Bitumen, a crucial constituent in the composition of asphalt pavements, plays a vital role in the performance and durability of pavements. Bitumen undergoes aging over time due to complex interactions between its chemical components and various environmental factors. In this investigation, the study focuses on examining the aging process of bitumen under the combined influence of moisture and reactive oxygen species (ROS). The findings highlight the importance of considering ROS and moisture as critical factors contributing to accelerated aging. Results obtained from Fourier-transform infrared (FTIR) spectroscopy, SARA fractionation, and optical inverse microscope (OIM), as well as dynamic shear rheometer (DSR) examination, indicate that the concurrent influence of these factors induces significant aging in bitumen, with the extent of this impact being modulated by the bitumen's inherent aging susceptibility. The insights obtained from this study enhance strategies to justify the destructive impacts of aging, extending the operational lifespan of asphalt pavements.

Developing a rapid and realistic binder aging protocol remains a challenge in pavement engineering. This study introduces the UV-Peroxide Aging (UPA) protocol, which employs hydrogen peroxide and UV light to accelerate oxidative reactions. The effects of hydrogen peroxide concentration, temperature, and aging duration were evaluated and compared with existing laboratory protocols and long-term field aging. Results show that UPA aging at 85°C for 3 h or 60°C for 6–9 h produces aging effects comparable to 9 years of field exposure. Additionally, new methods for lab-field comparisons of chemical and rheological properties were applied, offering a systematic framework for analysing optimized aging protocols.

The increasing demand for cleaner and more efficient refining processes has driven the development of advanced upgrading technologies for heavy crude residues. This study investigates a novel Visbreaking-Supercritical Fluid Extraction (SFE) approach to upgrade the Merey vacuum residue (VR), integrating experimental analysis with molecular dynamics (MD) simulations for atomic-level mechanism exploration. The Visbreaking process is optimized at 400 °C for 40 min, achieving a viscosity reduction of 89.0 % while minimizing coke formation. The SFE process fractionates the visbroken VR, with total extraction yields ranging from 70.1 wt% to 70.7 wt%, demonstrating remarkable efficiency. Higher extraction pressures enhance deasphalted oil (DAO) yield but compromise its quality with higher metal and sulfur contents, while lower temperatures improve extraction selectivity. The integrated process effectively removes Fe, Ni, V, and Na, with demetalization efficiencies exceeding 62 %, 75 %, and 95 %, respectively. Molecular dynamics simulations provide atomic-scale insights into solubility mechanisms, revealing that higher pressures and lower temperatures enhance solvent compatibility with lighter visbroken VR fractions. The extracted DAO meets marine fuel oil blending specifications, while raffinates show potential for bitumen production and modification. These findings highlight the Visbreaking-SFE combination as a promising and sustainable upgrading strategy for heavy crude residues.

Asphalt binders are critical for asphalt pavement performance, and understanding their rheological behavior is essential for designing durable roadways. The complex shear modulus (G⁎) and phase angle (δ) are primary parameters characterizing binder rheology. This study introduces a novel hybrid machine learning model combining deep neural networks (DNN) and Gaussian process regression (GPR) to predict G⁎ and δ for bituminous binders and binder-filler systems (mastics). DNN excel at capturing complex, nonlinear relationships among eleven binder and thirteen mastic input parameters, including aging conditions, chemical and physical properties, and test parameters. However, standalone DNN struggle with small datasets, common at the binder scale, and lack inherent uncertainty quantification, limiting reliability in engineering applications. GPR improves DNN by refining predictions through probabilistic modeling, while providing uncertainty estimates, and enhancing accuracy with limited or noisy data. The hybrid model leverages DNN's feature extraction capabilities and GPR's ability to smooth predictions, significantly improving performance over standalone DNN. The hybrid model achieves high prediction accuracy, with R2 values of 0.997 for G⁎ and 0.947 for δ for binders, and 0.993 for G⁎ and 0.972 for δ for mastics, reducing G⁎ prediction error from 22.7% to 0.031% for fresh asphalt binder compared to standalone DNN. Feature importance analysis using random forest and SHAP techniques identifies test temperature, aging conditions, and penetration as key influencers of G⁎ and δ. This hybrid approach enhances the characterization of complex asphalt materials, offering pavement engineers a robust, reliable tool for predicting material behavior under diverse conditions.

