Characterization of thermal storage stability of waste plastic pyrolytic char modified asphalt binders with sulfur.

Pyrolysis has gained a strong interest in recent times for sustainable treatment and recovery of energy-rich products from different wastes including plastic. Waste plastic pyrolytic char (PPC) generated as a carbonaceous by-product in the pyrolysis process, is gaining attention as an asphalt binder modifier. Adequate thermal storage stability is an essential requirement for a modified asphalt binder to ensure that the composite offers integrity and homogeneous properties during its storage, handling and transportation in the field. The objective of this study was to evaluate and characterize the thermal storage stability properties of PPC modified binders. PPC modified asphalt binders were fabricated and evaluated at multiple dosages of sulfur as a cross-linking agent. In addition to the conventionally used softening point difference (SPD), characterization of thermal storage stability was attempted using rheology-based separation indices (SIs) derived through temperature sweep, frequency sweep, and multiple stress creep and recovery (MSCR) tests. These rheological SIs were based on complex modulus (G*), Superpave rutting parameter (G*/sin δ), Shenoy rutting parameter (SRP), zero shear viscosity (ZSV), and MSCR Jnr (at three stress levels 0.1, 3.2 and 10 kPa). Two formulations of each rheology-based separation index were studied: (1) ratio, and (2) maximum-average difference formulations. The temperature and frequency dependencies of rheological SIs were also evaluated. Further, the Fourier transform infrared spectroscopy (FTIR) was used to characterize storage stability by comparing the chemical functionalities of the PPC modified binders. A 0.3% dosage of sulfur was found to produce the best results considering all SPD, rheology-based SIs and FTIR. Principal component analysis showed that the ratio and maximum-average formulations had similar contributions to the first principal component accounting for more than 99% of the variability.