Properties and Characterization Techniques of Graphene Modified Asphalt Binders

Polo-Mendoza, Rodrigo; Navarro-Donado, Tatiana; Ortega-Martinez, Daniela; Turbay, Emilio; Martínez-Arguelles, Gilberto; Peñabaena‐Niebles, Rita

doi:10.3390/nano13050955

Cited by 29 publications

(4 citation statements)

References 291 publications

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“…Additionally, ongoing efforts have been exerted to further explore the application of graphene nanosheets (GNs) to asphalt mixtures which contain asphalt binder and graded aggregates [16]. GNs could be produced from the exfoliated graphite or via thermal reduction of graphite oxide (GO) in presence of Ar gas [17].…”

Section: Introductionmentioning

confidence: 99%

Enhanced stability of a three-dimensional graphene nanosheets networks modified asphalt mixture

Nqabisa,

Khamlich,

Oliver

2024

E3S Web Conf.

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To date, several concepts have been developed to enhance the mechanical and service life of asphalt pavements. Additives such as graphene, carbon nanotubes, carbon fibers and carbon black are used in the hot mix asphalt (HMA) or the asphalt binder (i.e., bitumen) for higher resistance to permanent deformations such as rutting, and transverse thermal cracking due to increased traffic volumes, vehicle mass and axle loads. In this study, graphene nanosheets (GNs) were used as potential modifier of bitumen binder in the HMA. The objective of this work is to investigate the impact of GNs modified bitumen on the Marshall stability and flow of the asphalt mixture using laboratory-compacted samples. The X-ray diffraction (XRD) study revealed a diffraction peak of GNs (002) at 2θ =26.5° along the bitumen’s γ-band and 10-band, which confirm a successful dispersion of GNs into bitumen binder. Furthermore, morphological analysis showed formation of a three dimensional (3d) interconnected networks of GNs between the bitumen micro-structures which could act as bridges for increased flexural strength of the binder. The Marshall stability and flow test results indicate that the mechanical properties of asphalt mixture were influenced by the addition of GNs to the bitumen binder. At 5% by weight of GNs modified bitumen (GNs-B), the compacted hot-mix Asphalt sample showed a higher Marshall stability of 11.7 kN recording 13.6% enhancement in comparison with the asphalt mixture with pure bitumen (P-B). In addition, when GNs-B was used, a lower flow of 1.4 mm was recorded which is desirable to prevent rutting and other forms of failure in asphalt pavements. This study underlines that adding GNs into asphalt binders such as bitumen could play a key role in enhancing the performance of asphalt pavements, which in turn extends their service life and saves maintenance expenses.

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Section: Introductionmentioning

confidence: 99%

Enhanced stability of a three-dimensional graphene nanosheets networks modified asphalt mixture

Nqabisa,

Khamlich,

Oliver

2024

E3S Web Conf.

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“…One investigation undertook a detailed examination of sophisticated material characterization techniques, such as atomic force microscopy, thermal analysis, and X-ray diffraction. Particular focus was directed toward appraising the applicability of graphene as an emerging nanomaterial to heighten the performance characteristics of several materials employed in pavement engineering, including asphalt binders [11]. While laboratory methods can provide precise results on lubricant condition, they may not be sufficient in determining the optimal maintenance timeline, as it depends on various factors such as the machine's operating environment and duty cycle.…”

Section: Introductionmentioning

confidence: 99%

Unlocking the Potential of Soft Computing for Predicting Lubricant Elemental Spectroscopy

