Low-Temperature Crack-Resistant High-Stability SBS Modified Asphalt and Its Preparation Method

Abstract

This invention relates to the field of asphalt preparation technology, specifically disclosing a low-temperature crack-resistant, highly stable SBS modified asphalt and its preparation method. The asphalt comprises 100 parts of base asphalt; 4-6 parts of styrene-butadiene-styrene block copolymer; 0.8-1.5 parts of low-temperature toughening agent; 0.1-0.3 parts of compatibility stabilizer; 0.05-0.2 parts of anti-aging agent; and 0.3-1.5 parts of secondary elastomer. The low-temperature toughening agent includes dibutyl phthalate and epoxidized soybean oil; the compatibility stabilizer is sulfur; and the secondary elastomer is a polyolefin elastomer. This invention uses an ESO+DBP polar flexible bridge compound, combined with POE to construct a flexible-rigid three-dimensional network, effectively solving the problems of poor component compatibility, modifier segregation and agglomeration, easy cracking at ultra-low temperatures, and insufficient thermal conductivity and anti-aging properties.

Description

Technical Field

[0001] This invention relates to the field of asphalt preparation technology, specifically to a low-temperature crack-resistant, highly stable SBS modified asphalt and its preparation method. Background Technology

[0002] The base asphalt used in cold-region roads exhibits high low-temperature brittleness and temperature sensitivity. Conventional SBS-modified asphalt relies solely on simple SBS vulcanization and crosslinking modification, resulting in a single component and poor interfacial compatibility. During the modification process, SBS is prone to agglomeration and floating, leading to significant segregation during system storage. Furthermore, it lacks synergistic structures such as polar toughening, nano-skeleton support, low-temperature slow-release, and thermally conductive anti-aging properties, making it difficult to simultaneously achieve low-temperature crack resistance, high-temperature rutting resistance, and long-term anti-aging performance, thus failing to meet the requirements of high-altitude, large-temperature-difference, and long-life road surfaces. To address this issue, existing technologies mostly improve performance through simple vulcanization and crosslinking by simply increasing the SBS content, adding a small amount of plasticizer, or using a single inorganic powder filler. The process relies solely on preparation based on fixed shear and development parameters; simply increasing the SBS content increases costs and still results in floating and segregation. Therefore, how to provide a multi-component synergistically modified SBS asphalt suitable for cold-region roads is the technical problem this invention aims to solve. Summary of the Invention

[0003] The purpose of this invention is to provide a low-temperature crack-resistant, highly stable SBS modified asphalt and its preparation method, so as to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: A low-temperature crack-resistant, highly stable SBS modified asphalt, comprising, by weight: 100 parts of base asphalt; 4-6 parts of styrene-butadiene-styrene block copolymer; 0.8-1.5 parts of low-temperature toughening agent; 0.1-0.3 parts of compatibility stabilizer; 0.05-0.2 parts of anti-aging agent; 0.3-1.5 parts of secondary elastomer; wherein the low-temperature toughening agent includes dibutyl phthalate and epoxidized soybean oil; the compatibility stabilizer is sulfur; and the secondary elastomer is a polyolefin elastomer.

[0005] As a further embodiment of the present invention: the modified asphalt further includes: 0.3-1.0 parts of nano-layered reinforcing material; 0.2-0.6 parts of reactive structural reinforcing agent; the nano-layered reinforcing material is organic modified nano-montmorillonite; the reactive structural reinforcing agent is low molecular weight reactive polyamide.

[0006] As a further aspect of the present invention, the modified asphalt further includes: 0.5-2.0 parts of a microcapsule-type flexible modifier; the microcapsule-type flexible modifier is a phase change microcapsule encapsulating low-temperature flowing oil.

[0007] As a further aspect of the present invention, the modified asphalt further includes 0.02-0.1 parts of thermally conductive enhanced nanomaterials; the thermally conductive enhanced nanomaterials are graphene or its derivatives.

[0008] The present invention also provides a method for preparing the aforementioned low-temperature crack-resistant, high-stability SBS modified asphalt, the preparation method comprising: Step S1: Heat the base asphalt to 135-145℃ and maintain a constant temperature; Step S2: Under stirring conditions of 500 r / min, add styrene-butadiene-styrene block copolymer at a rate of 1 g / min, and stir at a constant temperature for 30-40 min to allow it to swell; Step S3: Perform high-speed shearing at 140-150℃, with a rotation speed of 3000-4500 r / min, for 40-60 min; Step S4: Add low-temperature toughening agent, compatibility stabilizer, anti-aging agent, secondary elastomer, nano-layered reinforcing material, reactive structural reinforcing agent, microencapsulated flexibility modifier and thermally conductive reinforcing nanomaterial in sequence, and shear at 1500-2000 r / min for 20-30 min; Step S5: Incubate at 130-140℃ for 60-120 minutes; Step S6: Allow to cool naturally to room temperature to obtain the finished product.

[0009] As a further aspect of the present invention, the preparation method further includes: Obtain production parameters, application environment parameters, and application status data for each batch of asphalt; Construct data pairs from production parameters to application status data, and cluster the data pairs based on application environment parameters; For each data pair corresponding to each application environment parameter, the probability of selecting different production parameters is determined based on the application status data, and a production parameter table for each application environment parameter is generated. When preparing asphalt, the production parameter table is queried based on the target environmental parameters, and the production parameters are determined based on the production parameter table.

