journal article·2023-09

Low‐velocity impact and self‐healing behavior of CFRP laminates with poly(ethylene‐co‐methacrylic acid) filament reinforcement

Zhenzhen Zhang, Ying Tie, Cheng Li

Polymer Composites· Volume 44· Issue 9
Publisher page

Abstract

Abstract An experimental study is performed to explore the low‐velocity impact (LVI) and self‐healing behavior of carbon‐fiber‐reinforced‐polymer (CFRP) laminates reinforced by thermoplastic poly(ethylene‐co‐methacrylic acid) (EMAA) filaments. Firstly, differential scanning calorimetry (DSC), thermos‐gravimetric analysis (TGA) and dynamic mechanical analysis (DMA) are used to determine the process parameters. Thereafter, the unreinforced laminates and EMAA reinforced laminates are prepared via phased hot‐processing curing process. The LVI tests with four energy levels (5, 15, 25 and 35 J) are then carried out on the two types of specimens. In these energy cases, the peak‐force values of the reinforced specimens are 2.2%, 1.9%, 2.3% and 7.5% higher than those of the unreinforced ones, while the energy‐absorption‐rate values of the reinforced ones are 6.02%, 3.53%, 4.24% and 2.32% lower. The comparisons demonstrate the impact‐resistance enhancement of EMAA. Moreover, multiple LVI tests are performed on the unhealed and healed specimens. In 15 and 25 J cases, around 6.92% higher peak load and 4.58% lower absorbed energy are observed within the healed specimens, which is attributed to the healing effect. The healing mechanism is investigated by utilizing attenuated total reflectance Fourier transform infrared spectroscopy (ATR‐FTIR), scanning electron microscope (SEM) and optical microscope (OM) technologies. It reveals that EMAA flows into the delaminations and cracks during the healing process, and thus accomplishing self‐healing behavior effectively.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Polymer composites and self-healing · Mechanical Behavior of Composites · Polymer crystallization and properties

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

Affiliations

School of Mechanical and Power Engineering Zhengzhou University Zhengzhou China

Funding

National Natural Science Foundation of China

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