A self-sensing polyurethane road repair material, its preparation method and application

Abstract

This invention belongs to the field of smart materials technology, specifically relating to a self-sensing polyurethane road repair material, its preparation method, and its application. The repair material includes a layered sensing layer and a support layer. The repair material uses polyurethane as the matrix material, wherein: the sensing layer is filled with oriented conductive nanofillers with an orientation degree greater than 80%; the support layer is filled with conductive micron-sized fillers; the conductive nanofillers and conductive micron-sized fillers form a gradient conductive network; the surface of the repair material is coated with a surface coating, which is a hydrophobic coating. Compared with existing technologies, this invention solves the problem that while existing self-sensing polyurethane road repair materials have superior mechanical strength, their sensitivity is poor. This solution uses a two-component polyurethane matrix, compounded with nano- to micron-sized conductive fillers, and constructs a multi-scale conductive network through gradient structure design and magnetic field orientation technology, achieving synergistic optimization of mechanical strength, strain sensitivity, and environmental stability.

Description

Technical Field

[0001] This invention belongs to the field of smart materials technology, specifically relating to a self-sensing polyurethane road repair material, its preparation method, and its application. Background Technology

[0002] Smart materials are a class of advanced functional materials capable of sensing environmental stimuli and responding proactively, with properties that can reversibly change with external conditions such as temperature, pressure, electric fields, or magnetic fields. Among numerous smart materials, self-sensing polyurethane has attracted much attention due to its unique electromechanical response characteristics, and in recent years has demonstrated significant application value in structural health monitoring, flexible electronics, and intelligent robotics.

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

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

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

[0006] (1) Imbalance between 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 are prone to agglomeration in thick cross-section materials, resulting in discontinuous conductive networks and signal drift rate as high as 35% / year;

[0008] (3) Severe environmental interference: temperature and humidity fluctuations cause matrix expansion, which masks 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 conductivity of conductive asphalt and the incorporation of carbon-based fillers to accelerate microcrack formation 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 mechanical strength (compressive strength > 50 MPa) to some extent, but this solution sacrifices sensitivity (strain coefficient GF < 2.5) and is prone to microcracks due to stress concentration.

[0011] Therefore, there is a need to develop a novel road repair material that can be used on polyurethane roads and has self-sensing properties, high compressive strength, and high sensitivity. Summary of the Invention

[0012] The purpose of this invention is to address at least one of the aforementioned problems by providing a self-sensing polyurethane road repair material, its preparation method, and its application. This addresses the issue that while existing self-sensing polyurethane road repair materials possess superior mechanical strength, their sensitivity is relatively poor. This solution uses a two-component polyurethane matrix, compounded with nano- to micron-scale conductive fillers (carbon nanotubes, graphene, and carbon black). Through gradient structure design and magnetic field orientation processes, a multi-scale conductive network is constructed, achieving synergistic optimization of mechanical strength, strain sensitivity, and environmental stability.

[0013] The objective of this invention is achieved through the following technical solution:

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

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

[0016] The sensing layer is filled with oriented conductive nanofillers, and the orientation degree of the conductive nanofillers is greater than 80%.

[0017] The support layer is filled with conductive micron-sized filler.

[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] The directional arrangement is arranged along the thickness direction of the sensing layer.

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

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

[0023] Preferably, 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.

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

[0025] The total amount of the conductive nanofiller and conductive micron-sized filler added is 20-35 wt% of the matrix material.

[0026] Preferably, the surface coating is a modified silica coating, wherein the amount of modified silica added is 0.5-2 wt% of the matrix material.

[0027] Preferably, the thickness of the sensing layer is 1-3 mm, the thickness of the support 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] A second aspect of this invention discloses a method for preparing a self-sensing polyurethane road repair material as described in any of the above descriptions, comprising the following steps:

[0029] S1: Plasma treatment of conductive nanofillers;

[0030] S2: The conductive nanofiller pretreated in step S1 is mixed with a portion of the polyurethane prepolymer, and then ultrasonically dispersed to obtain a conductive nanofiller mixture.

