Multi-layer waterproof bright-surface thermosensitive adhesive label and production process thereof

Abstract

The invention relates to the technical field of self-adhesive labels, in particular to a multi-layer waterproof bright-surface thermosensitive self-adhesive label and a production process thereof, and the multi-layer waterproof bright-surface thermosensitive self-adhesive label comprises a bright-surface waterproof layer, a thermosensitive layer, a pressure-sensitive adhesive layer and bottom paper which are sequentially stacked from top to bottom; the bright waterproof layer is made of polyethylene glycol terephthalate, the surface of the bright waterproof layer is subjected to plasma treatment to form a micro-nano coarse structure, and a layer of fluorosilane coupling agent is coated on the surface of the bright waterproof layer; the heat-sensitive layer is made of a nanoscale heat-sensitive material and mainly comprises colorless dye, a color developing agent and nano silicon dioxide; the particle size of the nano silicon dioxide is 10-50nm, and the content of the nano silicon dioxide is 5-20%; the thermosensitive characteristic curve is optimized through a neural network algorithm; according to the invention, polyethylene glycol terephthalate is adopted as a bright waterproof layer, and plasma treatment and fluorosilane coupling agent coating are carried out, so that the hydrophobicity and scratch resistance of the surface are improved; a micro-nano coarse structure formed by plasma treatment is combined with the fluorosilane coupling agent, so that the waterproof and wear-resisting properties of the label are remarkably improved.

Description

Technical Field

[0001] The invention relates to the technical field of self-adhesive labels, in particular to a multi-layer waterproof glossy surface heat-sensitive self-adhesive label and a production process thereof. Background Art

[0002] Self-adhesive labels are widely used for packaging and labeling of various products, playing a particularly important role in industries such as logistics, medicine, and food. However, traditional self-adhesive labels have several drawbacks, such as poor waterproofing, poor abrasion resistance, slow color development, and a short shelf life. These issues severely impact the lifespan and effectiveness of labels, particularly in high humidity or harsh environments, where labels can easily lose their stickiness or become blurred. To overcome these shortcomings, research and development of new self-adhesive label materials and production processes are ongoing. For example, some progress has been made by adding a waterproof coating to the label surface, using high-performance adhesives, and improving heat-sensitive materials. However, these improvements have mostly focused on a single aspect, lacking systematicity and integrity, making it difficult to fully enhance the overall performance of the label.

[0003] In recent years, with the development of materials science and intelligent algorithms, it has become possible to design and manufacture high-performance self-adhesive labels using multi-layer composite materials and optimization algorithms. By rationally designing the structure and composition of each layer of material and using optimization algorithms to fine-tune the production process, the comprehensive performance of the label, such as waterproofness, wear resistance, color development speed and shelf life, can be significantly improved. Therefore, to address the above problems, a multi-layer waterproof glossy thermal self-adhesive label and its production process are proposed. Summary of the Invention

[0004] The object of the present invention is to provide a multi-layer waterproof glossy surface heat-sensitive self-adhesive label and a production process thereof, so as to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A multi-layer waterproof glossy heat-sensitive self-adhesive label and its production process, comprising a glossy waterproof layer, a heat-sensitive layer, a pressure-sensitive adhesive layer and a base paper stacked in sequence from top to bottom;

[0007] The glossy waterproof layer is made of polyethylene terephthalate (PET), the surface of which is plasma-treated to form a micro-nano rough structure and coated with a layer of fluorosilane coupling agent (such as perfluorooctyltriethoxysilane or perfluorodecyltriethoxysilane) to improve hydrophobicity and scratch resistance. The plasma treatment parameters are: power 100-300W, treatment time 1-5 minutes, gas flow rate 10-50sccm. The fluorosilane coupling agent is applied by dip coating or spray coating, with a coating thickness of 50-200nm, and a curing temperature of 120-180°C for 10-30 minutes.

