The chemo-mechanical properties of bitumen undergo significant alternations during aging and rejuvenation, posing challenges for accurately evaluating and enhancing rejuvenation efficiency in asphalt recycling. This study investigates how bitumen source, aging degree, rejuvenator type and dosage influence the chemical and rheological performance of rejuvenated bitumen. Comprehensive characterizations are performed using saturate, aromatic, resin, and asphaltene (SARA) fractionation, elemental analysis, gel permeation chromatography (GPC), and dynamic shear rheometer (DSR) tests. To elucidate chemo-rheological correlations, statistical techniques (Pearson correlation, analysis of variance (ANOVA), and Chi-square tests) are combined with artificial neural networks (ANN). Results indicate that the NB bitumen with more colloidal stability and less sulfur content exhibits the highest resistance to long-term aging. FB bitumen with 4.3 % sulfur achieves the best high-temperature deformation resistance with rutting failure temperature (RFT) higher than 80 °C, and TB bitumen exhibits the longest fatigue life. Rejuvenation using bio-oil is most effective on reducing relaxation time by up to 60 % and increasing creep compliance (Jnr3.2) by 1.7–2.5 times, depending on bitumen type. Rejuvenator dosage sensitivity for relaxation stress follows the trend: bio-oil < engine-oil < naphthenic-oil, while aromatic-oil shows variability depending on its source. Among the tested rejuvenators, bio-oil proves most effective, particularly for rejuvenating TB and FB bitumen. The ANN model demonstrates strong predictive performance for rheological properties, achieving R2 values between 0.90 and 0.98, with the highest accuracy observed for relaxation indices, followed by fatigue and rutting properties.

The concept of self-healing asphalt has been developed to implement an extrinsic crack repair system, reduce maintenance efforts, and extend the service life of asphalt pavements. Various self-healing asphalt methods have been proposed and demonstrated, however, it is difficult to compare and finalize an optimum self-healing design for an upscaled application. To provide a better understanding of the prospects of each self-healing technology, this study investigates the physical properties and ranks the healing efficiency of each self-healing asphalt technology. Four self-healing systems were investigated, including alginate capsule system, conductive alginate capsule system, induction system, and a hybrid system (alginate capsule & induction). Laboratory tests, including Indirect Tensile test (ITT), Water Sensitivity test (WS), Binder Drainage test (BD), Triaxial test, and Semi-circular Bending test (SCB), were conducted to assess the physical performance of the asphalt mixtures. The healing efficiency of each mix was evaluated with a SCB bending and healing program. The results indicate that the addition of self-healing additives affects the physical properties of the SMA mix. The capsules reduce the mixture strength, stiffness and high-temperature stability, while the steel fibers have the opposite effect. The healing efficiency results show that the capsule healing system and conductive capsule healing system can be repeated twice, while the induction system and hybrid healing system showed a healing index above 60 % in all eight bending-healing cycles, demonstrating a promising and durable healing effect for the SMA mix.

Previous work demonstrated that Random Forest Regressors (RFRs) could estimate the physical properties of bitumen using molecular descriptors derived from Molecular Dynamics (MD) simulations, thereby reducing the need for computationally intensive simulations. However, due to their decision-tree structure, RFRs lack true predictive capabilities, particularly for interpolation and extrapolation beyond the training data.

This study advances that foundation by employing Artificial Neural Networks (ANNs), which—when properly trained—can capture complex relationships with greater continuity and generalizability. Beyond simply replacing RFRs, we develop a fully automated framework for constructing Machine Learning Models (MLMs) to predict density and thermal expansion coefficients of bitumen. Using Optuna for hyperparameter optimization, we ensure that the information extracted from MD simulations is utilized effectively.

The resulting ANN models accurately reproduce MD-predicted densities, achieving R2>0.99, MSEs below 0.1 %, and maximum absolute errors below 5 % on test data. In addition to reducing computational cost, the models exhibit improved interpolation and extrapolation capabilities, enabling reliable predictions for properties, ranges, and compositions not explicitly simulated.

Key aspects of our approach include:
• Transitioning from RFRs to ANNs, improving generalization, interpolation, and predictive accuracy.
• Automated hyperparameter optimization, leveraging Optuna to maximize model efficiency.
• Expanding applicability, enabling property prediction for unseen compositions without additional MD simulations.

