Method, system and equipment for designing and optimizing coating parameters of optical adhesive

Abstract

The present application provides a method, system and equipment for designing and optimizing the coating parameters of optical adhesives, including a material selection and pretreatment step for selecting suitable materials based on the input demand type and pre-treating the materials; a viscosity dynamic control step for dynamically adjusting the viscosity; a coating method selection step for selecting a suitable coating method; a coating thickness design step for presetting the coating thickness to achieve the best coating effect; a curing parameter optimization step for curing the coated product and improving its performance; the material selection and pretreatment steps include at least a surfactant addition operation for improving the wettability of the adhesive on the curved surface, reducing the edge contact angle, and reducing the risk of edge shrinkage; the coating method selection step includes at least a pre-setting coating trajectory operation, which can realize targeted coating parameter design and optimization based on different needs, especially the production needs of curved screen panels, thereby improving the quality of the final product.

Description

Technical Field

[0001] The present invention relates to the application field of optical adhesives, and in particular to a method, system and equipment for designing and optimizing adhesive coating parameters of optical adhesives. Background Art

[0002] Optical adhesive (adhesive for bonding optical components) is a polymer substance with excellent bonding properties that closely resemble those of optical components. It can be used to bond two or more optical components into optical assemblies that meet optical path design requirements; it can also be used to bond protective glass for high-precision optical scales, filters, and other components. The imaging quality and performance of optical instruments are closely related to the quality and performance of the optical adhesive.

[0003] Currently, optical adhesive is one of the commonly used raw materials for electronic device screens. As the types of electronic devices become more diverse (such as high-strength screens, curved screens, flexible screens, etc.), the consumer electronics industry's performance requirements for optical adhesives are constantly increasing. At the same time, based on different screens, the demand for optical adhesive performance has also branched out.

[0004] In recent years, mainstream consumer electronics companies have begun to focus on "special-shaped" screen technologies such as curved screens. Because they are different from previous flat and regular screen designs, they have put forward higher requirements for the optical adhesive coating process. In the existing technology, there are currently the following major problems:

[0005] 1. During the gluing process of special-shaped screens, especially curved or flexible screens, the special-shaped parts are not in the same plane as the rest of the screen, which can easily lead to uneven or abnormal gluing.

[0006] 2. Screens in the consumer electronics field are often used in a vibrating environment, which makes the delamination rate higher than that of large screens. Among them, due to the above-mentioned gluing problem, the delamination rate of special-shaped screens is more obvious than that of ordinary consumer electronics screens. Summary of the Invention

[0007] The present application provides a method, system and equipment for designing and optimizing the coating parameters of optical adhesives, which are used to design and optimize the coating parameters in a targeted manner based on different requirements, especially the production requirements of curved screen panels, so as to improve the quality of the final product.

[0008] In the first aspect, the present application discloses a method for designing coating parameters of optical adhesive, including: a material selection and pretreatment step, which is used to select suitable materials based on the input demand type and pretreat the materials; a viscosity dynamic control step, which is used to dynamically adjust the viscosity of the material; a coating method selection step, which is used to select a suitable coating method based on the material with adjusted viscosity; a coating thickness design step, which is used to preset the coating thickness based on the selected coating method to achieve the best coating effect; a curing parameter optimization step, which is used to cure the coated product and improve its performance; wherein, the material selection and pretreatment steps include at least a surfactant addition operation, which is used to improve the wettability of the adhesive on the curved surface, reduce the edge contact angle, and reduce the risk of edge shrinkage; the coating method selection step includes at least a preset coating trajectory operation, which is used to reduce material waste.

[0009] In the second aspect, the present application discloses a coating parameter design optimization system for implementing the above-mentioned coating parameter design method, including: a material selection and preprocessing module, which is used to select suitable materials based on the input demand type and preprocess the materials; a viscosity dynamic control module, which is used to dynamically adjust the viscosity of the material; a coating path planning module, which is used to select a suitable coating method based on the material with adjusted viscosity; a UV light control and thickness calibration module, which is used to preset the coating thickness based on the selected coating method to achieve the best coating effect; a curing and interface strengthening module, which is used to cure the coated product and improve its performance; a defect detection and feedback module, which is used to collect key data of at least one of the material selection and preprocessing module, the viscosity dynamic control module, the coating path planning module, the UV light control and thickness calibration module, and the curing and interface strengthening module, and optimize the parameter settings according to the defect detection results, and feed back to the corresponding steps.

