an edge region according to the interface spreading characteristic data, and calculate the surface curvature coefficient and the coating thickness distribution coefficient of the two regions to obtain the initial coating morphology characteristic data; According to the initial coating morphology characteristic data, select excitation lights with wavelengths of 350 nm, 380 nm, and 420 nm to perform layered excitation on the coating, and obtain the emission spectra of the second fluorescent label at different depths to obtain depth-resolved spectral data; Analyze the depth-resolved spectral data, calculate the displacement of the emission peak of the second fluorescent label in different regions and at different depths, and combine the change of the fluorescence resonance energy transfer efficiency to obtain the crosslinking reaction process data; According to the crosslinking reaction process data, calculate the correlation coefficient between the surface curvature coefficient and the crosslinking degree, and the corresponding relationship between the coating thickness distribution coefficient and the crosslinking depth to obtain the three-dimensional crosslinking degree distribution data; Normalize the three-dimensional crosslinking degree distribution data, calculate the gradient value of the crosslinking degree in adjacent regions and the uniformity coefficient of the crosslinking depth, and obtain the crosslinking degree distribution data of the coating.

[0052] The following specifically describes the steps involved in the above embodiments: The specific implementation method of dividing the coating area into the central area and the edge area according to the interface spreading characteristic data is as follows: Use a confocal microscope (such as Zeiss LSM 980) to scan the surface topography of the UV coating. First, based on the previously obtained radial spreading rate ratio (Vr / Vθ) data, determine the demarcation line between the central area and the edge area - define the position where the change rate of the Vr / Vθ ratio exceeds 20% as the demarcation point, define the area from the spreading center to the demarcation point as the central area, and define the area outside the demarcation point as the edge area. Then, measure the surface curvature coefficient (SC) of the two areas through three-dimensional topography analysis, that is, the ratio of the average value of the surface curvature to the standard deviation. Next, use confocal tomography technology to measure the coating thickness distribution and calculate the coating thickness distribution coefficient (TDC), that is, the ratio of the standard deviation of the thickness to the average thickness. In the application of the battery UV insulating coating, the SC value of the central area is usually less than 0.2, and the SC value of the edge area is relatively large (0.2 - 0.5); the ideal TDC value should be less than 0.15, indicating a uniform coating thickness distribution. The division of the central area and the edge area is crucial for subsequent crosslinking analysis because the two areas face different curing challenges: the central area has a large thickness and is prone to insufficient crosslinking; the edge area has a small thickness but a large curvature change and is prone to internal stress concentration.

[0053] The implementation method of selecting multi-wavelength excitation light for layer-by-layer excitation according to the initial morphological feature data of the coating is as follows: Use an ultraviolet excitation light source system (such as Edinburgh FLS1000) equipped with three excitation wavelengths (350 nm, 380 nm, and 420 nm) to perform layer-by-layer excitation on the coating. The selection of these three wavelengths is based on the difference in the penetration depth of light in the UV coating: 350 nm light mainly excites the surface layer (about 0 - 20 μm), 380 nm light can excite the middle layer (about 20 - 50 μm), and 420 nm light can reach the deep layer (about 50 - 100 μm). First, use the light of the three wavelengths to excite each test point in sequence, and collect the emission spectrum of the second fluorescent marker (coumarin derivatives) in the range of 550 - 600 nm. To ensure the comparability of the data, use a standard fluorescent sample for calibration before each measurement to eliminate the influence caused by equipment fluctuations. After the collection is completed, combine the emission spectra of each test point at the three excitation wavelengths into a multi-dimensional data set to form depth-resolved spectral data. The selection of these three specific wavelengths is carefully considered: the interval is large enough to ensure obvious depth discrimination, and not too large to cause gaps in depth coverage; at the same time, these three wavelengths are all within the absorption band of the second fluorescent marker (coumarin derivatives), which can effectively excite its fluorescence.

