journal article·2026-06-20

Bio‐Based Hyperbranched Polyurethane Sizing Agent With Self‐Catalytic Function for Improving the Mechanical Properties of Carbon Fiber/ PA6 Composites

Xuyang Li, Shengtao Dai, Guipeng Quan, Yunhuan Wu, Jiahuai Zhang, Kui Wang, Chuyan Zhang, Yuhui Ao, Zhouyang Zhao, Linghan Xiao

Polymer Composites· Volume 47· Issue S2
Publisher page

Abstract

ABSTRACT The application of conventional petroleum‐based waterborne polyurethane (WPU) sizing agents is constrained by their low solid content and poor stability. There is an urgent need to develop a stable and environmentally friendly sizing agent to address the interfacial issues of carbon fibers (CF). Bio‐based sizing agents with high solid content offer an environmentally friendly solution for improving the interfacial properties of carbon fiber (CF) composites. In this study, 2‐methyltetrahydrofuran (2‐MTHF), a biodegradable solvent, was selected as the reaction medium. Epoxidized soybean oil (ESBO) and caffeic acid (CA), both derived from renewable biobased resources, were employed as materials to successfully synthesize a hyperbranched waterborne polyurethane sizing agent (GWPU). The synthesis involved integrating a tertiary amine functionality into the branched architecture of epoxidized soybean oil, enabling self‐catalytic polyurethane formation without toxic catalysts. Theoretical calculations revealed comparable catalytic activity between the tertiary amine groups and DBTDL. The molecular architecture simultaneously improved the solid content and stability of GWPU. Furthermore, the hyperbranched architecture of GWPU created abundant hydrogen‐bonding sites, significantly enhancing the CF‐resin interfacial adhesion. At an optimal 1.5 wt% sizing concentration, the CF/PA6 composites exhibited 46.3% and 32.6% increases in flexural strength and modulus, respectively, along with 33.3% (ILSS) and 53.2% (IFSS) improvements compared to unsized CF. These results demonstrate the potential for industrial application of this green polyurethane sizing agent. These findings provide crucial implications for both the synthesis and industrialization of green polyurethane sizing agents.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Polymer composites and self-healing · Fiber-reinforced polymer composites · Carbon dioxide utilization in catalysis

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

Affiliations

Jilin Province Key Laboratory of Carbon Fiber Development and Application, College of Chemistry and Life Science, Changchun University of Technology Changchun China

Advanced Institute of Materials Science, Jilin Provincial Laboratory of Carbon Fiber and Composites, Changchun University of Technology Changchun China

School of Materials Science and Engineering, Zhejiang Sci‐Tech University Hangzhou China

References (47)

Show source-provided references
1. 10.1016/j.apsusc.2024.16058310.1016/j.apsusc.2024.160583 ↗
2. 10.1016/j.compscitech.2021.10878810.1016/j.compscitech.2021.108788 ↗
3. 10.1177/2633366X2097865710.1177/2633366X20978657 ↗
4. 10.3390/polym1315247410.3390/polym13152474 ↗
5. 10.1016/j.apsusc.2022.15630810.1016/j.apsusc.2022.156308 ↗
6. 10.1016/j.compscitech.2023.10998010.1016/j.compscitech.2023.109980 ↗
7. 10.1080/02670844.2017.142041710.1080/02670844.2017.1420417 ↗
8. 10.1016/j.surfcoat.2020.12675110.1016/j.surfcoat.2020.126751 ↗
9. 10.1016/j.diamond.2023.11073910.1016/j.diamond.2023.110739 ↗
10. 10.1016/j.ijbiomac.2024.12945710.1016/j.ijbiomac.2024.129457 ↗
11. 10.1016/j.compscitech.2022.10985110.1016/j.compscitech.2022.109851 ↗
12. 10.1016/j.compscitech.2022.10928010.1016/j.compscitech.2022.109280 ↗
13. 10.1016/j.compscitech.2018.05.05110.1016/j.compscitech.2018.05.051 ↗
14. 10.1016/j.pmatsci.2015.02.00310.1016/j.pmatsci.2015.02.003 ↗
15. 10.1016/j.coco.2023.10149810.1016/j.coco.2023.101498 ↗
16. 10.1002/app.4611110.1002/app.46111 ↗
17. 10.1016/j.polymertesting.2019.03.01410.1016/j.polymertesting.2019.03.014 ↗
18. 10.1016/j.eurpolymj.2017.04.01410.1016/j.eurpolymj.2017.04.014 ↗
19. 10.1039/d3gc04294d10.1039/d3gc04294d ↗
20. 10.1016/j.colsurfb.2015.07.04410.1016/j.colsurfb.2015.07.044 ↗
21. 10.1007/s11743‐016‐1909‐510.1007/s11743‐016‐1909‐5 ↗
22. 10.1021/acssuschemeng.9b0187310.1021/acssuschemeng.9b01873 ↗
23. 10.1021/ma400200y10.1021/ma400200y ↗
24. 10.1016/j.compscitech.2023.11021410.1016/j.compscitech.2023.110214 ↗
25. 10.1016/j.compscitech.2024.11044910.1016/j.compscitech.2024.110449 ↗
26. 10.1021/acs.joc.9b0131910.1021/acs.joc.9b01319 ↗
27. 10.1016/j.compscitech.2022.10966410.1016/j.compscitech.2022.109664 ↗
28. 10.1021/jf050731o10.1021/jf050731o ↗
29. 10.1002/app.2707710.1002/app.27077 ↗
30. 10.1016/j.porgcoat.2005.11.00710.1016/j.porgcoat.2005.11.007 ↗
31. 10.1080/01932691.2014.90380510.1080/01932691.2014.903805 ↗
32. 10.1016/j.infrared.2018.09.00110.1016/j.infrared.2018.09.001 ↗
33. 10.1039/d3gc00704a10.1039/d3gc00704a ↗
34. 10.1016/j.applthermaleng.2023.12058310.1016/j.applthermaleng.2023.120583 ↗
35. 10.1007/s13399‐024‐06145‐510.1007/s13399‐024‐06145‐5 ↗
36. 10.1016/j.compositesa.2018.06.02610.1016/j.compositesa.2018.06.026 ↗
37. 10.1039/c4ta04055d10.1039/c4ta04055d ↗
38. 10.1016/j.ijbiomac.2024.13271610.1016/j.ijbiomac.2024.132716 ↗
39. 10.1016/j.apsusc.2014.08.17510.1016/j.apsusc.2014.08.175 ↗
40. 10.1002/pc.2443910.1002/pc.24439 ↗
41. 10.1002/app.5361110.1002/app.53611 ↗
42. 10.1002/app.3512610.1002/app.35126 ↗
43. 10.3390/polym1109152810.3390/polym11091528 ↗
44. 10.1002/app.4188210.1002/app.41882 ↗
45. 10.1016/j.cej.2024.15409610.1016/j.cej.2024.154096 ↗
46. 10.1016/j.coco.2021.10084910.1016/j.coco.2021.100849 ↗
47. 10.1016/s1872‐5805(23)60705‐x10.1016/s1872‐5805(23)60705‐x ↗