[0031] S3: Mix the conductive micron-sized filler with the remaining polyurethane prepolymer, and then stir at low speed to obtain a conductive micron-sized filler mixture.

[0032] S4: Inject the conductive nanofiller mixture obtained in step S2 into the mold, apply a vertical magnetic field to the mold to orient the conductive nanofiller (along the thickness direction of the sensing layer), and at the same time, add a crosslinking agent to the conductive nanofiller mixture for curing to obtain the sensing layer.

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

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

[0035] Preferably, it includes one or more of the following:

[0036] i) In step S1, the plasma treatment power is 200-300 W and the time is 10-15 min; by bombarding the surface of the nanofiller with plasma, oxygen-containing functional groups (-COOH, -OH) can be generated, which enhances the interfacial bonding force with the polyurethane matrix; at the same time, it can also remove impurities (such as residual catalysts and organic solvents) adsorbed on the filler surface and improve the purity of the conductive network.

[0037] ii) In step S2, the ultrasonic dispersion time is 30-40 min; local high pressure is generated through ultrasonic cavitation effect to break up the CNT / graphene aggregates (aggregate size <200 nm).

[0038] iii) In step S3, the speed of the low-speed mechanical stirring is 200-300 rpm and the time is 20-30 min. The stirring paddle is an anchor type or a paddle type. Low-speed mechanical stirring avoids high-speed shearing damage to the structure of micron-sized carbon black.

[0039] iv) In step S4, the strength 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 ℃ and the time is 1-2 hours.

[0042] Furthermore, in step S1, the plasma treatment, if the treatment time is >15 minutes, will cause damage to the nanostructure, while if it is <5 minutes, the modification effect will be insufficient.

[0043] Furthermore, in step S2, if the ultrasonic dispersion time is too long (>50 minutes), it will damage the polyurethane molecular chains and cause the matrix material to crosslink prematurely; the mixing temperature is preferably maintained at 25±2 ℃ to prevent local overheating from causing side reactions.

[0044] Furthermore, in step S3, the low-speed mechanical stirring, with a rotation speed >500 rpm, will cause the filler-matrix interface to peel off, reducing the compressive strength; the stirring paddle is selected as either anchor type or blade type to avoid uneven dispersion caused by central vortex.

[0045] Furthermore, in step S4, the magnetic field strength is <0.5 T when the orientation degree is <50%. The orientation degree describes the degree to which the filler is aligned with the target direction in the polyurethane. When the orientation degree is less than 50%, it will lead to defects such as incomplete conductive network, reduced sensing sensitivity and unstable mechanical properties. If it is >1.5 T, it will cause filler aggregation. The curing environment humidity needs to be ≤60% to prevent moisture from interfering with the crosslinking reaction.

[0046] Furthermore, in step S5, the pouring is done layer by layer. Before pouring, impurities on the surface of the sensing layer must be removed to ensure that there are no bubbles or contamination at the interface. The curing environment must be protected from light to prevent ultraviolet rays from causing degradation of the matrix material.

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

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

[0049] The third aspect of this invention discloses the application of a self-sensing polyurethane road repair material as described above in road health monitoring.

[0050] Preferably, the resistivity drift rate of the repair material is <5% / year, and the temperature tolerance range is -30℃ to 60℃.

