Self-sensing polyurethane road repairing material as well as preparation method and application thereof

Abstract

The invention belongs to the technical field of intelligent materials, and particularly relates to a self-sensing polyurethane road repairing material and a preparation method and application thereof.The repairing material comprises a sensing layer and a supporting layer which are arranged in a stacked mode; the repairing material takes polyurethane as a base material, the sensing layer is filled with directionally arranged conductive nanofiller, and the orientation degree is greater than 80%; the support layer is filled with a conductive micron-sized filler; the conductive nano filler and the conductive micron filler form a gradient conductive network; the surface of the repairing material is coated with a surface coating, and the surface coating is a hydrophobic coating. Compared with the prior art, the self-sensing polyurethane road repairing material disclosed by the invention solves the problem that the self-sensing polyurethane road repairing material in the prior art has relatively excellent mechanical strength but relatively poor sensitivity. According to the scheme, the two-component polyurethane is taken as a matrix and compounded with the nano-micron conductive filler, and a multi-scale conductive network is constructed through gradient structure design and a magnetic field orientation process, so that collaborative optimization of mechanical strength, strain sensitivity and environmental stability is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of smart materials, and specifically relates to a self-sensing polyurethane road repair material and a preparation method and application thereof. Background Art

[0002] Smart materials are advanced functional materials that can sense and actively respond to environmental stimuli. Their properties can reversibly change with external conditions such as temperature, pressure, and electric or magnetic fields. Among the many smart materials, self-sensing polyurethane (PU) has attracted considerable attention due to its unique electromechanical response properties. In recent years, it has demonstrated significant application value in structural health monitoring, flexible electronics, and intelligent robotics.

[0003] Self-sensing polyurethane forms a conductive network structure by introducing conductive nanofillers (such as carbon nanotubes, graphene or metal nanoparticles) into the polyurethane matrix. When the material is subjected to external force, the resistance of its internal conductive path will change due to deformation, and the stress, strain and damage status can be sensed in real time by measuring the resistance signal. Compared with other smart materials, self-sensing polyurethane has both high flexibility and fatigue resistance, and can adapt to the integration needs of complex curved structures. In the engineering field, it has been used for bridge crack monitoring and wind blade damage warning; in the biomedical field, it can be used to make smart bandages to monitor the wound healing process; in the robotics field, it is used for the development of tactile sensors.

[0004] For example, CN107216643A discloses a self-healing polyurethane nanocomposite material, its preparation method and use, which realizes the application in the fields of electrodes, conductors, capacitors, sensors, etc. by constructing multiple self-healing polyurethane nanocomposites with Diels-Alder bonds, and realizes the self-healing function.

[0005] However, self-sensing polyurethane materials have significant drawbacks when applied to road repair scenarios:

[0006] (1) Imbalance in mechanical and electrical properties: Although high filler content improves conductivity, it leads to a decrease in matrix toughness (elastic modulus decreases by 30%-50%);

[0007] (2) Scale effect contradiction: Conductive nanofillers tend to agglomerate in thick-section materials, resulting in discontinuous conductive networks and signal drift rates as high as 35% / year;

[0008] (3) Severe environmental interference: Temperature and humidity fluctuations cause the matrix to expand, masking the true stress response signal.

[0009] For example, CN117986889A discloses a conductive modified asphalt, its preparation method and application, which overcomes the problems of unstable conductive properties of conductive asphalt and the incorporation of carbon-based fillers to accelerate the formation of microcracks by introducing conductive fillers containing polar functional groups; however, this solution can only be applied to asphalt materials.

[0010] In addition, existing solutions for polyurethane, such as adding fillers of different sizes, can improve the mechanical strength to a certain extent (compressive strength > 50MPa), but this solution sacrifices sensitivity (strain coefficient GF < 2.5) and is prone to microcracks due to stress concentration.

[0011] Therefore, it is necessary to propose a new type of road repair material that can be used on polyurethane roads and has self-sensing, high compressive strength and sensitivity. Summary of the Invention

[0012] The present invention aims to address at least one of the aforementioned issues by providing a self-sensing polyurethane road repair material, its preparation method, and its application. This approach addresses the problem of existing self-sensing polyurethane road repair materials, which exhibit excellent mechanical strength but poor sensitivity. This solution utilizes a two-component polyurethane matrix, compounded with nano- and micron-scale conductive fillers (carbon nanotubes, graphene, and carbon black), and through gradient structural design and magnetic field orientation, constructs a multiscale conductive network, achieving synergistic optimization of mechanical strength, strain sensitivity, and environmental stability.

