{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T15:45:00Z","timestamp":1785685500568,"version":"3.56.0"},"reference-count":54,"publisher":"American Society of Civil Engineers (ASCE)","issue":"11","content-domain":{"domain":["ascelibrary.org"],"crossmark-restriction":true},"short-container-title":["J. Mater. Civ. Eng."],"published-print":{"date-parts":[[2026,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Intelligent sensing technology offers great promise for structural health monitoring (SHM) of building structures. Nevertheless, conventional strain sensors suffer from fragility, low sensitivity, and limitations in real-time monitoring, which have hindered their widespread implementation in structural health monitoring systems. In this study, carbon nanotube (CNT)\/natural rubber (NR) composites with intrinsic sensing capability were fabricated using a solution mixing method. At a CNT loading of 4% by weight, a well-dispersed three-dimensional tunneling conductive network was achieved within the NR matrix. The resulting composites exhibited remarkable electromechanical performance, with tensile strength and elongation at break enhanced by 79.52% and 162.95%, respectively. Furthermore, the gauge factor (GF) increased from 3.91 to 196.37, approximately 49.2 times higher, and the storage modulus (\n                    <jats:inline-formula>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" alttext=\"upper E prime\" display=\"inline\" overflow=\"scroll\">\n                        <mml:msup>\n                          <mml:mrow>\n                            <mml:mi>E<\/mml:mi>\n                          <\/mml:mrow>\n                          <mml:mrow>\n                            <mml:mo>\u2032<\/mml:mo>\n                          <\/mml:mrow>\n                        <\/mml:msup>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    ) increased from 1378.57 to 3844.79\u00a0MPa, about 2.8 times higher. Dynamic resistance\u2013strain cycling tests confirmed highly stable and repeatable responses under cyclic loading. To further elucidate the sensing mechanism, molecular dynamics simulations were employed to calculate the mean square displacement (MSD), fractional free volume (FFV), and binding energy, which showed strong consistency with the experimental results. These findings highlight that the CNT\/NR composite not only achieves a unique synergy of mechanical robustness and high sensing sensitivity, but also bridges experimental observations with molecular-level simulations, demonstrating strong potential for next-generation smart sensing materials in SHM of building structures.\n                  <\/jats:p>","DOI":"10.1061\/jmcee7.mteng-22061","type":"journal-article","created":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T14:58:46Z","timestamp":1785682726000},"update-policy":"https:\/\/doi.org\/10.1061\/do.news.20190416.0001","source":"Crossref","is-referenced-by-count":0,"title":["Smart Rubber Composites for Building Structure Monitoring: Laboratory Experiments and Molecular Simulations"],"prefix":"10.1061","volume":"38","author":[{"given":"Lidan","family":"Li","sequence":"first","affiliation":[{"name":"Kaili Univ.","place":["PR China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1288-774X","authenticated-orcid":true,"given":"Cheng","family":"Li","sequence":"additional","affiliation":[{"name":"Kaili Univ.","place":["PR China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaotao","family":"Yu","sequence":"additional","affiliation":[{"name":"Huazhong Univ. of Science and Technology","place":["PR China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"30","reference":[{"key":"e_1_3_4_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compositesb.2023.110759"},{"key":"e_1_3_4_3_1","doi-asserted-by":"publisher","DOI":"10.3390\/s21051818"},{"key":"e_1_3_4_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compscitech.2025.111182"},{"key":"e_1_3_4_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.matdes.2017.06.011"},{"key":"e_1_3_4_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cej.2022.140384"},{"key":"e_1_3_4_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compositesb.2021.108641"},{"key":"e_1_3_4_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.progpolymsci.2013.07.007"},{"issue":"5","key":"e_1_3_4_9_1","first-page":"639","article-title":"Structural health monitoring of asphalt pavements using smart sensor networks: A comprehensive review","volume":"7","author":"Di Graziano A.","year":"2020","unstructured":"Di Graziano, A., V. 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