[0010] On the third aspect, the present application discloses a glue coating parameter design optimization device, which is used to implement the above-mentioned glue coating parameter design method and / or includes the above-mentioned glue coating parameter design optimization system, including: a plasma cleaning machine, a high-precision glue dispensing machine, an adjustable wavelength UV-LED light source, a UV curing furnace, a gradient heating oven, an automatic optical detector, and an ultrasonic flaw detector connected in sequence; used to process the substrate through the above-mentioned equipment in sequence to complete the processing.

[0011] Through the above technical solution, this application can achieve the following technical effects:

[0012] Adding hollow microspheres to the substrate reduces the overall density (reducing weight by 15%) while absorbing vibration stress through compression deformation of the microspheres, thereby improving the impact resistance of the vehicle display (the existing adhesive layer has a debonding rate of up to 8% under vibration conditions).

[0013] Active surface tension regulation: Adding light-responsive surfactants (such as azobenzene derivatives) to the glue, locally reducing the surface tension through ultraviolet light irradiation, and combining with the preset coating trajectory to achieve asymmetric flow, which is suitable for lamination of special-shaped substrates (such as curved screens).

[0014] Gradient thickness coating: Using a multi-channel coating head, a high modulus adhesive layer is applied to the edge area of the substrate, and a low modulus adhesive layer is applied to the center area to alleviate the edge mura problem caused by curing shrinkage.

[0015] Dynamic path planning reduces production losses and improves production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0017] Figure 1 A flow chart of a method for designing and optimizing coating parameters of optical adhesives according to any embodiment of the present application;

[0018] Figure 2 Schematic diagram of a system for designing and optimizing optical adhesive coating parameters according to any embodiment of the present application;

[0019] Figure 3 Schematic diagram of optical adhesive coating parameter design equipment for any embodiment of the present application.

[0020] The realization of the objectives, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0022] In addition, the descriptions of "first", "second", etc. in this application are for descriptive purposes only and should not be understood as indicating or implying their relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the fact that they can be implemented by ordinary technicians in this field. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0023] like Figure 1 As shown, this application discloses a method for designing optical adhesive coating parameters, which is used to optimize the optical adhesive coating process during the production of curved screens to achieve more efficient and stable curved screen production. Specifically, it includes the following steps and operations:

[0024] The material selection and pre-processing step 101 is used to select appropriate materials based on the input requirement type and pre-process the materials.

[0025] In this step, after receiving the design requirements from the outside (R&D personnel), the following steps can be implemented according to the requirements to complete the substrate customization and parameter adjustment based on the requirements.

[0026] In any embodiment, the material selection and pre-processing step 101 may perform the following specific operations:

[0027] Substrate matching: According to the curvature radius of the curved screen (R < 5mm), select bisphenol A epoxy acrylate and polyurethane acrylate in a 4:1 mixture to ensure the optical matching of the adhesive layer and the glass substrate.

[0028] Surfactant addition: Add 0.3% fluorocarbon photoresponsive surfactant (such as FS-3100) and mix in a high-speed shear disperser for 15 minutes to reduce the surface tension from 32 mN / m to 25 mN / m, and the edge contact angle to <10°. The addition of surfactant can reduce the surface tension and reduce and control the edge contact angle, which can better avoid curved screens in the production process.

[0029] Pre-embedded hollow glass microspheres: Borosilicate microspheres with a diameter of 5-20μm (10μm in this example) and a wall thickness of 1-2μm (2μm in this example) are evenly dispersed using ultrasonic dispersion (40 kHz). CT scanning verifies a porosity of ≤0.5%. The microspheres are filled with nitrogen, which expands during curing to compensate for contraction stress. Hollow glass microspheres are a readily available basic material. Pre-embedding hollow glass microspheres reduces substrate density while also improving the screen's impact resistance by absorbing vibration stress through compression and deformation. Compared to conventional screens, curved screens require greater impact resistance due to their curved structure.