[0054] The implementation process of analyzing the depth-resolved spectral data to obtain the cross-linking reaction process data is as follows: Use spectral analysis software (such as Avantes AvaSoft) to perform peak position analysis on the collected emission spectra. First, perform Gaussian fitting on each emission spectrum to accurately locate the position of the emission peak; then, calculate the displacement amount (Δλ) of the emission peak relative to the reference peak in the uncross-linked state. During the UV curing process, as the cross-linking degree increases, the emission peak of the second fluorescent marker will undergo a blue shift (move towards the short wavelength direction), and the displacement amount shows a positive correlation with the cross-linking degree. At the same time, extract the FRET efficiency change data of each test point and calculate the change rate of the FRET efficiency with time (dE / dt). Combine the emission peak displacement amount and the FRET efficiency change rate to construct an index for the cross-linking reaction process. During the curing process of the battery UV insulating coating, an ideal cross-linking process is manifested as similar S-shaped curves of the emission peak displacement amounts of each layer with time, but the greater the depth, the more obvious the hysteresis of the curve; at the same time, the change rate of the FRET efficiency rises rapidly in the initial stage of cross-linking, reaches a peak in the middle stage, and gradually decreases to zero in the later stage. This dual-index analysis method can capture the spatial non-uniformity of the cross-linking reaction at the molecular level, and is especially suitable for detecting insufficient cross-linking problems in the corners and curved surface areas of the battery.

[0055] The method for obtaining the three-dimensional distribution data of the crosslinking degree by calculating the correlation coefficient between the surface curvature coefficient and the crosslinking degree is as follows: Use statistical analysis software (such as SPSS) to perform a correlation analysis on the relationship between the surface curvature coefficient (SC), the coating thickness distribution coefficient (TDC), and the emission peak displacement (Δλ). First, calculate the Pearson correlation coefficient (r1) between SC and Δλ at each depth layer, which reflects the correlation strength between the surface morphology and the crosslinking degree; then, calculate the correlation coefficient (r2) between TDC and the crosslinking depth (the difference in Δλ at each layer). Based on these two sets of correlation coefficients and combined with the previously obtained emission peak displacement data, establish a spatial distribution function model of the crosslinking degree to generate the three-dimensional distribution data of the crosslinking degree. In the application of the battery UV insulating coating, an ideal curing process should show that r1 is close to 0 (-0.1 to +0.1), indicating that the surface curvature has little influence on the crosslinking uniformity; while r2 should be close to -1 (-0.7 to -0.9), indicating that the thicker the thickness is more uniform, the smaller the difference in crosslinking depth. When the absolute value of r1 is too large (>0.3), it indicates that the curing process is overly sensitive to the surface morphology and the UV light source distribution needs to be optimized; when the absolute value of r2 is too small (<0.5), it indicates that the correlation between thickness control and crosslinking depth is weak, and there may be other influencing factors, such as uneven distribution of photoinitiators.

[0056] The implementation method for obtaining the crosslinking degree distribution data by normalizing the three-dimensional distribution data of the crosslinking degree is as follows: Use data processing software (such as MATLAB) to perform standardization processing on the three-dimensional distribution data of the crosslinking degree. First, divide the crosslinking degree value at each position by the maximum crosslinking degree value in this batch of samples to obtain the normalized crosslinking degree (range 0 - 1); then, calculate the crosslinking degree gradient (ΔCD / Δd) between adjacent test points, that is, the change in crosslinking degree per unit distance; finally, calculate the crosslinking uniformity coefficient (CU) between each depth layer, that is, the ratio of the standard deviation to the average value of the crosslinking degree at different depths. In the battery UV insulating coating, a good curing effect should show that the absolute value of the crosslinking degree gradient is less than 0.2 / mm, indicating uniform crosslinking in the planar direction; the crosslinking uniformity coefficient is less than 0.15, indicating consistent crosslinking in the depth direction. These numerical indicators together constitute the crosslinking degree distribution data of the coating, providing a quantitative basis for evaluating the UV curing quality. Normalization processing makes the crosslinking degree data of coatings with different batches and different formulations comparable, facilitating the establishment of a general quality evaluation standard; at the same time, these two relative indicators, the gradient value and the uniformity coefficient, can better reflect the uniformity of the curing process than the absolute crosslinking degree, and have higher guiding significance for predicting the long-term reliability of the coating.