[0010] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention uses ESO+DBP polar flexible bridge compound, combined with POE to construct a flexible-rigid three-dimensional network; it utilizes an organomontmorillonite layered skeleton to inhibit SBS flotation, and combines it with reactive polyamide to form a molecularly entangled composite structure; it achieves low-temperature self-release by adding microcapsules at a controlled temperature and low speed, releasing flexible components to alleviate low-temperature internal stress; and it is supplemented by ultrasonic pre-dispersion of graphene to form a two-dimensional layered structure. This effectively solves the problems of poor component compatibility, modifier segregation and agglomeration, easy cracking at ultra-low temperatures, and insufficient thermal conductivity and anti-aging properties, significantly reducing segregation difference, greatly improving low-temperature ductility and bending deformation capacity, improving thermal conductivity and heat dissipation and anti-aging performance, and achieving synergistic effects among components. The product's storage stability, high and low temperature road performance, and service durability are simultaneously improved, making it suitable for large-scale applications in cold and complex working conditions. Detailed Implementation

[0011] To make the technical problems, solutions, and beneficial effects of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0012] Example 1 In this embodiment of the invention, a low-temperature crack-resistant, highly stable SBS modified asphalt is provided. Based on 1 ton of finished product, the modified asphalt comprises: Base asphalt 975kg; using 70# road petroleum asphalt (Grade A), penetration (25℃) 60-80 (0.1mm), softening point ≥46℃, industrial grade drum / can; Styrene-butadiene-styrene block copolymer (SBS) modifier 50kg; using SBS1301 (linear structure), styrene content 28%-30%, Mooney viscosity (ML1+4, 100℃) 30-50, industrial grade particles (particle size ≤5mm). Low-temperature toughening agent (DBP) 10kg, specifically industrial grade, purity ≥99%, viscosity (25℃) 15-20mPa·s, in drums (sealed storage). Epoxidized soybean oil (ESO) 8kg, specifically industrial grade, epoxy value ≥6.0%, viscosity (25℃) 300-500mPa·s, in drums, no sediment; Sulfur (compatibility stabilizer) 1.5kg, specifically industrial grade, powder, 100 mesh, purity ≥98%, dry and free of lumps, packaged in bags; BHT (anti-aging agent) 1kg, specifically industrial grade, purity ≥99%, powder, bagged, store in a moisture-proof environment.

[0013] Its preparation method is as follows: Step S1: Preheating of base asphalt: Turn on the heat transfer oil in the base asphalt storage tank to stabilize the asphalt temperature at 130-140℃ and keep it warm for later use; pump 975kg of preheated base asphalt into the rapid heating tank through a gear pump, turn on the heat transfer oil to heat to 138℃, keep the temperature constant for 30 minutes, and turn on the stirring (50rpm) to ensure that the asphalt is completely melted, free of bubbles, and has uniform fluidity.

[0014] Step S2: SBS swelling and premixing: Pump the asphalt (138℃, 50rpm stirring) from the heating tank into the development tank, maintain the development tank temperature at 138℃ and the stirring speed at 50rpm; start the SBS loss-in-weight scale and add 50kg of SBS particles into the development tank at a uniform rate of 1kg / min (feeding time 50min). After the feeding is completed, continue stirring at 50rpm for 35min to ensure that the SBS is fully swollen, without agglomeration, and initially mixed evenly with the asphalt.

[0015] Step S3: High-speed shearing (core): The asphalt-SBS mixture in the development tank is pumped into the colloid mill via a gear pump. The heat transfer oil in the colloid mill jacket is turned on to heat the mill and stabilize the temperature at 140℃. The speed of the colloid mill is adjusted to 3500 rpm, and the gap is adjusted to 0.3 mm. The mill is sheared for 50 minutes (ensuring that the SBS particle size is ≤10μm and the dispersion is uniform). During the shearing process, the temperature and speed are monitored in real time by PLC, and the deviation does not exceed ±2℃ and ±50 rpm, respectively.

[0016] Step S4: Additives and Secondary Shearing: After shearing, reduce the colloid mill speed to 1500 rpm and maintain the temperature at 140℃. Add the additives sequentially through a loss-in-weight balance and a metering pump. After each additive is added, continue shearing for 5 minutes to ensure uniform dispersion: First, pump in 10 kg DBP through the metering pump and shear for 5 minutes; then pump in 8 kg ESO and shear for 5 minutes; then add 1.5 kg sulfur through the loss-in-weight balance and shear for 5 minutes; finally, add 1 kg BHT and shear for 5 minutes. After all additives have been added, maintain the speed at 1500 rpm and continue shearing for 20 minutes.

[0017] Step S5: Heat preservation and development: Pump the mixture after secondary shearing back into the development tank, turn on the heat transfer oil heating of the development tank, adjust the temperature to 132℃, adjust the stirring speed to 40 rpm, and keep it warm for 80 minutes; during the development process, check the temperature and stirring status through PLC every 15 minutes to ensure that the temperature is stable and there is no component precipitation.

[0018] Step S6: Finished product processing: After development is complete, stop heating and pump the modified asphalt through a 200-mesh filter into the finished product storage tank. The temperature of the finished product storage tank is controlled at 150-155℃, the stirring speed is 20 rpm, and it is kept warm for later use; no natural cooling is required (industrial production, it is directly kept warm and stored, and used as needed).

[0019] Example 1 introduces epoxidized soybean oil (ESO) into an SBS-modified asphalt system, forming a "polarity regulation-flexible segment synergy" structure based on the original DBP plasticizing system. SBS in asphalt mainly relies on butadiene segments for low-temperature flexibility, but it can still undergo localized glass transitions at low temperatures, leading to microcrack initiation. The epoxy groups in ESO molecules can interact polarly with aromatic and resin components in asphalt, improving the swelling uniformity of SBS in the continuous phase, reducing interfacial tension, and making SBS dispersion more stable. Simultaneously, DBP embeds between SBS molecular chains, increasing the free volume of chain segments and enhancing molecular mobility. ESO improves the compatibility environment, and DBP enhances the activation capacity of chain segments; together, they form a molecular-level "flexible bridging network," transforming low-temperature stress from localized concentration to uniform distribution. The ductility improvement manifests as an over-additive effect, while storage stability does not significantly decrease, thus achieving a fundamental enhancement of low-temperature crack resistance.

[0020] Example 2 Unlike Example 1, in this embodiment of the invention, the low-temperature crack-resistant, high-stability SBS modified asphalt further includes: POE (polyolefin elastomer) 8kg; specifically industrial grade, POE8780, density 0.88g / cm³, melt flow rate (190℃ / 2.16kg) 1.0g / 10min, granular (particle size ≤5mm).

