Influence of Waste Catalyst Surface Characteristics on High-Temperature Performance and Adhesion Properties of Asphalt Mortar

Abstract

The incorporation of waste fluid catalytic cracking (FCC) catalysts (WFCs) into asphalt pavements represents an effective strategy for resource utilization. However, the influences of the composition of the waste catalyst and its surface characteristics on the performance of asphalt mortars are still unclear. Herein, five WFCs were selected as powder filler to replace partial mineral powder (MP) to prepare five asphalt mortars. The diffusion behaviors of asphalt binder on the components of WFCs were investigated based upon molecular dynamic simulation, as was the interfacial energy between them. The adhesion work values between asphalt and WFCs were evaluated based upon the surface free energy theory. A dynamic shear rheology test and multiple stress creep recovery test on the WFC asphalt mortar were also conducted. Furthermore, the gray correlation analysis (GCA) method was employed to analyze the correlation between the diffusion coefficient and interfacial energy with the performance of WFC asphalt mortar. The results showed that the asphalt exhibited a low diffusion coefficient and high interfacial energy with the alkaline components of WFCs. The adhesion work values between asphalt and WFCs are higher than those with MP. The addition of WFCs can enhance the anti-rutting property of asphalt mortar significantly. Among the five WFCs, 2# exhibited the best improvement effect on the anti-permanent deformation ability of asphalt mortar, which may be due to its large specific surface area and moderate pore width. The GCA results suggest that the diffusion coefficient and interfacial energy strongly correlated with the performance of asphalt mortar, with an order of adhesion > permanent deformation resistance > rutting resistance. This study provides both theoretical and experimental support for the application of WFCs in asphalt materials.

1. Introduction

Fluid catalytic cracking (FCC) catalysts are widely used in the petrochemical industry, and substantial amounts of solid waste are generated after their deactivation. Efficient resource utilization of FCC waste catalysts has become a critical area of research [1,2,3]. The main active components of FCC waste catalysts are silica (SiO₂), aluminum oxide (Al₂O₃), calcium oxide (CaO), and iron oxide (Fe₂O₃), with SiO₂ and Al₂O₃ accounting for approximately 90% of their mass fractions [4]. These catalysts exhibit notable physical characteristics, namely a large specific surface area (approximately 100 m²/g), small particle size (approximately 70 μm, corresponding to about 200 mesh), large open pores, and spherical particles. These physical properties suggest their potential for use as asphalt modification materials [5,6]. Although there have been few studies on the modification of waste catalysts in asphalt and asphalt mixtures, some have shown that it is feasible to use waste catalysts as fine aggregates or fillers in road engineering applications [7,8].

Schmitt (1990s) found that the high-temperature performance of waste catalysts was significantly improved after they were incorporated into an asphalt mixture as fillers [9]. Furimsky [10] further demonstrated through laboratory experiments that the addition of a small number of spent catalysts not only enhanced the performance of the asphalt mixture but also provided an effective solution to the disposal challenges associated with spent catalysts. Lin [11] studied the physical and chemical properties of waste catalysts and found that their use as fillers significantly improved the high-temperature and water stability of asphalt mixtures. Alshamsi et al. [12] systematically evaluated various batches of waste catalysts and identified the optimal mixing ratio. When used as a fine aggregate, the maximum permissible content was 20%, with a recommended mixing amount of 10%. As a filler, the recommended dosage was 5%. Furthermore, the heavy metal leachate levels of WFCs were lower than the environmental protection standards, making them environmentally safe when being used in the construction field [13].

The interaction of asphalt binder with filler is considered to play a key role in affecting the performance of asphalt mortar and mixtures [14]. Wu et al. [15] demonstrated that the strength of the interaction between asphalt and filler is positively correlated with the adhesion work; thus, the stronger the interaction, the better the high-temperature stability of asphalt mortar. Shi et al. [16] investigated the adhesion behavior and microscopic mechanism of the multi-phase complex interface of epoxy asphalt–recycled aggregate. The results showed that the addition of epoxy could improve the surface characteristics, thus improving the shear performance and dynamic mechanical performance of the asphalt–aggregate system. Our previous study [17] also proved that the improvement in the adhesion between asphalt and filler using silane as coupling agent could improve the anti-water stability of asphalt mixtures.