[0013] The purpose of the present invention is achieved through the following technical solutions:

[0014] The first aspect of the present invention discloses a self-sensing polyurethane road repair material, comprising a sensing layer and a supporting layer stacked together;

[0015] The repair material is based on polyurethane, wherein:

[0016] The sensing layer is filled with conductive nanofillers arranged in a direction, and the orientation degree of the conductive nanofillers is greater than 80%;

[0017] The support layer is filled with conductive micron-sized fillers;

[0018] The conductive nanofiller and the conductive micron-sized filler form a gradient conductive network in the repair material;

[0019] The surface of the repair material is also coated with a surface coating, which is a hydrophobic coating.

[0020] Wherein, the directional arrangement is arranged along the thickness direction of the sensing layer.

[0021] Preferably, the polyurethane is obtained by cross-linking a two-component polyurethane prepolymer, wherein the two-component polyurethane prepolymer consists of component A: isocyanate and component B: polyol with a hydroxyl value of 45-60 mg KOH / g.

[0022] Preferably, in the cross-linking reaction, component A and component B are mixed and reacted in a volume ratio of 1:1, and the cross-linking agent used in the cross-linking reaction includes trimethylolpropane, and the amount of the cross-linking agent is 1-3 wt % of the mass of the base material.

[0023] Preferably, the conductive nanofiller comprises carbon nanotubes with a diameter of 10-20 nm and graphene with a sheet thickness of less than 5 nm, and the conductive micron-sized filler comprises micron-sized carbon black with a particle size of 1-5 μm;

[0024] The mass ratio of the carbon nanotubes, graphene and micron-sized carbon black is 1-3:1-2:5-10;

[0025] The total addition amount of the conductive nano-filler and the conductive micron-size filler is 20-35 wt% of the mass of the matrix material.

[0026] Preferably, the surface coating is a modified silicon dioxide coating, wherein the added amount of the modified silicon dioxide is 0.5-2 wt % of the mass of the base material.

[0027] Preferably, the thickness of the sensing layer is 1-3 mm, the thickness of the supporting layer is 5-10 mm, the thickness of the surface coating is 50-100 μm, and the contact angle of the surface coating is not less than 120°.

[0028] The second aspect of the present invention discloses a method for preparing the self-sensing polyurethane road repair material as described above, comprising the following steps:

[0029] S1: plasma treatment of conductive nanofillers;

[0030] S2: mixing the conductive nanofiller pretreated in step S1 with a portion of the polyurethane prepolymer, and then ultrasonically dispersing the mixture to obtain a conductive nanofiller mixed solution;

[0031] S3: mixing the conductive micron-sized filler with the remaining portion of the polyurethane prepolymer, followed by low-speed mechanical stirring to obtain a conductive micron-sized filler mixed solution;

[0032] S4: injecting the conductive nanofiller mixture obtained in step S2 into a mold, applying a vertical magnetic field to the mold to align the conductive nanofillers (along the thickness direction of the sensing layer), and simultaneously adding a crosslinking agent to the conductive nanofiller mixture for curing to obtain a sensing layer;

[0033] S5: pouring the conductive micron-sized filler mixture obtained in step S3 onto the surface of the sensing layer obtained in step S4, and curing at room temperature;

[0034] S6: coating the surface of the semi-finished repair material obtained by curing in step S5 with a surface coating, followed by heat treatment to obtain the repair material.

[0035] Preferably, one or more of the following are included:

[0036] i) In step S1, the plasma treatment is performed at a power of 200-300 W for 10-15 minutes. The plasma bombards the surface of the nanofiller to generate oxygen-containing functional groups (-COOH, -OH), thereby enhancing the interfacial bonding with the polyurethane matrix. It also removes impurities adsorbed on the filler surface (such as residual catalysts and organic solvents), thereby improving the purity of the conductive network.

[0037] ii) in step S2, the ultrasonic dispersion time is 30-40 minutes; the ultrasonic cavitation effect generates local high pressure to break up the CNT / graphene agglomerates (agglomerate size <200 nm);

[0038] iii) in step S3, the low-speed mechanical stirring is performed at a speed of 200-300 rpm for 20-30 min, and the stirring paddle is an anchor type or a paddle type; the low-speed mechanical stirring is performed to avoid high-speed shearing that may damage the structure of the micron carbon black;

[0039] iv) in step S4, the intensity of the magnetic field is 0.5-1.5 T, and the curing time is 2-4 hours;

[0040] v) In step S5, the curing time is 24-48 hours;

[0041] vi) In step S6, the heat treatment temperature is 60-80° C. and the time is 1-2 hours.

