A scalable fiber bundle pullout manufacturing method for data-driven interfacial shear strength measurements of micro and nanomaterials

• Published in: Composites science and technology 2022-05, Vol.222, p.109375, Article 109375
• Main Authors: De Leon, Ana, Tank, Mehul, Sweat, Rebekah
• Format: Article
• Language: English
• Subjects: Carbon fiber reinforced plastics; Carbon fibers; Carbon nanotubes; Composite materials; Interfacial shear strength; Interfacial strength; Load transfer; Manufacturing; Molds; Nanomaterials; Polymer-matrix composites (PMCs); Production methods; Pull out tests; Shear strength; Statistical methods; Statistics; Structural integrity; Surface treatment; Variance analysis; Yarns
• ISSN: 0266-3538; 1879-1050
• DOI: 10.1016/j.compscitech.2022.109375

Adhesive and surface treatment technologies are crucial for the structural integrity of the composite parts. The interfacial shear strength (IFSS) reflects the load transfer efficiency between reinforcement and matrix. However, no current test can be performed quickly with statistically significant replications. As a solution, this paper presents a horizontal mold and geometry matched testing fixture for manufacturing samples for the pullout test in large quantity batches. The open-face mold design can accommodate matrices with a wide range of viscosity and solves the problem of testing nanomaterial and micromaterial bundle interfaces using the same pattern. The effectiveness of sample manufacturing made of carbon nanotube (CNT) yarns and IM7 carbon fiber (CF) with three different polymer matrices was demonstrated in this work. The IFSS of each sample were recorded using a conventional tensile machine, and their surface morphology was evaluated with SEM images. Analysis of Variance (ANOVA) and Tukey's pairwise comparison tests demonstrated a significant difference in IFSS means when changing matrices on CNT yarn specimens but no statistically significant difference on IM7-CF specimens for the three matrices in this study. This mold is expected to help researchers obtain faster results and study matrices that have not been thoroughly tested. [Display omitted]