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X. Liu
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UV and Thermal-Oxidative Ageing of SBS-Modified Binders
An Interlaboratory Study of Chemical and Rheological Response
Book chapter
(2026)
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Peng Lin, Gordon Airey, Johannes Büchner, Hinrich Grothe, Eyassu Hagos, Lakshmi Roja Kakumanu, Isabeau Kokken, Xueyan Liu, Rui Wu, More Authors
Polymer-modified binders are widely used in asphalt pavements, but their long-term performance and recyclability depend on how they age under both thermo-oxidative and photo-thermal conditions. Within RILEM TC 307-PPB, Task Group 2 (TG2) has set up an interlaboratory programme to compare a reference RTFOT+PAV ageing condition (PAV40) with a well-defined RTFOT+UV condition (UVA72) for two industrial SBS-modified binders with different SBS contents. Ageing was carried out centrally at TU Delft and the binders were characterised in ten laboratories using FTIR spectroscopy, BTSV rheological measurements and fluorescence microscopy. FTIR band indices indicate that PAV40 and UVA72 bring both binders to a similar overall oxidation level, while the balance between matrix oxidation and polymer-related changes depends on SBS content. BTSV results show comparable high-temperature stiffening for PAV40 and UVA72, with binder-dependent but modest differences. The interlaboratory data reveal larger scatter of FTIR indices for UVA72, and additional tests on solid and homogenised UV-aged films point to finite UV ageing depth and sampling/homogenisation procedures as important contributors. Fluorescence microscopy provides a qualitative microstructural counterpart and confirms the sensitivity to preparation protocols. Together, these findings offer an interlaboratory reference for relating UV and PAV ageing of SBS-modified binders and underline the need for clearly defined UV ageing and sampling procedures in future TG2 pre-standardisation work.
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Polymer-modified binders are widely used in asphalt pavements, but their long-term performance and recyclability depend on how they age under both thermo-oxidative and photo-thermal conditions. Within RILEM TC 307-PPB, Task Group 2 (TG2) has set up an interlaboratory programme to compare a reference RTFOT+PAV ageing condition (PAV40) with a well-defined RTFOT+UV condition (UVA72) for two industrial SBS-modified binders with different SBS contents. Ageing was carried out centrally at TU Delft and the binders were characterised in ten laboratories using FTIR spectroscopy, BTSV rheological measurements and fluorescence microscopy. FTIR band indices indicate that PAV40 and UVA72 bring both binders to a similar overall oxidation level, while the balance between matrix oxidation and polymer-related changes depends on SBS content. BTSV results show comparable high-temperature stiffening for PAV40 and UVA72, with binder-dependent but modest differences. The interlaboratory data reveal larger scatter of FTIR indices for UVA72, and additional tests on solid and homogenised UV-aged films point to finite UV ageing depth and sampling/homogenisation procedures as important contributors. Fluorescence microscopy provides a qualitative microstructural counterpart and confirms the sensitivity to preparation protocols. Together, these findings offer an interlaboratory reference for relating UV and PAV ageing of SBS-modified binders and underline the need for clearly defined UV ageing and sampling procedures in future TG2 pre-standardisation work.
Chemo-physical rejuvenation of aged SBS-modified bitumen
Multiscale effects of oils, polymer replenishment, and reactive chain extender
Journal article
(2026)
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Bowen Li, Xueyan Liu, Yvong Hung, Quentin Arnoux, Anthon Tolboom, Eyassu Hagos, Johannes Mirwald, Bernhard Hofko, Peng Lin
Styrene-butadiene-styrene (SBS)-modified binders in porous asphalt age rapidly, degrading both the viscoelastic bitumen phase and the crosslinked polymer network, hindering high-value recycling of reclaimed asphalt pavement (RAP). Conventional rejuvenation predominantly softens bitumen while overlooking polymer restoration. This study separates rejuvenation into two categories, what is repaired (bitumen vs SBS) and how it is repaired (physical vs chemical), to develop and compare four families: (1) oils targeting the bitumen phase, (2) oil–SBS blends supplying fresh polymer, (3) methylene diphenyl diisocyanate (MDI) promoting chemical reconnection of SBS chains, and (4) chemo-physical systems combining MDI with oil–SBS. Chemical properties were linked to performance using Fourier-Transformation Infrared (FTIR) spectroscopy, Gas Chromatography-Flame Ionization Detection (GC-FID), Dynamic Shear Rheometer (DSR) master curves, Multiple Stress Creep and Recovery Test (MSCRT), creep-relaxation, Linear Amplitude Sweep (LAS), fluorescence microscopy, and Environmental Scanning Electron Microscopy (ESEM). Results show that oils softened the binder and improved fatigue and low-temperature properties but diluted the SBS signal and failed to restore elasticity. Oil–SBS raised the SBS index and partially recovered elasticity, though microscopy revealed only discrete polymer domains. MDI on its own enhanced stiffness and elastic recovery but caused brittleness. Chemo-physical rejuvenators reconciled these trade-offs, yielding elasticity comparable to the unaged binder, creep-relaxation and LAS fatigue resistance approaching or exceeding the reference, and dense, well-dispersed polymer-rich domains. These findings highlight the need to combine bitumen softening, polymer replenishment, and chemical chain reconnection for effective SBS restoration and high-quality recycling of SBS-modified RAP, thereby advancing cleaner, resource-efficient pavement material systems.