[0057] In one embodiment of the present invention, the depth-resolved spectral data is analyzed, the displacement of the emission peak of the second fluorescent marker at different regions and different depths is calculated, and in combination with the change in the fluorescence resonance energy transfer efficiency, crosslinking reaction process data is obtained, including: Perform wavelength calibration on the emission spectra of the second fluorescent markers at different depths, establish a comparison between the baseline spectrum and the reference spectrum before crosslinking, and obtain spectral drift correction data; According to the spectral drift correction data, calculate the displacement of the emission peak of the second fluorescent marker, and perform hierarchical mapping in the depth direction to obtain the depth distribution data of the emission peak displacement; Analyze the change process of the fluorescence resonance energy transfer efficiency during the crosslinking reaction, calculate the rate of change of the fluorescence resonance energy transfer efficiency with time in different regions and at different depths, and obtain the crosslinking microenvironment evolution data; According to the depth distribution data of the emission peak displacement and the crosslinking microenvironment evolution data, analyze the spatial distribution of the crosslinking reaction rate in different regions to obtain the crosslinking reaction process data.

[0058] The following is a specific description of the steps involved in the above embodiments: The implementation method for performing wavelength calibration on the emission spectra of the second fluorescent markers at different depths is as follows: Use spectral calibration software (such as Ocean Insight OceanView) to process the collected raw spectral data. First, collect the emission spectrum of a standard reference sample (in the uncrosslinked state) before UV curing as the baseline spectrum. Then, use a mercury-argon lamp (with multiple emission lines of precisely known wavelengths) to calibrate the wavelength of the spectrometer to ensure measurement accuracy. Next, compare the measured spectra of each depth layer (the spectra obtained by 350nm, 380nm, and 420nm excitation correspond to the surface layer, middle layer, and deep layer respectively) with the baseline spectrum, and calculate the wavelength offset. Finally, correct the measured spectra according to the offset to eliminate systematic errors caused by factors such as instrument drift and temperature changes. In the application of the battery UV insulation coating, the accuracy of wavelength calibration is controlled within ±0.5nm, ensuring the accuracy of subsequent emission peak displacement analysis. This calibration step solves a key problem in fluorescence spectrum measurement: when the coating thickness changes, the optical paths of the incident light and fluorescence in the sample also change, resulting in possible systematic deviations in the spectra at different depths. If these deviations are not corrected, they will be misinterpreted as changes in the crosslinking degree.

[0059] The specific implementation method for calculating the emission peak displacement and performing depth distribution mapping based on spectral drift correction data is as follows: Use peak analysis software (such as PeakFit) to perform Gaussian-Lorentz mixed function fitting on the corrected spectrum to accurately determine the center position of the emission peak. Calculate the difference between the emission peak position of each measurement point and the position of the uncrosslinked reference peak to obtain the emission peak displacement (Δλ). Subsequently, group the displacement amounts of each measurement point according to the depth position (surface layer, middle layer, deep layer) to construct a three-dimensional spatial distribution map of the emission peak displacement. To enhance the data visualization effect, use pseudo-color display technology (such as blue representing small displacement amounts and red representing large displacement amounts) to intuitively present the distribution characteristics of the displacement amounts in the depth direction. During the crosslinking process of the battery UV insulating coating, the emission peak displacement amount of the second fluorescent marker (coumarin derivative) is positively correlated with the crosslinking degree, and the displacement range is usually between 2-15 nm. The advantage of choosing the emission peak displacement as the crosslinking degree index is that, compared with the change in fluorescence intensity, the peak displacement is not affected by factors such as coating thickness and fluorescent molecule concentration, providing a more reliable means for quantitative evaluation of the crosslinking degree and being suitable for the crosslinking uniformity analysis of the surfaces of batteries with complex shapes.

