{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T12:59:20Z","timestamp":1762261160177,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T00:00:00Z","timestamp":1762214400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Postgraduate Research & Practice Innovation Program of Jiangsu Province","award":["KYCX25_3760"],"award-info":[{"award-number":["KYCX25_3760"]}]},{"name":"Large Instruments Open Foundation of Nantong University","award":["KFJN2562"],"award-info":[{"award-number":["KFJN2562"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Materials"],"abstract":"<jats:p>To investigate the long-term water stability of graphene-modified permeable asphalt mixtures, in this study, we analysed the effects of single factors and multi-factor coupling. The single-factor water stability was investigated through the free thawing splitting test, standard Cantabro test, and immersion Cantabro test; the experimental indicators were the freeze\u2013thaw cracking ratio (TSR), mass loss rate, and immersion mass loss rate, respectively. The multi-factor water stability was studied through immersion operation tests of mixtures with different degrees of ageing. The dispersion of graphene was examined through Raman mapping, the formation of three-dimensional network structures of graphene and SBS was evaluated via the dynamic shear rheometer test (DSR), and the elemental distribution was quantitatively analysed using energy-dispersive spectroscopy (EDS) and an image pixel algorithm (RGB). The results indicate that an unaged graphene-composite- and SBS-modified permeable asphalt mixture with an optimal graphene content of 0.05% demonstrated a 4.5% improvement in the TSR, alongside reductions in the mass loss rate and water immersion mass loss rate of 25.64% and 23.52%, respectively. Even after prolonged thermal oxygen ageing, its TSR, mass loss rate, and water immersion mass loss rate improved by 5.1%, 23.04%, and 20.70%, respectively. Multi-factor coupling tests confirmed that the water stability met requirements under severe conditions, with better performance at high temperatures. Graphene was uniformly dispersed in the modified asphalt. The appearance of a plateau region at low frequencies in graphene-composite- and SBS-modified asphalt verified the formation of a three-dimensional network structure, and the oxygen content was positively correlated with deepening thermal oxidative ageing.<\/jats:p>","DOI":"10.3390\/ma18215024","type":"journal-article","created":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T12:13:08Z","timestamp":1762258388000},"page":"5024","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Long-Term Water Stability Analysis of Graphene-Composite-Modified Permeable Asphalt Mixture"],"prefix":"10.3390","volume":"18","author":[{"given":"Suzhan","family":"Ji","sequence":"first","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Li","sequence":"additional","affiliation":[{"name":"China Communications Construction Corporation General Contracting and Operation Branch, Beijing 100088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Wu","sequence":"additional","affiliation":[{"name":"Institute of Smart O&M and IoT, Nantong Institute of Technology, Nantong 226001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ke","family":"Liang","sequence":"additional","affiliation":[{"name":"Nantong Construction Engineering Quality Testing Center, Nantong 226000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8704-6703","authenticated-orcid":false,"given":"Xiaojian","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoguang","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiangru","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China"},{"name":"Institute of Smart O&M and IoT, Nantong Institute of Technology, Nantong 226001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Geng, J., Chen, M., Shang, T., Li, X., Kim, Y.R., and Kuang, D. 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