[0030] Substrate treatment: Plasma cleaning reduces the substrate surface energy to >72 mN / m and the contact angle from 75° to 5°. Ellipsometer analysis verifies that there is no residual hydrocarbon on the surface.

[0031] After completing the material selection and pretreatment step 101, the substrate can achieve the following performance effects:

[0032] The surface wettability is improved by 40%, and the risk of shrinkage is reduced to 0.5%;

[0033] The interface shear strength reaches 18 MPa (the ordinary adhesive layer is only 8 MPa).

[0034] The viscosity dynamic control step 102 is used to dynamically adjust the viscosity of the material so that the viscosity of the material better meets the special requirements of curved screen production.

[0035] After the material selection and pre-processing step 101 is completed, the current parameters of the substrate are input as input data to the viscosity dynamic control step 102 , and further viscosity adjustment can be performed through the specific operations of the viscosity dynamic control step 102 .

[0036] In any embodiment of the present application, the following operations can be achieved through the viscosity dynamic control step 102:

[0037] Thermal control: The hot air circulation system controls the glue liquid temperature at 30±0.5°C, reducing the initial viscosity to the target value of 800±50 mPa·s, meeting the needs of high-precision dispensing.

[0038] Diluent compensation: If the viscosity deviation is greater than 10%, start the precision pump to inject 1% PGMEA diluent and simultaneously monitor the rotational rheometer data to ensure that the dynamic adjustment response time is ≤ 2 seconds.

[0039] Defect feedback: When the online infrared thermal imager detects a local temperature fluctuation greater than 1°C, the temperature compensation program is triggered and recorded in the database as an input parameter for subsequent process optimization.

[0040] Through the above-mentioned viscosity dynamic control step 102, the following substrate performance improvement effects can be achieved:

[0041] The viscosity fluctuation CV value was reduced from 15% to 5%;

[0042] Coating uniformity is improved to 98%.

[0043] The coating method selection step 103 is used to select a suitable coating method based on the material with adjusted viscosity, thereby reducing coating loss and improving coating uniformity.

[0044] After completing the viscosity dynamic control step 102, the material parameters are input as input parameters into the coating method selection step 103. In any embodiment of the present application, the coating method selection step 103 can implement the following operations.

[0045] Equipment adaptation: A non-contact piezoelectric jet dispensing machine is selected to adapt to the changes in the curvature radius of the curved screen.

[0046] Preset coating trajectory: Generate a spiral progressive coating path based on the CAD model, avoid the camera opening area, and use the machine vision system for real-time deviation correction with a positioning accuracy of ±2μm.

[0047] Dynamic Adjustment: If a trajectory deviation >5μm is detected, a path replanning algorithm (A* and Dijkstra hybrid optimization) is automatically triggered, with adjustment time less than 30 seconds. This dynamic adjustment during the implementation process can avoid implementation errors in the initially planned path and further improve coating stability.

[0048] By selecting the coating method in step 103, the material can achieve the following performance optimization after coating:

[0049] Material waste rate reduced from 20% to 3%;

[0050] The coating yield of complex structures (such as openings and concave and convex surfaces) reaches 99.5%.

[0051] The coating thickness design step 104 is used to preset the coating thickness based on the selected coating method to achieve the best coating effect.

[0052] Inputting the parameter information after completing the coating method selection step 103 into the coating thickness design step can achieve the following operations:

[0053] Global thickness calculation: The target thickness is set to 50 ± 2 μm according to the optical refractive index matching formula (n_glue = √(n_substrate × n_cover)) and monitored online using a laser interferometer.

[0054] Local irradiation: Irradiate the curvature mutation area (R < 1 mm) with a 405 nm UV-LED light source to activate the photoresponse agent, causing a 15% instantaneous reduction in surface tension and controlling the adhesive layer thickness fluctuation to ± 1 μm. Activating the photoresponse agent in the curvature mutation area reduces surface tension and allows the adhesive layer to spread evenly.