[0042] Furthermore, in step S1, if the plasma treatment time is greater than 15 minutes, the nanostructure may be damaged, while if the treatment time is less than 5 minutes, the modification effect may be insufficient.

[0043] Furthermore, in step S2, if the ultrasonic dispersion is performed for too long (>50 minutes), the polyurethane molecular chains will be destroyed, resulting in premature cross-linking of the matrix material; the mixing temperature is preferably maintained at 25±2°C to prevent local overheating from causing side reactions.

[0044] Furthermore, in step S3, the low-speed mechanical stirring with a rotation speed > 500 rpm may cause delamination of the filler-matrix interface and reduce the compressive strength; the stirring paddle may be anchor type or blade type to avoid uneven dispersion caused by central vortex.

[0045] Furthermore, in step S4, when the magnetic field intensity is <0.5T, the orientation degree is <50%. The orientation degree describes the degree to which the filler is arranged along the target direction in the polyurethane. When the orientation degree is lower than 50%, defects such as an incomplete conductive network, reduced sensory sensitivity, and unstable mechanical properties will occur. If it is >1.5T, filler aggregation will occur. The humidity of the curing environment needs to be ≤60% to prevent moisture from interfering with the cross-linking reaction.

[0046] Furthermore, in step S5, the pouring is performed layer by layer. Before pouring, impurities on the surface of the sensing layer need to be removed to ensure that there are no bubbles or contamination on the interface; the curing environment needs to be light-proof to prevent ultraviolet rays from causing degradation of the base material.

[0047] Furthermore, in step S6, the coating is sprayed, and the substrate surface needs to be plasma cleaned (power 50W, time 1 min) before spraying to improve the adhesion of the coating; a heat treatment temperature > 80°C will cause the polyurethane substrate to soften, and < 50°C will result in incomplete curing.

[0048] Preferably, in step S4, the intensity of the magnetic field is 1.0-1.5T.

[0049] The third aspect of the present invention discloses an application of any of the above-described self-sensing polyurethane road repair materials in road health monitoring.

[0050] Preferably, the resistance drift rate of the repair material is less than 5% per year, and the temperature tolerance range is -30°C to 60°C.

[0051] The working principle of the present invention is:

[0052] The present invention adopts a two-component polyurethane matrix, and constructs a gradient conductive network by compounding nano-scale (magnetic field oriented curing to form a high-sensitivity sensing layer with a directional arrangement orientation degree >80%) and micron-scale (low-speed mechanical stirring dispersion to form a mechanical support layer, and then cast layer by layer on the high-sensitivity sensing layer) conductive fillers, and supplemented by a hydrophobic modified silica surface coating and precisely controlled cross-linking and curing processes to effectively isolate environmental interference and stabilize the resistance signal; each design unit cooperates with each other and synergizes to enhance efficiency, especially: the highly directional arrangement of the nanofillers in the repair material not only provides a sensitive electrical signal response, but also paves a continuous conductive channel for the micron-scale fillers cast layer by layer, and at the same time, the uniform dispersion of the micron-scale fillers effectively improves the compressive performance, not only achieving coordinated optimization of mechanical strength, strain sensitivity and environmental stability, and significantly optimizing the mechanics, perception and environmental stability of the material, but also effectively avoiding filler agglomeration and stress concentration, ensuring the comprehensive excellent performance of the material in road repair and health monitoring.

[0053] Gradient structure design:

[0054] Multi-scale conductive network: A highly sensitive sensing layer is constructed by nanofillers (CNT / graphene), and a mechanical support layer is enhanced by microfillers (carbon black);

[0055] Directional dispersion process: Magnetic field orientation technology (magnetic field strength 0.5-1.5T) is used to achieve directional arrangement of nanofillers (orientation degree >80%), combined with a layer-by-layer casting process to form a gradient conductive path;

[0056] Environmental robustness optimization: Through hydrophobic modification and cross-linking density control, the interference of temperature and humidity fluctuations on the resistance signal is reduced (error <±5%).

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] The self-sensing polyurethane road repair material based on a gradient conductive network disclosed in the present invention uses a two-component polyurethane as a matrix and is compounded with nano-micron-scale conductive fillers (carbon nanotubes, graphene, carbon black). Through gradient structure design and magnetic field orientation technology, a multi-scale conductive network is constructed to achieve high mechanical strength (compressive resistance ≥55MPa) and high strain sensitivity (GF ≥4.0); at the same time, combined with hydrophobic modification and cross-linking density control, it significantly reduces temperature and humidity interference and achieves environmental stability (signal error <±5%); ultimately, the coordinated optimization of mechanical strength, strain sensitivity and environmental stability is achieved.