Furthermore, existing research shows that the high-temperature performance of asphalt can be significantly improved by incorporating inorganic materials [18,19,20]. Jahroml et al. [21] emphasized that the inclusion of clay and its modified materials can enhance both the high-temperature performance and the structural stability of asphalt. Azarhoosh et al. [22] used sewage sludge ash (SSA) as a filler substitute in asphalt mastic. Their results indicated that the low density and high surface area of alkaline SSA contribute to the improvement in stiffness and elasticity of asphalt mastic, thus improving the high-temperature property of asphalt mastic. Fume silica nanoparticles have been proved to be a good filler for enhancing the high-temperature elasticity, fatigue resistance, and deformation resistance of asphalt binders [23]. Waste FCC catalysts (WFCs) are mainly composed of inorganic substances, which might be used as high-temperature modifiers for asphalt mortar.

The advancement of computational technologies has introduced molecular dynamic simulation (MDS) as a powerful tool for investigating interfacial interactions between asphalt and fillers [24]. Simultaneously, the gray correlation analysis method was also employed to investigate the sensibility parameters for asphalt binder or mixture performance [25]. An analysis of the microscopic diffusion behavior of nanomaterial/waste-material-modified asphalt was combined with a macroscopic performance test, and the modification mechanisms were explored through molecular dynamics simulations and gray correlation analysis in many previous reports [17,26,27]. For instance, Wei et al. [28] investigated the interfacial adhesion performance between asphalt and polyurethane (PU) based upon the MDS method, identifying strong linear correlations between interfacial energy, adhesion work, and the low-temperature performance of PU-modified asphalt. This combined approach offers both theoretical support and practical guidance for the efficient utilization of waste catalysts in road engineering applications [29,30].

The previous studies predominantly focused on the mechanical properties of asphalt without considering the diffusion behavior and the interfacial energy of asphalt components. However, there is currently still a lack of research on the diffusion behavior of asphalt components on the surface of waste catalyst oxides, especially the impact of interfacial energy variations on the adhesion and high-temperature properties of asphalt mortar. Therefore, it is still necessary to reveal the correlation of micro interface interaction with the macro performances of asphalt mortar, based upon theoretical calculation and experiments.

In this study, a molecular dynamics (MD) simulation method was used to analyze the diffusion behavior and interfacial energy changes of asphalt components with various waste catalyst oxides (WCOs). This was integrated with anti-rutting factor and anti-permanent deformation tests to systematically evaluate the influence of waste catalysts on the high-temperature stability of asphalt mortar. Simultaneously, using the gray correlation analysis theory, the relationships between diffusion behavior, interfacial energy, rutting resistance, and permanent deformation resistance were explored, further elucidating the action mechanism of waste catalyst-modified asphalt mortar. Unlike traditional studies that mainly focused on the physical properties of mineral fillers (such as particle size, specific surface area, and porosity), this study advances the understanding of the microscopic mechanism underlying asphalt component diffusion and interfacial energy changes, providing a new theoretical basis for understanding the effect of spent catalysts on the properties of asphalt mortar.

2. Materials and Methods

2.1. Materials

Five waste FCC catalysts (WFCs) named 1#, 2#, 3#, 4#, and 5# were obtained from Qingdao Huicheng Environmental Protection Technology Co., Ltd., Qingdao, China. They were used after harmless treatment. The main chemical compositions are Al₂O₃, SiO₂, La₂O₃, CeO₂, Fe₂O₃, NiO, and CaCO₃. The physicochemical properties and compositions of the five WFCs are shown in

Table 1. The physicochemical properties of the five WFCs.

WFC	Average Particle Size (μm)	Specific Surface Area (m2/g)	Average Pore Width (nm)	Density (g/cm3)	Hydrophilic Coefficient	Zeta Potential (mV)
1#	60.1	105	13.0	2.64	0.798	7.72
2#	71.5	116	11.6	2.49	0.969	7.93
3#	69.4	112	12.3	2.54	0.895	10.47
4#	81.0	107	10.8	2.63	1.001	8.05
5#	65.6	109	13.0	2.76	0.933	7.77

and

Table 2. The compositions and contents (%) of the five WFCs.

WFC	Al2O3	SiO2	La2O3	CeO2	Fe2O3	NiO	CaCO3	Others
1#	45.99	40.78	2.54	1.11	3	2.17	2.41	2
2#	44.3	42.11	2.49	1.33	2.95	2.52	2.3	2
3#	46.01	41	2.55	1.26	2.88	2.07	2.53	1.7
4#	48.01	39.99	2.93	1.03	3.56	0.98	1	2.5
5#	39.9	46.5	1.85	2.24	3.08	2.19	2.14	2.1

.

