journal article·1998-12

Interfacial properties of two SiC fiber–reinforced polycarbonate composites using the fragmentation test and acoustic emission

Joung‐Man Park, Eui‐Min Chong, Dong‐Jin Yoon, Joon‐Hyun Lee

Polymer Composites· Volume 19· Issue 6
Publisher page

Abstract

Abstract Interfacial shear strengths (IFSS) between the fiber and the matrix in two SiC fiber–reinforced polycarbonate (PC) composites (TFC) were investigated through the fragmentation method and the acoustic emission (AE) technique. Statistical analysis of SiC fiber tensile strength was performed mainly in terms of a Weibull distribution. The tensile strength and elongation for SiC fiber decreased with increasing gauge lengths, because of the heterogeneous distribution of flaws on the fiber surface. Using an amino‐silane coupling agent, the IFSS showed significant improvement, in the range of 150%, under dry conditions. On the other hand, in the aspect of the environmental effect, the IFSS was improved about 170% under wet conditions (immersed in hot water at 85°C for 75 min). This is probably due to chemical and hydrogen bonds in the two different interphases in the SiC fiber/silane coupling agent/PC matrix system. In ‐ situ monitoring of AE during straining of microspecimens showed the sequential occurrence of two distinct groups of AE data. The first group may result from SiC fiber breakages, and the second probably results from mainly PC matrix cracking. Characteristic frequencies coming from the failures of the fiber and the PC matrix were shown via fast Fourier transform (FFT) analysis. By setting an appropriate threshold level, a one‐to‐one correspondence between the number of AE events and fiber breakages was established. This AE method could be correlated successfully to the IFSS via the fragmentation technique, which can also applied to nontransparent specimens.
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Research context

OpenAlex topics: Fiber-reinforced polymer composites · Mechanical Behavior of Composites · Polymer crystallization and properties

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

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