journal article·2025-06-20

Defect-Functionalized Graphene-Modified Asphalt Binder via Multiscale Analyses: Effect of Defect Density with Implications for Pavement Durability

Zhiheng Wu, Wei Huang, Lei Zhang, Kai Huang, Chonghua Zhou, Wei Cai, Qi Cao

ACS Applied Nano Materials· Volume 8· Issue 24
Publisher page

Abstract

Defect-functionalized graphene offers considerable promise for enhancing the pavement performance of asphalt in pavement engineering, due to its unique nanostructural characteristics and surface chemistry. Nevertheless, the underlying mechanism of asphalt binder modified with defect-functionalized graphene is still unclear. Herein, the influence of defect density on graphene-modified asphalt binder is comprehensively explored by multiscale analyses. Rheological tests show that defect-functionalized graphene with higher defect density is beneficial for improving the high- and low-temperature performance of modified asphalt, and the rutting factor of high defect-functionalized graphene-modified asphalt binder increases by 16.24% compared to that of low defect-functionalized graphene. Theoretical calculations indicate that a higher density of defects leads to an increase in the number of sites available for vacancy adsorption, thereby improving the interaction between graphene and nonpolar molecules present in asphalt. Higher defect density leads to a more uneven charge distribution on the graphene surface, giving it greater polarity. Subsequently, the interaction of van der Waals forces between graphene and nonpolar molecules present in asphalt is further intensified, leading to improved thermal-mechanical characteristics of asphalt binder modified with defect-functionalized graphene. These findings provide valuable insights for advancing the use of graphene in asphalt to bolster the durability of pavement.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Asphalt Pavement Performance Evaluation · Infrastructure Maintenance and Monitoring · Polymer Nanocomposites and Properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Intelligent Transportation System Research Center

Southeast University

School of Chemistry and Chemical Engineering

China Airport Construction Group Corporation

CCCC Dredging (Group) Corporation Limited

Anzhenghang New Materials Technology (Shanghai) Company Limited

Funding

National Natural Science Foundation of China · CCCC Highway Consultants Co., Ltd. · China Airport Construction Group Corporation

References (53)

Show source-provided references
1. 10.1016/j.jclepro.2024.14159210.1016/j.jclepro.2024.141592 ↗
2. 10.1016/j.conbuildmat.2023.13312810.1016/j.conbuildmat.2023.133128 ↗
3. 10.1021/acs.energyfuels.3c0086010.1021/acs.energyfuels.3c00860 ↗
4. 10.1007/s11431-023-2724-710.1007/s11431-023-2724-7 ↗
5. 10.1007/s11595-010-0063-610.1007/s11595-010-0063-6 ↗
6. 10.1080/14680629.2022.207237410.1080/14680629.2022.2072374 ↗
7. 10.1016/j.matdes.2023.11187110.1016/j.matdes.2023.111871 ↗
8. 10.1016/j.aej.2023.12.03110.1016/j.aej.2023.12.031 ↗
9. 10.1016/j.conbuildmat.2024.13751210.1016/j.conbuildmat.2024.137512 ↗
10. 10.1515/ntrev-2021-008210.1515/ntrev-2021-0082 ↗
11. 10.1016/j.conbuildmat.2024.13767110.1016/j.conbuildmat.2024.137671 ↗
12. 10.1016/j.conbuildmat.2022.12843110.1016/j.conbuildmat.2022.128431 ↗
13. 10.1016/j.cscm.2024.e0335410.1016/j.cscm.2024.e03354 ↗
14. 10.1016/j.jmst.2014.11.01910.1016/j.jmst.2014.11.019 ↗
15. 10.1002/qua.2690010.1002/qua.26900 ↗
16. 10.3390/mi805016310.3390/mi8050163 ↗
17. 10.1007/s42947-023-00401-z10.1007/s42947-023-00401-z ↗
18. 10.1080/10408436.2015.106816010.1080/10408436.2015.1068160 ↗
19. 10.1016/j.cclet.2020.10.03010.1016/j.cclet.2020.10.030 ↗
20. 10.1039/C7TA07612F10.1039/C7TA07612F ↗
21. 10.1016/j.triboint.2024.11012410.1016/j.triboint.2024.110124 ↗
22. 10.1016/j.apsusc.2025.16316810.1016/j.apsusc.2025.163168 ↗
23. 10.1016/j.cej.2024.14866810.1016/j.cej.2024.148668 ↗
24. 10.1039/D4TA07947G10.1039/D4TA07947G ↗
25. Fang Z. · J. Municipal Technol. · 2024 · 42 · 208
26. 10.1016/j.ccr.2024.21642110.1016/j.ccr.2024.216421 ↗
27. 10.1007/s42947-022-00251-110.1007/s42947-022-00251-1 ↗
28. 10.1002/adma.20120533210.1002/adma.201205332 ↗
29. 10.1016/j.conbuildmat.2024.13713910.1016/j.conbuildmat.2024.137139 ↗
30. 10.1016/j.matdes.2023.11215710.1016/j.matdes.2023.112157 ↗
31. 10.1016/j.molliq.2024.12549710.1016/j.molliq.2024.125497 ↗
32. 10.1016/j.fuel.2021.12203710.1016/j.fuel.2021.122037 ↗
33. 10.1016/j.fuel.2023.12819210.1016/j.fuel.2023.128192 ↗
34. 10.1016/j.fuel.2013.07.01210.1016/j.fuel.2013.07.012 ↗
35. 10.1016/j.carbon.2024.11954710.1016/j.carbon.2024.119547 ↗
36. AASHTO · 2023
37. AASHTO · 2023
38. 10.3390/ma1419567210.3390/ma14195672 ↗
39. 10.7498/aps.71.2021236610.7498/aps.71.20212366 ↗
40. 10.1016/j.fuel.2017.07.04810.1016/j.fuel.2017.07.048 ↗
41. 10.1016/j.conbuildmat.2020.12171310.1016/j.conbuildmat.2020.121713 ↗
42. 10.1016/j.conbuildmat.2022.12833210.1016/j.conbuildmat.2022.128332 ↗
43. 10.1021/ef020200r10.1021/ef020200r ↗
44. 10.1016/j.matdes.2021.10999410.1016/j.matdes.2021.109994 ↗
45. 10.1016/j.conbuildmat.2021.12305810.1016/j.conbuildmat.2021.123058 ↗
46. 10.1016/j.matdes.2024.11295710.1016/j.matdes.2024.112957 ↗
47. 10.1016/j.fuel.2024.13324410.1016/j.fuel.2024.133244 ↗
48. 10.1016/j.apsusc.2024.16140710.1016/j.apsusc.2024.161407 ↗
49. 10.1016/j.conbuildmat.2019.11770610.1016/j.conbuildmat.2019.117706 ↗
50. 10.1021/acsomega.3c0986110.1021/acsomega.3c09861 ↗
51. 10.1016/j.conbuildmat.2024.13592310.1016/j.conbuildmat.2024.135923 ↗
52. 10.1021/acsanm.3c0556510.1021/acsanm.3c05565 ↗
53. 10.1016/j.conbuildmat.2024.13542610.1016/j.conbuildmat.2024.135426 ↗