The mineral powder used in this study was limestone powder, which was obtained from Chongqing Highway Maintenance Engineering (Group) Co., Ltd., Chongqing, China. All the technical indicators met the requirements of JTG F40-2004, “Technical Specification for Highway Asphalt Pavement Construction”.

The SK70# base asphalt was used in this work, and its basic parameters met the requirements of JTG F40-2004 (see

Table 3. The basic indicators of SK70# base asphalt.

Indicators	Results	Technical Requirement
Softening point (°C)	47.8	>46
Penetration (25 °C, 5 s, 100 g)/0.1 mm	67.1	60~80
Penetration index	0.51	−1.5~1
Ductility (5 cm/min, 10 °C)/cm	31.5	>20
Ductility (5 cm/min, 15 °C)/cm	>100	>100
60 °C dynamic viscosity/(Pa·s)	226	>180
Residual needle penetration ratio after TFOT/%	65.2	>61

).

2.2. Preparation of WFC-Modified Asphalt Mortar

Before the preparation, the asphalt binder and powder (MP and WFC) were heated in an oven (DHG-9055A, Shanghai Yiheng Scientific Instrument Co., Ltd, Shanghai, China) for 1 h at temperatures of 150 and 165 °C, respectively. Then, the MP and WFC (120 g) were mixed at 165 °C with weight ratios of 15/85, 30/70, 45/55, and 60/40, corresponding to WFC dosages of 15%, 30%, 45%, and 60%. Finally, the hot asphalt binder (100 g) was poured into the MP/WFC mixture, followed by shearing at 150 °C for 0.5 h to obtain the asphalt mortar.

2.3. MD Simulation and Test Methods

The simulation process was conducted using Materials Studio software (Materials Studio 2020, Accelrys, San Diego, CA, USA). The asphalt molecular model was constructed based upon previous studies [31,32]. The values of interfacial energies between asphalt and various components in WFCs were calculated based on the asphalt–aggregate interface model [33]. Simultaneously, the diffusion coefficient (D) was calculated using the following equation [33,34].

$$D=\underset{t\to \infty }{lim}{\displaystyle \frac{1}{6Nt}}\left({{\displaystyle {\sum }_{i=1}^N\left|r_i(t)-r_0(t)\right|}}^2\right)={\displaystyle \frac{k}{6}}$$

(1)

where N is the number of molecules; t is the simulation time (ps); r₀(t) and r_i(t) are the positions of the molecule at 0 and t ps; k is the slope of mean square displacement.

The adhesion performance of asphalt with WFCs was evaluated based upon the surface free energy (SFE) theory. The contact angles between the asphalt and three indicating liquids (water, glycerol, and formamide) were measured using a HARKE-SPCAX3 contact-angle meter (Beijing Harke Test Instrument Factory, Beijing, China). The contact angles of WFCs were measured using a column wicking method [17]. All the tests were repeated three times to obtain the average values.

The high-temperature property of asphalt mortar was analyzed using a temperature sweep test on a dynamic shear rheometer (TA DHR-3, TA Instruments Inc., New Castle, DE, USA). The test temperatures were 52, 58, 64, 70, 76, and 82 °C, with a strain value of 1%, and an oscillation frequency of 10 rad/s. The upper and lower plates of the dynamic shear rheometer consisted of 25 mm parallel plates with a spacing of 1 mm. The rutting factor (G*/sinδ) was calculated to assess the high-temperature performance of asphalt mortar, where G* and δ are the complex modulus and phase angle.

Multiple stress creep recovery (MSCR) tests were performed under stress levels of 0.1 and 3.2 kPa at 64 °C to measure the rutting resistance of asphalt mortars. The deformation recovery rate (R_rec) and nonrecoverable creep compliance (J_nr) were calculated using Equations (2) and (3).

$$R_{rec}={\displaystyle \frac{{\gamma }_r}{{\gamma }_p}}\times 100\%$$

(2)

$$J_{nr}={\displaystyle \frac{{\gamma }_u}{\tau }}$$

(3)

2.4. Gray Relational Degree Theory

Gray relational degree analysis is a multifactor statistical analysis method primarily used to examine the degree of correlation among various factors within a system [35,36]. The gray relational degree analysis measures the degree of correlation by accessing the similarity or dissimilarity in the development trends of these factors, referred to as the gray relational degree. This method is suitable for the quantitative analysis of the relationship between system factors when information is sparse or incomplete. For discrete data, it is necessary to determine whether the slopes of the two curves are closely aligned. As a quantitative comparison method of the development situation, the core of the gray relational analysis is to calculate the degree of correlation between the target value (reference sequence) and a set of influencing factors (comparison sequence). By ranking these correlations, one can systematically identify the main factors that significantly impact the target value.