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Styrene-butadiene-styrene (SBS)-modified binders in porous asphalt age rapidly, degrading both the viscoelastic bitumen phase and the crosslinked polymer network, hindering high-value recycling of reclaimed asphalt pavement (RAP). Conventional rejuvenation predominantly softens bitumen while overlooking polymer restoration. This study separates rejuvenation into two categories, what is repaired (bitumen vs SBS) and how it is repaired (physical vs chemical), to develop and compare four families: (1) oils targeting the bitumen phase, (2) oil–SBS blends supplying fresh polymer, (3) methylene diphenyl diisocyanate (MDI) promoting chemical reconnection of SBS chains, and (4) chemo-physical systems combining MDI with oil–SBS. Chemical properties were linked to performance using Fourier-Transformation Infrared (FTIR) spectroscopy, Gas Chromatography-Flame Ionization Detection (GC-FID), Dynamic Shear Rheometer (DSR) master curves, Multiple Stress Creep and Recovery Test (MSCRT), creep-relaxation, Linear Amplitude Sweep (LAS), fluorescence microscopy, and Environmental Scanning Electron Microscopy (ESEM). Results show that oils softened the binder and improved fatigue and low-temperature properties but diluted the SBS signal and failed to restore elasticity. Oil–SBS raised the SBS index and partially recovered elasticity, though microscopy revealed only discrete polymer domains. MDI on its own enhanced stiffness and elastic recovery but caused brittleness. Chemo-physical rejuvenators reconciled these trade-offs, yielding elasticity comparable to the unaged binder, creep-relaxation and LAS fatigue resistance approaching or exceeding the reference, and dense, well-dispersed polymer-rich domains. These findings highlight the need to combine bitumen softening, polymer replenishment, and chemical chain reconnection for effective SBS restoration and high-quality recycling of SBS-modified RAP, thereby advancing cleaner, resource-efficient pavement material systems.
The evolving bitumen market is increasingly complex due to variations in crude sources and transitions in refining processes, affecting the properties of bitumen. Unexpected additions of materials to alter bitumen’s properties could occur, where traditional PEN grade testing fails to detect modifications by inclusion of, for example, Re-refined Engine Oil Bottoms. This is the first study to comprehensively compare REOBs from European vs. North American sources and assess their effects on binder performance in a unified framework, performed by assessing the REOB-modified binders by identification, stability, compatibility, ageing susceptibility, and low-temperature properties. Two series of REOB-modified bitumen were prepared by blending 5, 10, and 15 wt.% REOB into hard grade bitumen. Results showed increased carbonyl formations (likely caused by lubricant additives) and phase instability during storage which can be attributed to saturates exudation. Rheological assessment demonstrated that REOB softens bitumen, although ageing causes a pronounced gain in stiffness. Low temperature rheological measurements showed that REOB-modified bitumen is prone to brittle fracture, suggesting a loss of relaxation properties. This study highlights that REOB is a material of inconsistent nature, with complex interactions with molecular groups of the base bitumen, causing increased ageing, phase instability, and brittle fracture susceptibilities.
