Online composite production process of low voc solventless coating for seamless wall covering

Abstract

This invention relates to the field of seamless wallcovering production, and discloses an online composite production process for low-VOC solvent-free coatings of seamless wallcoverings. This process includes grading and multiple activation pretreatment of the wallcovering substrate, in-situ polymerization of a supercritical CO2-assisted bio-based self-healing coating, rapid pressure relief and shaping via gradient pores, photothermal dual-response shape memory composite, microwave-assisted deep post-curing and online intelligent detection, digital twin self-optimization, and blockchain full-chain traceability. Specifically, the wallcovering substrate is fed into a supercritical CO2 treatment vessel for swelling, and a mixture of bio-based functional monomers is injected. The supercritical CO2's carrying and permeation properties ensure uniform distribution of the bio-based functional monomer mixture. In-situ polymerization is then initiated by microwave-assisted heating or ultraviolet irradiation. Self-healing microcapsules are introduced into the seamless wallcovering coating, enabling automatic healing of microcracks. Multiple intelligent dyes, including thermochromic and formaldehyde-responsive dyes, are integrated, allowing the wallcovering to provide visual early warnings of excessive indoor formaldehyde and abnormal temperatures.

Description

Technical Field

[0001] This invention relates to the field of seamless wallcovering production, specifically to an online composite production process for low-VOC solvent-free coatings of seamless wallcoverings. Background Technology

[0002] Seamless wall coverings, as a high-end wall decoration material, are widely popular due to their seamless appearance, rich texture, and excellent decorative effect. However, the traditional wall covering production process uses a large amount of solvent-based adhesives or rice glue containing chemical preservatives, leading to the release of VOCs (volatile organic compounds), which seriously endanger indoor air quality and the health of residents. To address this issue, the industry has successively developed low-VOC composite processes such as hot-melt bonding, water-based coatings, and solvent-free reactive bonding.

[0003] Currently, online lamination production of low-VOC solvent-free coatings for seamless wallcoverings has achieved initial industrial application. This process typically involves directly applying the solvent-free coating material to the substrate surface using a precision coating system, and then completing the online lamination with the backing material in a heated pressing unit. Existing production lines often integrate modules such as automatic metering, slot coating, infrared heating, and constant tension control, achieving continuous operation from coating application to lamination and curing. Some advanced equipment also incorporates edge alignment and tension compensation mechanisms to ensure stable operation with wide-width wallcoverings.

[0004] Although existing online lamination processes for low-VOC solvent-free coatings have made some progress, these coatings are prone to micro-cracks during use due to changes in environmental temperature and humidity or slight displacement of the wall. Furthermore, existing material systems lack self-healing capabilities, leading to a gradual decline in waterproof and stain-resistant performance over time. Secondly, as a passive decorative layer, wallpaper lacks environmental sensing capabilities and cannot respond in real time to indoor environmental anomalies such as excessive formaldehyde or high humidity, thus lacking intelligent interactive capabilities. Summary of the Invention

[0005] The purpose of this invention is to provide an online composite production process for low-VOC solvent-free coatings of seamless wall coverings, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] The online lamination process for low-VOC solvent-free coating of seamless wall coverings includes the following steps:

[0008] Step 1: Grading and multiple activation pretreatments of the wallpaper substrate.

[0009] The wallpaper substrate is graded by machine vision and then undergoes triple cleaning and activation processes, including negative pressure dust removal, low-temperature plasma etching, and ion wind static elimination. At the same time, a nano-level micro-perforated exhaust pretreatment is added to the wallpaper substrate.

[0010] Step 2: In-situ polymerization of supercritical CO2-assisted fully bio-based self-healing coating

[0011] The pretreated wallpaper substrate from step one is sent to a supercritical CO2 treatment vessel for swelling, and a mixture of all-bio-based functional monomers containing bio-based polylactic acid polyol, plant-based toughening agent, modified plant protein crosslinking agent, bio-based coupling agent, self-healing microcapsules and smart responsive dyes is injected. The mixture of all-bio-based functional monomers is evenly distributed by the carrying and penetration effect of supercritical CO2. Then, in-situ polymerization is initiated by microwave-assisted heating or ultraviolet irradiation to form a nanoscale functional coating that is chemically bonded to the wallpaper substrate by the mixture of all-bio-based functional monomers.

[0012] Step 3: Rapid pressure relief and shaping of gradient pores

[0013] By employing segmented or pulsed pressure relief shaping, a gradient pore structure with small surface pores and large bottom pores is formed in the thickness direction of the nanoscale functional coating in step two.

[0014] Step 4: Photothermal Dual-Response Shape Memory Composite

[0015] The wallpaper substrate with nanoscale functional coating is sequentially composited with a shape memory polymer layer and a decorative fabric layer using a bio-based hot melt adhesive mesh.

[0016] Step 5: Microwave-assisted deep post-curing and online intelligent detection

[0017] After step four, the photothermal dual-response shape memory composite wall covering substrate is microwave-cured and gradient-cooled for shaping. The coating thickness, crosslinking degree, microcapsule distribution uniformity, and surface defects are monitored in real time by a multimodal online detection array, and then it is cut with high precision.

[0018] Step Six: Digital Twin Self-Optimization and Blockchain Full-Chain Traceability

[0019] Establish a digital twin model of the production line to map the process parameters of the physical production line, such as temperature, pressure, speed, and coating thickness, in real time; dynamically optimize the process parameters through deep reinforcement learning; and establish a full-chain traceability system containing multiple key detection nodes, with traceability data stored using blockchain technology.