[0055] Microsphere expansion compensation: During curing, the microspheres expand due to heat, offsetting the shrinkage stress of the adhesive layer and improving thickness uniformity by 40%. Through microsphere expansion compensation, while ensuring the above beneficial effects of the microspheres, it can also avoid uneven material thickness caused by microsphere expansion.

[0056] After the coating thickness design step 104, the coating operation details can be further optimized to achieve the following performance parameter optimization:

[0057] The thickness deviation of the curvature mutation area is less than ±1μm;

[0058] The incidence of Newton ring defects is reduced to 0.1%.

[0059] The curing parameter optimization step 105 is used to cure the coated product and improve its performance.

[0060] In any embodiment of the present application, after the parameter design of the above steps 101-104, the product parameters are input into the curing parameter optimization step 105, so that further design of the curing operation can be achieved.

[0061] In the curing parameter optimization step 105 , curing operation design is performed by adopting a segmented curing method, which can further improve the curing efficiency. The specific implementation steps are as follows.

[0062] Pre-curing: 365nm UV light source locks the glue layer shape to prevent flow deformation;

[0063] Main curing: 395nm UV light source completes cross-linking, and synchronous gradient heating reduces internal stress.

[0064] Interface strengthening: CTBN toughening agent forms an interpenetrating network structure, the interface shear strength is increased to 20MPa, and the bending life is greater than 200,000 times.

[0065] Yellowing inhibition: Use low yellowing photoinitiator (TPO-L and 819 compound), Δb* value <0.5 (CIE Lab standard).

[0066] By optimizing the curing operation in step 105 using the curing parameters, the following performance improvements can be achieved:

[0067] The curing time is shortened to 70 seconds (120 seconds for traditional process);

[0068] The interface bonding strength is increased by 125%.

[0069] The defect detection and feedback step 106 is used to collect data from each of the above steps and further adjust and optimize various parameters according to the actual defect situation to improve the stability of the above method.

[0070] Through the above-mentioned defect feedback and data aggregation of each operation in other steps, the defect detection and feedback step 106 can complete the analysis of the defect generation according to the conditions and parameters of the defect feedback, and based on the analysis results, correct the data feedback to the input parameter set of each step, thereby optimizing the subsequent design process and further reducing the probability of defect generation.

[0071] In any embodiment of the present application, the defect detection and feedback step 106 includes:

[0072] Multimodal detection;

[0073] Based on AOI system: 5μm resolution detection of bubbles and fisheyes, classification accuracy>99%;

[0074] Based on ultrasonic flaw detection equipment: 10 MHz probe identifies microsphere breakage or interface debonding.

[0075] Use AI tools for root cause analysis: Build a defect-parameter correlation matrix and predict the optimal parameter combination using the LSTM model.

[0076] Dynamic feedback: If the edge bubble density is detected to be greater than 0.1 / cm², the coating speed will be automatically optimized and the pre-curing energy will be increased, and the information will be updated to the MES system.

[0077] By implementing the defect detection and feedback step 106, the design method can be closed-loop and the design stability can be continuously improved. At the same time, because the detection results are monitored and analyzed in real time, feedback can be obtained in a timely manner, thereby quickly correcting errors.

[0078] By implementing the defect detection and feedback step 106, the following functions can be achieved:

[0079] Defect closed-loop response time < 5 minutes;

[0080] The first coating yield rate increased from 85% to 93%.

[0081] At this point, in any embodiment of the present application, by introducing the above-mentioned optical glue coating parameter design method, it is possible to complete targeted optimization of various parameters based on the characteristics and requirements of the curved screen before the optical glue coating operation is carried out, and the parameters can be gradually further optimized as the operation progresses, thereby greatly improving the efficiency and stability of the optical glue coating operation in the curved screen usage scenario.

[0082] like Figure 2As shown, in any embodiment of the present application, a system for designing and optimizing glue coating parameters is disclosed, which can implement the above-mentioned glue coating parameter design method. It includes:

[0083] The material selection and preprocessing module 111 is used to select appropriate materials based on the input demand type and preprocess the materials, executing the operations of the material selection and preprocessing step 101; this module includes:

[0084] The substrate matching unit 1111 is used to confirm the type and ratio of the substrate, and in response to the external input of the curved screen demand, perform substrate matching and preparation, and perform calculations according to the substrate matching operation and complete the operation.