Fatigue cracking is one of the most notable distresses in steel bridge deck pavement (SBDP), necessitating the development of high performance pavement materials to extend service life. In this paper, the fatigue resistance characteristics of natural rock asphalt (NRA)/SBS systematically evaluated. Twelve types of composite-modified asphalt binders were prepared by incorporating Iranian rock asphalt (IRA), Buton rock asphalt (BRA), and SBS as modifiers. IRA and BRA were added at 5 wt%, 10 wt%, and 15 wt%, while SBS was introduced at 2 wt% and 3 wt%. The modified asphalt binders subjected to time sweep (TS) test and linear amplitude sweep (LAS) test to comparatively analyze fatigue damage and fatigue life. DSR-C model was applied to calculate the fatigue crack length. The research also comparative evaluate differences and correlations between fatigue crack length indexes and conventional fatigue life indexes. The results showed that NRA enhanced the fatigue performance of modified asphalt binders. With the increase of NRA content, the fatigue properties of modified asphalt also become better. S₃I₁₅ is better than other composite modified asphalt binders in both fatigue life and fatigue cracking indexes, demonstrating that it offers the best resistance to fatigue damage. The fatigue cracking index calculated by the DSR-based cracking (DSR-C) model could effectively evaluate the fatigue performance of NRA/SBS composite modified asphalt binders. NRA/SBS composite modified asphalt could be widely used in steel bridge deck pavement.

Pavement materials that could enhance the mechanical properties of open-graded porous asphalt mixtures in long-term service periods could offer a solution to produce long-life pavements, causing a reduction of interventions' needs, as well as the associated disruptions to road users and user costs. One option to improve the longevity of open-graded porous mixtures is with the use of epoxy asphalt that, despite its high initial cost, offers enhanced longevity that might offset any future user and intervention costs. This study aimed to evaluate the durability of plant-produced epoxy-modified open-graded porous asphalt mixtures. A batch production plant was employed to produce loose mixtures, which were used to pave a test road in the Province of Gelderland, the Netherlands, and compact specimens in the laboratory. Control mixtures with a non-epoxy-modified asphalt binder were also produced in the same plant. The durability of laboratory- and field-compacted mixtures was evaluated by conducting indirect tensile tests before and after oven conditioning. Results illustrated that the epoxy-modified asphalt demonstrated the highest strength and stiffness values, while the strength was reduced after conditioning in a water bath with the retained strength within the allowable specification limits. This attribute was confirmed from drill cores obtained from the test road after one year in service. Also, the materials compacted in the field had slightly higher strength and stiffness values than the laboratory-produced mixtures. Although the results provided have illustrated the improvement of durability of open-graded porous asphalt with implementing epoxy modification, further evidence from the test road over the years is needed for validation.

Scymol is a Python-based software package specifically designed to facilitate the setup and execution of molecular simulations in LAMMPS. It comes equipped with a user-friendly interface, which simplifies the process of initializing molecular systems and defining simulation parameters. Moreover, the software generates and executes LAMMPS simulation sequences, enabling researchers to establish comprehensive simulation schemes, such as heating or deformation cycles, in a single run. Through its successful application in diverse research projects and its modular design, Scymol demonstrates considerable promise as an indispensable tool for researchers aiming to carry out molecular dynamics simulations without sacrificing complexity or high-throughput capabilities in their methodologies.

To increase the utilization of used tires, reduce carbon emissions and improve asphalt pavement performance, SBS/TB crumb rubber modified asphalt binder was designed, which was enhanced by SBS and terminal blend (TB) crumb rubber. SBS/TB crumb rubber modified asphalt binder was prepared by mixing 0 %, 10 %, and 15 % TB crumb rubber with 2 % and 3 % SBS, respectively. This study investigated the microstructure, thermal stability and rheological properties of SBS/TB crumb rubber modified asphalt binder. The Spearman correlation coefficient is introduced to analyze the correlation of microstructural, thermodynamic and rheological parameters. The results showed that SBS and TB crumb rubber were uniformly dispersed in asphalt binder without agglomeration phenomenon. In addition, the interaction between SBS and TB crumb rubber resulted in the formation of cross-links between the polymer and the asphalt binder, significantly improving the storage stability and the thermal stability of the modified asphalt binder. The pyrolysis mechanism of the modified asphalt binder is One-dimension diffusion or One-dimension phase boundary. With the addition of SBS and TB crumb rubber, the rheological, high-and-low temperature properties of modified asphalt binder are improved. Finally, microstructural, thermodynamic and rheological parameters have an extremely strong correlation by Spearman correlation coefficient analysis.