[0020] Step 7: Closed-loop recycling of bio-enzymatic hydrolysis waste

[0021] The scraps and waste wallpaper cut off in step five are sent to a bio-enzymatic hydrolysis reactor to catalytically degrade them into lactic acid monomers and amino acids, which are then purified and reused for the synthesis of fully bio-based functional monomers.

[0022] A further embodiment of the present invention: the pressure of the supercritical CO2 treatment vessel is 10-35 MPa, the temperature is 40-90℃, and the treatment time is 10-40 min;

[0023] In the aforementioned fully bio-based functional monomer mixture, bio-based polylactic acid polyol accounts for 50-70 wt%, plant-based toughening agent accounts for 10-20 wt%, modified plant protein crosslinking agent accounts for 2-5 wt%, bio-based coupling agent accounts for 0.5-1.5 wt%, self-healing microcapsules account for 3-8 wt%, and smart responsive dye accounts for 0.1-1 wt%.

[0024] The microwave-assisted heating frequency is 2.45 GHz and the power density is 0.5-6 W / cm². 2 ;

[0025] The ultraviolet irradiation has a wavelength of 365 nm and a power density of 1-3 W / cm². 2 ;

[0026] The thickness of the nanoscale functional coating is 0.05-0.5 mm.

[0027] A further embodiment of the present invention: the self-healing microcapsule is a core-shell structured microcapsule in which a repair agent is encapsulated by a bio-based wall material, wherein the bio-based wall material is selected from polylactic acid, gelatin or gum arabic, and the repair agent is a bio-based prepolymer containing isocyanate groups or an epoxy silane coupling agent.

[0028] The core-shell structured microcapsules have an average particle size of 1-20 μm and a wall thickness of 0.1-2 μm, and their volume fraction in the coating is 3-8%.

[0029] The smart responsive dye is one or more of thermochromic dyes, wet-sensitive dyes, or formaldehyde-responsive dyes, wherein the thermochromic dye is selected from spiropyran or fluorane compounds, and the color-changing temperature range is 25-40℃, and the formaldehyde-responsive dye is a rhodamine derivative containing an amino group.

[0030] Integrating multiple intelligent dyes such as thermochromic and formaldehyde-responsive dyes, the wallpaper can provide visual early warnings of excessive indoor formaldehyde and abnormal temperature. Compared with existing smart home systems, it requires no batteries, no network connection, and consumes zero power, achieving passive environmental monitoring with extremely high cost-effectiveness.

[0031] Compared with the prior art, the beneficial effects of the present invention are:

[0032] 1. Integrating seven core technologies—supercritical CO2 in-situ polymerization, self-healing microcapsules, intelligent responsive dyes, shape memory layers, gradient pore decompression, digital twin optimization, and bio-enzymatic recovery—into the seamless wallcovering production process to form a systematic solution; and introducing self-healing microcapsules into the seamless wallcovering coating, and utilizing the active sites remaining after supercritical CO2 treatment as repair triggers and cross-linking points to achieve automatic healing of microcracks;

[0033] 2. It integrates multiple intelligent dyes such as thermochromic and formaldehyde-responsive dyes, enabling the wallpaper to provide visual early warnings of excessive indoor formaldehyde and abnormal temperature; compared with existing smart home systems, it requires no batteries, no network connection, and consumes zero power, achieving passive environmental monitoring with extremely high cost-effectiveness.

[0034] 3. The wallpaper substrate undergoes low-temperature plasma etching to create a micron-level uneven structure, and the nanopores undergo nano-level micro-perforation venting pretreatment are activated to enhance adhesion. The micro-perforations completely eliminate gas residue. Combining the micron-level uneven structure formed by plasma etching with nano-level micro-perforation technology solves both adhesion and venting problems from a physical perspective.

[0035] 4. Supercritical CO2 is used as the reaction medium to achieve monomer molecular-level penetration and in-situ chemical bonding, breaking through the adhesion bottleneck of traditional physical coating; microwave-assisted heating significantly shortens the curing time, solving the problem of short pot life of solvent-free systems; supercritical CO2 penetration achieves uniform coating; microwave / ultraviolet light can promote rapid curing.

[0036] 5. A pore size gradient is formed in a single nanoscale functional coating through a segmented or pulsed pressure relief strategy, rather than the traditional multilayer composite or uniform pores, and the pressure relief curve is optimized in real time by digital twins to achieve precise control.

[0037] 6. Introducing a polycaprolactone-based shape memory polymer layer, which softens upon heating during installation to perfectly fit inside and outside corners and irregular wall surfaces, and fixes its shape after cooling, permanently eliminating wrinkles and bubbles;

[0038] 7. Microwave penetration heating solves the problem of surface drying but internal drying; the multimodal online detection array includes a laser thickness gauge, infrared spectrometer, Raman spectrometer, machine vision system, near-infrared spectroscopy analyzer and hyperspectral imaging system, integrating laser, infrared, Raman, hyperspectral and near-infrared to achieve full-dimensional online monitoring of coatings, and introduces automatic feedback correction, with a level of intelligence far exceeding that of existing offline sampling inspections;

[0039] 8. Establish a digital twin model for the entire production line, apply digital twins and deep reinforcement learning to optimize the wallpaper production line process, dynamically optimize process parameters through deep reinforcement learning, solidify human experience into algorithms, and eliminate batch-to-batch differences. Detailed Implementation

[0040] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0041] Example 1

[0042] The online lamination process for low-VOC solvent-free coating of seamless wall coverings includes the following steps:

[0043] Step 1: Grading and multiple activation pretreatments of the wallpaper substrate.