Understanding aging across material scales is critical for predicting the long-term performance of bituminous materials. This study investigates the aging of binder, mastic, and asphalt mixture samples under various temperature, pressure, reactive oxygen species (ROS), and humidity. Chemical aging processes were analysed using attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR), principal component analysis (PCA), and Euclidean distance. Normalisation, baseline correction, and advanced ATR correction were used to enhance the accuracy of FTIR results. Hydrated lime in mastics enhanced the resistance to oxidative aging, particularly under hygrothermal conditions. PCA identified key spectral regions for understanding aging processes of bituminous materials. Porous asphalt (PA) mixtures aged more than stone mastic asphalt under field-like conditions. PCA identified distinct aging clusters at low and high pressure. Euclidean distance analysis indicated that binder-level aging can approximate mastic and mixture aging under certain conditions. The findings confirm that FTIR indices are effective for multi-scale aging studies.

This study aims to improve laboratory aging procedures for bituminous materials to better replicate field conditions. Two binders and mixtures were subjected to various levels of humidity, temperatures, pressures, film thicknesses, and aging durations. By comparing these lab-aged samples to field-aged samples, the study aims to simulate real-world aging more accurately. Fourier-transform infrared (FTIR) spectroscopy and frequency sweep tests were employed to analyse these samples. Multivariate techniques—Principal Component Analysis (PCA), Multiple Linear Regression (MLR), and Support Vector Regression (SVR)—were used to explore chemical and rheological relationships, evaluate the interchangeability of aging factors, and quantify the equivalency between laboratory and field aging. The findings revealed that increased temperature, pressure, and duration lead to more oxidative products. The PCA distinguished between two binders and aging trends, highlighting the importance of both FTIR and rheological measurements. The SVR model demonstrated strong predictive performance for rheological properties, identifying critical FTIR region, 710–912 -1cm. By MLR model, optimal aging conditions to simulate nine years of field aging for porous asphalt and stone mastic asphalt were back-calculated. The Euclidean distance found laboratory conditions that closely match field-aged samples. SVR models provided predictions of simulated field aging time for various laboratory aging conditions.

This study aims to correlate the chemical and rheological properties of bitumen at different ageing states and understand the chemical mechanisms of bitumen degradation due to ageing. The relationship between Fourier transform infrared (FTIR) spectral data and rheological results is investigated using partial least squares (PLS) regression integrated with two variable selection methods. The spectral region of 1800 – 800 cm1 is identified as the most informative for accurate estimation of the rheological properties of bitumen. Variable selection methods, particularly moving windows (MW), improve the prediction accuracy of the regression models.

Bituminous binders naturally age, affecting the properties and performance of asphalt pavements. The physical and chemical characteristics of binders are influenced by environmental factors, leading to a decline in their performance and durability. Therefore, it is essential to understand the mechanisms of binder environmental aging to design more resilient and long-lasting asphalt pavements. This study examines the effects of temperature, liquid, and vapor water on binder aging to develop more durable pavements. Aging was induced at three temperatures (60°C, 70°C, 85°C) under dry air, 90% relative humidity, and water immersion conditions. Field-aged samples were also analyzed to compare with laboratory-aged samples. Fourier-transform infrared spectroscopy (FTIR) and dynamic shear rheometer (DSR) were used to assess chemical and rheological changes. To assess the similarity between samples and identify the lab aging protocol closest to field aging, Hierarchical Cluster Analysis (HCA) was employed for data analysis.

Attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR) is an essential tool for the analysis of bituminous binders due to its cost-effectiveness, user-friendliness, and non-destructive nature. However, its effectiveness is often hampered by challenges such as non-informative regions, lack of standardized analysis methods, and inconsistent baselines in spectral data. Addressing these challenges, this study aims to comprehensively evaluate the impact of various data pre-processing (DP) methods on ATR-FTIR spectra from diverse bituminous binder types, sources, and aging conditions. Using partial least squares discriminant analysis (PLSDA) classification, the study assesses the effectiveness of baseline correction, normalization, and their combinations. The methodology involves analyzing peak areas, indices, entire spectra, and first derivative spectra to determine the most effective pre-processing strategies. Key findings reveal that the effectiveness of DP methods is influenced by the classification goals, characteristics of the spectral dataset, and the specific methods employed for input data preparation. The study demonstrates that using entire spectra or their first derivatives leads to higher classification accuracy compared to indices or specific spectral peak areas. The choice between peak area and indices calculation methods should align with the study’s objectives. For efficient and rapid selection of DP methods, tools like PLSDA are recommended. Among the normalization methods, normalization to constant vector length (NCV), normalization to change the maximum to 1 (NMO), robust scaling (RS), and normalization to sum (NTS) are suitable for peak area or indices-based classification. For entire spectra and their first derivatives, NTS, NCV, autoscaling (AS), pareto scaling (PS), and standard normal variate (SNV) methods are recommended. Regarding baseline correction, Adaptive Smoothness Penalized Least Squares (aspls) is suitable for studies focusing on gradual material changes, such as multi-level aging studies, but not for additive
detection studies. The findings of this study provide valuable insights and practical recommendations for selecting appropriate DP methods, thereby enhancing the classification accuracy and reliability of ATR-FTIR spectral analysis of bituminous binders. This contributes significantly to the design of experiments, reduces operational risks, and optimizes resource utilization in the field.

The complex structure of bituminous mixtures ranging from nanoscale binder components to macroscale pavement performance requires a comprehensive approach to material characterization and performance prediction. This paper provides a critical analysis of advanced techniques in paving materials modeling. It focuses on four main approaches: finite element method (FEM), discrete element method (DEM), phase field method (PFM), and artificial neural networks (ANNs). The review highlights how these computational methods enable more accurate predictions of material behavior, from asphalt binder rheology to mixture performance, while reducing reliance on extensive empirical testing. Key advances, such as the smooth integration of information across multiple scales and the emergence of physics-informed neural networks (PINNs), are discussed as promising avenues for enhancing model accuracy and computational efficiency. This review not only provides a comprehensive overview of current methodologies but also outlines future research directions aimed at developing more sustainable, cost-effective, and durable paving solutions through advanced multiscale modeling techniques.

Refurbishing of milled asphalt into new bound layers of pavement is recognized as a sustainable maintenance practice. However, limited attention has been paid towards investigating their circularity aspects. Furthermore, evolving legislative requirements call for integration of circularity and sustainability facets. Therefore, this study presents a flexible framework that aims at assessing and integrating the environmental, economic, and circularity aspects associated with two maintenance alternatives, i.e., reconstruction of pavement with a bound base layer using bituminous materials (BSM) versus routine patch repair and resurfacing. The integration of different assessment categories was performed using a metric termed as net risk reduction gain (NRRG). The results revealed that the NRRG for BSM option was 2.5 times higher than routine maintenance over a 50 year analysis period, thereby emphasizing its higher circularity and sustainability benefits. The proposed framework is envisioned to pave way for integration of circular thinking along with sustainability considerations for pavement design and construction.

Asphalt pavements are subjected to various environmental factors such as rainfall, sunlight, humidity and wind that causes oxidative aging of bitumen, leading to reduced structural and functional performances in the longer run. Antioxidants are often added to asphalt binders to enhance their resistance to oxidative ageing. In the current study, two different antioxidants, Zinc Diethyldithiocarbamate and Lignin were evaluated for their effectiveness in improving the performance of asphalt binders. The laboratory mixing procedures were conducted at two different percentages, and laboratory aging were performed. Rheological and chemical tests were then conducted to evaluate the performance of the binders at different temperatures. The current study provides valuable insights into the use of antioxidants for improving the performance and service life of asphalt pavements, which will help in the development of perpetual asphalt pavements in the future.