[0085] The glue premixing unit 1112 is used to add hollow glass microspheres to the substrate, is connected to the substrate matching unit signal, and performs surfactant addition operations and hollow glass microsphere pre-embedding operations after receiving data from the substrate matching unit.

[0086] The substrate processing unit 1113 is used to clean the substrate and is connected to the glue premixing unit by signal. After receiving the data signal from the glue premixing unit, it performs the substrate processing operation.

[0087] The viscosity dynamic control module 112 is used to dynamically adjust the viscosity of the material, receives the signal from the material selection and preprocessing module 111 and performs the viscosity dynamic control step 102 based on the signal. This module includes:

[0088] The thermal control unit 1121 is connected to the substrate processing unit 1113 by signal, controls the viscosity and adjusts the heat, and performs thermal control and regulation operations;

[0089] The diluent injection unit 1122 is connected to the thermal control unit 1121 via a signal, and is used to inject diluent into the substrate to complete the diluent compensation operation.

[0090] The defect feedback unit 1123 identifies the defect information, performs defect feedback operations, and stores the defect information in a memory for feeding back to the defect detection and feedback module 116 .

[0091] The coating path planning module 113 receives information from the viscosity dynamic control module 112 and is used to select an appropriate coating method based on the material with adjusted viscosity. This module includes:

[0092] The trajectory generating unit 1131 receives information from the diluent injecting unit 1122, performs device adaptation and preset coating trajectory operations, and generates a preset coating trajectory;

[0093] The visual positioning unit 1132 receives information from the trajectory generation unit 1131, performs dynamic adjustment operations, performs real-time positioning, and adjusts the offset.

[0094] The UV light control and thickness calibration module 114 receives information from the coating path planning module 113 and presets the coating thickness based on the selected coating method to achieve the best coating effect. This module includes:

[0095] The local UV irradiation unit 1141 receives information from the thickness monitoring unit 1142 and the visual positioning unit 1132, performs local irradiation operation and microsphere expansion compensation, and locally irradiates the substrate;

[0096] The thickness monitoring unit 1142 performs global thickness calculation, monitors the coating thickness and outputs adjustment instructions to the local UV irradiation unit 1141.

[0097] The curing and interface strengthening module 115 receives information from the UV light control and thickness calibration module 114, cures the coated product, and improves its performance. This module includes:

[0098] The segmented curing unit 1151 performs pre-curing and main curing operations for segmented curing of the substrate;

[0099] The interface strengthening unit 1152 performs interface strengthening and yellowing suppression operations to strengthen the bonding force between the colloid and the interface.

[0100] The defect detection and feedback module 116 is used to collect key data from at least one of the material selection and pretreatment module, the viscosity dynamic control module, the coating path planning module, the UV light control and thickness calibration module, and the curing and interface strengthening module, and optimize the parameter settings based on the defect detection results and feedback to the corresponding modules and steps. This module includes the following for performing multimodal detection operations:

[0101] Based on AOI system 1161, it can detect bubbles and fisheyes with a resolution of 5μm and a classification accuracy of >99%;

[0102] Based on the ultrasonic flaw detection equipment 1162, it is possible to identify microsphere breakage or interface debonding using a 10 MHz probe.

[0103] AI unit 1163 can perform root cause analysis: establish a defect-parameter correlation matrix, such as bubble ↔ coating speed too fast / insufficient UV energy, and predict the optimal parameter combination through the LSTM model.

[0104] Dynamic feedback unit 1164: If the edge bubble density is detected to be greater than 0.1 / cm², the coating speed is automatically optimized, increasing or decreasing the speed, and increasing the pre-curing energy. For example, an adjustment is usually made from 28 to 32 mJ / cm², and the data is updated to the MES system.

[0105] Through the coordination between the above modules and their various units, a complete and cyclical negative feedback mechanism can be established in the design optimization system, so that parameter design can be carried out during the application of optical glue, adapting to the special application scenarios of curved screens and achieving more efficient curved screen production.