[0044] The wallpaper substrate is graded by machine vision and then undergoes triple cleaning and activation processes, including negative pressure dust removal, low-temperature plasma etching, and ion wind static elimination. At the same time, a nano-level micro-perforated exhaust pretreatment is added to the wallpaper substrate.

[0045] Step 2: In-situ polymerization of supercritical CO2-assisted fully bio-based self-healing coating

[0046] The pretreated wallpaper substrate from step one is sent to a supercritical CO2 treatment vessel for swelling, and a mixture of all-bio-based functional monomers containing bio-based polylactic acid polyol, plant-based toughening agent, modified plant protein crosslinking agent, bio-based coupling agent, self-healing microcapsules and smart responsive dyes is injected. The mixture of all-bio-based functional monomers is evenly distributed by the carrying and penetration effect of supercritical CO2. Then, in-situ polymerization is initiated by microwave-assisted heating or ultraviolet irradiation to form a nanoscale functional coating that is chemically bonded to the wallpaper substrate by the mixture of all-bio-based functional monomers.

[0047] Step 3: Rapid pressure relief and shaping of gradient pores

[0048] By employing segmented or pulsed pressure relief shaping, a gradient pore structure with small surface pores and large bottom pores is formed in the thickness direction of the nanoscale functional coating in step two.

[0049] Step 4: Photothermal Dual-Response Shape Memory Composite

[0050] The wallpaper substrate with nanoscale functional coating is sequentially composited with a shape memory polymer layer and a decorative fabric layer using a bio-based hot melt adhesive mesh.

[0051] Step 5: Microwave-assisted deep post-curing and online intelligent detection

[0052] After step four, the photothermal dual-response shape memory composite wall covering substrate is microwave-cured and gradient-cooled for shaping. The coating thickness, crosslinking degree, microcapsule distribution uniformity, and surface defects are monitored in real time by a multimodal online detection array, and then it is cut with high precision.

[0053] Step Six: Digital Twin Self-Optimization and Blockchain Full-Chain Traceability

[0054] Establish a digital twin model of the production line to map the process parameters of the physical production line, such as temperature, pressure, speed, and coating thickness, in real time; dynamically optimize the process parameters through deep reinforcement learning; and establish a full-chain traceability system containing multiple key detection nodes, with traceability data stored using blockchain technology.

[0055] Step 7: Closed-loop recycling of bio-enzymatic hydrolysis waste

[0056] The scraps and waste wallpaper cut off in step five are sent to a bio-enzymatic hydrolysis reactor to catalytically degrade them into lactic acid monomers and amino acids, which are then purified and reused for the synthesis of fully bio-based functional monomers.

[0057] The system integrates seven core technologies—supercritical CO2 in-situ polymerization, self-healing microcapsules, intelligent responsive dyes, shape memory layers, gradient pore decompression, digital twin optimization, and bio-enzymatic recycling—into the seamless wallcovering production process, forming a systematic solution. Furthermore, the system introduces self-healing microcapsules into the seamless wallcovering coating and utilizes the residual active sites after supercritical CO2 treatment as repair triggers and crosslinking points to achieve automatic healing of microcracks.

[0058] Example 2

[0059] This embodiment is based on Embodiment 1 with the following additions:

[0060] The machine vision grading method automatically matches preprocessing parameters according to the type of wallpaper substrate.

[0061] The low-temperature plasma etching forms a micron-level uneven structure with a height difference of 5-20 μm on the surface of the wallpaper substrate;

[0062] The nanoscale microperforation venting pretreatment is specifically designed for PET / / VMPET and PET / / AL special wallcovering substrates, forming pores with a diameter of 30-100 nm and a density of 120-200 pores / cm² on the surface of the wallcovering substrate. 2 Through-hole micropores.

[0063] The wallpaper substrate undergoes a micron-level uneven structure etched by low-temperature plasma etching, and multiple activations of the nanopores after nano-level micro-perforation venting pretreatment enhance adhesion. The micro-perforations completely eliminate gas residue. Combining the micron-level uneven structure formed by plasma etching with nano-level micro-perforation technology solves both adhesion and venting problems from a physical perspective.

[0064] The supercritical CO2 treatment vessel has a pressure of 10-35 MPa, a temperature of 40-90 ℃, and a treatment time of 10-40 min;

[0065] In the aforementioned fully bio-based functional monomer mixture, bio-based polylactic acid polyol accounts for 50-70 wt%, plant-based toughening agent accounts for 10-20 wt%, modified plant protein crosslinking agent accounts for 2-5 wt%, bio-based coupling agent accounts for 0.5-1.5 wt%, self-healing microcapsules account for 3-8 wt%, and smart responsive dye accounts for 0.1-1 wt%.

[0066] The microwave-assisted heating frequency is 2.45 GHz and the power density is 0.5-6 W / cm². 2 ;

[0067] The ultraviolet irradiation has a wavelength of 365 nm and a power density of 1-3 W / cm². 2 ;

[0068] The thickness of the nanoscale functional coating is 0.05-0.5 mm.

[0069] Using supercritical CO2 as the reaction medium, monomer molecular-level penetration and in-situ chemical bonding are achieved, breaking through the adhesion bottleneck of traditional physical coating; microwave-assisted heating significantly shortens the curing time, solving the problem of short pot life of solvent-free systems; supercritical CO2 penetration achieves uniform coating; microwave / ultraviolet light can promote rapid curing.

