Unraveling oxidative aging behavior of asphaltenes using ab initio molecular dynamics and static density functional theory

Hu, Dongliang; Gu, Xingyu; Lyu, Lei; Wang, Guoliang; Cui, Bingyan

doi:10.1016/j.conbuildmat.2021.126032

Cited by 26 publications

(5 citation statements)

References 51 publications

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“…It also leads to a rapid increase in the oxygen content of the asphalt because of the formation of sulfoxide groups and carbonyl groups. 18 However, the effect of aging on the atomic scale of asphalt has always been a difficult issue. This is because of the difficulties in the construction of molecular models of aged asphalt.…”

Section: ■ Introductionmentioning

confidence: 99%

“…In terms of microstructure, aging destroys the two-phase structure of styrene–butadiene–styrene (SBS)-modified asphalt and increases the bee-like structure. It also leads to a rapid increase in the oxygen content of the asphalt because of the formation of sulfoxide groups and carbonyl groups . However, the effect of aging on the atomic scale of asphalt has always been a difficult issue.…”

Section: Introductionmentioning

confidence: 99%

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Deterioration Effects of Oxidative Aging on Graphene-Asphalt Nanocomposite Interfaces: Multiscale Modeling

Yang

2023

Langmuir

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The purpose of this study is to explore the mechanism of interfacial degradation of graphene-asphalt nanocomposites by oxidative aging and to explain the principle of reduced cracking resistance. In this study, density functional theory (DFT), molecular dynamics (MD) simulation, atomic force microscopy (AFM), Fourier transform infrared (FTIR) spectroscopy, and linear amplitude scanning test (LAS) were used to quantify the effect of oxidative aging on the interfacial degradation of graphene-asphalt nanocomposites with different scales, and the coupling mechanism between scales was systematically analyzed. The results show that interfacial degradation is a complex multiscale coupling behavior. Oxidative aging reduced the fatigue life (N f ) of graphene-asphalt nanocomposites by 8.6% due to a 63.9% reduction in shear barriers and a 14.2% reduction in energy barriers at the molecular interface. Furthermore, oxidative aging enhanced the intermolecular interactions and compatibility of the graphene-asphalt molecules. The interfacial interaction of aged graphene-asphalt nanocomposites is mainly van der Waals force. Graphene-aged aromatics and graphene-aged saturates were the most compatible interfaces, and there was typical benzene ring stacking between graphene and aged aromatic 2. Aged aromatics and aged saturates are the main promoters of interfacial strength and stress transfer, while aged asphaltenes and aged resins sometimes play a weakening role, as verified by the AFM. In addition, DFT calculations show that there is no chemical reaction between graphene and aged asphalt molecules, which is consistent with the FTIR results. This study provides a theoretical basis for the development of targeted antiaging and anticracking technologies for asphalt-based materials.

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Section: ■ Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deterioration Effects of Oxidative Aging on Graphene-Asphalt Nanocomposite Interfaces: Multiscale Modeling

Yang

2023

Langmuir

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“…McDaniel et al and Mogawer et al assumed that the regenerant was completely mixed with aged asphalt, and they estimated the dynamic modulus of the mixture from the volume ratio of regenerant to aged asphalt to determine the dosage of RAP to add [18,19]. Furthermore, scholars have explored the aging mechanism of asphalt and the diffusion behavior of regenerant at the molecular scale, revealing the interaction mechanism between aged asphalt and regenerant [20][21][22][23][24]. The above background information fully demonstrates that on the premise of adding regenerants to restore the performance of aged asphalt, the RAP content can be increased.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Factors Influencing the Modulus of Hot-Recycled Asphalt Mixture with High RAP