[0060] The analysis method for the change process of the fluorescence resonance energy transfer efficiency during the crosslinking reaction is as follows: Use a time-resolved fluorescence spectrometer (such as Edinburgh FLS1000) to measure the FRET efficiency of the sample every 10 seconds during the UV curing process. The calculation of the FRET efficiency uses the donor fluorescence lifetime method, that is, measure the fluorescence lifetime of the first fluorescent marker (donor) in the presence and absence of the second fluorescent marker (acceptor), and calculate the FRET efficiency according to the formula E = 1 - τDA / τD, where τDA is the donor fluorescence lifetime when the donor and acceptor coexist, and τD is the donor fluorescence lifetime when only the donor exists. For the obtained FRET efficiency-time data sequence, calculate the change rate of the FRET efficiency (dE / dt) at each time point, and this change rate directly reflects the crosslinking reaction rate. Integrate the change rate data of the FRET efficiency in different regions (center and edge) and different depth layers to form the data on the evolution of the crosslinking microenvironment. During the curing process of the battery UV insulating coating, the change rate of the FRET efficiency rises rapidly in the initial stage (0-30% crosslinking degree) of the crosslinking reaction, reaches a peak in the middle stage (30-70% crosslinking degree), and gradually decreases in the later stage (70-100% crosslinking degree). This change pattern reflects the autocatalytic characteristics and diffusion-limiting effects of the crosslinking reaction, providing a microscopic perspective for understanding the crosslinking kinetic differences in different regions on the battery surface.

[0061] The method for realizing the spatial distribution of the crosslinking reaction rate based on the depth distribution data of the emission peak shift and the analysis of the crosslinking microenvironment evolution is as follows: Use data analysis software (such as Origin Pro) to perform cross-correlation analysis on the two sets of data. First, compare the rate of change of the emission peak shift with time (dΔλ / dt) and the rate of change of the FRET efficiency (dE / dt), and calculate the correlation coefficient (r) and the deviation coefficient (d) between the two. A high correlation coefficient (r > 0.8) and a low deviation coefficient (d < 0.1) indicate that the measurement results of the two indicators are consistent, enhancing the credibility of the data. Then, based on these two complementary indicators, calculate the crosslinking reaction rate constant (k) at each measurement point, rearrange it according to the spatial position, and construct a three-dimensional distribution map of the crosslinking reaction rate. Finally, by comparing the differences in the crosslinking reaction rates between different regions, identify the non-uniform crosslinking regions and form the crosslinking reaction process data. In the application of the battery UV insulation coating, the ideal crosslinking process should show a gentle crosslinking rate gradient in the depth direction (the rate difference between adjacent layers < 20%) and a uniform crosslinking rate in the plane direction (the rate difference between different regions at the same depth < 15%). This analysis method combines molecular spectroscopy means (emission peak shift and FRET efficiency) with reaction kinetics analysis, realizing multi-scale and all-round monitoring of the crosslinking process of the battery complex surface UV coating, and providing a scientific basis for solving the problem of non-uniform crosslinking.

[0062] Please continue to refer to Figure 1 , and perform a thermoacoustic scan on the coating during the curing process according to the crosslinking degree distribution data to obtain the crosslinked network structure characteristics of the coating.

[0063] In one embodiment of the present invention, the performing a thermoacoustic scan on the coating during the curing process according to the crosslinking degree distribution data to obtain the crosslinked network structure characteristics of the coating includes: Determine the sampling point distribution of the thermoacoustic scan according to the crosslinking degree distribution data, perform thermoacoustic response detection on the coating surface, obtain the frequency, amplitude, and phase parameters of the acoustic signal, and obtain the acoustic response data of the coating; Perform frequency domain analysis on the acoustic response data, calculate the spatial distribution of the sound velocity and the sound attenuation coefficient in different regions, and correlate it with the crosslinking degree distribution to obtain the elastic modulus distribution data; Analyze the spatial structure characteristics of the crosslinked network according to the elastic modulus distribution data, calculate the elastic modulus gradient and the network connectivity parameter between adjacent regions, and obtain the crosslinked network structure characteristics of the coating.