Elastomer/plastic compound-modified bitumen was created by adding reactive elastomeric terpolymer (RET) to plastic-modified bitumen, made of either high-density polyethylene (HDPE) or recycled polyethylene (RPE). The rheological properties of the modified bitumen were analyzed. The results indicated that RET elastomer improved high-temperature modulus, temperature insensitivity, anti-rutting properties, elastic recovery, and shear-resistance of both HDPE and RPE-modified bitumen. A high dosage of RET had a negative impact on the cracking resistance of plastic-modified bitumen, thus it is recommended to use 1wt% for optimal results. The increased elasticity in the bitumen was attributed to the creation of a polymer network by RET.

Atomistic simulations are crucial for understanding material properties at the molecular level but are limited by high computational costs, especially for large, complex systems like bituminous materials. Our team developed a Force-matched United Atom (UA) Coarse Graining (CG) force field to enhance computational efficiency while retaining atomic detail. However, converting all-atom models to CG models is complex, requiring detailed atom-to-bead mapping and compatibility with molecular dynamics (MD) engines like LAMMPS. To address this, we introduce AA2UA, an open-source software that simplifies the conversion of PDB files into LAMMPS-readable structure topology files, facilitating broader use of the developed UA force field.

Pdb2dat, developed in Python, is an open-source, self-contained utility that facilitates the conversion of PDB files into LAMMPS data files, catering to the need of initializing atomistic simulation from initial atomic configurations. It extracts molecular details from PDB files, uses Rdkit and Xyz2mol for bonding analysis and 3D conformer generation, and uses Pysimm for assigning force field types and charges. Designed to be lightweight and fully Pythonic, pdb2dat is suitable for use in privilege-limited high-throughput environments. The output details system topologies for use in MD simulations, significantly simplifying the preparatory steps needed by researchers to explore materials phenomena through LAMMPS.

The advent of computational techniques, particularly atomistic simulations, has lessened the dependency on physical experiments in various scientific fields. Yet, the preparation complexity for simulations using platforms like LAMMPS and GROMACS persists. We introduce SMI2PDB, a Python tool that automates molecular systems assembly from SMILES to PDB format, easing molecular dynamics simulation setups. SMI2PDB manages molecule configuration and quantification effortlessly, establishes stable conformers, applies random rotations, and positions them in a simulation box with a Sobol sequence to reduce overlaps. This script facilitates the rapid preparation of complex organic mixtures for use in simulations, enhancing the exploration of novel materials.

This study enhances the molecular analysis of bitumen by transitioning from traditional chemical descriptors, such as SARA (Saturates, Aromatics, Resins, and Asphaltenes) fractions and elemental compositions, to specific force field atom types in Molecular Dynamics (MD) models. This shift improves the precision in predicting material properties critical for bituminous material characterization. Machine Learning Models (MLMs) were developed to use these atom types as input features, inherently reflecting fundamental chemical characteristics. Trained on data from over 1,770 LAMMPS simulations of diverse bitumen types and conditions, these MLMs enable the prediction of properties like density, heat capacity, solubility parameters, and thermal expansion coefficients without the need for additional MD simulations. The models utilize 30 chemical descriptors corresponding to specific atom types in the PCFF force field, which collectively account for over 95% of the influence on these properties. By accurately predicting fundamental, thermodynamic, and kinetic properties, the use of MLMs and force field atom types allows researchers to efficiently tweak the chemical nature of organic molecules and mixtures to achieve desired properties. With near-instantaneous prediction times, these MLMs offer valuable insights for advancing bitumen research in the construction and petroleum industries, reducing the need for more intensive simulation techniques.

Bitumen fatigue resistance is critical to determine the overall fatigue performance and service life of asphalt pavements. However, the mechanisms responsible for fatigue damage of bitumen have previously not been well understood. Molecular dynamics (MD) simulation has recently emerged as a powerful computer-aided numerical technique to model the microscopic failure behaviours in materials. This study aims to use the MD method to investigate the molecular origin of bitumen fatigue damage. The molecular models of the virgin and aged PEN70/100 bitumen were firstly constructed based on their saturate, aromatic, resin and asphaltene (SARA) four fractions. An MD equilibrium was run on the developed bitumen models with the assigned interatomic potentials. Following an MD-based tensile simulation, a strain-controlled fatigue simulation was performed to study the nanostructure and damage behaviours of the virgin and aged bitumen under fatigue loading by calculating the stress-strain response, potential energy, molecular structure and nanovoid volumes. Furthermore, a rheometer measurement was also conducted to characterise the fatigue damage of the bitumen directly by a crack length at the macroscale. Results indicate that the bitumen molecules become unfolded and tend to align along the loading direction when fatigue loading was applied. The change in the molecular configuration helped the molecular chains move closer together and thus contributed to the reduction of the intermolecular interactions including the van der Waals and Coulombic energies. With the increasing load cycles, nanovoids were formed and grew in the bitumen through molecular rearrangement and movement, leading to microscopic fatigue damage of the bitumen. It was found that the aged bitumen produced more severe fatigue damage than the virgin bitumen, which was indicated by the MD-based nanovoid volume at the molecular scale and the DSR-based crack length at the macroscale. The findings from MD simulation provide a fundamental understanding of the molecular origin of fatigue damage, that cannot be experimentally detected for bitumen materials.