[0051] The working principle of this invention is as follows:

[0052] This invention employs a two-component polyurethane matrix, constructing a gradient conductive network by combining nanoscale (formed by magnetic field orientation curing to form a high-sensitivity sensing layer with an orientation degree >80%) and microscale (formed by low-speed mechanical stirring dispersion to form a mechanical support layer, which is then cast layer by layer onto the high-sensitivity sensing layer) conductive fillers. This is further enhanced by a hydrophobic modified silica surface coating and precise control of crosslinking and curing processes to effectively isolate environmental interference and stabilize resistance signals. Each design unit works in concert, synergistically enhancing performance. In particular, the highly oriented arrangement of the nanofillers in the repair material not only provides a sensitive electrical signal response but also lays a continuous conductive channel for the layer-by-layer cast microscale fillers. Simultaneously, the uniform dispersion of the microscale fillers effectively improves compressive strength. This not only achieves coordinated optimization of mechanical strength, strain sensitivity, and environmental stability, significantly optimizing the material's mechanical, sensing, and environmental stability, but also effectively avoids filler agglomeration and stress concentration, ensuring the material's comprehensive superior performance in road repair and health monitoring.

[0053] Gradient structure design:

[0054] Multi-scale conductive network: A high-sensitivity sensing layer is constructed using nanofillers (CNT / graphene), and a mechanical support layer is enhanced using microfillers (carbon black).

[0055] Directional dispersion process: Magnetic field orientation technology (magnetic field strength 0.5-1.5 T) is used to achieve the 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: By modifying hydrophobicity and controlling crosslinking density, 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] This invention discloses a self-sensing polyurethane road repair material based on a gradient conductive network. Using a two-component polyurethane matrix, it is compounded with nano- to micro-scale conductive fillers (carbon nanotubes, graphene, and carbon black). Through gradient structure design and magnetic field orientation technology, a multi-scale conductive network is constructed, achieving high mechanical strength (compressive strength ≥ 55 MPa) and high strain sensitivity (GF ≥ 4.0). Simultaneously, combined with hydrophobic modification and crosslinking density control, it significantly reduces temperature and humidity interference, achieving environmental stability (signal error < ± 5%). Ultimately, it achieves synergistic optimization of mechanical strength, strain sensitivity, and environmental stability.

[0059] This invention solves the problems of mechanical-electrical performance imbalance, discontinuous conductive network and high signal drift rate of existing self-sensing materials in road repair scenarios. It is suitable for complex field conditions and for integrated application of structural repair and health monitoring of intelligent roads. Attached Figure Description

[0060] Figure 1 A schematic diagram of the gradient conductive network in the repair material;

[0061] Figure 2 This is a schematic diagram of a magnetic field orientation device (applying a vertical magnetic field to orient conductive nanofillers).

[0062] Figure 3 This is a schematic diagram of the process for preparing repair materials. Detailed Implementation

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

[0064] Unless otherwise specified, the products used in the following description are conventional commercial products in the field, and the methods used are common knowledge in the field. Any matters not covered herein may be handled using existing technology.

[0065] A self-sensing polyurethane road repair material based on a gradient conductive network, comprising the following component base contents:

[0066] Matrix material: Two-component polyurethane prepolymer (component A: isocyanate; component B: polyol, hydroxyl value 45-60mg KOH / g), component A and component B are mixed in a 1:1 volume ratio;

[0067] Conductive filler: A nano-micro composite system comprising carbon nanotubes (CNTs, diameter 10-20 nm), 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.

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

[0069] Gradient structure design:

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

[0071] Directional dispersion process: Magnetic field orientation technology (magnetic field strength 0.5-1.5 T) is used to achieve the 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: By modifying hydrophobicity and controlling crosslinking density, 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 gradient conductive networks, such as... Figure 3 As shown, it includes the following steps:

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

[0075] S2: Mix the nanofiller (CNT / graphene) with polyurethane prepolymer I (partial polyurethane prepolymer) and disperse it ultrasonically (frequency 40 kHz, time 30-40 min).