[0059] The present invention solves the problems of existing self-sensing materials in road repair scenarios, such as imbalance in mechanical and electrical properties, discontinuous conductive networks, and high signal drift rates. It is suitable for complex outdoor working conditions and for the integrated application of structural repair and health monitoring of smart roads. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 Schematic diagram of the structure of the gradient conductive network in the repair material;

[0061] Figure 2 Schematic diagram of the structure of a magnetic field orientation device (applying a vertical magnetic field to orient the conductive nanofillers);

[0062] Figure 3 Schematic diagram of the process for preparing repair materials. DETAILED DESCRIPTION

[0063] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0064] In the following description, unless otherwise specified, conventional commercial products in the field are used, and the methods used are common knowledge in the field. Any matters not covered may adopt existing technologies.

[0065] A self-sensing polyurethane road repair material based on a gradient conductive network includes the following components:

[0066] Base material: two-component polyurethane prepolymer (component A: isocyanate; component B: polyol, hydroxyl value 45-60 mgKOH / g), component A and component B are mixed in a volume ratio of 1:1;

[0067] Conductive filler: A nano-micro composite system comprising carbon nanotubes (CNTs, 10-20 nm in diameter), graphene (sheet thickness <5 nm), and micron-sized carbon black (particle size 1-5 μm), with a mass ratio of (1-3):(1-2):(5-10); the total amount of conductive filler added is 20-35 wt% of the matrix material mass;

[0068] Functional additives: hydrophobic modified silica (added amount 0.5-2 wt%), crosslinking agent (trimethylolpropane, added amount 1-3 wt%).

[0069] Gradient structure design:

[0070] Multiscale conductive networks, such as Figure 1 As shown: a high-sensitivity sensing layer (1-3 mm) is constructed by nanofillers (CNT / graphene), and a mechanical support layer (5-10 mm) is reinforced by microfillers (carbon black);

[0071] Directional dispersion process: Magnetic field orientation technology (magnetic field strength 0.5-1.5T) is used to achieve directional arrangement of nanofillers (orientation degree >80%), combined with a layer-by-layer casting process to form a gradient conductive path;

[0072] Environmental robustness optimization: Through hydrophobic modification and cross-linking density control, the interference of temperature and humidity fluctuations on the resistance signal is reduced (error <±5%).

[0073] Furthermore, the preparation method of the self-sensing polyurethane road repair material based on the gradient conductive network is as follows: Figure 3 As shown, the following steps are included:

[0074] S1: Filler pretreatment: CNT and graphene are treated with plasma (power 200-300W, time 10-15min) to enhance surface activity;

[0075] S2: Mix the nanofiller (CNT / graphene) with polyurethane prepolymer I (part of the polyurethane prepolymer) and disperse them by ultrasonication (frequency 40 kHz, time 30-40 min);

[0076] S3: Mix the micron-sized carbon black with prepolymer II (remaining polyurethane prepolymer) and stir mechanically at low speed (200-300 rpm for 20-30 min).

[0077] S4: Magnetic field orientation: The nanofiller mixture is injected into the mold and a vertical magnetic field (0.5-1.5T) is applied to orient the fillers. The sensing layer is formed after curing (2-4 hours).

[0078] S5: Layer-by-layer pouring: pour a micron-sized filler mixture on the sensing layer and cure it at room temperature for 24-48 hours to form a mechanical reinforcement layer;

[0079] S6: Post-treatment: The surface of the material is coated with a coating composed of hydrophobic modified silica and heat-treated at 60-80°C for 1-2 hours.

[0080] Furthermore, in step S1, the plasma bombards the CNT and graphene surfaces to generate oxygen-containing functional groups (-COOH, -OH), thereby enhancing the interfacial bonding with the polyurethane matrix; and removing impurities (such as residual catalysts and organic solvents) adsorbed on the filler surface to improve the purity of the conductive network.

[0081] Furthermore, in step S1, the plasma treatment time of more than 15 minutes may result in damage to the nanostructure, while the modification effect may be insufficient if the treatment time is less than 5 minutes.

[0082] Furthermore, in step S2, the ultrasonic cavitation effect generates local high pressure to break up CNT / graphene agglomerates (agglomerate size <200 nm); the nanofiller is fully mixed with component A (isocyanate) of the polyurethane prepolymer to form a stable suspension.