[0064] The following specifically describes the steps involved in the above embodiments: The specific implementation method for determining the sampling point distribution of thermoacoustic scanning based on crosslinking degree distribution data for thermoacoustic response detection is as follows: Use a laser ultrasonic system (such as PacNDT LUS-100) to perform non-contact scanning on the UV-cured coating. First, based on the crosslinking degree distribution data obtained previously, a weighted sampling strategy is adopted to determine the scanning positions. The sampling density is increased (point spacing is 0.5 mm) in the region with a large crosslinking degree gradient (absolute value of gradient > 0.15 / mm), and a larger spacing (1.0 mm) is used in the region with a uniform crosslinking degree. Then, laser pulses with a modulation frequency of 1 - 10 MHz (pulse width 10 ns, energy density < 10 mJ / cm²) are used to irradiate the surface of the coating, generating transient thermoelastic stress and triggering ultrasonic waves. Thermoelastic stress refers to the internal stress generated by the thermal expansion of materials when heated, and this stress is released and propagated in the form of ultrasonic waves. Piezoelectric sensors or laser interferometric detectors are used to capture the ultrasonic signals, and the frequency distribution (0.5 - 15 MHz), amplitude (relative intensity), and phase (time delay relative to the excitation pulse) parameters of the sound waves are recorded. Pulse thermal excitation is used instead of continuous heating to avoid thermal damage to the UV-cured coating and improve the signal-to-noise ratio at the same time; the modulation frequency range of 1 - 10 MHz is selected based on the precise matching of the typical thickness (20 - 100 μm) and acoustic properties of the battery UV insulation coating. This thermoacoustic measurement technique does not require contact with the sample and does not damage the coating; it can reflect the internal structure of the material rather than just the surface characteristics; it is extremely sensitive to microstructural changes and can detect hidden defects that cannot be found by traditional mechanical tests.

[0065] The specific steps to obtain the elastic modulus distribution data through frequency-domain analysis of acoustic response data are as follows: Use acoustic signal processing software (such as Polytec PSV-500) to perform a fast Fourier transform (FFT) on the collected time-domain ultrasonic signals and convert them into a frequency-domain representation. Extract key acoustic parameters such as the sound velocity (c) and the sound attenuation coefficient (α) from the spectrum. The sound velocity is calculated based on the ratio of the ultrasonic propagation time to the propagation distance (c = d / t, where d is the propagation distance and t is the propagation time), and the sound attenuation coefficient is based on the attenuation rate of the acoustic wave intensity with the propagation distance (α = -ln(A / A0) / d, where A is the amplitude at the measurement point, A0 is the amplitude at the reference point, and d is the propagation distance). Subsequently, according to the acoustic-elastic relationship formula E = ρc²(1 + σ)(1 - 2σ) / (1 - σ), convert the sound velocity into the elastic modulus (E). In this formula, ρ is the coating density, σ is the Poisson's ratio (usually taken as 0.3 - 0.4), and c is the longitudinal wave sound velocity. Rearrange the calculated elastic modulus values according to the spatial position, construct a two-dimensional distribution map of the elastic modulus, perform spatial registration and correlation analysis with the crosslinking degree distribution map obtained previously, calculate the point-to-point correspondence between the two, and obtain the elastic modulus-crosslinking degree mapping function. In the application of the battery UV insulating coating, this mapping function usually shows the characteristics of an S-shaped curve: the elastic modulus changes slightly in the low crosslinking degree region (0 - 30%); it rises rapidly in the medium crosslinking degree region (30 - 70%); and the growth of the elastic modulus tends to level off in the high crosslinking degree region (70 - 100%). This analysis method directly establishes a quantitative correlation between the microscopic crosslinking structure and the macroscopic mechanical properties of the coating, providing a scientific basis for evaluating the actual performance of the coating.