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

[0077] S4: Magnetic field orientation: Inject the nanofiller mixture into the mold, apply a vertical magnetic field (0.5-1.5 T) to orient the filler, and form a sensing layer after curing (2-4 hours);

[0078] S5: Layer-by-layer casting: Micron-level filler mixture is cast onto the sensing layer and cured at room temperature for 24-48 hours to form a mechanically reinforcing layer;

[0079] S6: Post-treatment: Coat the material surface with a coating made of hydrophobic modified silica, and heat treat at 60-80 ℃ 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), enhancing the interfacial bonding force with the polyurethane matrix; it also removes impurities (such as residual catalysts and organic solvents) adsorbed on the filler surface, improving the purity of the conductive network.

[0081] Furthermore, in step S1, the plasma treatment, if the treatment time is >15 minutes, will cause damage to the nanostructure, and if it is <5 minutes, the modification effect will be insufficient.

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

[0083] Furthermore, in step S2, if the ultrasonic dispersion time is too long (>50 minutes), it will damage the polyurethane molecular chains and cause the matrix material to crosslink prematurely; the mixing temperature is maintained at 25±2℃ to prevent local overheating from causing side reactions.

[0084] Furthermore, in step S3, the low-speed mechanical stirring avoids high-speed shearing from damaging 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, will cause the filler-matrix interface to peel off, reducing the compressive strength; the stirring paddle is selected as either anchor type or blade type to avoid uneven dispersion caused by central vortex.

[0086] Further, in step S4, the magnetic field drives the CNTs / graphene to align along the magnetic field lines, such as... Figure 2 As shown, a through conductive path is formed; during the curing process, polyurethane prepolymer I locks the orientation of the filler, and the resistivity drops to <10 Ω·cm.

[0087] Furthermore, in step S4, the magnetic field orientation is such that when the magnetic field strength is <0.5 T, the orientation degree is <50%, and when it is >1.5 T, it will cause filler aggregation; the curing environment humidity needs to be ≤60% to prevent moisture from interfering with the crosslinking reaction.

[0088] Furthermore, in step S5, before pouring the layer-by-layer concrete, impurities on the surface of the sensing layer must be removed to ensure that there are no bubbles or contamination at the interface; the curing environment must be protected from light to prevent ultraviolet rays from causing degradation of the substrate.

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

[0090] This embodiment is implemented based on the technical solution of the present invention, and provides detailed implementation methods and specific operation processes. However, the scope of protection of the present invention is not limited to the following embodiment.

[0091] Example 1

[0092] A self-sensing polyurethane road repair material based on a gradient conductive network is prepared by the following steps: a filler compound is prepared according to a mass ratio of CNT:graphene:carbon black = 2:1:8, with a total addition amount of 25 wt%; CNT / graphene is mixed with prepolymer I and ultrasonically dispersed, injected into a mold and cured for 3 hours under a 1.0 T magnetic field; a carbon black / prepolymer II mixture is poured, cured at room temperature, and then coated with a hydrophobic coating.

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

[0094] Conductive fillers: Carbon nanotubes (CNTs) are sourced from Shenzhen Nanoport, with a diameter of 15 nm and a purity >95%; graphene is sourced from Ningbo Moxi Technology, with a sheet thickness of 3 nm and a specific surface area of ​​800 m². 2 / g; Micron-sized carbon black from Cabot Corporation, with a particle size of 3 μm.

[0095] Functional additives: Hydrophobic modified silica is produced by Evonik Industries, and trimethylolpropane (crosslinking 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: CNTs and graphene are 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 surface activity.

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

[0099] S3: Preparation of mechanical layer: Micron-sized carbon black (8 wt%) is mixed with polyurethane prepolymer II and mechanically stirred at low speed (250 rpm, 25 min).

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

[0101] S5: Layer-by-layer pouring: Pour the mechanical layer mixture onto the cured sensing layer and cure at room temperature (25±2℃) for 36 hours.

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

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

[0104] This embodiment combines the "Methods for Measuring Resistivity of Metallic Materials" (GB / T 351-2019) to test the electrical properties of self-sensing polyurethane road repair material, and the strain sensing sensitivity (GF) was measured to be 4.3 (linearity R at 200% strain). 2 =0.95), resistivity drift rate is 4.2% / year (100 cycles from -30℃ to 60℃).

