材料科学
尺寸
复合材料
聚丙烯
极限抗拉强度
聚合物
表面能
复合数
表面改性
涂层
化学工程
化学
有机化学
工程类
作者
Wei Liu,Yaofeng Zhu,Qian Chen,Hongbo Dai,Yaqin Fu,Yubing Dong
标识
DOI:10.1016/j.compositesb.2022.110029
摘要
High performance structural applications of utilizing glass fiber (GF) reinforced polypropylene (PP) composites are normally hindered by the notoriously weak interfacial bonding between GF and PP resulting from their chemical inertness and the great mismatch in surface energies of both raw materials. Tremendous efforts have been made on the development of fiber sizing agents for interfacial modifications of GF-PP composites, since a viable sizing agent can directly build robust and efficient coupling interface between GF and PP, enabling effective stress transfer between fiber and matrix. Herein, this paper reports an interfacial modification methodology of using a novel amphiphilic sizing agent that is a polyacrylate-based waterborne coating synthesized strategically following a one-step reversible addition-fragmentation chain-transfer (RAFT)-mediated polymerization-induced self-assemble (PISA) approach. Specifically, after the proposed sizing treatment the surface energy of the sized GF surface decreases from 74.51 mJ·m−2 (of the typical pristine GF surface) to 56.43 mJ·m−2, approaching to 30.2 mJ·m−2 (of the raw PP) and enabling strong possibility of facilitating GF-PP interfacial compatibility. Additionally, the GF-PP interfacial shear strength (IFSS) evaluated by single-fiber fragmentation tests increases from 8.34 MPa (for bare GF) and 11.14 MPa (for commercial GF) to 17.62 MPa for the sized GF. Notably, a series of the sized short GF/PP composite coupons were fabricated and demonstrates promoted tensile and flexural properties, validating the effectiveness and scalability of the proposed GF/PP interfacial treatment. We believe that this amphiphilic polyacrylate-based sizing agent can serve as an effective GF-PP interfacial modifier, offering great potential for practical applications of developing high performance GF-PP composites.
科研通智能强力驱动
Strongly Powered by AbleSci AI