Developed by Delft University of Technology, the tri-component polyurethane modified cold binder (PMCB) displays impressive durability and strength in asphalt mixtures, showing promise as a reliable binder for cold in-place recycling. However, when applying PMCB for rapid, in-situ recycling, the presence of moisture in reclaimed asphalt pavement (RAP) poses a significant challenge. To address this, an innovative approach involving treatment of the wet RAP with Calcium dioxide (CaO) prior to the integration of PMCB was tested. Evaluation methods used included the Indirect Tensile Test (ITT), followed by the calculation of the Indirect Tensile Strength Ratio (ITSR) to assess moisture susceptibility. Furthermore, Cantabro tests were performed to determine the material loss under abrasion and weathering conditions. These assessments underscored the feasibility of this approach. The treatment of wet RAP with CaO has proven a viable strategy for rapid in-situ recycling with PMCB, contributing to sustainable pavement construction. In addition, the research identified that a 5.5% concentration of the PMCB binder maximizes structural integrity and performance in the considered RAP.

The low-temperature relaxation and fatigue cracking performance are two essential aspects in estimating the rejuvenation efficiency of recycling agents (RAs). This study aims to fundamentally investigate the effects of recycling agent type/dosage and aging degree of bitumen on thermodynamic and rheological properties of rejuvenated bitumen at low and intermediate temperatures. Molecular dynamics (MD) simulations are utilized to predict thermodynamic indices of rejuvenated bitumen, further linked to critical low-temperature and fatigue indicators from experiments. The results reveal that all RAs show a regeneration effect on fractional free volume (FFV), self-diffusion coefficient (DS), glass transition temperature (Tg), and surface free energy (γ). Bio-oil and engine-oil exhibit higher rejuvenation efficiency on these thermodynamic properties than naphthenic-oil and aromatic-oil. The aging degree of bitumen and temperature show significant effects on rejuvenation efficiency. It is recommended to use the FFV parameter to predict the relaxation properties of rejuvenated bitumen. However, these thermodynamic indicators inadequately differentiate between rejuvenators and softeners. Based on crossover parameter results, most recycling agents (bio-oil, engine oil, and naphthenic oil) in this study display softening characteristics. Only aromatic oil effectively rejuvenates the crossover modulus (Gc) of aged binder. Notably, engine oil demonstrates the least rejuvenation in crossover parameters for the recovery of aged bitumen. Further, γ demonstrates a strong association with both Glover-Rowe (G-R) and fatigue crack width C500 indices across all cases involving rejuvenated bitumen. This work will build a multi-scale evaluation framework on the rejuvenation effectiveness of recycling agents on low-temperature and fatigue performance of aged bitumen.

This paper presents a United Atom (UA) force field for simulating hydrocarbon molecules in bituminous materials, integrating explicit hydrogens into beads with their parent atom. This method simplifies all-atom molecular models, significantly accelerating Molecular Dynamics (MD) simulations of bitumen by 10 to 100 times. Key advantages include halving the particle count, eliminating complex hydrogen interactions, and decreasing the degrees of freedom of the molecules. Developed by mapping forces from an all-atom model to the centers of mass of UA model beads, the force field ensures accurate replication of energies, forces, and molecular conformations, mirroring properties like pressure and density. It features 17 bead types and 287 interaction types, encompassing various hydrocarbon molecules. The UA force field's stability, surpassing all-atom models, is a notable achievement. This stability, stemming from smoother potential energy surfaces, leads to consistent property measurements and improved stress tensor accuracy. It enables the extension of MD simulations to larger spatiotemporal scales, crucial for understanding complex phenomena such as phase separation in bituminous materials. This foundational work sets the stage for future developments, including refining parameters and introducing new bead types, to enhance the modeling capabilities of the force field, thereby advancing the application and understanding of bituminous materials.

