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Contributions of fourier-transform infrared spectroscopy technologies to the research of asphalt materials: A comprehensive review.

Authors :
Zhang, Hongfei
Zheng, Fusen
Zhang, Jiupeng
Hu, Dongliang
Minelli, Matteo
Pei, Jianzhong
Sangiorgi, Cesare
Source :
Fuel. Sep2024:Part B, Vol. 371, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

• The applications of FTIR in asphalt materials research are reviewed. • The mechanisms of different ageing method are discussed from FTIR perspective. • The performance prediction models based on FTIR and chemometrics is discussed. • Multispectral data fusion approach is envisaged for future research. Fourier-transform infrared spectroscopy (FTIR) has become a crucial method for both qualitative and quantitative analysis in characterizing asphalt materials. The present work aims to provide a comprehensive review of recent uses of FTIR in this field, that ranged from material quality control, material identification, to the analysis of modification mechanism, including ageing mechanisms, as well as for macroscopic performance prediction. The narrative unfolds within a broader context, with the basic principles, and insightful comparisons with ultraviolet–visible (UV–vis) spectroscopy, Raman spectroscopy, and fluorescence spectroscopy. The instrumentations employed in FTIR research are inspected in detail, delving into testing modes, sample preparation, and data analysis methods, with a particular emphasis on its ability to identify asphalt components at the molecular level. Furthermore, FTIR analysis provides useful indications for various applications: i) quality identification; ii) asphalt materials modifications and ageing states identification according to molecular changes; iii) prediction for the physical and rheological properties of asphalt binder based on chemometric method. The prospects in asphalt research are proposed stressing the relevance of combining FTIR analysis to high-throughput experimental methods and other spectroscopy technologies, and coupling to machine learning (ML) methods. This paper provides a reference for researchers who intend to explore the quality control and to analyze asphalt binders from a microscale perspective, fostering further research on relationships between microscopic compositions and macroscopic properties. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00162361
Volume :
371
Database :
Academic Search Index
Journal :
Fuel
Publication Type :
Academic Journal
Accession number :
177845627
Full Text :
https://doi.org/10.1016/j.fuel.2024.132078