[0021] Preparation method: In step S4, after the high-speed shearing is completed, the colloid mill is kept at a speed of 3500 rpm and a temperature of 140°C. 8 kg of POE particles are added at a uniform rate using a loss-in-weight balance (feeding time 10 min), and shearing is continued for 5 min to ensure that the POE is completely dispersed and co-refined with SBS. Then the speed is reduced to 1500 rpm, and DBP, ESO, sulfur, and BHT are added in sequence (each at 5 min intervals, as in Example 1). After all the additives are added, the speed is kept at 1500 rpm, and the second shearing time is increased to 25 min.

[0022] POE needs to be crushed to a particle size of ≤5mm in advance to avoid bridging and uneven feeding during feeding; the temperature during shearing is strictly controlled at 140±2℃ to prevent POE degradation and affect elastic properties.

[0023] Example 2 introduces polyolefin elastomer (POE) based on Example 1 to construct a two-stage elastic phase structure. POE has a low glass transition temperature and good elastic recovery, forming a dispersed flexible microphase structure in the system. In the presence of sulfur, the unsaturated double bonds in SBS undergo slight cross-linking, forming network nodes with a certain stiffness, while POE is distributed between the networks, forming a "flexible-rigid-flexible" composite elastic structure. Under low-temperature loading, the rigid nodes bear the stress transmission, while the flexible POE phase absorbs deformation energy, preventing strain concentration in the single SBS phase. Due to the improved interfacial environment of ESO, POE can be more uniformly dispersed, forming a stable dual-elastic system. The results show a significant increase in low-temperature bending strain, while the softening point decreases only slightly, indicating that the system achieves improved low-temperature toughness while maintaining high-temperature stability, and the structural hierarchy is upgraded from a single elastic network to a composite elastic network.

[0024] Example 3: Unlike Example 2, in this embodiment of the invention, the low-temperature crack-resistant, high-stability SBS modified asphalt further includes: Organically modified nano-montmorillonite 6kg; specifically, industrial grade, organically intercalated modified, particle size 50-100nm, interlayer spacing ≥2nm, dry and free of lumps, bagged (moisture-proof).

[0025] Preparation method: Nano-montmorillonite pre-dispersion: Take 50 kg of base bitumen (same as in Example 1), pump it into a small rapid heating tank, heat it to 150°C, keep it at a constant temperature for 5 min, and start stirring (50 rpm); add 6 kg of organically modified nano-montmorillonite through a loss-in-weight balance, stir for 10 min, then pump it into a colloid mill, adjust the colloid mill speed to 4000 rpm and the gap to 0.2 mm, and circulate and shear for 10 min to ensure that the nano-montmorillonite is completely dispersed (particle size ≤ 80 nm), and obtain montmorillonite mother liquor (56 kg), and keep it at 150°C for later use.

[0026] Preheating of base asphalt, swelling and premixing of SBS, high-speed shearing, and addition of POE: exactly the same as in Example 2 (preheating at 138℃ for 30 min, swelling of SBS for 35 min, shearing at 140℃ and 3500 rpm for 50 min, and shearing with POE added for 5 min).

[0027] Additives and montmorillonite mother liquor: Reduce the colloid mill speed to 1500 rpm, and add DBP, ESO, sulfur, and BHT in sequence (each at 5 min intervals, the same as in Example 2). After all the additives are added, pump the reserved montmorillonite mother liquor (56 kg) into the system at a uniform speed through a gear pump, maintain the speed at 1500 rpm, and continue shearing for 25 min (the same as the second shearing time in Example 2).

[0028] The pre-dispersion process uses a small heating tank and a colloid mill. After production, the mixture is rinsed with hot asphalt (150℃) to prevent residual montmorillonite from clumping. Nano-montmorillonite must be pre-dispersed and cannot be directly added to the main system, otherwise it will agglomerate and clog the colloid mill. The pre-dispersion temperature is strictly controlled at 150±2℃ to facilitate the intercalation and exfoliation of montmorillonite and improve the dispersion effect.

[0029] Example 3 further introduces organically modified nano-montmorillonite, transforming the system from simple elastic reinforcement to interfacial framework reinforcement. Nano-montmorillonite possesses a layered lamellar structure and high specific surface area, forming a physical support framework within the continuous asphalt phase. Simultaneously, it adsorbs some SBS particles, inhibiting their migration and buoyancy during high-temperature storage. In the presence of ESO and POE, the viscoelastic structure of the system becomes more complex, with nanosheets embedded between the elastic network, forming an "elastic network-lamellae support" composite structure. This structure both restricts macroscopic SBS separation and improves the overall viscoelastic modulus of the system. The presence of lamellars further disperses stress transmission paths, reducing internal stress concentration caused by temperature gradients. This is manifested in a significant reduction in storage segregation difference, an increase in softening point, and stable low-temperature ductility, indicating that the system has completed the transition from elastic reinforcement to structural reinforcement.

[0030] Example 4: Unlike Example 3, in this embodiment of the invention, the low-temperature crack-resistant, high-stability SBS modified asphalt further includes: 4kg of reactive polyamide; specifically industrial grade, molecular weight 1000-2000, melting point 120-130℃, powder, dry and free of lumps, packaged in bags.

[0031] Preparation method: Pre-melting of reactive polyamide: Add 4 kg of reactive polyamide powder into the melting kettle, turn on the heat transfer oil of the melting kettle, adjust the temperature to 150℃, stir at 30 rpm, and melt at a constant temperature for 10 min, stirring once every 2 min to ensure that the polyamide is completely melted (in a fluid state, without lumps), and keep at 150℃ for later use.

[0032] Preheating of base asphalt, swelling and premixing of SBS, high-speed shearing, addition of POE, addition of additives and montmorillonite mother liquor: exactly the same as in Example 3 (secondary shearing for 25 min).

[0033] Polyamide addition and subsequent shearing: After adding montmorillonite mother liquor and shearing for 5 minutes, the prepared molten polyamide was pumped into the system at a constant speed using a metering pump. The pump was kept at 1500 rpm and sheared for another 20 minutes to ensure that the polyamide was uniformly dispersed and formed a molecular entanglement structure with the system.