[0008] The thermal layer is made of nanoscale thermally sensitive materials, the main components of which are colorless dyes (such as fluorocarbons or spiropyrans), color developers (such as bisphenol A or phenolphthalein), and nano-silica. The nano-silica has a particle size of 10-50nm and a content of 5-20%, which is used to improve the thermal stability and wear resistance of the thermal layer. The thermal characteristic curve is optimized using a neural network algorithm to achieve faster color development, higher sensitivity, and longer shelf life.

[0009] The pressure-sensitive adhesive layer is made of an acrylate copolymer, primarily composed of butyl acrylate, hydroxyethyl acrylate, and acrylic acid. By adjusting the monomer ratio and polymerization conditions, pressure-sensitive adhesives with varying adhesion, cohesion, and peel strengths are obtained. These adhesion, cohesion, and peel strengths are optimized using a particle swarm optimization (PSO) algorithm to adapt to the demands of different temperatures, humidity levels, and substrate surfaces. The optimization process involves first determining the target ranges for adhesion, cohesion, and peel strength, and then using the PSO algorithm to optimize the acrylate copolymer formulation.

[0010] The base paper is made of degradable polylactic acid (PLA) and coated with a silicone oil release layer on the surface; the thickness of the PLA base paper is 50μm, the thickness of the silicone oil release layer is 1-3μm, and the coating method is roller coating or spraying.

[0011] Preferably, the surface energy of the PET glossy waterproof layer is less than 20 mN / m, the rolling angle of water droplets on the surface is less than 10°, and the wear resistance reaches more than 4 hours. The specific plasma treatment parameters are: power 150 W, treatment time 3 minutes, gas flow rate 30 sccm, fluorosilane coupling agent coating thickness 100 nm, curing temperature 150°C, and curing time 20 minutes.

[0012] Preferably, the thermosensitive characteristic curve of the nanoscale thermosensitive material has a linear response in the range of 50-100°C, a color development speed of less than 0.5 seconds, and a storage time of more than 2 years under the conditions of 70°C and 50% RH. Specifically, the nano-silica content is 10%, the colorless dye content is 70%, and the color developer content is 20%.

[0013] Preferably, the acrylate copolymer adhesive has stable adhesion in the temperature range of -20°C to 80°C, the adhesion is 12-15N / 25mm at 23°C and 50% RH, the cohesion is less than 1mm at 23°C and 50% RH, and the peel strength is 6-8N / 25mm at 23°C and 50% RH. The specific optimized formula is 55% butyl acrylate, 35% hydroxyethyl acrylate, and 10% acrylic acid.

[0014] Preferably, the degradation period of the degradable polylactic acid (PLA) base paper under industrial composting conditions (temperature 60±2° C., humidity 55-65%) is less than 2 months, and the degradation products are harmless to the environment.

[0015] A production process for a multi-layer waterproof glossy thermal self-adhesive label comprises the following steps:

[0016] Step 1: Prepare a PET glossy waterproof layer by co-extrusion casting method, and perform plasma treatment and fluorosilane coupling agent coating on its surface;

[0017] Step 2: Prepare nanoscale thermosensitive material coating using solvent casting method and optimize its thermosensitive characteristic curve using neural network algorithm;

[0018] Step 3: Apply the acrylate copolymer adhesive to the heat-sensitive layer using a doctor blade coating method, and optimize its formulation using a particle swarm optimization algorithm;

[0019] Step 4: Composite the degradable polylactic acid (PLA) backing paper with the adhesive layer using a composite coating method, and apply a silicone oil release layer on the surface of the backing paper;

[0020] Step 5: Use a laser slitting machine to cut the composite material into labels of the required size. The laser cutting parameters are: power 50-100W, frequency 10-50kHz, and cutting speed 1-5m / s.

[0021] Preferably, the plasma treatment uses oxygen, argon or nitrogen as the treatment gas, the treatment pressure is 0.1-1 Pa, specifically 0.5 Pa, the treatment time is 3 minutes, and the gas flow rate is 20 sccm.