(1)

Reference sequence and comparison sequences

The dataset that represented the characteristics of the target object was selected as the reference sequence, while the data corresponding to the multiple influencing factors were used as the comparison sequences.

The reference sequence is denoted as

$$X_0=\left\{x_0\left(1\right),x_0\left(2\right),\cdot \cdot \cdot ,x_0\left(n\right)\right\}$$

(4)

The comparison sequence is denoted as

$$X_i=\left\{x_i\left(1\right),x_i\left(2\right),\cdot \cdot \cdot ,x_i\left(n\right),i=1,2,\dots \dots n\right\}$$

(5)

(2)

Non-dimensional processing

Because the original data of each series differ in dimension, unit, and nature, direct analysis may lead to inaccurate conclusions. Therefore, in this study, the averaging method was applied to standardize the original data, eliminate the inconsistency between data, enable meaningful comparisons, and ensure the accuracy and reliability of the subsequent analysis results. The calculation formulas are as follows:

$$Y_0=\left\{{\displaystyle \frac{x_0\left(1\right)}{{\overline{x}}_0}},{\displaystyle \frac{x_0\left(2\right)}{{\overline{x}}_0}},\cdot \cdot \cdot ,{\displaystyle \frac{x_0\left(n\right)}{{\overline{x}}_0}}\right\}$$

(6)

$$Y_i=\left\{{\displaystyle \frac{x_i\left(1\right)}{{\overline{x}}_i}},{\displaystyle \frac{x_i\left(2\right)}{{\overline{x}}_i}},\cdot \cdot \cdot ,{\displaystyle \frac{x_i\left(n\right)}{{\overline{x}}_i}}\right\}$$

(7)

(3)

First-order difference quotient

The first-order difference quotient was utilized to calculate the absolute difference between the reference sequence and comparison sequences over the same period.

$${\Delta }_i(k)=\left|Y_0-Y_i\right|$$

(8)

(4)

Correlation coefficient

The correlation coefficient of the series Y₀ and Y_i can be written as

$${\xi }_i(k)={\displaystyle \frac{\frac{min}{i}\frac{min}{k}\left|y_0(k)-y_i(k)\right|+\rho \frac{max}{i}\frac{max}{k}\left|y_0(k)-y_i(k)\right|}{{\Delta }_i(k)+\rho \frac{max}{i}\frac{max}{k}{\Delta }_i(k)}}$$

(9)

where ${\xi }_i(k)$ is the correlation coefficient, that is, the relative difference value between the comparison curve and the reference curve of the number i-th factor at the k-th point; ${\displaystyle \frac{min}{i}}{\displaystyle \frac{min}{k}}\left|y_0(k)-y_i(k)\right|$ is the minimum difference between the two levels; and ${\displaystyle \frac{max}{i}}{\displaystyle \frac{max}{k}}\left|y_0(k)-y_i(k)\right|$ is the maximum difference between the two levels.

ρ is the resolution coefficient, with a value range of 0 ≤ ρ ≤ 1. The ρ value is usually taken as 0.5 according to previous studies [37]. This coefficient reflects the discrimination sensitivity to the influential factors. The smaller the ρ value, the stronger the ability to distinguish the influential factors.

(5)

Degree of gray correlation

The average correlation coefficient of the group was obtained according to the component correlation coefficient of each sequence group, and the average represented the Dunn correlation degree between the reference sequence and the corresponding comparison sequence.

$$y_i={\displaystyle \frac{1}{N}}{\displaystyle {\sum }_{K=1}^N{\xi }_i(K)}$$

(10)

The closer y_i is to 1, the stronger the correlation between the reference sequence and the comparison sequence; that is, the better the correlation between the two.