[0105] In this embodiment, the weather resistance of polyurethane road repair material was tested according to the "Determination of Freeze-Thaw Cycling Resistance of Architectural 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 in accordance with the requirements of the above testing methods.

[0108] Comparative Example 2

[0109] The filler uses a conductive filler system with only a single carbon nanotube, prepared according to the same steps as in Example 1, and the specimens were prepared for testing in accordance with the requirements of the above test methods.

[0110] Comparative Example 3

[0111] The filler used was a conductive filler system with only carbon black, prepared according to the same steps as in Example 1, and the test specimens were prepared and tested in accordance with the requirements of the above test methods.

[0112] The evaluation results show that:

[0113] Compared to traditional road repair materials, the strength is increased by 10-30% compared to epoxy resin and concrete (Comparative Example 1), and the repair and monitoring functions can be integrated into a single material, reducing construction costs. Compared to single filler systems (Comparative Examples 2 and 3), the continuous conductive network constructed by nano-micro synergy coordinates mechanical properties. Furthermore, the magnetic field orientation process solves the problem of uneven filler dispersion in thick-section materials, resulting in a 75% reduction in the resistivity drift of the material prepared in Example 1.

[0114] Example 2

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

[0116] The source of materials is the same as in Example 1.

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

[0118] S1: Filler pretreatment: CNTs and graphene are 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 surface activity.

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

[0120] S3: Preparation of mechanical layer: Micron-sized carbon black (8 wt%) is mixed with polyurethane prepolymer II and mechanically stirred at low speed (250 rpm, 25 min).

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

[0122] S5: Layer-by-layer pouring: Pour the mechanical layer mixture onto the cured sensing layer and cure at room temperature (25±2℃) for 36 hours.

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

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

[0125] This embodiment combines the "Methods for Measuring Resistivity of Metallic Materials" (GB / T 351-2019) to test the electrical properties of self-sensing polyurethane road repair material, and the strain sensing sensitivity (GF) was measured to be 3.8 (linearity R at 200% strain). 2 =0.93), resistivity drift rate is 3.5% / year (100 cycles from -30℃ to 60℃).

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

[0127] The evaluation results show that compared with Example 1, the strength increased by 6.9%, the sensitivity decreased by 11.6%, and the other indicators were not significantly different.

[0128] Comparative Example 4

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

[0130] The source of materials is the same as in Example 1.

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

[0132] S1: Filler pretreatment: CNTs and graphene are 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 surface activity.

[0133] S2: Sensing layer preparation: Pretreated CNTs (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: Micron-sized carbon black (8 wt%) is mixed with polyurethane prepolymer II and mechanically stirred at low speed (150 rpm, 40 min).

[0135] S4: Layer-by-layer pouring: Pour the mechanical layer mixture onto the cured sensing layer and cure at room temperature (25±2℃) for 36 hours.

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

[0137] In this embodiment, the compressive strength of the self-sensing polyurethane road repair material specimen was measured to be 48 MPa, based on the mechanical property testing method for cement and cement concrete specimens in the "Test Procedures for Cement and Cement Concrete in Highway Engineering" (JTG E30-2005).

[0138] In this embodiment, the electrical properties of the self-sensing polyurethane road repair material were tested in accordance with the "Method for Measurement of Resistivity of Metallic 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 intensity 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 means it is only suitable for low-precision monitoring scenarios.

[0140] Example 3

[0141] This embodiment is basically the same as Example 1, the main difference being: the compound filler is added in a mass ratio of CNT:graphene:carbon black = 1:1:5, with a total addition amount of 20 wt%; then, it is oriented using 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 elaborated here.