Pourramezan,

Rohani,

Abbaspour-Fard

2023

Lubricants

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Predictive maintenance of mechanical systems relies on accurate condition monitoring of lubricants. This study assesses the performance of soft computing models in predicting the elemental spectroscopy (Fe, Pb, Cu, Cr, Al, Si, and Zn) of engine lubricants, based on the electrical properties (ε′, ε″, and tan δ) of oil samples. The study employed a dataset of 49 lubricant samples, comprising elemental spectroscopy and dielectric properties, to train and test several soft computing models (RBF, ANFIS, SVM, MLP, and GPR). Performance of the models was evaluated using error metrics such as MAPE, RMSE, and EF. The RBF model delivered the most accurate predictions for silicon at 7.4 GHz, with an RMSE of 0.4 and MAPE of 0.7. Performance was further improved by fine-tuning RBF parameters, such as the hidden size and training algorithm. The sensitivity analysis showed that utilizing all three input electrical properties (ε′, ε″, and tan δ) resulted in the lowest errors. Nevertheless, there are limitations to the study. In our country, measuring the electrical properties of engine lubricants and equipment is not a common practice, which leads to a limited number of samples studied. Despite these limitations, this study offers a proof-of-concept for predicting lubricant conditions based on readily measurable electrical properties. This paves the way for developing machine learning-based real-time lubricant monitoring systems.

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“…These factors can lead to the deterioration of the pavement, causing cracks, rutting, and other forms of damage. To mitigate these issues, researchers have explored the use of various additives and reinforcements in asphalt mixtures [12,13]. In recent years, the incorporation of fibers into asphalt mixtures has gained considerable attention as a potential solution to enhance the material's resistance to freeze-thaw damage.…”

Section: Introductionmentioning

confidence: 99%

Freeze–Thaw Damage Mechanism Analysis of SBS Asphalt Mixture Containing Basalt Fiber and Lignocellulosic Fiber Based on Microscopic Void Characteristics

Wang,

Yang,

Cui

et al. 2023

Polymers

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Freeze–thaw effects pose the significant challenge to asphalt pavement durability, leading to various types of distress and deterioration. This study investigates the freeze–thaw damage mechanism of Styrene–Butadiene–Styrene (SBS) asphalt mixtures containing reinforcement fibers, specifically basalt fiber as well as lignocellulosic fiber, through a microscopic void characteristics analysis. This investigation aims to understand how the presence of basalt fiber as well as lignocellulosic fiber influences void characteristics for SBS asphalt mixtures during freeze–thaw cycles. A comprehensive experimental program was conducted for the void and mechanical characteristics, which involved the preparation of SBS asphalt mixtures containing basalt fiber as well as lignocellulosic fiber. The mechanical performances of the two types of asphalt mixtures decrease with more freeze–thaw cycles. The decline is faster initially and gradually slows down. Basalt-fiber-modified SMA-13 has higher air void content and mechanical properties compared to lignocellulosic-fiber-modified SMA-13, indicating that adding basalt fibers improves the mechanical performances of SMA-13 asphalt mixture. Both types of asphalt mixtures experience increasing damage with more freeze–thaw cycles, indicating irreversible damage. The stability damage levels are similar, but basalt-fiber-modified SMA-13 has lower splitting strength damage and stiffness modulus damage compared to lignocellulosic-fiber-modified SMA-13. This suggests that adding basalt fibers enhances the resistance to freeze–thaw damage. Surface wear of asphalt mixtures under repeated freeze–thaw cycles is a complex and dynamic process. Fractal theory can uncover the mechanism of surface wear, while describing surface wear behavior and void deformation characteristics using fractal dimension, angularity, roundness, and aspect ratio is a logical and effective approach. The findings provide insights into freeze–thaw damage mechanisms at the microscopic level, highlighting the effects of reinforcement fibers. They provide valuable insights that can be used to optimize the design and maintenance of asphalt pavements.

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Properties and Characterization Techniques of Graphene Modified Asphalt Binders

Cited by 29 publications

References 291 publications

Enhanced stability of a three-dimensional graphene nanosheets networks modified asphalt mixture

Enhanced stability of a three-dimensional graphene nanosheets networks modified asphalt mixture

Unlocking the Potential of Soft Computing for Predicting Lubricant Elemental Spectroscopy

Freeze–Thaw Damage Mechanism Analysis of SBS Asphalt Mixture Containing Basalt Fiber and Lignocellulosic Fiber Based on Microscopic Void Characteristics

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