[0083] Furthermore, in step S2, the ultrasonic dispersion, if carried out for too long (>50 minutes), will destroy the polyurethane molecular chains and cause premature cross-linking of the matrix material; the mixing temperature is maintained at 25±2°C to prevent local overheating from causing side reactions.

[0084] Furthermore, in step S3, the low-speed mechanical stirring prevents high-speed shearing from destroying the structure of the micron-sized carbon black; the micron-sized carbon black is uniformly dispersed in the polyurethane prepolymer II to form a mechanical support network.

[0085] Furthermore, in step S3, the low-speed mechanical stirring with a rotation speed > 500 rpm may cause delamination of the filler-matrix interface and reduce the compressive strength; the stirring paddle may be anchor type or blade type to avoid uneven dispersion caused by central vortex.

[0086] Furthermore, in step S4, the magnetic field drives the CNT / graphene to align along the direction of the magnetic field lines, such as Figure 2 As shown, a conductive path is formed throughout the polyurethane prepolymer I during the curing process to lock the filler orientation and reduce the resistivity to <10Ω·cm.

[0087] Furthermore, in step S4, the magnetic field is oriented, and when the magnetic field intensity is <0.5T, the orientation degree is <50%, and when it is >1.5T, filler aggregation is triggered; the humidity of the curing environment needs to be ≤60% to prevent moisture from interfering with the cross-linking reaction.

[0088] Furthermore, in step S5, the layer-by-layer pouring is performed, and impurities on the surface of the sensing layer need to be removed before pouring to ensure that there are no bubbles or contamination on the interface; the curing environment needs to be light-proof to prevent ultraviolet rays from causing degradation of the matrix.

[0089] Furthermore, in step S6, the post-treatment requires plasma cleaning of the substrate surface before spraying (power 50W, time 1 min) to improve the coating adhesion; a heat treatment temperature > 80°C will cause the polyurethane substrate to soften, and < 50°C will result in incomplete curing.

[0090] This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0091] Example 1

[0092] A self-sensing polyurethane road repair material based on a gradient conductive network has a preparation method comprising: compounding fillers in a mass ratio of CNT: graphene: carbon black = 2:1:8, with a total addition amount of 25wt%; mixing the CNT / graphene with prepolymer I and ultrasonically dispersing the mixture, injecting it into a mold and curing it in a 1.0T magnetic field for 3 hours; pouring the carbon black / prepolymer II mixture, curing it at room temperature, and then coating it with a hydrophobic coating.

[0093] Among them, the base material polyurethane component A (isocyanate) is produced by Wanhua Chemical, and the polyurethane component B (polyol) is produced by Wanhua Chemical, with a hydroxyl value of 50 mg KOH / g.

[0094] Conductive filler: Carbon nanotubes (CNTs) are produced from Shenzhen Nanoport, with a diameter of 15nm and a purity of >95%. Graphene is produced from Ningbo Moxi Technology, with a sheet thickness of 3nm and a specific surface area of 800m 2 / g; micron-grade carbon black was produced by Cabot Corporation, with a particle size of 3μm.

[0095] Functional additives: Hydrophobic modified silica is produced by Evonik Industries, and trimethylolpropane (cross-linking agent) is produced by Sinopharm Group.

[0096] The preparation method of the self-sensing polyurethane road repair material includes the following steps:

[0097] S1: Filler pretreatment: CNT and graphene were placed in a plasma treatment instrument (Zhongke Instrument, PECVD-300) with a power of 250 W and a treatment time of 12 min to enhance the surface activity.

[0098] S2: Sensing layer preparation: pretreated CNT (2 wt%) and graphene (1 wt%) were mixed with polyurethane prepolymer I and ultrasonically dispersed (40 kHz, 35 min);

[0099] S3: Preparation of mechanical layer: Mix micron carbon black (8 wt%) with polyurethane prepolymer II and stir mechanically at low speed (250 rpm, 25 min).

[0100] S4: Magnetic field orientation: inject the sensing layer mixture into the mold, apply a 1.0T vertical magnetic field, and cure for 3 hours.

[0101] S5: Layer-by-layer pouring: pour the mechanical layer mixture on the solidified sensing layer and solidify it at room temperature (25±2°C) for 36 hours.

[0102] S6: Post-treatment: coating with a hydrophobic modified silica coating (thickness 80 μm, contact angle ≥ 120°), and heat treatment at 70° C. for 1.5 hours.

[0103] In this embodiment, the mechanical properties test method of cement concrete specimens in the "Testing Procedures for Cement and Cement Concrete in Highway Engineering" (JTG E30-2005) was used to measure the compressive strength of the self-perceived polyurethane road repair material specimen to be 58 MPa and the elongation at break to be 235%.