Oxidative aging induces significant stiffening of asphalt binders that leads to a pronounced reduction in the overall durability of asphalt pavements. The strategic implementation of antioxidant additives provides a potential solution to alleviate this issue. This work presents results from the second phase of the global consortium for antioxidants research aimed at investigating the effectiveness of potential antioxidants in increasing the durability of asphalt binders. Sixteen laboratories around the world participated in this effort and a total of 28 binders from diverse geographical regions were tested. Two promising antioxidants, namely zinc diethyldithiocarbamate (ZDC) and kraft lignin were evaluated in this phase and blended with the binders at specific proportions. Subsequently, a comprehensive investigation was conducted to assess rheological characteristics and chemical properties of the various blends, utilising Dynamic Shear Rheometer (DSR) measurements and Fourier Transform Infrared (FTIR) Spectroscopy. The findings indicate that additives such as ZDC hold considerable promise as an effective antioxidant, particularly when considering a wide diversity of binders. In general, its incorporation does not compromise the rutting performance of the binders and significantly improves fatigue performance. Therefore, research efforts should be focused on exploring additional facets to assess its practical applicability in field.

The objective of this research was to evaluate the lifecycle costs associated with emerging pavement maintenance technologies, namely, in-situ rejuvenation and very open emulsion asphalt concrete (ZOEAB+), and scrutinise their suitability over corrective resurfacing maintenance using a stochastic approach. A rational lifecycle inventory was developed by conducting interviews and questionnaire surveys with experts and referring to standard guidelines and international databases. The net present value (NPV) was found sensitive to 12 different inputs with traffic growth rate and discount rate causing the highest uncertainty followed by gasoline and diesel prices. Monte Carlo simulations suggested that the median uncertainty in NPV by using in-situ rejuvenation and ZOEAB+ was 13% and 4% lower than resurfacing. It is envisioned that the research outcomes will assist decision-makers in understanding the uncertainties and costs associated with different maintenance alternatives in the early stages of the project to foster procurement of sustainable and circular pavement maintenance strategies.

Water transport is one of the major factors responsible for moisture damage in asphalt pavements. To study the thermodynamics and kinetics of water transport in bitumen and to uncover microscale mechanisms of moisture-induced damage, molecular dynamics simulations were performed for up to 600 ns for water–bitumen systems with realistic water contents that varied from 0 to 1.76 wt%. Hydrogen bonding interactions and clustering of water molecules at various combinations of temperature and water content were investigated, and their effects on the self-diffusion coefficient of water and bitumen properties are computed and discussed. It is shown that the saturated water concentration in bitumen is small, especially at low temperatures, and additional water molecules tend to form large water clusters via hydrogen bonding, indicating micro-phase separation of the water and bitumen phases inside the simulation box. Hydrogen bonding and water clustering play a crucial role on the magnitude of the self-diffusion coefficient of water. Physical properties of bitumen that include viscosity and cohesive energy are affected by water. The presence of large water clusters is indicative of how degradation in cohesion is observed on the microscale.

The concept of a circular economy, where waste materials are transformed into valuable resources, is gaining increasing attention. However, many waste streams are difficult to recycle due to their mixed composition and broad molecular distribution. This paper explores the potential of repurposing mixed materials, specifically focusing on creating a circular alternative to bitumen, a fossil-based binder used in road construction. The molecular weight and composition of bitumen are analyzed using gas chromatography (GC) and infrared spectroscopy (IR). This study proposes using waste plastics and bio-based oils to develop a paving binder with similar molecular distribution. Various plastic types, such as low-density polyethylene (LDPE), high-density polyethylene (HDPE), isotactic polypropylene (PP), polystyrene (PS) and polyethylene terephthalate (PET), are examined for their compatibility with different oils. It is observed that the compatibility of both the molecular weight and composition between the plastic and oil is crucial for the successful dissolution and homogeneity of the binder. Additionally, the crystallinity of the plastic plays a role in the flexibility and durability of the resulting binder. It is demonstrated that by carefully selecting waste materials and understanding their molecular characteristics, it is possible to create circular alternatives to fossil-based materials like bitumen. This approach has the potential to reduce waste, lower dependence on fossil resources, and contribute to sustainable and circular construction materials.