[0066] The implementation method for analyzing the crosslinking network structure characteristics based on the elastic modulus distribution data is as follows: Use a material structure analysis software (such as ANSYS) to perform a gradient field analysis on the elastic modulus distribution data. First, calculate the elastic modulus gradient value between adjacent test points, that is, the change in elastic modulus per unit distance (ΔE / Δd). The gradient field reflects the severity of the change in the crosslinking network structure. Regions with large gradients are often stress concentration points and potential failure initiation points. Then, based on the spectral characteristics of the acoustic signal, especially the energy distribution of the high-frequency components (>5 MHz), calculate the network connectivity parameter (NCP). The calculation method of the network connectivity parameter is: NCP = Ehf / Etotal, where Ehf is the acoustic energy in the high-frequency band (5 - 15 MHz) and Etotal is the total acoustic energy. The physical meaning of this parameter is clear because a highly crosslinked network structure has good conductivity for high-frequency sound waves, while regions with insufficient crosslinking or defects will cause strong scattering and attenuation of high-frequency sound waves. This parameter quantitatively characterizes the spatial integrity of the crosslinking network. The higher the value, the more continuous and uniform the crosslinking network. In the UV insulation coating of the battery, an ideal crosslinking network structure shows a low elastic modulus gradient (<1 MPa / mm) and a high network connectivity parameter (>0.85). On the contrary, if the elastic modulus gradient in a certain region exceeds 2 MPa / mm and the network connectivity parameter is lower than 0.7, it indicates that there are obvious defects in the crosslinking network in this region and special attention is needed. Combining the elastic modulus gradient and the network connectivity parameter forms a comprehensive evaluation system for the crosslinking network structure characteristics of the coating. This system can not only evaluate the current coating quality but also predict the long-term reliability of the coating during service.

[0067] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structural transformation made under the inventive concept of the present invention by using the content of the specification and drawings of the present invention, or directly / indirectly applied in other related technical fields, is included in the patent protection scope of the present invention.

Claims

1. A uniform inkjet printing process for battery UV insulation coating, characterized in that: include: Adding a first fluorescent marker and a second fluorescent marker into the UV coating material, wherein the first fluorescent marker and the second fluorescent marker can undergo fluorescence resonance energy transfer, to obtain a labeled UV coating material; Collecting the spectral characteristics of the micro-droplets formed by the marked UV coating material at multiple positions to obtain spectral dynamic characteristic data of the micro-droplets; Dynamically tracking the spreading process of the micro-droplets according to the spectral dynamic characteristic data to obtain interface spreading characteristic data; According to the interface spreading characteristic data, a multi-wavelength excitation light is used to excite the coating during the curing process, and the change law of the fluorescence emission spectrum is obtained to obtain the crosslinking degree distribution data of the coating; The coating during the curing process is subjected to a thermoacoustic scan according to the crosslinking degree distribution data to obtain the crosslinking network structure characteristics of the coating.

2. The ink jet printing process for battery UV insulation coating according to claim 1, characterized in that: The first fluorescent marker is a hydrophobically modified pyran fluorescent dye, and the maximum emission wavelength of the pyran fluorescent dye is 460-500nm; the second fluorescent marker is a hydrophobically modified coumarin derivative, and the maximum emission wavelength of the coumarin derivative is 550-600nm.

3. The ink jet printing process for battery UV insulation coating according to claim 2, characterized in that: The method of adding a first fluorescent marker and a second fluorescent marker to the UV coating material, wherein the first fluorescent marker and the second fluorescent marker can undergo fluorescence resonance energy transfer, to obtain a labeled UV coating material comprises: The first fluorescent marker is added to the UV coating material at a mass fraction of 0.03-0.07%, and the second fluorescent marker is added to the UV coating material at a mass fraction of 0.01-0.05%, to obtain a UV coating material containing fluorescent markers; Performing high-speed shear dispersion on the UV coating material containing the fluorescent marker, measuring the fluorescence resonance energy transfer efficiency during the dispersion process, and obtaining a uniformly dispersed UV coating material when the change rate of the fluorescence resonance energy transfer efficiency is less than 5%; The viscosity of the uniformly dispersed UV coating material is adjusted so that the ratio of the viscosity of the UV coating material to the surface energy of the substrate is between 0.8-1.2 and the average distance between the two fluorescent markers in the UV coating material is within the range of 2-10 nm to obtain a marked UV coating material.