3. Results and Discussion

3.1. Diffusion Coefficient

The effect of spent catalyst oxides on the diffusion behavior of asphalt components is primarily determined by the diffusion coefficient. The diffusion coefficient directly reflects the movement of asphalt components on the oxide surface. Higher diffusivity results in a shorter residence time of the molecules on the surface, weaker adsorption strength, and reduced interfacial stability. Conversely, the lower the diffusivity, the stronger the adsorption force of the molecule to the surface, but with limited mobility, which may lead to a decrease in the flexibility of the material. Moderate diffusivity is a crucial factor in the design of road materials. Moderate diffusivity not only ensures that the components form a stable interface on the surface, improving the bonding properties of the material, but also does not excessively restrict the movement of the molecules, thus achieving a good balance between viscoelastic properties and fatigue resistance. This performance optimization is significant for improving the high-temperature stability and permanent deformation resistance of asphalt mixtures. Herein, the diffusion behavior of asphalt binder with the various components of WFCs was investigated based upon molecular dynamics simulations. The diffusion coefficients were calculated using Equation (1). The results are shown in Figure 1.

As shown in Figure 1, the surface saturation fraction of Al₂O₃ is the most diffuse, indicating that the saturation fraction has a high motivity on the surface of the oxide. The highest aromatic diffusion coefficient on the SiO₂ surface suggests that the aromatic component has the strongest fluidity on the surface, resulting in a shorter molecular residence time. The surface of CaCO₃ demonstrates the strongest gelatinization, which indicates that macromolecular structures with complex compositions exhibit better diffusivity on CaCO₃. The diffusivity of the four components on the Fe₂O₃ surface shows minimal variation. The adsorption or diffusion of different molecular types on the Fe₂O₃ surface is balanced, which may be related to the uniform distribution of active sites on the surface. The asphaltene diffusivity on the NiO surface is significantly higher than that of other components, while the diffusivity of other components remains relatively low. The diffusion of aromatic components on the CeO₂ surface is significantly higher than that of other components, which may be due to the strong polarity of the CeO₂ surface, which enhances its adsorption capacity. The diffusional characteristics of the four components on the La₂O₃ surface show minimal differences, indicating that the adsorption characteristics of the different components in La₂O₃ are similar, resulting in consistent adsorption and diffusion behaviors.

Overall, the diffusion behavior is directly affected by surface characteristics such as polarity, surface energy, and active site. The diffusivity of different asphalt components on various surfaces reflects the strength of their interaction with the surface. This difference ultimately affects the macroscopic properties of the material, such as adhesion and rheology. The previous work of our group also proved that the asphalt binder exhibits poor diffusion behaviors on the alkaline aggregates, such as CaO, MgO, and CaCO₃, due to the strong electrostatic attractions and hydrogen bonds between them, which affect the macroscopic properties of asphalt mortar [38].

3.2. Interfacial Energy of Asphalt and Components of WFCs

MS software (2020) was used for molecular dynamics simulation to calculate the total interfacial energy and nonbonding interfacial energy between asphalt and the components of WFC interfaces. This analysis evaluated the adhesion performance between asphalt and spent catalyst systems. The total interfacial energy represents the strength of interaction between asphalt components and spent catalyst oxides. The greater the total interfacial energy, the greater the interaction between asphalt and waste catalysts, and the better the adhesion.

As shown in Figure 2a–d, CaCO₃ and Fe₂O₃ exhibited high total interfacial energies, indicating strong adhesion to bitumen. This strong adhesion property can effectively improve the anti-spalling performance of asphalt mixtures, especially under high-temperature or wet conditions. Surfaces with strong nonbonding interactions, such as van der Waals forces, demonstrated optimal adhesion, as observed in Fe₂O₃ and CaCO₃. The optimal adhesion is due to the strong adsorption of van der Waals forces, which can enhance the strength of the interface between the surface and asphalt, thereby effectively preventing spalling and water damage. Surfaces with high electrostatic interface energies (such as NiO) form strong adhesion through polar interactions, making them ideal for applications where improved water resistance and bond strength are required. Conversely, for surfaces with low electrostatic interface energies (such as Al₂O₃), surface modification is required to enhance their adhesion and avoid interface failure due to insufficient adhesion.

Because Fe₂O₃ and CaCO₃ have strong van der Waals and nonbonding forces, they are suitable for the design of road materials in high-temperature and high-humidity environments, which can significantly improve the adhesion and durability of asphalt mixtures. NiO, with its strong electrostatic forces, enhances the interface strength between asphalt and the surface, making it ideal for road materials designed to resist water damage. Although Al₂O₃ and SiO₂ exhibit low interface energies, their adhesion can be improved by surface modification or the addition of active agents, making them suitable for applications under low-to-medium-stress conditions.