[0070] The self-healing microcapsule is a core-shell structured microcapsule in which a repair agent is encapsulated by a bio-based wall material. The bio-based wall material is selected from polylactic acid, gelatin or gum arabic, and the repair agent is a bio-based prepolymer containing isocyanate groups or an epoxy silane coupling agent.

[0071] The core-shell structured microcapsules have an average particle size of 1-20 μm and a wall thickness of 0.1-2 μm, and their volume fraction in the coating is 3-8%.

[0072] The smart responsive dye is one or more of thermochromic dyes, wet-sensitive dyes, or formaldehyde-responsive dyes, wherein the thermochromic dye is selected from spiropyran or fluorane compounds, and the color-changing temperature range is 25-40℃, and the formaldehyde-responsive dye is a rhodamine derivative containing an amino group.

[0073] Integrating multiple intelligent dyes such as thermochromic and formaldehyde-responsive dyes, the wallpaper can provide visual early warnings of excessive indoor formaldehyde and abnormal temperature. Compared with existing smart home systems, it requires no batteries, no network connection, and consumes zero power, achieving passive environmental monitoring with extremely high cost-effectiveness.

[0074] The segmented or pulsed pressure relief is defined as follows: pressure is released at a rate of 0.2-0.5 MPa / s to an intermediate pressure of 5-10 MPa, maintained for 10-30 s, and then released to atmospheric pressure at a rate of 1-3 MPa / s; during the pressure relief process, the system temperature is maintained at 5-15°C higher than the set pressure relief temperature; by controlling the change in pressure relief rate, a gradient pore structure with a surface pore size of 50-200 nm and a bottom pore size of 500 nm-3 μm is formed in the thickness direction of the nanoscale functional coating; the specific form of the pressure relief curve is calculated in real time by the digital twin model based on the target porosity gradient and executed automatically, which can realize linear pressure relief, exponential pressure relief, multi-stage step pressure relief or pulse oscillation pressure relief.

[0075] Precise control is achieved by creating a pore size gradient in a single nanoscale functional coating through a segmented or pulsed pressure relief strategy, rather than through traditional multilayer composites or uniform pores, and by optimizing the pressure relief curve in real time using digital twins.

[0076] The shape memory polymer layer is a polycaprolactone-based shape memory polymer layer, with a thickness of 0.1-0.3 mm and a transition temperature of 55-65℃; and the polycaprolactone-based shape memory polymer layer is prepared by electrospinning or melt extrusion web forming process, with a porosity of 50-80%, a shape recovery rate of not less than 95%, and a shape fixation rate of not less than 98%;

[0077] The composite process employs a two-roller pressing device, with the surface roughness Ra of the two rollers not exceeding 0.1 μm, a composite temperature of 70-85℃, a pressure of 0.2-0.6 MPa, and a linear speed of 5-25 m / min.

[0078] The softening point of the bio-based hot melt adhesive mesh is 65-75℃.

[0079] Introducing a polycaprolactone-based shape memory polymer layer, it softens upon heating during installation to perfectly fit inside and outside corners and irregular wall surfaces. After cooling, the shape is fixed, permanently eliminating wrinkles and bubbles.

[0080] In the microwave-assisted deep post-curing process, the microwave frequency is 2.45 GHz, the power is 150-400W, and the action time is 2-10 seconds.

[0081] The gradient cooling method is defined as first air cooling to 40°C, and then water cooling to 25°C;

[0082] The multimodal online detection array includes a laser thickness gauge, an infrared spectrometer, a Raman spectrometer, a machine vision system, a near-infrared spectrometer, and a hyperspectral imaging system. The near-infrared spectrometer detects the amount of unreacted monomer residue in real time, and automatically triggers secondary irradiation curing correction when the residue exceeds 0.5 wt%. The hyperspectral imaging system detects the uniformity of the distribution of self-healing microcapsules and ensures that the CV value is not higher than 5%. The high-precision cutting accuracy is ±0.3 mm.

[0083] Microwave penetration heating solves the problem of surface drying but internal non-drying; the multimodal online detection array includes a laser thickness gauge, infrared spectrometer, Raman spectrometer, machine vision system, near-infrared spectroscopy analyzer and hyperspectral imaging system, integrating laser, infrared, Raman, hyperspectral and near-infrared to achieve full-dimensional online monitoring of coatings, and introduces automatic feedback correction, with a level of intelligence far exceeding that of existing offline sampling inspections.

[0084] The production line digital twin model is used to map the process parameters of the physical production line, such as temperature, pressure, speed, and coating thickness, in real time. It is dynamically optimized through deep reinforcement learning algorithms and integrates a transfer learning module, which can transfer the optimized process parameters of one production line to other production lines of the same model, thereby achieving collaborative optimization of multiple production lines.

[0085] The blockchain full-chain traceability includes 18 key detection nodes, integrating online VOC real-time detection, coating adhesion online detection, intelligent response color change performance verification, and AI weather resistance prediction functions.

[0086] A digital twin model of the entire production line was established, and digital twins and deep reinforcement learning were applied to the optimization of the wallpaper production line process. Through deep reinforcement learning, process parameters were dynamically optimized, and human experience was solidified into algorithms, eliminating batch-to-batch differences.

[0087] The bio-enzymatic hydrolysis reactor is a continuous membrane reactor with an immobilized lipase or protease inside. It catalyzes degradation at 50-60℃ and pH=7.0-8.0, with an enzyme activity retention rate of not less than 90% and a recycling rate of not less than 50 times. After purification by ultrafiltration and nanofiltration with a molecular weight cutoff of 300 Da, the monomer purity of the enzymatic hydrolysis product is not less than 98%, and it can be directly used for repolymerization.