Chen¹,

Liu

Feng

et al. 2023

Materials

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Generally, the dynamic modulus and bending stiffness modulus are used to evaluate the mechanical properties of asphalt mixture, and they are also used as basic parameters for asphalt mixture design. Therefore, a study was conducted on changes in the dynamic modulus and bending stiffness modulus of hot-recycled asphalt mixture with high levels of reclaimed asphalt pavement (RAP) under the influence of different factors: dosage of regenerant, curing temperature, and curing time. The performance of reclaimed asphalt pavement (RAP) was first evaluated. Then, the hot-recycled asphalt mixture was adjusted and designed in order to conduct modulus experiments, composed of the dynamic modulus test and three-point bending test. Finally, the influencing factors were not only qualitatively but also quantitatively analyzed to clarify the change laws of the mechanical parameters of hot-recycled asphalt mixture. The results showed that the modulus of the recycled asphalt mixture first decreased, then increased, and then decreased with increasing dosage of regenerant. As the curing time or temperature increased, the modulus first decreased and then increased. In terms of the dynamic modulus of the hot-recycled asphalt mixture, the curing time had the greatest impact, followed by dosage of the regenerant and curing temperature. For bending stiffness modulus, the influence of dosage of the regenerant was the greatest, followed by curing time and curing temperature. For the bending stiffness modulus of hot-recycled asphalt mixture, the curing conditions had a greater influence compared with the dynamic modulus.

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“…These limitations consequently pose a formidable hurdle when attempting to explore more extensive biochemical systems 14 or phenomena unfolding over prolonged temporal scales, such as the intricate dynamics of protein folding or the progressive evolution of materials. 15 Consequently, an escalating interest has emerged in devising approaches that capitalize on the speed of classical force fields while also harnessing the precision of quantum mechanical calculations. 16 In this context, machine learning (ML) has garnered considerable attention for its potential to surmount the limitations inherent in these two techniques.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Consequently, its application is primarily constrained to relatively small systems, typically encompassing fewer than 100 atoms, and short simulation durations, generally within the range of 100 ps. These limitations consequently pose a formidable hurdle when attempting to explore more extensive biochemical systems or phenomena unfolding over prolonged temporal scales, such as the intricate dynamics of protein folding or the progressive evolution of materials …”

Section: Introductionmentioning

confidence: 99%

TrIP─Transformer Interatomic Potential Predicts Realistic Energy Surface Using Physical Bias

Hedelius,

Tingey,

Della Corte

2023

J. Chem. Theory Comput.

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Accurate interatomic energies and forces enable high-quality molecular dynamics simulations, torsion scans, potential energy surface mappings, and geometry optimizations. Machine learning algorithms have enabled rapid estimates of the energies and forces with high accuracy. Further development of machine learning algorithms holds promise for producing universal potentials that support many different atomic species. We present the Transformer Interatomic Potential (TrIP): a chemically sound potential based on the SE(3)-Transformer. TrIP's species-agnostic architecture, which uses continuous atomic representation and homogeneous graph convolutions, encourages parameter sharing between atomic species for more general representations of chemical environments, maintains a reasonable number of parameters, serves as a form of regularization, and is a step toward accurate universal interatomic potentials. TrIP achieves state-of-the-art accuracies on the COMP6 benchmark with an energy prediction of just 1.02 kcal/mol MAE. We introduce physical bias in the form of Ziegler−Biersack−Littmark-screened nuclear repulsion and constrained atomization energies. An energy scan of a water molecule demonstrates that these changes improve longand near-range interactions compared to other neural network potentials. TrIP also demonstrates stability in molecular dynamics simulations, demonstrating reasonable exploration of Ramachandran space.

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Unraveling oxidative aging behavior of asphaltenes using ab initio molecular dynamics and static density functional theory

Cited by 26 publications

References 51 publications

Deterioration Effects of Oxidative Aging on Graphene-Asphalt Nanocomposite Interfaces: Multiscale Modeling

Deterioration Effects of Oxidative Aging on Graphene-Asphalt Nanocomposite Interfaces: Multiscale Modeling

Analysis of Factors Influencing the Modulus of Hot-Recycled Asphalt Mixture with High RAP

TrIP─Transformer Interatomic Potential Predicts Realistic Energy Surface Using Physical Bias

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