[0022] Preferably, an improved neural network algorithm is used to optimize the thermal characteristic curve of the nanoscale thermosensitive material, and the specific optimization steps include:

[0023] Step 1: First, the colorimetric data of thermosensitive materials were collected under different temperature (20-120°C) and humidity (20-80% RH) conditions to construct a multivariate training dataset containing temperature, humidity, and colorimetric data.

[0024] Step 2: Use the multi-layer perceptron (MLP) neural network model to train the dataset, setting the input layer to temperature and humidity, the output layer to colorimetry, the number of hidden layers to 3, the number of neurons in each layer to 50, the activation function to ReLU, the loss function to mean square error (MSE), the optimizer to Adam, the learning rate to 0.001, and the number of training rounds to 500;

[0025] Step 3: Use an optimized learning rate adjustment algorithm (such as RMSprop or Adadelta) to further optimize the model training process. The final optimized function is:

[0026] y=0.015x1+0.025x2+x0.12x1 x2+0.45

[0027] Among them, y is color rendering, x1 is temperature, and x2 is humidity.

[0028] Preferably, when the particle swarm optimization algorithm optimizes the formula of the acrylate copolymer adhesive, the population size is 100, the number of iterations is 300, the inertia weight is 0.7, the learning factor is 1.7, and an adaptive inertia weight adjustment algorithm is used to improve the convergence speed and optimization effect. The final optimized formula is 58% butyl acrylate, 32% hydroxyethyl acrylate, and 10% acrylic acid.

[0029] Preferably, the laser slitting machine uses a CO2 laser with a wavelength of 10.6 μm, a cutting accuracy of ±0.05 mm, a power of 75 W, a frequency of 30 kHz, and a cutting speed of 3 m / s, and further adopts a real-time monitoring and feedback adjustment system to ensure cutting accuracy and consistency.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. In the present invention, polyethylene terephthalate (PET) is used as a glossy waterproof layer, and plasma treatment and fluorosilane coupling agent coating are used to improve the surface hydrophobicity and scratch resistance. The combination of the micro-nano rough structure formed by plasma treatment and the fluorosilane coupling agent makes the label surface energy less than 20mN / m, the water droplet rolling angle less than 10°, and the wear resistance reaches more than 4H, thereby significantly improving the waterproof and wear resistance of the label.

[0032] 2. In the present invention, the thermal sensitivity characteristic curve is optimized through a neural network algorithm, so that the color development speed is less than 0.5 seconds, and the storage time at 70°C and 50% RH is greater than 2 years; the specific optimization process includes constructing a multivariate training data set, using a multilayer perceptron (MLP) neural network model for training, and adopting an optimized learning rate adjustment algorithm to improve the color development speed and storage time.

[0033] 3. In the present invention, the formulation is optimized through the particle swarm optimization algorithm (PSO) to adapt to the pasting requirements of different temperatures, humidity and substrate surfaces; the optimized adhesive has stable adhesion within the temperature range of -20°C to 80°C, with specific parameters of adhesion of 12-15N / 25mm, cohesion less than 1mm, and peel force of 6-8N / 25mm, thus ensuring that the label can maintain good adhesion in various environments.

[0034] 4. In the present invention, the production process adopts a co-extrusion casting method to prepare a PET glossy waterproof layer, a solvent casting method to prepare a nano-scale thermosensitive material coating, a doctor blade coating method to coat an acrylate copolymer adhesive on the thermosensitive layer, a composite coating method to composite the PLA base paper and the adhesive layer, and a laser slitting machine to cut the composite material into labels of the required size. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0036] In the figure: 1. Glossy waterproof layer; 2. Heat-sensitive layer; 3. Pressure-sensitive adhesive layer; 4. Base paper. DETAILED DESCRIPTION

[0037] See also Figure 1 , the present invention provides a technical solution:

[0038] A multi-layer waterproof glossy heat-sensitive self-adhesive label, comprising a glossy waterproof layer 1, a heat-sensitive layer 2, a pressure-sensitive adhesive layer 3 and a backing paper 4 stacked in sequence from top to bottom;