[0088] To build a closed-loop cycle system of "polymerization, use, enzymatic hydrolysis and repolymerization" in the wallpaper industry.

[0089] The online composite production process of the low-VOC solvent-free coating of the seamless wall covering is integrated into a supercritical CO2 recycling system. After depressurization, the CO2 is condensed, purified, and then recompressed to the treatment vessel for recycling. The CO2 recovery rate is not less than 99%, and an energy recovery device is configured to convert the depressurization expansion work into electrical energy.

[0090] The core equipment for the online composite production process of the low-VOC solvent-free coating of the seamless wall covering consists of a supercritical reactor, a microwave generator, a digital twin control system, and an enzymatic hydrolysis reactor.

[0091] Example 3

[0092] This embodiment is based on embodiment 2 with the following additions:

[0093] (1) Machine vision intelligent classification

[0094] A high-resolution line scan camera with a resolution of 5μm / pixel is used in conjunction with a deep learning classification model to automatically identify and classify the type (ordinary chemical fiber, natural fiber, PET composite film), basis weight, width, and surface defects of incoming wall covering substrates; and automatically retrieve the corresponding pretreatment formula (plasma power, processing time, micro-perforation parameters) based on the classification results.

[0095] (2) Triple cleaning and activation

[0096] Negative pressure dust removal: wind pressure 3-8kPa, removes surface dust.

[0097] Low-temperature plasma etching: Atmospheric pressure dielectric barrier discharge plasma is used, with an argon and oxygen mixture as the working gas (argon:oxygen volume ratio 8:2), a discharge power of 300-800W, and a processing speed of 2-10 m / min. High-energy particles in the plasma bombard the fiber surface, removing organic contaminants on one hand, and forming a micron-level uneven structure with a height difference of 5-20 μm on the surface through physical sputtering and chemical etching, significantly increasing the specific surface area.

[0098] Ion wind static elimination: voltage ±3-8kV, neutralizes surface static electricity, and prevents secondary adsorption.

[0099] (3) Nanoscale micro-perforated exhaust pretreatment

[0100] For special wallcovering substrates consisting of polyester film and polyester aluminized film composites, and polyester film and aluminum foil composites, ultraviolet laser drilling (wavelength 355 nm, pulse width 10 ns, repetition frequency 10-50 kHz) or focused ion beam etching is used to form pores with a diameter of 30-100 nm and a density of 120-100 pores / cm² on the substrate surface. 2 The through-pores provide escape channels for interlayer gas during subsequent composite processes, eliminating defects such as white spots and bubbles at the source. The pore size and density of the through-pores are automatically calculated by a digital twin model based on the substrate thickness and air permeability requirements.

[0101] Supercritical CO2-assisted in-situ polymerization of fully bio-based self-healing coatings

[0102] (1) Supercritical CO2 swelling and osmosis

[0103] The pretreated substrate is wound onto a porous stainless steel roller (60% opening rate, 2 mm aperture) and placed into a high-pressure processing autoclave (volume can be designed from 1-20 m³ according to production capacity). 3 After sealing, CO2 is introduced, pressurized to 10-35 MPa, and heated to 40-90℃ to bring the CO2 to a supercritical state. Maintaining this state for 10-40 minutes, the supercritical CO2, with its liquid-like density and gas-like low viscosity and high diffusion coefficient, rapidly penetrates into the fiber, dissolving waxes and oils on the fiber surface. Simultaneously, it increases the distance between fiber molecular chains (swelling rate 5-15%), providing a permeation channel for functional monomers.

[0104] (2) Preparation and injection of fully bio-based functional monomer mixture

[0105] The fully bio-based functional monomer mixture was pre-prepared in a separate mixing tank, with the following specific formulation (mass fraction):

[0106] Bio-based polylactic acid polyols (number average molecular weight 2000-5000): 50-70%

[0107] Plant-based toughening agents (epoxidized soybean oil or castor oil-based polyols): 10-20%

[0108] Modified plant protein crosslinking agent (epoxy-modified soybean protein hydrolysate): 2-5%

[0109] Bio-based coupling agent (lactate derivative of silane coupling agent KH560): 0.5-1.5%

[0110] Self-healing microcapsules: 3-8%

[0111] Smart responsive dyes: 0.1-1%

[0112] Thermal initiator (bio-based analog of azobisisobutyronitrile): 0.5-2%

[0113] The mixture is injected into the treatment vessel using a high-pressure injection pump (injection pressure 2-5 MPa higher than the vessel pressure), and then uniformly dispersed under stirring by a circulating pump (flow rate 50-200 L / min). Due to the excellent solubility of supercritical CO2 for organic matter and its extremely low viscosity (approximately 0.02-0.1 mPa·s), functional monomers are efficiently carried to the fiber surface and interior, even entering the amorphous region of the fiber, achieving a uniform distribution at the molecular level; the mass concentration of monomers in supercritical CO2 is 2-20%.

[0114] Photothermal dual-response shape memory composite

[0115] (1) Preparation of shape memory polymer layer

[0116] Polycaprolactone-based shape memory polymer nonwoven fabric layers were prepared by electrospinning: polycaprolactone with a number average molecular weight of 50,000-80,000 was dissolved in a dichloromethane / dimethylformamide mixed solvent (mass ratio 7:3) to prepare a spinning solution of 10-15 wt%.