4. The ink jet printing process for battery UV insulation coating according to claim 1, characterized in that: The multi-position spectral characteristic acquisition of the micro-droplets formed by the marked UV coating material to obtain spectral dynamic characteristic data of the micro-droplets includes: The morphological parameters of the micro-droplets are collected at the nozzle outlet, the mid-point of the flight and the position before landing, wherein the morphological parameters include the diameter, eccentricity and surface curvature of the micro-droplets, and the dynamic change data of the morphology of the micro-droplets are obtained; The emission spectrum of the first fluorescent marker and the emission spectrum of the second fluorescent marker of the microdroplet are collected at the nozzle outlet, the mid-flight point and the position before landing, respectively, and the fluorescence resonance energy transfer efficiency between the two fluorescent markers is calculated to obtain the spectrum change data of the microdroplet; According to the dynamic change data of the micro-droplet morphology, the change rate of the morphological parameters of the micro-droplet between adjacent collection positions is calculated to obtain the flight stability data of the micro-droplet; Analyzing the spectral variation data of the microdroplet, calculating the ratio of the emission peak intensity of the first fluorescent marker to the emission peak intensity of the second fluorescent marker, and the spatial variation gradient of the fluorescence resonance energy transfer efficiency, and obtaining the internal component uniformity data of the microdroplet; According to the flight stability data and internal component uniformity data of the micro-droplets, a corresponding relationship map between morphological parameters and spectral parameters is established to obtain spectral dynamic characteristic data of the micro-droplets.

5. The ink jet printing process for battery UV insulation coating according to claim 4, characterized in that: The spectral variation data of the microdroplets are analyzed, the ratio of the emission peak intensity of the first fluorescent marker to the emission peak intensity of the second fluorescent marker, and the spatial variation gradient of the fluorescence resonance energy transfer efficiency are calculated, and the internal component uniformity data of the microdroplets are obtained, including: Normalizing the emission peak intensities of the first fluorescent marker and the second fluorescent marker of the microdroplet at three positions to obtain standardized fluorescence intensity data; According to the standardized fluorescence intensity data, the fluorescence intensity ratio of each position is calculated, and the change rate of the fluorescence intensity ratio between adjacent positions is calculated to obtain fluorescence intensity spatial distribution data; The fluorescence resonance energy transfer efficiency at three positions was subjected to gradient analysis, and the correlation coefficient between the fluorescence resonance energy transfer efficiency and the microdroplet surface curvature was calculated to obtain the component distribution state data; According to the fluorescence intensity spatial distribution data and the component distribution state data, the component distribution uniformity coefficient and uniformity variation coefficient inside the microdroplet are calculated to obtain the internal component uniformity data of the microdroplet.

6. The ink jet printing process for battery UV insulation coating according to claim 1, characterized in that: The step of dynamically tracking the spreading process of the micro-droplets according to the spectral dynamic characteristic data to obtain interface spreading characteristic data includes: Performing time series analysis on the spectral dynamic characteristic data to obtain the initial contact angle and contact area after the microdroplet lands, and obtaining the initial spreading state data; According to the initial spreading state data, tracking the fluorescence intensity distribution at the edge of the spreading area, calculating the rate of change of the spreading radius over time, and obtaining spreading kinetics data; Scanning the spatial distribution of the first fluorescent marker and the second fluorescent marker in the spreading area, calculating the radial distribution of the fluorescence resonance energy transfer efficiency, and obtaining the interface action uniformity data; According to the spreading kinetics data and interface uniformity data, the spatiotemporal evolution of the fluorescence resonance energy transfer efficiency in the spreading area is analyzed, and the ratio of radial and tangential spreading rates is calculated to obtain interface spreading characteristic data.