[0039] The glossy waterproof layer 1 is made of polyethylene terephthalate (PET), the surface of which is plasma-treated to form a micro-nano rough structure and coated with a layer of fluorosilane coupling agent (such as perfluorooctyltriethoxysilane or perfluorodecyltriethoxysilane) to improve hydrophobicity and scratch resistance. The plasma treatment parameters are: power 100-300W, treatment time 1-5 minutes, gas flow rate 10-50sccm; the fluorosilane coupling agent is applied by dip coating or spray coating, with a coating thickness of 50-200nm, a curing temperature of 120-180°C, and a curing time of 10-30 minutes.

[0040] The heat-sensitive layer 2 is made of a nanoscale heat-sensitive material, the main components of which are a colorless dye (such as a fluorocarbon or spiropyran), a color developer (such as bisphenol A or phenolphthalein), and nano-silicon dioxide. The nano-silicon dioxide has a particle size of 10-50 nm and a content of 5-20%, which is used to improve the thermal stability and wear resistance of the heat-sensitive layer. The heat-sensitive characteristic curve is optimized using a neural network algorithm to achieve faster color development, higher sensitivity, and longer shelf life.

[0041] The pressure-sensitive adhesive layer 3 is made of an acrylate copolymer, primarily composed of butyl acrylate, hydroxyethyl acrylate, and acrylic acid. By adjusting the monomer ratio and polymerization conditions, pressure-sensitive adhesives with varying adhesion, cohesion, and peel strengths are obtained. Adhesion, cohesion, and peel strengths are optimized using a particle swarm optimization (PSO) algorithm to adapt to the requirements of adhesion under varying temperatures, humidity levels, and substrate surfaces. The specific optimization process involves first determining the target ranges for adhesion, cohesion, and peel strength; then optimizing the acrylate copolymer formulation using the PSO algorithm.

[0042] The base paper 4 is made of degradable polylactic acid (PLA) and coated with a silicone oil release layer on its surface; the thickness of the PLA base paper is 50 μm, the thickness of the silicone oil release layer is 1-3 μm, and the coating method is roller coating or spraying.

[0043] The structural design of the PET glossy waterproof layer, nano-scale heat-sensitive layer, acrylic copolymer pressure-sensitive adhesive layer and degradable PLA backing paper stacked from top to bottom significantly improves the label's waterproofness, wear resistance, color development speed, shelf life and environmental performance; the overall design not only improves the performance of the label, but also has environmental advantages.

[0044] The surface energy of the PET glossy waterproof layer is less than 20 mN / m, the rolling angle of water droplets on the surface is less than 10°, and the wear resistance reaches more than 4 hours. The specific plasma treatment parameters are: power 150 W, treatment time 3 minutes, gas flow rate 30 sccm, fluorosilane coupling agent coating thickness 100 nm, curing temperature 150°C, and curing time 20 minutes.

[0045] This improvement greatly enhances the waterproof and wear-resistant effects of the label in various environments, especially in high humidity and frequent contact, the label can still maintain good appearance and function.

[0046] The nanoscale thermosensitive material has a thermal characteristic curve with a linear response within the range of 50-100°C, a color development speed of less than 0.5 seconds, and a storage time of more than 2 years under the conditions of 70°C and 50% RH. Specifically, the nano-silica content is 10%, the colorless dye content is 70%, and the color developer content is 20%.

[0047] Through this optimization, the label can quickly develop color within a wide temperature range and maintain it for a long time, meeting the needs of high efficiency and durability.

[0048] The acrylate copolymer adhesive has stable adhesion within the temperature range of -20°C to 80°C, an adhesion of 12-15N / 25mm at 23°C and 50% RH, a cohesive force of less than 1mm at 23°C and 50% RH, and a peel force of 6-8N / 25mm at 23°C and 50% RH. The specific optimized formula is 55% butyl acrylate, 35% hydroxyethyl acrylate, and 10% acrylic acid.