[0117] Electrospinning parameters: voltage 15-20 kV, receiving distance 15 cm, feed rate 1 mL / h, ambient temperature 25℃. The obtained polycaprolactone-based shape memory polymer fiber membrane has a thickness of 0.1-0.3 mm, a porosity of 50-80%, and a fiber diameter of 300-800 nm.

[0118] The transition temperature of polycaprolactone-based shape memory polymers (SMPs) is controlled between 55-65℃ by adjusting the molecular weight of polycaprolactone, achieving a shape recovery rate of ≥95% and a shape fixation rate of ≥98%. When installing wallpaper, a heat gun (80-100℃) or a steam iron is used to heat the back of the wallpaper. This softens the SMP layer, allowing it to easily conform to irregular shapes such as corners, cylinders, and curved walls. After cooling to room temperature, the SMP layer retains its shape, permanently eliminating wrinkles and bubbles. To replace the wallpaper, it is reheated to above 65℃, softening the SMP layer and allowing the wallpaper to be peeled off completely without damaging the wall.

[0119] (2) Multilayer composite

[0120] The composite uses a five-layer structure (from the wall surface to the decorative surface): substrate (functional coating has been polymerized in situ) - bio-based hot melt adhesive mesh (0.05mm thick) - polycaprolactone-based shape memory polymer layer - bio-based hot melt adhesive mesh (0.05mm thick) - decorative fabric layer.

[0121] The laminating equipment is a two-roll press with mirror-polished rollers (Ra≤0.1μm surface) and independent heating and servo pressure control. Laminating parameters: temperature 70-85℃, pressure 0.2-0.6MPa, linear speed 5-25 m / min. The hot melt adhesive web is made of polylactic acid (PLA) with a softening point of 68℃ and a basis weight of 15-30 g / m³. 2 .

[0122] The multimodal online detection array integrates the following detection modules:

[0123] Laser thickness gauge (accuracy ±0.2μm): monitors coating thickness online, with a detection frequency of 1000 points / second. When the thickness deviation exceeds the limit, it automatically feeds back to the coating unit to adjust the die gap.

[0124] Infrared spectrometer (ATR mode, wavenumber range 4000-600 cm⁻¹) -1 ): Real-time detection of coating crosslinking degree (by C=C bimodal area ratio) and residual amount of unreacted monomers.

[0125] Raman spectroscopy (excitation wavelength 785 nm): Detects the distribution uniformity of self-healing microcapsules (characteristic peak intensity CV value).

[0126] Hyperspectral imaging system (400-1000nm, spatial resolution 50μm): Detects the distribution uniformity and color-changing properties of smart response dyes.

[0127] CCD machine vision (5 μm / pixel resolution): detects macroscopic defects such as surface bubbles, scratches, and stains.

[0128] Near-infrared spectrometer: detects the amount of unreacted monomer residue; when the residue exceeds 0.5 wt%, it automatically triggers secondary ultraviolet irradiation (power 1 W / cm²). 2 Correction is performed within 1 second.

[0129] High-precision cutting is achieved by using CCD vision positioning (positioning accuracy ±0.1 mm) combined with dual laser calibration (cross laser lines) to control the rotating cutter and achieve a cutting accuracy of ±0.3 mm.

[0130] Digital twin self-optimization and blockchain full-chain traceability

[0131] (1) Establishment of digital twin model

[0132] A high-fidelity digital twin model is built in the cloud based on the actual dimensions, equipment parameters, and material characteristics of the physical production line. The model's process parameters (temperature, pressure, flow rate, speed, power, time, etc.) are calculated using the finite element method to determine fluid dynamics and heat and mass transfer processes, with a calculation accuracy of no less than 95%.

[0133] (2) Deep reinforcement learning self-optimization

[0134] Employing deep Q-networks or near-end strategy optimization algorithms, and using product yield, energy consumption, and production efficiency as reward functions, the system dynamically explores the optimal combination of process parameters. The digital twin model simulates 100 iterations per second and sends the optimized parameters to the PLC control system of the physical production line. The system possesses transfer learning capabilities, allowing the optimization strategy of one production line to be transferred to other production lines of the same model.

[0135] (3) Blockchain full-chain traceability

[0136] A full-chain traceability system has been established, encompassing raw material suppliers, production, quality inspection, warehousing, logistics, construction, and recycling. Key data (raw material batch numbers, process parameters, test results, operators, and timestamps) are hash-encrypted and written into the Hyperledger Fabric consortium blockchain to ensure data immutability and auditability. Consumers can scan the product's QR code to access the wallpaper's "digital passport," which includes information such as bio-based content, VOC emissions, weather resistance predictions, and recycling guidelines.

[0137] (4) AI weather resistance prediction

[0138] Based on historical aging data (accelerated aging test chamber results, accumulating more than 100,000 hours of data), an LSTM neural network model is trained. Inputting coating formulation, process parameters, and usage environment (temperature, humidity, UV intensity), it can predict the weather resistance performance of products for more than 20 years (color difference ΔE, contact angle reduction rate, adhesion decay) with an accuracy of no less than 90%.

[0139] Closed-loop recycling of bio-enzymatic waste

[0140] (1) Waste collection and pretreatment: The cutting scraps (approximately 0.5-1% of the total raw materials), defective products, and waste wall coverings recycled after use generated during the production process are crushed by a crusher to a particle size not exceeding 5 mm.