[0142] Example 4

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

[0144] Example 5

[0145] This embodiment is basically the same as Embodiment 1, with the main differences being: in step S1, the plasma treatment power is 200 W for 15 min; in step S2, the ultrasonic dispersion time is 30 min; in step S3, the low-speed mechanical stirring speed is 200 rpm for 30 min; in step S5, the curing time is 48 h; and in step S6, the thickness of the hydrophobic modified silica coating is 50 μm, the heat treatment temperature is 80 ℃, and the time is 1 hour. The performance test results of the obtained repair material are basically the same as those of Embodiment 1, and will not be repeated here.

[0146] Example 6

[0147] This embodiment is basically the same as Embodiment 1, with the main differences being: in step S1, the plasma treatment power is 300 W for 10 min; in step S2, the ultrasonic dispersion time is 40 min; in step S3, the low-speed mechanical stirring speed is 300 rpm for 20 min; in step S5, the curing time is 24 h; and in step S6, the heat treatment temperature is 60℃ for 2 hours. The performance test results of the obtained repair material are basically the same as those of Embodiment 1, and will not be repeated here.

[0148] The above description of the embodiments is provided to enable those skilled in the art to understand and use the invention. It will be apparent to those skilled in the art that various modifications can be made to these embodiments, and the general principles described herein can be applied to other embodiments without inventive effort. Therefore, the present invention is not limited to the above embodiments, and any 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 invention should be within the protection scope of the present invention.

Claims

1. A self-sensing polyurethane road repair material, characterized in that, This includes a stacked sensing layer and a support layer; The repair material is based on polyurethane, wherein: The sensing layer is filled with oriented conductive nanofillers, the orientation degree of which is greater than 80%. The conductive nanofillers include carbon nanotubes with a diameter of 10-20 nm and graphene with a sheet thickness of less than 5 nm. The mass ratio of carbon nanotubes, graphene, and micron-sized carbon black is 1-3:1-2:5-10. The total addition amount of the conductive nanofillers and conductive micron-sized fillers is 20-35 wt% of the matrix material. The support layer is filled with conductive micron-sized filler; the conductive micron-sized filler includes micron-sized carbon black with a particle size of 1-5 μm. The conductive nanofiller and the conductive micron-sized filler form a multi-scale 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: a modified silica coating; The repair material is prepared through the following steps: S1: Plasma treatment of conductive nanofillers; S2: The conductive nanofiller pretreated in step S1 is mixed with a portion of the polyurethane prepolymer, and then ultrasonically dispersed to obtain a conductive nanofiller mixture. S3: Mix the conductive micron-sized filler with the remaining polyurethane prepolymer, and then stir at low speed to obtain a conductive micron-sized filler mixture. S4: Inject the conductive nanofiller mixture obtained in step S2 into the mold, apply a vertical magnetic field to the mold to orient the conductive nanofiller, and at the same time, add a crosslinking agent to the conductive nanofiller mixture for curing to obtain the sensing layer. S5: Pour the conductive micron-sized filler mixture obtained in step S3 onto the surface of the sensing layer obtained in step S4, and cure at room temperature; S6: The surface of the semi-finished repair material obtained in step S5 is coated with a surface coating, followed by heat treatment to obtain the repair material.

2. The self-sensing polyurethane road repair material according to claim 1, characterized in that, The polyurethane is obtained by crosslinking 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.

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

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

4. 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 support 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°.

5. The self-sensing polyurethane road repair material according to claim 1, characterized in that, Includes 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 speed of the low-speed mechanical stirring is 200-300 rpm, the time is 20-30 min, and the stirring paddle is an anchor type or a paddle type. iv) In step S4, the strength 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 ℃ and the time is 1-2 hours.

6. The self-sensing polyurethane road repair material according to claim 5, characterized in that, In step S4, the strength of the magnetic field is 1.0-1.5 T.

7. The application of a self-sensing polyurethane road repair material as described in any one of claims 1-6 in road health monitoring.

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