[0104] In this embodiment, the electrical performance of the self-sensing polyurethane road repair material was tested in accordance with the "Method for Measuring the Resistivity of Metallic Materials" (GB / T 351-2019). The strain sensing sensitivity (GF) was 4.3 (linearity R at 200% strain). 2 =0.95), resistance drift rate is 4.2% / year (-30℃ to 60℃ cycle 100 times)

[0105] In this example, the weather resistance of polyurethane road repair materials was tested with reference to the "Determination of Freeze-Thaw Cycling Resistance of Building Coatings" (JG / T 25-2017). The measured signal error at 95% humidity was ±4.1%, and the resistance fluctuation after freeze-thaw cycles was ±2.8%.

[0106] Comparative Example 1

[0107] Traditional road repair materials: epoxy resin and concrete were selected, and specimens were prepared for testing according to the requirements of the above test method.

[0108] Comparative Example 2

[0109] The conductive filler system using only a single carbon nanotube was prepared according to the same steps as in Example 1, and test pieces were prepared and tested according to the requirements of the above test method.

[0110] Comparative Example 3

[0111] A conductive filler system containing only carbon black as filler was prepared according to the same steps as in Example 1, and test pieces were prepared and tested according to the requirements of the above test method.

[0112] The evaluation results show that:

[0113] Compared with traditional road repair materials, the strength is 10-30% higher than that of epoxy resin and concrete (Comparative Example 1), and the repair and monitoring functions can be integrated into a single material, reducing construction costs; compared with a single filler system (Comparative Examples 2 and 3), the continuous conductive network collaboratively constructed by nano-micrometers coordinates the mechanical properties, and the magnetic field orientation process solves the problem of uneven filler dispersion in thick-section materials, so that the resistance drift rate of the material prepared in Example 1 is reduced by 75%.

[0114] Example 2

[0115] A self-sensing polyurethane road repair material based on a gradient conductive network has a preparation method comprising: adjusting the filler ratio to CNT: graphene: carbon black = 3:2:10, with a total addition amount of 30wt%; mixing the CNT / graphene with prepolymer I and ultrasonically dispersing the mixture; injecting the mixture into a mold and applying a 1.5T magnetic field to enhance orientation; and curing the mixture for 4 hours; pouring the carbon black / prepolymer II mixture, curing it at room temperature, and then coating it with a hydrophobic coating.

[0116] The sources of materials refer to Example 1.

[0117] The preparation method of the self-sensing polyurethane road repair material includes the following steps:

[0118] S1: Filler pretreatment: CNT and graphene were placed in a plasma treatment instrument (Zhongke Instrument, PECVD-300) with a power of 250 W and a treatment time of 12 min to enhance the surface activity.

[0119] S2: Sensing layer preparation: pretreated CNT (2 wt%) and graphene (1 wt%) were mixed with polyurethane prepolymer I and ultrasonically dispersed (40 kHz, 35 min);

[0120] S3: Preparation of mechanical layer: Mix micron carbon black (8 wt%) with polyurethane prepolymer II and stir mechanically at low speed (250 rpm, 25 min).

[0121] S4: Magnetic field orientation: inject the sensing layer mixture into the mold, apply a 1.5T enhanced magnetic field, and cure for 4 hours.

[0122] S5: Layer-by-layer pouring: pour the mechanical layer mixture on the solidified sensing layer and solidify it at room temperature (25±2°C) for 36 hours.

[0123] S6: Post-treatment: coating with a hydrophobic modified silica coating (thickness 100 μm, contact angle ≥ 125°), and heat treatment at 70° C. for 1.5 hours.

[0124] In this embodiment, the mechanical properties test method of cement concrete specimens in the "Testing Procedures for Cement and Cement Concrete in Highway Engineering" (JTG E30-2005) was used to measure the compressive strength of the self-perceived polyurethane road repair material specimen to be 62 MPa and the elongation at break to be 210%.

[0125] In this embodiment, the electrical performance of the self-sensing polyurethane road repair material was tested in accordance with the "Method for Measuring the Resistivity of Metallic Materials" (GB / T 351-2019). The strain sensing sensitivity (GF) was 3.8 (linearity R at 200% strain). 2 =0.93), resistance drift rate is 3.5% / year (-30℃ to 60℃ cycle 100 times)

[0126] In this example, the weather resistance of polyurethane road repair materials was tested with reference to the "Determination of Freeze-Thaw Cycling Resistance of Architectural Coatings" (JG / T 25-2017). The measured signal error at 95% humidity was ±4.5%, and the resistance fluctuation after freeze-thaw cycles was ±3%.