From the results for the diffusion coefficient and interface energy, one can see that the two parameters are inversely correlated. This phenomenon indicates that the strong interfacial interaction between asphalt binder and filler may prevent the movement of asphalt on the surface of the filler [34]. Generally, strong interfacial energy of asphalt with filler means good adhesion ability of the asphalt [38]. From this point of view, one can judge the adhesion of an asphalt binder to an aggregate from the value of the diffusion coefficient.

3.3. Adhesion Analysis of Asphalt and Waste Catalyst

Asphalt mortar is a gelatinized, non-uniform structure formed by the diffusion of asphalt components and their adsorption onto the surface of the filler. The adsorption of molten asphalt components onto the surface and within the pores of the filler forms structural asphalt through physicochemical interactions, thus bonding the interfaces of different materials. The interfacial adhesion between the filler and asphalt determines the stability of the asphalt mortar and significantly affects the high-temperature stability, low-temperature crack resistance, and water stability of the asphalt mixture. The larger the surface and specific surface areas of the filler added to the asphalt, the stronger the adsorption effect on the asphalt components. In particular, the specific surface area of the waste catalyst is approximately 60 times that of limestone mineral powder, and its high surface potential energy has a significant effect on adsorption. Therefore, the energy changes in the mineral powder, waste catalyst, and asphalt during the adhesion process were tested and analyzed using surface free energy theory to explore the internal development law of the adhesion of the asphalt and filler. The surface energy and the components of bitumen, mineral powder, and spent catalyst were measured using the laying drop method. The adhesion work between the bitumen, mineral powder, and spent catalyst was calculated using the relevant formulas [17]. The results of these calculations are presented in Figure 3.

As shown in Figure 3, the adhesion work of asphalt, mineral powder, and the five waste catalysts is relatively consistent, ranging from 44.93 to 53.67 mJ·m⁻², with an average value of 47.411 mJ·m⁻². Notably, the adhesion work of asphalt, mineral powder (MP), and waste catalyst in a unit area is approximately 45.64 mJ·m⁻², indicating similar performances. This further proves that the waste catalyst is alkaline and has good adhesion to asphalt, demonstrating that the performance of the waste catalyst asphalt mortar is stable. Previous studies suggest that the treatment of aggregate with alkaline silane coupling can improve the adhesion work between asphalt and aggregates due to the acid–base interaction [17,39].

3.4. Dynamic Shear Rheometer (DSR)

The high-temperature stability of the waste catalyst asphalt mortars was analyzed using dynamic shear rheometer (DSR) tests. The complex modulus G* and phase angle δ could be obtained. The rutting factors (G*/δ) of the mortars were calculated and are shown in Figure 4.

As shown in Figure 4, under the same temperature conditions, the rutting factor of waste catalyst asphalt mortar is significantly higher than that of the mineral powder asphalt mortar, and the rutting factor of different types of waste catalyst asphalt mortar exhibits an increasing trend with the rising content of substitute mineral powder. The addition of waste catalysts significantly enhanced the deformation resistance of the asphalt mortar at high temperatures. Xiao et al.’s study shows that the addition of coarse WFCs as filler can increase the rutting factor (G*/sinδ) of asphalt mortar by around four times more than that with limestone as filler at 58 °C (filler/binder = 0.8–1.2) [4]. The results are similar to those in this work. However, the modification effects of different types of waste catalysts vary, even when used at the same mixing ratio, highlighting their distinct performance characteristics.

3.5. Resistance to Permanent Deformation of WFC Asphalt Mortar

Rutting deformation of asphalt pavements primarily occurs due to insufficient resistance to permanent deformation under vehicular loads in high-temperature conditions, which greatly reduces the performance and durability of asphalt pavements. The addition of a waste catalyst as a modifier in asphalt mortar effectively enhances its resistance to permanent deformation, as demonstrated through multiple stress creep recovery (MSCR) tests. The test results are shown in Figure 5.