7. The ink jet printing process for battery UV insulation coating according to claim 6, characterized in that: The step of scanning the spatial distribution of the first fluorescent marker and the second fluorescent marker in the spreading area, calculating the radial distribution of the fluorescence resonance energy transfer efficiency, and obtaining the interface uniformity data includes: Divide the spreading area into grids at intervals of 0.5 mm, obtain the emission spectrum of the first fluorescent marker and the second fluorescent marker at each grid point, and obtain fluorescence spectrum spatial distribution data; Normalizing the fluorescence spectrum spatial distribution data, calculating the fluorescence resonance energy transfer efficiency of each grid point, and obtaining a fluorescence resonance energy transfer efficiency distribution map; Slice and analyze the fluorescence resonance energy transfer efficiency distribution diagram along the radial direction, calculate the energy transfer efficiency gradients at different radial positions, and obtain radial uniformity distribution data; The radial uniformity distribution data is circumferentially integrated, and the discrete coefficients of the energy transfer efficiency at different radii are calculated to obtain the interface action uniformity data.

8. The ink jet printing process for battery UV insulation coating according to claim 1, characterized in that: According to the interface spreading characteristic data, a multi-wavelength excitation light is used to excite the coating during the curing process, and the change law of the fluorescence emission spectrum is obtained to obtain the crosslinking degree distribution data of the coating, including: Dividing the coating area into a central area and an edge area according to the interface spreading characteristic data, and calculating the surface curvature coefficient and coating thickness distribution coefficient of the two areas to obtain initial morphological characteristic data of the coating; According to the initial morphological characteristic data of the coating, selecting excitation light with wavelengths of 350nm, 380nm and 420nm to excite the coating in layers, and obtaining emission spectra of the second fluorescent marker at different depths to obtain depth-resolved spectral data; Analyzing the depth-resolved spectral data, calculating the displacement of the emission peak of the second fluorescent marker in different regions and depths, and combining the change of fluorescence resonance energy transfer efficiency to obtain the cross-linking reaction progress data; According to the cross-linking reaction progress data, the correlation coefficient between the surface curvature coefficient and the cross-linking degree, and the corresponding relationship between the coating thickness distribution coefficient and the cross-linking depth are calculated to obtain the three-dimensional distribution data of the cross-linking degree; The three-dimensional distribution data of the degree of crosslinking are normalized, and the gradient value of the degree of crosslinking in adjacent regions and the uniformity coefficient of the crosslinking depth are calculated to obtain the distribution data of the degree of crosslinking of the coating.

9. The ink jet printing process for battery UV insulation coating according to claim 8, characterized in that: The depth-resolved spectral data is analyzed to calculate the displacement of the emission peak of the second fluorescent marker in different regions and depths, and combined with the change of fluorescence resonance energy transfer efficiency to obtain the cross-linking reaction progress data, including: Performing wavelength correction on the emission spectra of the second fluorescent markers at different depths, establishing a baseline spectrum for comparison with a reference spectrum before cross-linking, and obtaining spectral drift correction data; Calculating the displacement of the emission peak of the second fluorescent marker according to the spectral drift correction data, and performing layered mapping in the depth direction to obtain depth distribution data of the emission peak displacement; The change process of fluorescence resonance energy transfer efficiency along with the cross-linking reaction was analyzed, and the change rate of fluorescence resonance energy transfer efficiency along with time in different regions and depths was calculated to obtain the cross-linking microenvironment evolution data; According to the depth distribution data of the emission peak shift and the cross-linking microenvironment evolution data, the spatial distribution of the cross-linking reaction rates in different regions is analyzed to obtain the cross-linking reaction progress data.

10. The ink jet printing process for battery UV insulation coating according to claim 1, characterized in that: The step of performing a thermoacoustic scan on the coating during the curing process according to the crosslinking degree distribution data to obtain the crosslinking network structure characteristics of the coating includes: Determining the sampling point distribution of the thermoacoustic scan according to the crosslinking degree distribution data, performing thermoacoustic response detection on the coating surface, acquiring the frequency, amplitude and phase parameters of the acoustic signal, and obtaining the acoustic response data of the coating; Performing frequency domain analysis on the acoustic response data, calculating the spatial distribution of the sound velocity and the acoustic attenuation coefficient in different regions, and correlating them with the crosslinking degree distribution to obtain elastic modulus distribution data; The spatial structural characteristics of the cross-linked network are analyzed according to the elastic modulus distribution data, and the elastic modulus gradient and network connectivity parameters between adjacent regions are calculated to obtain the cross-linked network structural characteristics of the coating.

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