[0127] The evaluation results show that compared with Example 1, the strength is increased by 6.9%, the sensitivity is reduced by 11.6%, and the other indicators are not much different.

[0128] Comparative Example 4

[0129] A self-sensing polyurethane road repair material based on a gradient conductive network, the preparation method of which includes: adjusting the filler ratio CNT: graphene: carbon black = 1:1:10, with a total addition amount of 20wt%; mixing the CNT / graphene with prepolymer I, and then dispersing them by low-speed stirring (speed of 150 rpm, time of 40 minutes), eliminating magnetic field orientation; pouring the carbon black / prepolymer II mixture, curing it at room temperature, and then applying a hydrophobic coating.

[0130] The sources of materials refer to Example 1.

[0131] The preparation method of the self-sensing polyurethane road repair material includes the following steps:

[0132] S1: Filler pretreatment: CNT and graphene were placed in a plasma treatment instrument (Zhongke Instrument, PECVD-300) with a power of 250 W and a treatment time of 12 min to enhance the surface activity.

[0133] S2: Preparation of sensing layer: pretreated CNT (2 wt%), graphene (1 wt%) and polyurethane prepolymer I were mixed and mechanically stirred at low speed (150 rpm, 40 min).

[0134] S3: Preparation of mechanical layer: Mix micron carbon black (8 wt%) with polyurethane prepolymer II and stir mechanically at low speed (150 rpm, 40 min).

[0135] S4: Layer-by-layer pouring: pour the mechanical layer mixture on the solidified sensing layer and solidify it at room temperature (25±2°C) for 36 hours.

[0136] S5: Post-treatment: coating with a hydrophobic modified silica coating (thickness 80 μm, contact angle ≥ 120°), and heat treatment at 70° C. for 1.5 hours.

[0137] In this embodiment, the self-perceived compressive strength of the polyurethane road repair material specimen was measured to be 48 MPa by combining the mechanical properties test method of cement concrete specimens in the "Testing Procedures for Cement and Cement Concrete in Highway Engineering" (JTG E30-2005).

[0138] In this embodiment, the electrical performance of the self-sensing polyurethane road repair material was tested in combination with the "Method for Measuring the Resistivity of Metal Materials" (GB / T 351-2019), and the strain sensing sensitivity (GF) was measured to be 2.5.

[0139] The evaluation results show that compared with Example 1, the strength is reduced by 17.2%, which can only meet the basic needs of road repair. At the same time, its sensitivity is reduced by 41.9%, which is only applicable to low-precision monitoring scenarios.

[0140] Example 3

[0141] This embodiment is basically the same as Example 1, with the main difference being that the compound filler is prepared in a mass ratio of CNT: graphene: carbon black = 1:1:5, with a total addition amount of 20 wt%; and orientation is then carried out in a 0.5 T vertical magnetic field for 4 hours; the other parameters remain unchanged, and the performance test results of the prepared repair material are slightly worse than those of Example 1, which will not be repeated here.

[0142] Example 4

[0143] This embodiment is basically the same as Example 1, with the main differences being that the total amount of the composite filler added is 35 wt%; orientation is then performed in a 1.2 T vertical magnetic field for 2 hours; the other parameters remain unchanged, and the performance test results of the prepared repair material are basically equivalent to those in Example 1, which will not be repeated here.

[0144] Example 5

[0145] This example is essentially the same as Example 1, with the following main differences: in step S1, the plasma treatment power was 200 W for 15 minutes; in step S2, the ultrasonic dispersion was performed for 30 minutes; in step S3, the low-speed mechanical stirring was performed at 200 rpm for 30 minutes; in step S5, the curing time was 48 hours; and in step S6, the hydrophobic modified silica coating had a thickness of 50 μm, and the heat treatment temperature was 80°C for 1 hour. The performance test results of the resulting repair material were essentially equivalent to those of Example 1 and are not further detailed here.

[0146] Example 6

[0147] This embodiment is essentially the same as Example 1, with the following main differences: in step S1, the plasma treatment power is 300 W and the duration is 10 minutes; in step S2, the ultrasonic dispersion duration is 40 minutes; in step S3, the low-speed mechanical stirring speed is 300 rpm and the duration is 20 minutes; in step S5, the curing duration is 24 hours; and in step S6, the heat treatment temperature is 60°C and the duration is 2 hours. The performance test results of the resulting repair material are essentially equivalent to those of Example 1 and are not further described here.