[0106] In any embodiment of the present application, the present application also discloses a method such as Figure 3 The gluing parameter design optimization device shown includes:

[0107] The material pretreatment and dispersion equipment 121 includes a plasma cleaner, a high-speed shear disperser, an ultrasonic dispersion system, and a precision diluent injection pump connected in sequence. The output end of the precision diluent injection pump is reconnected to the plasma cleaner to complete a cycle of processing operations. During operation, the substrate enters the plasma cleaner, passes through various devices, and returns to the plasma cleaner to complete the material selection and pretreatment step 101.

[0108] The viscosity dynamic control device 122 includes a hot air circulation temperature control system and a rotational rheometer connected in sequence. The substrate output by the material pretreatment and dispersion device 121 is added to the hot air circulation temperature control system to achieve the viscosity dynamic control step 102.

[0109] The coating path planning and execution device 123 includes a machine vision positioning system, dynamic path planning software, a high-precision dispensing machine, and a laser interferometer connected in sequence to perform the coating method selection step 103 operation, wherein the material output by the viscosity dynamic control device 122 enters the high-precision dispensing machine, and the high-precision dispensing machine can operate based on the path output by the machine vision positioning system and the dynamic path planning software.

[0110] UV light control and thickness calibration equipment 124, including a wavelength-adjustable UV-LED light source and a UV curing oven connected in sequence, UV-cures the material output by the coating path planning and execution equipment 123 and controls the light exposure to achieve the coating thickness design step 104;

[0111] Curing and interface strengthening equipment 125, including a gradient heating oven and an interface shear strength tester, is used to verify the microsphere-colloid interface bonding strength and implement the curing parameter optimization step 105;

[0112] Defect detection and feedback equipment 126, including an automated optical inspection (AOI) instrument, an ultrasonic flaw detector, an X-ray micro-CT scanner, and an industrial AI platform, is used to perform root cause analysis and parameter optimization based on the data and parameters of all these devices. The industrial AI platform collects the parameters of all these devices and analyzes the parameters corresponding to defects and good products using the AI system, thereby avoiding the use of parameters corresponding to defective products in subsequent steps. Finally, it generates a defect data packet and feeds it back to the aforementioned devices to optimize the parameters, thereby further optimizing the gluing process and improving gluing efficiency.

[0113] The above-mentioned method, system and device can take into account the particularity of curved or special-shaped screens during the design of optical adhesive coating for curved or special-shaped screens, thereby achieving the following:

[0114] Innovation on the material side: Photoresponsive agents are used to impart dynamic properties to the adhesive, breaking through the limitations of traditional static materials;

[0115] Process-side collaboration: combining UV light control with coating paths to achieve a closed loop of "materials-equipment-algorithms";

[0116] Prevent defects early: Actively control surface tension during the coating phase, reducing the need for subsequent post-curing repairs.

[0117] The above description is merely an optional embodiment of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made using the contents of the present application specification and drawings under the inventive concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for designing coating parameters of optical adhesive, characterized in that: include: a material selection and preprocessing step, responding to the input requirement information and completing material selection based on the requirement information; The viscosity dynamic control step responds to the information output from the material selection and pre-processing steps to complete the viscosity control information design; The coating method selection step responds to the information output by the viscosity dynamic control step to complete the coating information design; The coating thickness design step responds to the information output by the coating method selection step to complete the coating thickness design and monitoring; a curing parameter optimization step, in response to the information outputted from the coating thickness design step, curing the coated product; in, The material selection and pretreatment steps include at least the addition of a surfactant to adjust and design the surface parameters of the substrate; The surfactant includes at least a fluorocarbon light-responsive surfactant at a concentration of 0.3%; After adding the surfactant, the surfactant and the substrate are mixed; The coating mode selection step at least includes a coating trajectory preset operation, and responds to the information output by the viscosity dynamic control step to complete the coating trajectory preset action; The material selection and pretreatment steps also include pre-embedding hollow glass microspheres, selecting appropriate glass microspheres and adding them into the substrate. The diameter of the hollow glass microspheres is not less than 5 microns and not more than 20 microns, and the wall thickness is 1-2 microns.