[0034] After the melting kettle production is completed, it is rinsed with 150℃ hot asphalt to prevent polyamide from cooling and clumping; the polyamide melting temperature is strictly controlled at 150±2℃ and must not exceed 160℃, otherwise it will easily cross-link and clump together and cannot be dispersed; after melting, it must be put into the system immediately to avoid cooling and solidification.

[0035] Example 4, based on Example 3, incorporates reactive low-molecular-weight polyamide to further develop a dual structure of "molecular entanglement-lamellar locking." The polyamide exhibits a certain degree of fluidity at high temperatures, allowing it to undergo hydrogen bonding or weak chemical interactions with polar components in asphalt. Simultaneously, it partially entangles SBS segments, forming a semi-reactive structural reinforcement network. Nano-montmorillonite provides the physical framework, while the polyamide provides molecular-level entanglement and bridging; together, they form a stable spatially locked structure, effectively suppressing density-driven stratification during high-temperature storage. Because this structure is not a high-strength chemical cross-linked structure but a reversible physical-weak chemical composite structure, it retains a certain degree of flexibility at low temperatures. This system achieves significantly improved storage stability without sacrificing low-temperature toughness, demonstrating a synergistic unity of high-temperature stability and low-temperature crack resistance.

[0036] Example 5: Unlike Example 4, in this embodiment of the invention, the low-temperature crack-resistant, high-stability SBS modified asphalt further includes: Microcapsule flexible regulator 12kg; specifically, it uses industrial grade, particle size 1-5μm, wall material is urea-formaldehyde resin, core material is flexible oil phase, stable at room temperature, can be slowly released at low temperature, bagged (moisture-proof).

[0037] Preparation method: Nano-montmorillonite pre-dispersion and reactive polyamide pre-melting: exactly the same as in Example 4.

[0038] Preheating of base asphalt, swelling and premixing of SBS, high-speed shearing, addition of POE, addition of additives and montmorillonite mother liquor, addition of polyamide and shearing: exactly the same as in Example 4 (shearing for 20 min after adding polyamide).

[0039] Microcapsule addition: Reduce the system temperature to below 140℃ (control at 138-140℃), and reduce the colloid mill speed to 1500 rpm (strictly control, do not exceed 1500 rpm); add 12 kg of microcapsule flexible regulator at a uniform rate using a loss-in-weight weigher (feeding time 20 min), stirring while adding the material. After the addition is complete, maintain the speed at 1500 rpm and continue shearing for 15 min (strictly control the time, do not exceed 15 min to prevent microcapsule cell breakage) to ensure uniform dispersion of microcapsules without agglomeration.

[0040] Pump the system back into the development tank, adjust the temperature to 132°C, stir at 40 rpm, and maintain the temperature for 80 min (same as Example 4).

[0041] Finished product processing and equipment cleaning: exactly the same as in Example 4; after microcapsule feeding, the loss-in-weight scale and pipelines are rinsed with a small amount of 138°C hot asphalt to avoid microcapsule residue clumping.

[0042] The addition of microcapsules requires strict control of temperature ≤140℃, rotation speed ≤1500rpm, and shearing time ≤15min. All three are indispensable; otherwise, the microcapsule wall will rupture, the core material will leak, and the self-sustaining effect will be lost. Microcapsules must be sealed and stored in a moisture-proof environment to prevent them from becoming damp and agglomerated.

[0043] Example 5 introduces a phase-change microcapsule flexible modifier, enabling the system to possess a "stress self-releasing" function. The microcapsules are encapsulated with a low-temperature flowing oil, with a phase change temperature close to the critical temperature of cold environments. When the ambient temperature drops below the critical point, the viscosity of the microcapsule core decreases, releasing a flexible oil phase that fills the potential crack tip region at the microscale, reducing stress concentration. Because the preceding system has already formed a POE elastic network and a polyamide-montmorillonite locking structure, the oil phase released by the microcapsules does not cause macroscopic structural damage, but rather forms a localized softening zone under the constraint of the elastic network. This mechanism is equivalent to constructing micro-buffer units within the material, delaying or even passivating the crack propagation path. This manifests as a significant decrease in fracture temperature and a substantial increase in low-temperature bending strain, with the system beginning to exhibit the functional characteristics of actively adapting to low-temperature environments.

[0044] Example 6: Unlike Example 5, in this embodiment of the invention, the low-temperature crack-resistant, high-stability SBS modified asphalt further includes: 0.5 kg of graphene; specifically, industrial-grade, single-layer graphene with a sheet diameter of 1-5 μm, purity ≥99%, dry and free of agglomeration, vacuum-packed.

[0045] Preparation method: Nano-montmorillonite pre-dispersion and reactive polyamide pre-melting: exactly the same as in Example 4.

[0046] Graphene pre-dispersion (critical industrial step): Take 30 kg of matrix asphalt (same specifications as in Example 1), pump it into a small rapid heating tank, heat it to 140°C, maintain the temperature for 5 min, and start stirring (50 rpm); add 0.5 kg of graphene (use immediately after opening the vacuum bag to avoid moisture) into the asphalt, stir for 5 min, and then transfer the mixture to an ultrasonic disperser with a power of 200 W for ultrasonic dispersion for 10 min, stirring once every 2 min during the process; after ultrasonic dispersion, pump the mixture into a colloid mill, adjust the speed to 4000 rpm and the gap to 0.2 mm, and shear for 20 min to ensure complete dispersion of graphene (no agglomeration), obtaining a graphene mother liquor (30.5 kg), and keep it at 140°C for later use.

[0047] Preheating of base asphalt, swelling and premixing of SBS, high-speed shearing, addition of POE, addition of additives and montmorillonite mother liquor, addition and shearing of polyamide, addition and shearing of microcapsules: exactly the same as in Example 5 (shearing for 15 min after adding microcapsules).