[0049] This optimization ensures that the label can maintain good adhesion under various environmental conditions, improving its reliability and durability in use.

[0050] The degradation period of the degradable polylactic acid (PLA) base paper under industrial composting conditions (temperature 60±2° C., humidity 55-65%) is less than 2 months, and the degradation products are harmless to the environment.

[0051] This setting not only ensures the environmentally friendly disposal of the label after use, but also meets the requirements of sustainable development and reduces the negative impact on the environment.

[0052] A production process for a multi-layer waterproof glossy thermal self-adhesive label comprises the following steps:

[0053] Step 1: Prepare a PET glossy waterproof layer by co-extrusion casting method, and perform plasma treatment and fluorosilane coupling agent coating on its surface;

[0054] Step 2: Prepare nanoscale thermosensitive material coating using solvent casting method and optimize its thermosensitive characteristic curve using neural network algorithm;

[0055] Step 3: Apply the acrylate copolymer adhesive to the heat-sensitive layer using a doctor blade coating method, and optimize its formulation using a particle swarm optimization algorithm;

[0056] Step 4: Composite the degradable polylactic acid (PLA) backing paper with the adhesive layer using a composite coating method, and apply a silicone oil release layer on the surface of the backing paper;

[0057] Step 5: Use a laser slitting machine to cut the composite material into labels of the required size. The laser cutting parameters are: power 50-100W, frequency 10-50kHz, and cutting speed 1-5m / s.

[0058] This setup provides an advanced production process, preparing each layer of material through co-extrusion casting, solvent casting, doctor blade coating and composite coating methods, and using a laser slitting machine to cut into labels of the required size; neural network algorithms and particle swarm optimization algorithms are used to fine-tune the material layers and process parameters, improving the consistency and stability of the product; this process ensures high quality and consistency of the labels, meeting the requirements of large-scale production.

[0059] The plasma treatment uses oxygen, argon or nitrogen as the treatment gas, the treatment pressure is 0.1-1 Pa, specifically 0.5 Pa, the treatment time is 3 minutes, and the gas flow rate is 20 sccm.

[0060] This selection and optimization makes the surface treatment of the PET glossy waterproof layer more uniform and stable, thereby further improving the waterproofness and wear resistance of the label and ensuring the performance of the label in various environments.

[0061] An improved neural network algorithm is used to optimize the thermal characteristic curve of nanoscale thermosensitive materials. The specific optimization steps include:

[0062] Step 1: First, the colorimetric data of thermosensitive materials were collected under different temperature (20-120°C) and humidity (20-80% RH) conditions to construct a multivariate training dataset containing temperature, humidity, and colorimetric data.

[0063] Step 2: Use the multi-layer perceptron (MLP) neural network model to train the dataset, setting the input layer to temperature and humidity, the output layer to colorimetry, the number of hidden layers to 3, the number of neurons in each layer to 50, the activation function to ReLU, the loss function to mean square error (MSE), the optimizer to Adam, the learning rate to 0.001, and the number of training rounds to 500;

[0064] Step 3: Use an optimized learning rate adjustment algorithm (such as RMSprop or Adadelta) to further optimize the model training process. The final optimized function is:

[0065] y=0.015x1+0.025x2+0.12x1 x2+0.45

[0066] Among them, y is color rendering, x1 is temperature, and x2 is humidity.

[0067] Through the specific application of this optimization algorithm, the color rendering performance of thermosensitive materials under different temperature and humidity conditions has been comprehensively improved, ensuring the efficient color rendering and long-term stability of the label.

[0068] When the particle swarm optimization algorithm is used to optimize the formula of the acrylic copolymer adhesive, the population size is 100, the number of iterations is 300, the inertia weight is 0.7, the learning factor is 1.7, and an adaptive inertia weight adjustment algorithm is used to improve the convergence speed and optimization effect. The final optimized formula is 58% butyl acrylate, 32% hydroxyethyl acrylate, and 10% acrylic acid.