This study employs strain-controlled oscillatory deformations in Molecular Dynamics (MD) simulations to evaluate the dynamic properties of all-atom molecular systems, specifically targeting the SARA fractions of bitumen. Twelve molecular systems representing these fractions were modeled using the PCFF force field. The simulations effectively captured their viscoelastic properties across multiple frequency domains, including Elastic, Glassy, Rubbery, and Viscous responses. Reported storage and loss moduli range from thousands to tens of megapascals, with viscosities from tens to near-zero Pascal-seconds across various frequencies and temperatures, aligning well with experimental observations. Saturates and Aromatics were identified as the softest and most thermally susceptible fractions, while Resins and Asphaltenes were the stiffest and least susceptible. The study reveals that the relaxation time of all-atom molecular systems is significantly shorter than in experimental setups, necessitating careful comparison of stress-related phenomena across equivalent relaxation times. Although this allows for the exploration of response profiles in computationally tractable simulations, the nature of all-atom force fields and simulation algorithms introduces spatiotemporal scale discrepancies that must be addressed in future simulations involving the study of stress-related phenomena using MD.

An asphalt joint is formed when a fresh mix is laid and compacted next to an existing layer, brings about temperature difference during compaction, and therefore requires extra care in quality control and expose to higher cracking risks. Self-healing asphalt aims to stimulate the healing capacity of asphalt mixture and prolong its service life. The main objective of this study is to develop and optimize a calcium alginate capsules healing system for an asphalt joint mix. Capsules following two different self-healing concepts were prepared, namely conventional alginate capsules and conductive alginate capsules. Microscopy, Computed Tomography (CT) and Thermogravimetry analysis (TGA) were used to investigate the performance of alginate capsules. The results show that both types of capsules have a porous structure and a stable performance under high temperature, and therefore potentially survive from the asphalt mixing and production process. These capsules will be implemented and evaluated in full asphalt mix in future research.

In order to explore the feasibility and efficacy of reed-fiber-modified bitumen (RFMB), three lengths and three dosages of reed fibers were selected to modify bitumen and bituminous mortar, while the physicochemical properties of RFMB and RFMB mortar were analyzed. In this work, FTIR spectroscopy was employed to characterize the chemical impact of fiber on bitumen. The viscidity and rheology of RFMB and the tensile strength of RFMB mortar were evaluated using a Brookfield viscometer, dynamic shear rheometer, and monotonic tensile test. The results showed that adding fibers primarily affects the physical structure rather than the chemical composition of bitumen, confirmed by FTIR spectroscopy. RFMB viscosity increased with higher fiber dosage and fiber length. Rheological evaluations showed an enhanced complex shear modulus for RFMB, suggesting improved performance at higher temperatures but increased stiffness at lower temperatures, with the latter indicating reduced flexibility. RFMB also demonstrated superior fatigue and rutting resistance, albeit with compromised stress sensitivity. Tensile tests on RFMB mortar highlighted significant improvements, especially with longer fibers, while shorter 0.4 mm fibers showed modest reinforcement effects, possibly due to uneven distribution during sample preparation.

This study implements molecular dynamics (MD) simulations to explore the atomic-level energy properties of rejuvenated bitumen, considering the influence of different recycling agent (RA) types, dosages and aging levels of bitumen. Moreover, the potential correlations between energy indices and high-temperature performance of rejuvenated bitumen are explored. Our findings show that recycling agents can effectively reinstate the cohesive energy density (CED) values of aged bitumen, correlating well with their high-temperature rheological properties. The results reveal that the energy parameters of potential energy (UVEP), kinetic energy (UWEK), non-bond energy (EN), total energy (UVET), diagonal energy (UNED), and cross-terms energy (ECT) can reflect the restoration level of recycling agents (RAs) on atomic-level energy characteristics of aged bitumen. Compared to rutting failure temperature (RFT), elastic recovery (R3.2), and creep compliance (Jnr3.2), the zero-shear viscosity (ZSV) greatly correlates with CED. Meanwhile, the UWEK index from MD simulations demonstrates a strong correlation with high-temperature rheological indicators of rejuvenated bitumen. With the rise in UWEK, there is a linear decrease in the RFT, Log(ZSV), and R3.2 values of rejuvenated bitumen. Conversely, the Log(Jnr3.2) exhibits a linear increasing trend. However, the correlation patterns between rheological indicators and either EN or ECT are contingent on the aging degree of bitumen. Based on the correlation coefficient, the UWEK stands out as the primary choice among all energy indices for predicting high-temperature rheological performance of rejuvenated bitumen.