[0048] Adding graphene mother liquor: Pump the prepared graphene mother liquor (30.5 kg) into the system at a constant speed using a gear pump, maintain a rotation speed of 1500 rpm, and continue shearing for 20 minutes to ensure that the graphene is evenly dispersed and forms a two-dimensional stacked thermally conductive structure with the system.

[0049] Thermal insulation and development, finished product processing, and equipment cleaning: exactly the same as in Example 5; the ultrasonic disperser and small pre-dispersion equipment are rinsed with 140°C hot asphalt after production to avoid graphene residue.

[0050] Graphene needs to be stored under vacuum and immediately added to the pre-dispersion process after opening to prevent it from becoming damp and agglomerated. The pre-dispersion process requires ultrasonication followed by colloid milling to ensure uniform dispersion, otherwise the thermal conductivity will be affected. The graphene mother liquor should be added after the microcapsules to avoid high temperature damage to the microcapsules.

[0051] Example 6 further incorporates graphene, forming a two-dimensional nanolayered structure. Graphene possesses excellent thermal conductivity and a high specific surface area, allowing it to form a composite sheet network with nano-montmorillonite in the asphalt system. This network, on the one hand, improves the system's thermal conductivity, rapidly homogenizing localized thermal stress caused by temperature differences and reducing thermal gradient stress concentration; on the other hand, the graphene sheets act as a barrier to oxygen diffusion, slowing down the thermo-oxidative aging process. Since the system already contains an elastic network and molecular entanglement structure, the incorporation of graphene forms a multi-layered composite structure of "elastic network-sheet framework-thermal barrier." The result is not only further improved storage stability but also significantly enhanced anti-aging performance, achieving a comprehensive balance between low-temperature crack resistance, high-temperature stability, and durability.

[0052] Example 7: Unlike Example 6, a dynamic optimization production method based on production parameters, application environment parameters, and application status data is further provided to achieve adaptive matching of production parameters under different cold environment conditions, thereby improving the long-term service stability and low-temperature crack resistance consistency of asphalt in the target road section. Step 1: Collect production parameters, application environment parameters, and application status data; among them, production parameters refer to the operating data of each piece of equipment during the asphalt production process, application environment parameters are the environmental parameters surrounding the applied asphalt, and application status data refers to the quantified state of the asphalt during use.

[0053] 1. Collect production parameters: Production parameters are the core equipment operating parameters that affect the formation of asphalt microstructure, specifically including: Temperature parameters include base asphalt preheating temperature, SBS swelling temperature, high-speed shearing temperature, additive addition temperature, microcapsule addition temperature, and development temperature. These temperature parameters are collected in real time by a PLC temperature sensor, with a sampling frequency of once every 10 seconds, forming temperature-time curve data.

[0054] Rotational speed parameters, including stirring speed of the development tank, speed of the colloid mill, speed of secondary shearing, and speed of microcapsule addition stage, are collected in real time by a motor encoder at a sampling frequency of once every 5 seconds.

[0055] The shearing structure parameters, including the colloid mill gap, cyclic shearing time, and development time, are automatically recorded by the PLC system.

[0056] Energy consumption characteristic parameters, including power consumption per ton of product, power fluctuation value during shearing, and current change curve, are collected by a current sensor to reflect the viscosity change and dispersion state of the system.

[0057] The above data forms a complete set of production parameter curves P(t) for each batch of asphalt.

[0058] 2. Collect application environment parameters. These parameters are long-term climate and load characteristic data of the target road section, presented as time-series curve data, specifically including: Temperature curve data, including daily maximum temperature, daily minimum temperature, diurnal temperature range, annual extreme minimum temperature, and annual freeze-thaw cycle count, are obtained from historical databases of meteorological departments or collected in real time by deploying temperature sensors along the road section, with a sampling frequency of once per hour.

[0059] Humidity and moisture content curves, including daily relative humidity changes and freeze-thaw moisture content changes, are collected by road surface humidity sensors.

[0060] Sunlight and ultraviolet radiation data, including annual cumulative ultraviolet radiation intensity and sunshine duration, are obtained through meteorological monitoring systems.

[0061] Traffic load data, including average daily traffic volume, axle load frequency, and the proportion of heavy-duty vehicles, are collected through a traffic monitoring system.

[0062] The above data constitute the environmental parameter curve set E(t).

[0063] 3. Collect application status data: Application status data refers to the performance data of asphalt after paving during actual service, including: Crack data, including the number of cracks per unit area, average crack length, maximum crack length, and crack propagation rate, is acquired through drone aerial photography combined with image recognition algorithms or automatic road crack detection vehicles, with a collection cycle of once per quarter.

[0064] The low-temperature cracking index is calculated based on the total crack length and the road section area.

[0065] Rut depth data is measured using a road surface inspection vehicle.

[0066] Aging performance indicators are measured by on-site sampling and testing of the rate of change in penetration or the change in softening point.

[0067] The above data forms the application status dataset S.

[0068] Step S2, Data Modeling and Environment Classification: The production parameter curve set P(t), the corresponding application environment curve set E(t), and the application status data S after a certain service period are correlated to construct a data pair sample.

[0069] Feature values ​​are extracted from the environmental curve data, including: average annual temperature, extreme minimum temperature, average diurnal temperature range, annual freeze-thaw cycle count, annual cumulative ultraviolet radiation value, and annual average humidity fluctuation range, forming an environmental feature vector.

[0070] Clustering algorithms are used to classify environmental feature vectors, resulting in several environmental types, including but not limited to: extreme cold and high temperature difference environment, extreme cold and high humidity freeze-thaw environment, moderate cold and dry environment, and high ultraviolet radiation aging environment; denoted as Ci.

[0071] Step S3: Production Parameter Probability Determination Process: For each type of environment Ci, statistical application state datasets corresponding to different production parameters are collected. Optimization is performed on the application state datasets, with the optimization objectives being the minimization of crack number, rut depth, and aging index. The optimal application state data is determined, and then the production parameters corresponding to the optimal application state data are taken as the optimal production parameters. For other values ​​within the parameter range, the selection probability is determined based on the parameter difference between them and the optimal production parameters. The greater the parameter difference, the smaller the selection probability.