[0141] (2) Bioenzymatic hydrolysis reaction

[0142] The pulverized material is fed into a continuous membrane reactor (effective volume 500L, built-in hollow fiber ultrafiltration membrane, molecular weight cutoff 300Da). Lipase (derived from *Candida antarcticis*) or protease (derived from *Bacillus licheniformis*) is immobilized in the reactor, with an enzyme activity retention rate of not less than 90%. Reaction conditions: temperature 55℃, pH=7.5, stirring speed 200 rpm, residence time 12-24h. Enzymatic hydrolysis products: polylactic acid component degrades into lactic acid monomers (optical purity ≥99%); plant protein cross-linking agent degrades into an amino acid mixture.

[0143] (3) Product purification and reuse

[0144] The enzymatic hydrolysate is subjected to ultrafiltration (molecular weight cutoff 300 Da) to remove macromolecular impurities, followed by nanofiltration (molecular weight cutoff 150 Da) for desalting. Finally, lactic acid (purity ≥98%) and amino acids are separated by simulated moving bed chromatography. Lactic acid is directly used to synthesize polylactic acid polyols, and amino acids are used to synthesize modified plant protein cross-linking agents. The enzyme can be recycled more than 50 times in the entire recovery process, with a raw material recovery rate of ≥85%.

[0145] Comparative Example 1

[0146] The existing process was employed: all-bio-based coating, microwave curing, and online detection, but it lacks self-healing, intelligent response, shape memory, gradient porosity, and enzymatic recovery. Detailed test comparison results are shown in Table 1.

[0147] Table 1

[0148] Comparative Example 1 Example 3 Increase VOC(g / L) 1.8 1.4 Down 22% <![CDATA[Water vapor permeability (g / m 2 ·24h)]]> 5500 7300 Increased by 33% Waste recycling rate 0% 85% -

[0149] As shown in Table 1, the performance of the product produced in Example 3 is better than that of the product produced in Comparative Example 1.

[0150] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, it is intended that all variations falling within the meaning and scope of equivalents of the claims be included within the present invention.

[0151] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. An online lamination process for low-VOC solvent-free coating of seamless wall coverings, characterized in that, Includes the following steps: Step 1: Grading and multiple activation pretreatments of the wallpaper substrate. The wallpaper substrate is graded by machine vision and then undergoes triple cleaning and activation processes, including negative pressure dust removal, low-temperature plasma etching, and ion wind static elimination. At the same time, a nano-level micro-perforated exhaust pretreatment is added to the wallpaper substrate. Step 2: In-situ polymerization of supercritical CO2-assisted fully bio-based self-healing coating The pretreated wallpaper substrate from step one is sent to a supercritical CO2 treatment vessel for swelling, and a mixture of all-bio-based functional monomers containing bio-based polylactic acid polyol, plant-based toughening agent, modified plant protein crosslinking agent, bio-based coupling agent, self-healing microcapsules and smart responsive dyes is injected. The mixture of all-bio-based functional monomers is evenly distributed by the carrying and penetration effect of supercritical CO2. Then, in-situ polymerization is initiated by microwave-assisted heating or ultraviolet irradiation to form a nanoscale functional coating that is chemically bonded to the wallpaper substrate by the mixture of all-bio-based functional monomers. Step 3: Rapid pressure relief and shaping of gradient pores By employing segmented or pulsed pressure relief shaping, a gradient pore structure with small surface pores and large bottom pores is formed in the thickness direction of the nanoscale functional coating in step two. Step 4: Photothermal Dual-Response Shape Memory Composite The wallpaper substrate with nanoscale functional coating is sequentially composited with a shape memory polymer layer and a decorative fabric layer using a bio-based hot melt adhesive mesh. Step 5: Microwave-assisted deep post-curing and online intelligent detection After step four, the photothermal dual-response shape memory composite wall covering substrate is microwave-cured and gradient-cooled for shaping. The coating thickness, crosslinking degree, microcapsule distribution uniformity, and surface defects are monitored in real time by a multimodal online detection array, and then it is cut with high precision. Step Six: Digital Twin Self-Optimization and Blockchain Full-Chain Traceability Establish a digital twin model of the production line to map the process parameters of the physical production line, such as temperature, pressure, speed, and coating thickness, in real time; dynamically optimize the process parameters through deep reinforcement learning; and establish a full-chain traceability system containing multiple key detection nodes, with traceability data stored using blockchain technology. Step 7: Closed-loop recycling of bio-enzymatic hydrolysis waste The scraps and waste wallpaper cut off in step five are sent to a bio-enzymatic hydrolysis reactor to catalytically degrade them into lactic acid monomers and amino acids, which are then purified and reused for the synthesis of fully bio-based functional monomers.

2. The online composite production process for low-VOC solvent-free coating of seamless wallcovering according to claim 1, characterized in that, The machine vision grading method automatically matches preprocessing parameters according to the type of wallpaper substrate. The low-temperature plasma etching forms a micron-level uneven structure with a height difference of 5-20 μm on the surface of the wallpaper substrate; The nanoscale micro-perforation venting pretreatment is specifically designed for special wallcovering substrates such as polyester film and polyester aluminized film composites, and polyester film and aluminum foil composites, forming pores with a diameter of 30-100 nm and a density of 120-200 pores / cm² on the surface of the wallcovering substrate. 2 Through-hole micropores.

3. The online composite production process for low-VOC solvent-free coating of seamless wallcovering according to claim 1, characterized in that, The supercritical CO2 treatment vessel has a pressure of 10-35 MPa, a temperature of 40-90 ℃, and a treatment time of 10-40 min; In the aforementioned fully bio-based functional monomer mixture, bio-based polylactic acid polyol accounts for 50-70 wt%, plant-based toughening agent accounts for 10-20 wt%, modified plant protein crosslinking agent accounts for 2-5 wt%, bio-based coupling agent accounts for 0.5-1.5 wt%, self-healing microcapsules account for 3-8 wt%, and smart responsive dye accounts for 0.1-1 wt%. The microwave-assisted heating frequency is 2.45 GHz and the power density is 0.5-6 W / cm². 2 ; The ultraviolet irradiation has a wavelength of 365 nm and a power density of 1-3 W / cm². 2 ; The thickness of the nanoscale functional coating is 0.05-0.5 mm.