Implementation of the circular economy and resource efficiency has the potential to significantly tackle the root causes of global challenges such as climate change, biodiversity loss and pollution whilst at the same time providing regenerative design for generations to come. The CEDR funded CERCOM project facilitates a move towards circular public procurement of national road infrastructure. A flexible and stable approach using ranked interpolation is used to generate KPI values for various criterion, where the user can specify the desired level of complexity based on scheme requirements and data available. The framework considers technical, economic, environmental and social criteria, as well as circularity, while assessing the change in risks in moving from a linear to a circular economy. National Road Authorities (NRAs) are at different maturity levels in relation to circularity. The developed framework caters for this, allowing flexibility for NRAs to tailor their application of the framework to suit their maturity level and the scheme under consideration. The outcome is a user-friendly intuitive tool with a step-by-step approach to enable informed decision making around adoption of the principles of circular economy in the maintenance of highway infrastructure.

The rejuvenation efficiency of aged bitumen is the main concern when developing rejuvenating agents. It is necessary to develop a method to assess the efficiency of rejuvenators using rheological parameters in the whole frequency region. To this end, the 2S2P1D micromechanics model is adopted to fit the entire G∗ master curves of various rejuvenated bitumen, and the influence of rejuvenator type/dosage and aging grade of bitumen on the whole G∗ master curve and chemical indices are investigated. Critical parameters for evaluating rejuvenation efficiency derived from viscoelastic models and chemical characterizations are proposed. Furthermore, the potential relationships between the rheological model-based parameters (E _∞, δ, β, and τ) and chemical indices (carbonyl index CI and sulfoxide index SI) are explored. The results indicate that rejuvenators restore the δ, τ, CI, and SI values of aged bitumen towards the virgin bitumen level. The E _∞ parameter is not applicable to evaluate the rejuvenation efficiency of engine-oil and naphthenic-oil rejuvenators, but the positive E _∞R values of bio-oil and aromatic-oil rejuvenated bitumen are detected. All rejuvenators fail to restore the β parameter of aged bitumen. The τ and CI parameters are selected as critical evaluation indicators from the perspective of viscoelastic models and chemical characteristics. Linear correlations between all rheological parameters and chemical indices are observed and established.

Correction to: Materials and Structures (2022) 55:146 https://doi.org/10.1617/s11527-022-01986-w

The article “Do chemistry and rheology follow the same laboratory ageing trends in bitumen?”, written by Georgios Pipintakos, Caitlin Lommaert, Aikaterini Varveri and Wim Van den bergh, was originally published in volume 55, issue 5, ID 146 without open access. With the society's decision to grant Open Choice the copyright of the article changed in February 2023 to © The Author(s) 2022 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0. Open access funding enabled and organized by RILEM.

The chemical characterization of bitumen type and ageing state are fundamental in determining structural and mechanical properties of bitumen. This work aims to classify various bitumen types at different ageing states and to identify the primary chemical differences relevant to the classification. Fourier transform infrared (FTIR) spectral data of eight bitumen types at five ageing states were analyzed using a chemometric procedure that incorporates principal component analysis (PCA), linear discriminant analysis (LDA) models, variable selection methods. The models presented results of high accuracy in differentiating bitumen type and ageing state. The results show that the spectral regions that describe the aliphatic and aromatic bonds are critical to the identification of bitumen types. The chemical changes due to bitumen ageing are mainly revealed at the region of 1800–900 cm-1. This chemometric method is instructive for the characterization of chemical bitumen properties.