As shown in Figure 5, the strain of the five types of asphalt mortar increases with loading time under both stress levels. The strain of asphalt mortar after adding waste catalysts is lower than that of asphalt mortar containing only mineral powder, indicating that the addition of waste catalysts can improve the resistance of asphalt mortar to permanent deformation. This improvement is attributed to the waste catalysts’ significantly larger specific surface area, which is about 60 times that of the mineral powder; further, the waste catalysts have the characteristics of rich pore structure and high surface potential energy. These properties strengthen the adsorption of the asphalt components, thereby improving the resistance to permanent deformation of the asphalt mortar.

Furthermore, as the proportion of waste catalyst replacing mineral powder increases, the strain of the five types of asphalt mortar gradually decreases. The asphalt mortar had the best resistance to permanent deformation when the proportion of waste catalyst that replaced the mineral powder was 60%. Compared with the other three types of asphalt mortar under 0.1 and 3.2 kPa stress, the permanent deformation resistance of asphalt mortar mixed with 2# and 3# waste catalysts is smaller. This finding suggests that two types of waste catalyst modifiers, 2# and 3#, have the greatest influence on reducing strain in asphalt mortar.

The average elastic recovery rate R_rec and average nonrecoverable creep compliance index J_nr were used to further evaluate the permanent deformation resistance of the waste catalyst-modified asphalt. R_rec indicates the ability of asphalt to recover from deformation during creep, while J_nr represents irrecoverable deformation. The greater the elastic recovery rate, the stronger the elastic property and recovery ability of the material, whereas the opposite is true for nonrecoverable creep compliance. The smaller the value, the stronger the permanent deformation resistance of the asphalt in the pavement. The R_rec and J_nr of the asphalt mortars were calculated using Equations (2) and (3). The results are presented in Figure 6 and Figure 7.

As shown in Figure 6 and Figure 7, the elastic recovery rate of asphalt mortar after adding the waste catalyst modifier is higher than that of asphalt mortar containing only mineral powder. This indicates that waste catalyst modifiers can effectively improve the performance of asphalt mortar. The average elastic recovery rate of asphalt mortar under 0.1 kPa stress is greater than that under 3.2 kPa stress. For the same number of waste catalyst modifiers, the elastic recovery rates of 2# and 3# are better than those of others. Generally, an inorganic aggregate with high surface area exhibits good adsorptive ability to small organic molecules due to the capillary effect [40]. The asphalt molecules, such as resins and aromatics, can be more likely adsorbed into the pores and surface of 2# and 3# WFCs with high surface area and moderately wide pores to form a uniform stable mortar system, preventing phase separation of asphalt mortar during pressing [41]. Therefore, the improvement in the elastic recovery rates can be attributed to the large specific surface area of these two types of waste catalyst modifiers and the stronger adsorption effect on asphalt, thus improving the permanent deformation resistance of asphalt mortar. Overall, the elastic recovery rate of the asphalt mortar was the highest when the content of waste catalyst replacing the mineral powder was 30%. Although the average elastic recovery rate of asphalt mortar is also better at 60%, the content of the waste catalyst modifier is recommended to be less than 30% from the perspective of comprehensive cost and other properties. From Figure 5, it can be seen that as the average elastic recovery rate of the modified asphalt mortar increases, the average nonrecoverable creep compliance value decreases. Under 0.1 kPa stress, the nonrecoverable creep compliance value is very small and almost negligible, indicating that it has little influence on the performance of asphalt mortar under these conditions. However, under a stress of 3.2 kPa, the nonrecoverable creep compliance value shows a change by an order of magnitude. This result suggests that long-term nonrecoverable deformation is generated under a higher load. Still, the value of asphalt mortar with an added waste catalyst is smaller than that of asphalt mortar with only mineral powder added.

3.6. Gray Correlation Analysis

To analyze the reasons for the improvement in the high-temperature performance of asphalt mortar after the addition of a waste catalyst, a correlation analysis was carried out. The analysis examined the relationships between the adhesion work, high-temperature performance, and permanent deformation resistance of asphalt mortar, using two key parameters: the total interfacial energy between asphalt and waste catalyst oxides and the diffusion coefficient on the surface of the waste catalyst.

Using the molecular dynamics simulation results, the total interfacial energy between the asphalt and waste catalyst oxides and the diffusion coefficient on the surface of the waste catalyst were obtained. These parameters, along with adhesion work, rutting factor (evaluated at 64 °C as a representative example), and the resistance to permanent deformation (R_rec and J_nr) of the waste catalyst asphalt mortar, were analyzed. The results of the original series are shown in

Table 4. Original series.