2. The method for designing glue coating parameters according to claim 1, characterized in that: The coating thickness designing step at least includes a local irradiation operation, and in response to the information outputted by the coating mode selecting step, the substrate is locally irradiated.

3. The method for designing glue coating parameters according to claim 1 or 2, characterized in that: The method further comprises: The defect monitoring and feedback step monitors the quantitative data of all steps, records the key data of at least one of the material selection and pretreatment step, the viscosity dynamic control step, the coating method selection step, the coating thickness design step, and the curing parameter optimization step, and optimizes the parameter settings based on the defect detection results and feeds back to the corresponding step.

4. A glue coating parameter design optimization system, used to implement the glue coating parameter design method according to any one of claims 1 to 3, characterized in that: include: Material selection and pretreatment module, which selects appropriate materials based on the input demand type and pre-processes the materials; The material selection and pre-processing module includes a glue pre-mixing unit, which includes at least the following operations: A surfactant addition operation, wherein the surfactant includes at least a fluorocarbon photoresponsive surfactant at a concentration of 0.3%, After adding the surfactant, the surfactant and the substrate are mixed; The viscosity dynamic control module responds to the information output by the material selection and pre-processing modules and dynamically adjusts the viscosity of the material; The coating path planning module responds to the information output by the viscosity dynamic control module and selects the appropriate coating method based on the material with adjusted viscosity; It also includes the operation of pre-embedding hollow glass microspheres, selecting appropriate glass microspheres and adding them into the substrate, wherein the diameter of the hollow glass microspheres is not less than 5 microns and not more than 20 microns, and the wall thickness is 1-2 microns; The UV light control and thickness calibration module responds to the information output by the coating path planning module and presets the coating thickness based on the selected coating method to achieve the best coating effect; The curing and interface strengthening module responds to the information output by the UV light control and thickness calibration module to cure the coated product and improve its performance; The defect detection and feedback module collects key data from at least one of the material selection and pretreatment module, viscosity dynamic control module, coating path planning module, UV light control and thickness calibration module, and curing and interface strengthening module, optimizes parameter settings based on the defect detection results, and feeds back to the corresponding module.

5. The gluing parameter design optimization system according to claim 4, characterized in that: The material selection and pretreatment module includes: The glue premixing unit completes the glass microsphere parameter design and adds the hollow glass microspheres into the substrate; The substrate processing unit cleans the substrate.

6. The gluing parameter design optimization system according to claim 5, characterized in that: The viscosity dynamic control module includes: The thermal control unit adjusts the heat and substrate viscosity in response to data output from the material selection and pre-processing modules; The diluent injection unit injects the diluent into the substrate.

7. A device for designing and optimizing glue coating parameters, used to implement the method for designing glue coating parameters according to any one of claims 1 to 3 and / or comprising the system for designing and optimizing glue coating parameters according to any one of claims 4 to 6, characterized in that: Includes sequential connections: Plasma cleaning machine, high-precision dispensing machine, adjustable wavelength UV-LED light source, UV curing oven, gradient heating oven, ultrasonic flaw detector and automatic optical inspection instrument; The device further comprises: Material pretreatment and dispersion equipment, including a high-speed shear disperser and an ultrasonic dispersion system connected in sequence, including the operation of pre-embedding hollow glass microspheres, selecting appropriate glass microspheres and adding them to the substrate. The diameter of the hollow glass microspheres is not less than 5 microns and not more than 20 microns, and the wall thickness is 1-2 microns; The high-speed shear disperser is used to mix the surfactant with the substrate after adding a 0.3% fluorocarbon photoresponsive surfactant; the viscosity dynamic control equipment includes a rotational rheometer, a hot air circulation temperature control system and a precision diluent injection pump; Coating path planning and execution equipment, including machine vision positioning system and dynamic path planning software equipment; UV light control and thickness calibration equipment, including laser interferometers and X-ray micro-CT scanners; Curing and interface strengthening equipment, including interface shear strength testers; Defect detection and feedback equipment, including industrial AI platforms.

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