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The evolving bitumen market is increasingly complex due to variations in crude sources and transitions in refining processes, affecting the properties of bitumen. Unexpected additions of materials to alter bitumen’s properties could occur, where traditional PEN grade testing fails to detect modifications by inclusion of, for example, Re-refined Engine Oil Bottoms. This is the first study to comprehensively compare REOBs from European vs. North American sources and assess their effects on binder performance in a unified framework, performed by assessing the REOB-modified binders by identification, stability, compatibility, ageing susceptibility, and low-temperature properties. Two series of REOB-modified bitumen were prepared by blending 5, 10, and 15 wt.% REOB into hard grade bitumen. Results showed increased carbonyl formations (likely caused by lubricant additives) and phase instability during storage which can be attributed to saturates exudation. Rheological assessment demonstrated that REOB softens bitumen, although ageing causes a pronounced gain in stiffness. Low temperature rheological measurements showed that REOB-modified bitumen is prone to brittle fracture, suggesting a loss of relaxation properties. This study highlights that REOB is a material of inconsistent nature, with complex interactions with molecular groups of the base bitumen, causing increased ageing, phase instability, and brittle fracture susceptibilities.
Scymol
A python-based software package for initializing and running molecular dynamics simulations using LAMMPS
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.
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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.
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. ...
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. ...
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.
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.
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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.
Journal article
(2025)
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Shi Xu, Amir Tabaković, Alan Lynch, Peter Recordon, Xueyan Liu, Ciaran Collier, Edward Winterlich, Erik Schlangen
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.
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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.
Journal article
(2025)
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Panos Apostolidis, Robbert Naus, Xueyan Liu, Remco Hermsen, Sandra Erkens, Tom Scarpas
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.
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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.
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.
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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.
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.
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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.
SMI2PDB
A self-contained Python tool to generate atomistic systems of organic molecules using their SMILES notations
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.
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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 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.
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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.
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.
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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.
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.
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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.
Conference paper
(2024)
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S. Xu, A. Tabaković, A. Lynch, P. Recordon, C. Collier, X. Liu, E. Winterlich, E. Schlangen
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.
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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.
This study explores the use of chemical descriptors derived from force field atom types to predict Fickian diffusion coefficients of rejuvenators in bitumen, utilizing machine learning models trained on data from 240 non-equilibrium molecular dynamics simulations. The simulations cover three bitumen types (NO, TO, FO), five aging degrees, and four temperatures (60 °C, 120 °C, 160 °C, 200 °C), capturing diffusion coefficients ranging from 0.0068e-10 m2/s in highly aged bitumens at 60 °C to 4.35e-10 m2/s in fresher samples at 200 °C. The MLM, built with 18 chemical descriptors for bitumen and rejuvenator sides, achieves an R2 of 0.97, accurately predicting diffusion across varied conditions. This approach abstracts away from the need for repeated MD simulations, enabling diffusion predictions even for systems outside the original dataset. The manuscript presents three case studies to illustrate how the model can be used for the iterative design of rejuvenators by optimizing molecular structures based on critical chemical features, such as rejuvenator oxygen content, bitumen sulfur content, and molecular weights. It also demonstrates how the model offers a practical framework for understanding the diffusion and performance of rejuvenators by linking time-dependent factors—such as concentration, depth, and rejuvenation time—with the bulk properties of bitumen-rejuvenator systems, facilitating industrial applications.
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This study explores the use of chemical descriptors derived from force field atom types to predict Fickian diffusion coefficients of rejuvenators in bitumen, utilizing machine learning models trained on data from 240 non-equilibrium molecular dynamics simulations. The simulations cover three bitumen types (NO, TO, FO), five aging degrees, and four temperatures (60 °C, 120 °C, 160 °C, 200 °C), capturing diffusion coefficients ranging from 0.0068e-10 m2/s in highly aged bitumens at 60 °C to 4.35e-10 m2/s in fresher samples at 200 °C. The MLM, built with 18 chemical descriptors for bitumen and rejuvenator sides, achieves an R2 of 0.97, accurately predicting diffusion across varied conditions. This approach abstracts away from the need for repeated MD simulations, enabling diffusion predictions even for systems outside the original dataset. The manuscript presents three case studies to illustrate how the model can be used for the iterative design of rejuvenators by optimizing molecular structures based on critical chemical features, such as rejuvenator oxygen content, bitumen sulfur content, and molecular weights. It also demonstrates how the model offers a practical framework for understanding the diffusion and performance of rejuvenators by linking time-dependent factors—such as concentration, depth, and rejuvenation time—with the bulk properties of bitumen-rejuvenator systems, facilitating industrial applications.
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.
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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.
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.
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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.
PDB2DAT
Automating LAMMPS data file generation from PDB molecular systems using Python, Rdkit, and Pysimm
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.
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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.
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.
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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.