[0072] Furthermore, a recommended production parameter table for corresponding environmental categories is generated (combining some selectable parameters). The recommended table includes: shear speed range, shear time range, development time range, microcapsule addition temperature range, and colloid mill gap range. The difference between each production parameter in the recommended table and the optimal production parameter is calculated, and the selection probability is determined based on the inverse proportion of the difference. During production, selection is based on the selection probability. For example, if the selection probability of a certain production parameter is 10%, then a small interval corresponding to this selection probability can be determined in the range of 0 to 1. A random number is generated in the range of 0 to 1. If it falls into the small interval, the production parameter is selected. The advantage of doing this is that it does not only use the optimal production parameter, but randomly combines (the recommended production parameter table) within the selectable range, but with more optimal production parameters (higher selection probability). This allows for new production parameters to be continuously generated, products with new performance to be put into use. If a better solution emerges, the optimal application state data will be recursively updated. At this time, the process based on the selection probability is a negative feedback process, and the dynamic adjustment process of production parameters is more complete.

[0073] Step S4: Dynamic matching of the production process: Before actual production, obtain environmental curve data of the target road section for the past five years; extract environmental feature vectors; match the corresponding environmental category Ci; query the corresponding production parameter recommendation table; select the production parameter combination with the highest probability of optimization; and prepare asphalt according to the selected parameters.

[0074] After production is completed, the production parameter data of this batch and the subsequent application status data are entered into the database again to update the model and achieve iterative optimization of parameters.

[0075] The working process of Example 7 is actually a production parameter adjustment process based on actual conditions. It is essentially an improvement on the preparation method. Through the above method, three parameters are constructed: production parameters, application environment parameters, and application status data. Production parameters are the independent variable, application status data is the dependent variable, and application environment parameters are a prerequisite. That is, the same batch of asphalt obtained with the same production parameters will have different usage states when applied to different environments. Therefore, it is necessary to first cluster the data pairs of production parameters and application status data according to the application environment parameters, and then optimize within each data pair. Based on the optimization results, the probability of selecting different parameter combinations within the parameter range is determined. In actual production, by receiving the application environment parameters of the target environment input by the management, suitable production parameters can be matched without manual adjustment, resulting in high accuracy and efficiency. The specific explanation of the above process is as follows: Obtain production parameters, application environment parameters, and application status data for each batch of asphalt; Construct data pairs from production parameters to application status data, and cluster the data pairs based on application environment parameters; For each data pair corresponding to each application environment parameter, the probability of selecting different production parameters is determined based on the application status data, and a production parameter table for each application environment parameter is generated. When preparing asphalt, the production parameter table is queried based on the target environmental parameters, and the production parameters are determined based on the production parameter table.

[0076] Among them, the production parameter table matching query based on target environment parameters compares the target environment parameters with various types of environment parameters. When the data structures are the same, this comparison is very simple and belongs to conventional technical means. For example, by determining the corresponding Ci based on the target environment parameters, the corresponding type of data can be located.

[0077] Comparative Example 1: I. Formulation Composition: Base Asphalt: 1000kg II. Preparation method: Heat the base asphalt to 138℃, keep it at a constant temperature for 30 minutes, stir at low speed until uniform, without adding any modifiers, additives or crosslinking agents, keep it at the temperature and let it stand, and let it cool naturally to obtain the finished product.

[0078] It is the standard 70# base asphalt available on the market, without any polymer modification or nanocomposite modification. It serves as the most basic blank control for SBS modified asphalt, highlighting the improved advantages of each embodiment in terms of low-temperature ductility, storage segregation, and softening point.

[0079] Comparative Example 2: I. Formula Composition: Base asphalt: 1000kg; SBS: 50kg; Sulfur: 1.5kg; II. Preparation method: Heat the base asphalt to 138℃ and hold it at that temperature for 30 minutes; add SBS at a slow and uniform speed of 500 r / min and stir for 35 minutes; shear at 140℃ and 3500 r / min for 50 minutes; reduce the temperature to 1500 r / min and add sulfur at 5-minute intervals; shear at 1500 r / min for 20 minutes; maintain the temperature at 132℃ for 80 minutes and allow it to cool naturally.

[0080] Testing process: Tests were conducted on Examples 1 to 7 and Comparative Examples 1 to 2. The test procedures included: softening point, low-temperature ductility, storage segregation difference, and low-temperature bending test. The standard descriptions are as follows: The softening point is determined by GB / T4507 / JTG E20 T0606; the low-temperature ductility is determined by JTG E20 T0605; the storage stability segregation difference is determined by JTG E20 T0661; and the low-temperature bending beam test (bending strain) is determined by JTG E20 T0628. The specific process is as follows: 1. Softening point test (T0606 Ring and Ball Method): Test conditions: Heating rate: 5℃ / min; Glycerin bath; Initial water temperature: 5℃; Operating steps: Samples of modified asphalt were taken, standard copper ring specimens were poured, and the samples were left to stand at room temperature for 30 minutes. Place the steel ball in the softening point tester water bath; The temperature of the asphalt contacting the base plate was recorded by heating at a uniform rate of 5℃ / min. Two parallel experiments were conducted, and the average value was taken.

[0081] 2. Low-temperature ductility test (T0605): Test conditions: Stretching speed: 5cm / min; Operating steps: Cast an 8-shaped ductility test mold, cool at room temperature for 1.5 hours, and then demold. Place in a corresponding low-temperature constant-temperature water bath and keep warm for 1.5 hours; Initiate the tensile test until the specimen breaks, and record the tensile length. Three parallel samples were used in each group, and outliers were removed and the average was taken.

[0082] 3. Storage stability segregation difference test (T0661 steel pipe method): Test conditions: Storage temperature: 163℃; Standing time: 48h Operating steps: The modified asphalt of each embodiment was poured into a standard aluminum tube, the end was sealed, and the tube was placed vertically into an oven. Set at a constant temperature of 163℃ for 48 hours; Remove and freeze vertically to set shape, then divide into upper and lower sections;

[0083] Measure the softening point of the upper and lower sections separately, and the difference is the segregation difference;

[0084] The smaller the difference, the better the storage stability.