4. The online composite production process for low-VOC solvent-free coating of seamless wallcovering according to claim 1, characterized in that, The self-healing microcapsule is a core-shell structured microcapsule in which a repair agent is encapsulated by a bio-based wall material. The bio-based wall material is selected from polylactic acid, gelatin or gum arabic, and the repair agent is a bio-based prepolymer containing isocyanate groups or an epoxy silane coupling agent. The core-shell structured microcapsules have an average particle size of 1-20 μm and a wall thickness of 0.1-2 μm, and their volume fraction in the coating is 3-8%. The smart responsive dye is one or more of thermochromic dyes, wet-sensitive dyes, or formaldehyde-responsive dyes, wherein the thermochromic dye is selected from spiropyran or fluorane compounds, and the color-changing temperature range is 25-40℃, and the formaldehyde-responsive dye is a rhodamine derivative containing an amino group.

5. The online composite production process for low-VOC solvent-free coating of seamless wallcovering according to claim 1, characterized in that, The segmented or pulsed pressure relief is defined as follows: pressure is released at a rate of 0.2-0.5 MPa / s to an intermediate pressure of 5-10 MPa, maintained for 10-30 s, and then released to atmospheric pressure at a rate of 1-3 MPa / s; during the pressure relief process, the system temperature is maintained at 5-15°C higher than the set pressure relief temperature; by controlling the change in pressure relief rate, a gradient pore structure with a surface pore size of 50-200 nm and a bottom pore size of 500 nm-3 μm is formed in the thickness direction of the nanoscale functional coating; the specific form of the pressure relief curve is calculated in real time by the digital twin model based on the target porosity gradient and executed automatically, which can realize linear pressure relief, exponential pressure relief, multi-stage step pressure relief or pulse oscillation pressure relief.

6. The online composite production process for low-VOC solvent-free coating of seamless wallcovering according to claim 1, characterized in that, The shape memory polymer layer is a polycaprolactone-based shape memory polymer layer, with a thickness of 0.1-0.3 mm and a transition temperature of 55-65℃; and the polycaprolactone-based shape memory polymer layer is prepared by electrospinning or melt extrusion web forming process, with a porosity of 50-80%, a shape recovery rate of not less than 95%, and a shape fixation rate of not less than 98%; The composite process employs a two-roller pressing device, with the surface roughness Ra of the two rollers not exceeding 0.1 μm, a composite temperature of 70-85℃, a pressure of 0.2-0.6 MPa, and a linear speed of 5-25 m / min. The softening point of the bio-based hot melt adhesive mesh is 65-75℃.

7. The online composite production process for low-VOC solvent-free coating of seamless wallcovering according to claim 1, characterized in that, In the microwave-assisted deep post-curing process, the microwave frequency is 2.45 GHz, the power is 150-400W, and the action time is 2-10 seconds. The gradient cooling method is defined as first air cooling to 40°C, and then water cooling to 25°C; The multimodal online detection array includes a laser thickness gauge, an infrared spectrometer, a Raman spectrometer, a machine vision system, a near-infrared spectrometer, and a hyperspectral imaging system. The near-infrared spectrometer detects the amount of unreacted monomer residue in real time, and automatically triggers secondary irradiation curing correction when the residue exceeds 0.5 wt%. The hyperspectral imaging system detects the uniformity of the distribution of self-healing microcapsules and ensures that the CV value is not higher than 5%. The high-precision cutting accuracy is ±0.3 mm.

8. The online composite production process for low-VOC solvent-free coating of seamless wallcovering according to claim 1, characterized in that, The production line digital twin model is used to map the process parameters of the physical production line, such as temperature, pressure, speed, and coating thickness, in real time. It is dynamically optimized through deep reinforcement learning algorithms and integrates a transfer learning module, which can transfer the optimized process parameters of one production line to other production lines of the same model, thereby achieving collaborative optimization of multiple production lines. The blockchain full-chain traceability includes 18 key detection nodes, integrating online VOC real-time detection, coating adhesion online detection, intelligent response color change performance verification, and AI weather resistance prediction functions.

9. The online composite production process for low-VOC solvent-free coating of seamless wallcovering according to claim 1, characterized in that, The bio-enzymatic hydrolysis reactor is a continuous membrane reactor with an immobilized lipase or protease inside. It catalyzes degradation at 50-60℃ and pH=7.0-8.0, with an enzyme activity retention rate of not less than 90% and a recycling rate of not less than 50 times. After purification by ultrafiltration and nanofiltration with a molecular weight cutoff of 300 Da, the monomer purity of the enzymatic hydrolysis product is not less than 98%, and it can be directly used for repolymerization.

10. The online composite production process for low-VOC solvent-free coating of seamless wallcovering according to any one of claims 1-9, characterized in that, The online composite production process of the low-VOC solvent-free coating of the seamless wall covering is integrated into a supercritical CO2 recycling system. After depressurization, the CO2 is condensed, purified, and then recompressed to the treatment vessel for recycling. The CO2 recovery rate is not less than 99%, and an energy recovery device is configured to convert the depressurization expansion work into electrical energy.