[0148] The above description of the embodiments is intended to facilitate understanding and use of the invention by those skilled in the art. It will be apparent that those skilled in the art can readily make various modifications to these embodiments and apply the general principles described herein to other embodiments without requiring inventive effort. Therefore, the present invention is not limited to the above-described embodiments. Improvements and modifications made by those skilled in the art based on the disclosure of the present invention, without departing from the scope of the present invention, should be within the scope of protection of the present invention.

Claims

1. A self-sensing polyurethane road repair material, characterized in that: comprising a sensing layer and a supporting layer arranged in a stacked manner; The repair material is based on polyurethane, wherein: The sensing layer is filled with conductive nanofillers arranged in a direction, and the orientation degree of the conductive nanofillers is greater than 80%; The support layer is filled with conductive micron-sized fillers; The conductive nanofiller and the conductive micron-sized filler form a gradient conductive network in the repair material; The surface of the repair material is also coated with a surface coating, which is a hydrophobic coating.

2. The self-sensing polyurethane road repair material according to claim 1, characterized in that: The polyurethane is obtained from a two-component polyurethane prepolymer through a crosslinking reaction, wherein the two-component polyurethane prepolymer consists of component A: isocyanate and component B: polyol with a hydroxyl value of 45-60 mg KOH / g.

3. The self-sensing polyurethane road repair material according to claim 2, characterized in that: In the cross-linking reaction, component A and component B are mixed and reacted in a volume ratio of 1:

1. The cross-linking agent used in the cross-linking reaction includes trimethylolpropane, and the amount of the cross-linking agent is 1-3wt% of the mass of the base material.

4. The self-sensing polyurethane road repair material according to claim 1, characterized in that: The conductive nanofiller includes carbon nanotubes with a diameter of 10-20 nm and graphene with a sheet thickness of less than 5 nm, and the conductive micron-sized filler includes micron-sized carbon black with a particle size of 1-5 μm; The mass ratio of the carbon nanotubes, graphene and micron-sized carbon black is 1-3:1-2:5-10; The total addition amount of the conductive nano-filler and the conductive micron-size filler is 20-35 wt% of the mass of the matrix material.

5. The self-sensing polyurethane road repair material according to claim 1, characterized in that: The surface coating is a modified silicon dioxide coating.

6. The self-sensing polyurethane road repair material according to claim 1, characterized in that: The thickness of the sensing layer is 1-3 mm, the thickness of the supporting layer is 5-10 mm, the thickness of the surface coating is 50-100 μm, and the contact angle of the surface coating is not less than 120°.

7. A method for preparing the self-sensing polyurethane road repair material according to any one of claims 1 to 6, characterized in that: The steps include: S1: plasma treatment of conductive nanofillers; S2: mixing the conductive nanofiller pretreated in step S1 with a portion of the polyurethane prepolymer, and then ultrasonically dispersing the mixture to obtain a conductive nanofiller mixed solution; S3: mixing the conductive micron-sized filler with the remaining portion of the polyurethane prepolymer, followed by low-speed mechanical stirring to obtain a conductive micron-sized filler mixed solution; S4: injecting the conductive nanofiller mixture obtained in step S2 into a mold, applying a vertical magnetic field to the mold to align the conductive nanofillers, and simultaneously adding a crosslinking agent to the conductive nanofiller mixture for curing to obtain a sensing layer; S5: pouring the conductive micron-sized filler mixture obtained in step S3 onto the surface of the sensing layer obtained in step S4, and curing at room temperature; S6: coating the surface of the semi-finished repair material obtained by curing in step S5 with a surface coating, followed by heat treatment to obtain the repair material.

8. The method for preparing a self-sensing polyurethane road repair material according to claim 7, characterized in that: Include one or more of the following: i) in step S1, the power of the plasma treatment is 200-300 W, and the time is 10-15 min; ii) in step S2, the ultrasonic dispersion time is 30-40 min; iii) in step S3, the low-speed mechanical stirring is performed at a speed of 200-300 rpm for 20-30 min, and the stirring paddle is an anchor type or a paddle type; iv) in step S4, the intensity of the magnetic field is 0.5-1.5 T, and the curing time is 2-4 hours; v) In step S5, the curing time is 24-48 hours; vi) In step S6, the heat treatment temperature is 60-80° C. and the time is 1-2 hours.

9. The method for preparing a self-sensing polyurethane road repair material according to claim 8, characterized in that: In step S4, the intensity of the magnetic field is 1.0-1.5T.

10. Use of the self-sensing polyurethane road repair material according to any one of claims 1 to 6 in road health monitoring.

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