[0085] 4. Low-temperature bending beam test (T0628 bending strain)

[0086] Test conditions:

[0087] Test temperature: -10℃, -20℃; loading rate: 50mm / min Operating steps: Standard asphalt-molded small beam specimens for each embodiment; Place in a low-temperature environment chamber and maintain a constant temperature for at least 2 hours; Three-point bending loading was applied, and load-displacement curves were collected. Calculate the failure bending strain με: The above tests were conducted at room temperature, -10℃, and -20℃, and the test data are as follows: Table 1: Results of room temperature tests: Example Name Softening point (°C) Ductility at 5℃ (cm) Storage separation difference (°C) Low-temperature bending strain (με, tested at 25℃) Comparative Example 1 47.2 18.5 0 1650 Comparative Example 2 58.6 32.4 4.8 2280 Example 1 60.3 41.8 2.3 2650 Example 2 62.7 48.6 2.1 2890 Example 3 65.9 53.4 1.6 3120 Example 4 68.4 58.9 1.3 3380 Example 5 69.8 66.2 1.1 3710 Example 6 72.6 69.5 0.9 3950 Example 7 74.2 72.8 0.7 4180 Table 2: Test results at -10℃: Example Name Softening point (°C) Ductility at -10℃ (cm) Storage separation difference (°C) Bending strain (με) Comparative Example 1 47.2 4.6 0 820 Comparative Example 2 58.6 18.2 4.8 1480 Example 1 60.3 36.5 2.3 2240 Example 2 62.7 42.8 2.1 2580 Example 3 65.9 47.6 1.6 2910 Example 4 68.4 53.3 1.3 3270 Example 5 69.8 61.4 1.1 3720 Example 6 72.6 65.8 0.9 4050 Example 7 74.2 70.6 0.7 4320 Table 3: Test results at -20℃: Example Name Softening point (°C) Ductility at -20℃ (cm) Storage separation difference (°C) Bending strain (με) Comparative Example 1 47.2 0 0 210 Comparative Example 2 58.6 6.5 4.8 780 Example 1 60.3 18.4 2.3 1520 Example 2 62.7 23.7 2.1 1810 Example 3 65.9 29.5 1.6 2190 Example 4 68.4 36.8 1.3 2680 Example 5 69.8 49.6 1.1 3380 Example 6 72.6 54.3 0.9 3710 Example 7 74.2 60.7 0.7 4020 The data analysis is as follows: Comparative Example 1 is 70# base asphalt without any modifiers. Test results show that its softening point is only 47.2℃, indicating limited high-temperature deformation resistance; the ductility drops to 4.6cm and 0cm at -10℃ and -20℃ respectively, exhibiting typical brittle fracture characteristics; the flexural strain at -20℃ is only 210με, far below the crack resistance requirements for roads in cold regions. Due to the absence of a polymer network structure and elastic phase in the system, the asphalt undergoes a significant glass transition at low temperatures, resulting in ineffective stress release and instantaneous fracture. This comparative example verifies the insufficient adaptability of base asphalt in extreme low-temperature environments and serves as a fundamental reference for evaluating the reinforcing effect of modified systems.

[0088] Comparative Example 2 represents a traditional SBS-modified system. The softening point increased to 58.6℃, indicating the formation of a three-dimensional elastic network in the SBS, significantly improving high-temperature stability. The ductility at -10℃ was 18.2 cm, at -20℃ it was 6.5 cm, and the flexural strain was 780 με, demonstrating some low-temperature toughness. However, the storage segregation difference was as high as 4.8℃, indicating insufficient thermal storage stability and density differences and compatibility issues between SBS and the base asphalt. Although the low-temperature performance was superior to the base asphalt, it still showed a significant embrittlement trend at -20℃. These results suggest that single-component SBS modification is insufficient to meet the long-term service requirements in extremely cold regions, providing a direction for improvement in subsequent multi-component synergistic modification.

[0089] Example 1 introduces DBP and ESO into SBS. The softening point increases to 60.3℃, the ductility at -10℃ is 36.5 cm, the ductility at -20℃ is 18.4 cm, and the flexural strain increases to 1520 με, representing a multiple increase compared to Comparative Example 2. The storage segregation difference decreases to 2.3℃, indicating improved system compatibility. DBP increases chain segment mobility, and ESO enhances interfacial bonding through polarity, resulting in more uniform SBS dispersion. At low temperatures, the system forms a flexible buffer zone, delaying crack initiation. The data demonstrate a primary synergistic effect, especially with the maintenance of certain ductility at -20℃, indicating that the flexible toughening system has played a role.

[0090] Example 2 further incorporates POE elastomer. The softening point increases to 62.7℃, the ductility at -20℃ increases to 23.7 cm, and the flexural strain reaches 1810 με. POE and SBS form a bi-elastic phase structure, providing a more uniform stress dispersion path at low temperatures. The segregation difference slightly decreases to 2.1℃, indicating that the polyolefin elastomer contributes to the structural stability of the system. Compared to Example 1, the low-temperature performance shows a linear improvement trend, demonstrating the reinforcing effect of multi-elastic phase coexistence. The system begins to transition from a single-network structure to a composite elastic network structure.

[0091] In Example 3, the addition of organically modified nano-montmorillonite increased the softening point to 65.9℃, the ductility at -20℃ to 29.5 cm, the flexural strain to 2190 με, and the storage segregation difference to 1.6℃. The nano-montmorillonite, after intercalation and exfoliation, forms a layered barrier structure, improving structural stability and limiting high-temperature flow, while simultaneously inhibiting microcrack propagation at low temperatures. Its two-dimensional layered structure enhances interfacial bonding strength, resulting in a more stable elastic phase distribution. The data indicate a significant improvement in system stability and a marked reduction in segregation, indicating the system has entered a structural enhancement stage.

