Asphalt omics is an emerging interdisciplinary field that integrates biology, materials science, computational science, and transportation science to address the complex properties of asphalt and the growing volume of high-throughput testing data. This study traces the early adoption of omics concepts in asphalt research, including asphalt fingerprinting, fractionation, and mixture design programming. It then outlines the core components of the asphalt omics framework, which operates across three levels: asphalt material, pavement, and environmental omics. Furthermore, a systematic architecture for asphalt omics is presented, comprising testing, analysis, and data platforms. Leveraging omics principles, this study examines the integration of multiscale asphalt information through advanced characterization techniques, the application of artificial intelligence for efficient data processing, and the development of a comprehensive smart asphalt omics database. As a transformative research paradigm, asphalt omics provides a data-driven approach that bridges empirical, theoretical, experimental, and practical insights, thereby accelerating the development of multifunctional asphalt materials, high-performance pavements, and sustainable road transportation.
Ni et al. (Sun,) studied this question.