[0069] This optimization ensures the adhesive’s stability and efficient adhesion under various temperature and humidity conditions, improving the overall performance of the label.

[0070] The laser slitting machine uses a CO2 laser with a wavelength of 10.6μm, a cutting accuracy of ±0.05mm, a power of 75W, a frequency of 30kHz, and a cutting speed of 3m / s. It further adopts a real-time monitoring and feedback adjustment system to ensure cutting accuracy and consistency.

[0071] This setup improves the accuracy and quality of label production and meets the label quality requirements of the high-end market.

[0072] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only used to help understand the method of the present invention and its core ideas. The above is only a preferred implementation method of the present invention. It should be pointed out that due to the limitations of textual expression, there are objectively infinite specific structures. For ordinary technicians in this technical field, without departing from the principles of the present invention, they can make several improvements, modifications or changes, and can also combine the above technical features in an appropriate manner; these improvements, modifications, changes or combinations, or the direct application of the inventive concept and technical solution to other occasions without improvement, should be regarded as the scope of protection of the present invention.

Claims

1. A multi-layer waterproof glossy thermal self-adhesive label, characterized by: It comprises a bright waterproof layer (1), a heat-sensitive layer (2), a pressure-sensitive adhesive layer (3) and a base paper (4) which are stacked in sequence from top to bottom; The bright surface waterproof layer (1) is made of polyethylene terephthalate (PET), the surface of which is treated with plasma to form a micro-nano rough structure, and is coated with a layer of fluorosilane coupling agent; the plasma treatment parameters are: power 100-300W, treatment time 1-5 minutes, gas flow rate 10-50sccm; the coating method of the fluorosilane coupling agent is dip coating or spray coating, the coating thickness is 50-200nm, the curing temperature is 120-180°C, and the curing time is 10-30 minutes; The thermosensitive layer (2) is made of nano-scale thermosensitive material, the main components of which are colorless dye, developer and nano-silicon dioxide; the particle size of the nano-silicon dioxide is 10-50nm, and the content is 5-20%; the thermosensitive characteristic curve is optimized by a neural network algorithm; The pressure-sensitive adhesive layer (3) is made of an acrylate copolymer, the main components of which are butyl acrylate, hydroxyethyl acrylate and acrylic acid. By adjusting the monomer ratio and polymerization conditions, a pressure-sensitive adhesive with different adhesion, cohesion and peeling forces is obtained; the adhesion, cohesion and peeling forces are optimized by a particle swarm optimization algorithm (PSO) to meet the requirements of pasting at different temperatures, humidity and substrate surfaces; the specific optimization process is as follows: firstly, the target value range of adhesion, cohesion and peeling force is determined; then, the formula of the acrylate copolymer is optimized by using the PSO algorithm; The base paper (4) is made of degradable polylactic acid (PLA), and a silicone oil release layer is coated on its surface; the thickness of the PLA base paper is 50 μm, the thickness of the silicone oil release layer is 1-3 μm, and the coating method is roller coating or spray coating.

2. The multi-layer waterproof glossy thermal self-adhesive label according to claim 1, characterized in that: The surface energy of the PET bright surface waterproof layer is less than 20mN / m, the rolling angle of water droplets on the surface is less than 10°, the wear resistance reaches more than 4H, and the specific plasma treatment parameters are: power 150W, treatment time 3 minutes, gas flow rate 30sccm, fluorosilane coupling agent coating thickness 100nm, curing temperature 150°C, and curing time 20 minutes.

3. The multi-layer waterproof glossy thermal self-adhesive label according to claim 1, characterized in that: The thermosensitive characteristic curve of the nanoscale thermosensitive material has a linear response in the range of 50-100°C, a color development speed of less than 0.5 seconds, and a storage time of more than 2 years under the conditions of 70°C and 50% RH. Specifically, the nano-silicon dioxide content is 10%, the colorless dye content is 70%, and the color developer content is 20%.