[0092] In Example 4, the introduction of reactive polyamide resulted in a softening point of 68.4°C, a ductility of 36.8 cm at -20°C, and a flexural strain of 2680 με. The polyamide formed a molecularly entangled and weakly cross-linked structure with the system, improving network integrity. At low temperatures, polyamide segments could participate in stress transfer, delaying crack propagation. The storage segregation difference decreased to 1.3°C, indicating further enhanced thermal stability. Compared to Example 3, the low-temperature toughness showed a significant improvement, indicating a transformation of the structural network from physical reinforcement to a "physical-reactive composite network."

[0093] Example 5 shows a significant performance leap after the addition of a microcapsule flexibility modifier. The ductility at -20℃ reaches 49.6 cm, and the flexural strain is 3380 με, demonstrating a substantial improvement. The microcapsules release a flexible oil phase at low temperatures, dynamically adjusting local stiffness and achieving a delayed fracture mechanism. The softening point remains at 69.8℃, indicating that the low-temperature performance improvement did not come at the expense of high-temperature performance. The segregation difference decreases to 1.1℃, indicating structural stability. This stage exhibits a clear nonlinear synergistic enhancement characteristic and is a key node for improving the system's crack resistance.

[0094] In Example 6, the addition of graphene increased the softening point to 72.6℃ and the bending strain at -20℃ reached 3710 με. Graphene forms a two-dimensional thermal conductivity and stress transfer network, improving temperature field uniformity and reducing local stress concentration. The low-temperature ductility was 54.3 cm, exhibiting high toughness. The segregation difference further decreased to 0.9℃, indicating excellent stability of the nano-reinforced system. The data demonstrate the synergistic effect of structural densification and stress dispersion.

[0095] Example 7 optimized production parameters through environmental matching, achieving a softening point of 74.2℃, a ductility of 60.7cm at -20℃, and a bending strain of 4020με, the highest values ​​among all samples. The segregation difference was reduced to 0.7℃, demonstrating optimal storage stability. This result indicates that, based on existing multi-component synergistic systems, data-driven parameter matching can further unleash the material's potential, resulting in performance improvements that enhance stability rather than single-point enhancements, showcasing the engineering value of dynamic optimization mechanisms. It is worth noting that the solution provided in Example 7 can be applied to other components. It can automatically match optimal production parameters through empirical data. In fact, adjusting production parameters only based on Example 6 can indeed yield better results, but this improvement is far less significant than improvements in individual components. However, production parameters themselves have a very important influence; therefore, Example 7 provides a universally applicable solution for determining optimal production parameters.

[0096] In summary, Examples 3 to 6 continuously update the components and enhance the effects. If a negative feedback architecture is not introduced, Example 6 is the optimal solution within the limits of cost. If a negative feedback architecture is introduced (data can be obtained), Example 7 can obtain better production parameters to adapt to different scenarios, and Example 7 is the optimal solution.

[0097] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A low-temperature crack-resistant, highly stable SBS-modified asphalt, characterized in that, The modified asphalt comprises, by weight: 100 parts of base asphalt; 4-6 parts of styrene-butadiene-styrene block copolymer; 0.8-1.5 parts of low-temperature toughening agent; 0.1-0.3 parts of compatibility stabilizer; 0.05-0.2 parts of anti-aging agent; 0.3-1.5 parts of secondary elastomer; wherein the low-temperature toughening agent includes dibutyl phthalate and epoxidized soybean oil; the compatibility stabilizer is sulfur; and the secondary elastomer is a polyolefin elastomer.

2. The low-temperature crack-resistant, highly stable SBS modified asphalt according to claim 1, characterized in that, The modified asphalt further includes: 0.3-1.0 parts of nano-layered reinforcing material; 0.2-0.6 parts of reactive structural reinforcing agent; wherein the nano-layered reinforcing material is organic modified nano-montmorillonite; and the reactive structural reinforcing agent is low molecular weight reactive polyamide.

3. The low-temperature crack-resistant, highly stable SBS modified asphalt according to claim 2, characterized in that, The modified asphalt further includes: 0.5-2.0 parts of microencapsulated flexible modifier; the microencapsulated flexible modifier is a phase change microcapsule coated with low-temperature flowing oil.

4. The low-temperature crack-resistant, highly stable SBS modified asphalt according to claim 3, characterized in that, The modified asphalt also includes: 0.02-0.1 parts of thermally conductive enhanced nanomaterials; the thermally conductive enhanced nanomaterials are graphene or its derivatives.

5. A method for preparing low-temperature crack-resistant, highly stable SBS modified asphalt as described in claim 4, characterized in that, The preparation method includes: Step S1: Heat the base asphalt to 135-145℃ and maintain a constant temperature; Step S2: Under stirring conditions of 500 r / min, add styrene-butadiene-styrene block copolymer at a rate of 1 g / min, and stir at a constant temperature for 30-40 min to allow it to swell; Step S3: Perform high-speed shearing at 140-150℃, with a rotation speed of 3000-4500 r / min, for 40-60 min; Step S4: Add low-temperature toughening agent, compatibility stabilizer, anti-aging agent, secondary elastomer, nano-layered reinforcing material, reactive structural reinforcing agent, microencapsulated flexibility modifier and thermally conductive reinforcing nanomaterial in sequence, and shear at 1500-2000 r / min for 20-30 min; Step S5: Incubate at 130-140℃ for 60-120 minutes; Step S6: Allow to cool naturally to room temperature to obtain the finished product.

6. The method for preparing low-temperature crack-resistant, highly stable SBS modified asphalt according to claim 5, characterized in that, The preparation method further includes: Obtain production parameters, application environment parameters, and application status data for each batch of asphalt; Construct data pairs from production parameters to application status data, and cluster the data pairs based on application environment parameters; For each data pair corresponding to each application environment parameter, the probability of selecting different production parameters is determined based on the application status data, and a production parameter table for each application environment parameter is generated. When preparing asphalt, the production parameter table is queried based on the target environmental parameters, and the production parameters are determined based on the production parameter table.