Material ID	Xi (1)	Xi (2)	Xi (3)	Xi (4)	X0 (1)	X0 (2)
	Work of Adhesion	Rrec	Jnr	Rutting Factor	Total Interface Energy	Diffusion Coefficient
1#	46.28	4.05243	0.000756725	7788.41	233.66	0.0086
2#	44.93	6.617825	0.000549541	10581.09	231.76	0.0092
3#	49.19	5.123895	0.000687345	10336.39	229.96	0.0085
4#	48.18	4.124365	0.000779037	9061.17	237.52	0.0085
5#	53.67	4.2187575	0.000954275	7486.77	482.38	0.0339

.

Each index of the original series in Table 1 corresponds to a different unit of measurement, and there are differences in their orders of magnitude. To ensure comparability, the data were normalized using the dimensionless approach, employing the mean value method for calculation. The gray correlation coefficients of the data were calculated, and the results are shown in

Table 5. Correlation coefficient calculation results.

Material ID	Work of Adhesion		Resistance to Permanent Deformation		Rutting Factor
	Total Interface Energy	Diffusion Coefficient	Total Interface Energy	Diffusion Coefficient	Total Interface Energy	Diffusion Coefficient
1#	0.97	0.78	0.92	0.74	1.00	0.81
2#	1.00	0.84	0.79	0.77	0.73	0.65
3#	0.89	0.73	0.86	0.70	0.74	0.64
4#	0.94	0.75	0.91	0.72	0.87	0.71
5#	0.62	0.39	0.57	0.36	0.50	0.35

.

The data in Table 5 were calculated to obtain the gray correlation degree based upon Equations (4)–(10), and the calculation results are shown in Figure 8.

As shown in Figure 8, based on the results of molecular dynamics simulation, the correlation of the performance of each index of the waste catalyst asphalt mortar was greater than 0.6, indicating a good correlation. The correlation of the total interfacial energy with the adhesion work, rutting factor, and stress sensitivity index of the waste catalyst asphalt mortar was higher than that of the diffusion coefficient. The correlation degree ranking of the three indices with respect to the total interfacial energy and diffusion coefficient was as follows: adhesion work > resistance to permanent deformation > rutting factor. This trend is primarily attributed to the adhesion of the waste catalyst to asphalt, which is driven by van der Waals forces or electrostatic interactions. Nonbonding forces, which mainly include van der Waals and electrostatic forces, are particularly significant on highly polar or active surfaces [32,38].

4. Conclusions

(1)

There was a strong correlation between the diffusion behavior of the asphalt components on the oxide surface and the interface between them. On the surfaces of rare-earth metal oxides, the asphalt components exhibited slower diffusion rates, higher interfacial energy, and stronger adhesion. Conversely, on the surfaces of alumina and silicon oxide, the diffusion rates were faster, and the interfacial energy was lower. The presence of rare-earth oxides significantly enhanced the adhesion between the asphalt components and oxide surfaces. This finding is consistent with the results of the adhesion test, which further validates the strong adhesive interactions between the asphalt components and waste catalysts.

(2)

With the addition of the waste catalyst instead of mineral powder to asphalt cement, the rutting factor increased with the amount of waste catalyst. When the proportion of waste catalyst replacing the mineral powder reached 30%, the rutting resistance factor increased by 50%, which significantly improved the high-temperature deformation resistance of the waste catalyst-modified asphalt mortar.

(3)

Through creep recovery, elastic recovery, and nonrecoverable creep compliance tests, it can be seen that the addition of a waste catalyst effectively improves the average elastic recovery rate of asphalt mortar and significantly reduces the nonrecoverable creep compliance. Under a stress of 3.2 kPa, although nonrecoverable creep compliance increases by orders of magnitude, the nonrecoverable deformation value of the waste catalyst-modified asphalt mortar is always lower than that of the mineral powder asphalt mortar. Among the tested waste catalysts, types 2# and 3# showed the best deformation resistance.

(4)

Gray correlation analysis showed that the correlation between the performance indices of the waste catalyst asphalt mortar was strong, with correlation coefficients greater than 0.6. The degree of correlation between the interfacial energy and diffusion coefficient was influenced by adhesion work, resistance to permanent deformation, and the rutting factor. The results showed that the stronger the interfacial interaction between asphalt components and the waste catalyst, the weaker the diffusion behavior and the better the high-temperature performance of the asphalt mortar.