4. The multi-layer waterproof glossy thermal self-adhesive label according to claim 1, characterized in that: The acrylate copolymer adhesive has stable adhesion within the temperature range of -20°C to 80°C, the adhesion is 12-15N / 25mm at 23°C and 50%RH, the cohesion is less than 1mm at 23°C and 50%RH, and the peeling force is 6-8N / 25mm at 23°C and 50%RH. The specific optimized formula is 55% butyl acrylate, 35% hydroxyethyl acrylate, and 10% acrylic acid.

5. The multi-layer waterproof glossy thermal self-adhesive label according to claim 1, characterized in that: The degradation period of the degradable polylactic acid (PLA) base paper under industrial composting conditions (temperature 60±2° C., humidity 55-65%) is less than 2 months, and the degradation products are harmless to the environment.

6. A production process for a multi-layer waterproof glossy thermal self-adhesive label, characterized by: The following steps are involved: Step 1: Prepare a PET glossy waterproof layer by co-extrusion casting method, and perform plasma treatment and fluorosilane coupling agent coating on its surface; Step 2: Prepare nanoscale thermosensitive material coating by solvent casting method, and optimize its thermosensitive characteristic curve by neural network algorithm; Step 3: coating the acrylate copolymer adhesive on the heat-sensitive layer by a doctor blade coating method, and optimizing its formulation by a particle swarm optimization algorithm; Step 4: Compounding the degradable polylactic acid (PLA) backing paper with the adhesive layer by a composite coating method, and coating a silicone oil release layer on the surface of the backing paper; Step 5: Use a laser slitting machine to cut the composite material into labels of the required size. The laser cutting parameters are: power 50-100W, frequency 10-50kHz, and cutting speed 1-5m / s.

7. The production process of a multi-layer waterproof glossy thermal self-adhesive label according to claim 6, characterized in that: The plasma treatment uses oxygen, argon or nitrogen as the treatment gas, the treatment pressure is 0.1-1Pa, specifically 0.5Pa, the treatment time is 3 minutes, and the gas flow rate is 20sccm.

8. The production process of a multi-layer waterproof glossy thermal self-adhesive label according to claim 6, characterized in that: The improved neural network algorithm is used to optimize the thermal characteristic curve of nanoscale thermosensitive materials. The specific optimization steps include: Step 1: First, the colorimetric data of thermosensitive materials were collected under different temperature (20-120°C) and humidity (20-80% RH) conditions to construct a multivariate training data set including temperature, humidity and colorimetric; Step 2: Use the multi-layer perceptron (MLP) neural network model to train the data set, set the input layer to temperature and humidity, the output layer to color rendering, the number of hidden layers to 3, the number of neurons in each layer to 50, the activation function to ReLU, the loss function to mean square error (MSE), the optimizer to Adam, the learning rate to 0.001, and the number of training rounds to 500; Step 3: Use an optimized learning rate adjustment algorithm (such as RMSprop or Adadelta) to further optimize the model training process. The final optimized function is: y=0.015x1+0.025x2+0.12x1x2+0.45 Among them, y is the color rendering, x1 is the temperature, and x2 is the humidity.

9. The production process of a multi-layer waterproof glossy thermal self-adhesive label according to claim 6, characterized in that: When the particle swarm optimization algorithm is used to optimize the formula of the acrylic copolymer adhesive, the population size is 100, the number of iterations is 300, the inertia weight is 0.7, the learning factor is 1.7, and an adaptive inertia weight adjustment algorithm is used to improve the convergence speed and optimization effect. The final optimized formula is 58% butyl acrylate, 32% hydroxyethyl acrylate, and 10% acrylic acid.

10. The production process of a multi-layer waterproof glossy thermal self-adhesive label according to claim 6, characterized in that: The laser slitting machine adopts a CO2 laser with a wavelength of 10.6μm, a cutting accuracy of ±0.05mm, a power of 75W, a frequency of 30kHz, and a cutting speed of 3m / s. It further adopts a real-time monitoring and feedback adjustment system to ensure cutting accuracy and consistency.

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