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Evaluation of mechanical properties of basalt and aramid fiber reinforced hybrid composites with polyvinyl chloride (PVC) core material

  • Dalya Fadıl , Ahmet Erkliğ and Mehmet Bulut EMAIL logo
Published/Copyright: October 13, 2025
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Abstract

This study investigates the mechanical performance of sandwich composites comprising basalt (B) and aramid (A) fiber-reinforced skins with a PVC foam core, focusing on the effects of fiber hybridization and stacking sequence. Tensile, flexural, and 25 J impact tests were conducted to evaluate monolithic and hybrid configurations. Monolithic Basalt (B5/PVC/B5) exhibited lower tensile strength (average ∼109.5 MPa) with higher flexural modulus (average ∼36.7 GPa) compared to Aramid (A5/PVC/A5) skins. Conversely, Aramid skins (A5/PVC/A5) demonstrated higher flexural strain (average ∼1.35 %), indicating greater ductility. Hybrid configurations balanced these properties; the BA-PVC (B3A2/PVC/A2B3) arrangement achieved optimal energy absorption (average ∼25 J) under impact, outperforming AB-PVC (A2B3/PVC/B3A2) (average ∼20 J). Tensile testing revealed A5/PVC/A5 had the highest strength (average ∼136.7 MPa), while B5/PVC/B5 showed the highest strain (average ∼9.56 %). Flexural testing confirmed B5/PVC/B5 possessed the highest strength (43.7 MPa) and modulus (36.7 GPa). Stacking sequence critically governed failure modes, with basalt-dominated exteriors prioritizing stiffness but suffering abrupt core shear failure, while Aramid exteriors enhanced damage tolerance through progressive matrix cracking and fiber bridging. The PVC core’s low shear modulus amplified delamination in stiff hybrids, underscoring interfacial adhesion as a key limitation. Findings reveal that the BA-PVC architecture (Aramid outer/Basalt inner) optimally balances strength, ductility, and impact resistance.


Corresponding author: Mehmet Bulut, Sivas Vocational School of Technical Sciences Machine Department, Sivas Cumhuriyet University, 58140 Sivas, 58140, Türkiye, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author(s) have (has) accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The author(s) state(s) no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: The raw data can be obtained on request from the corresponding author.

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Received: 2025-06-19
Accepted: 2025-08-12
Published Online: 2025-10-13
Published in Print: 2025-11-25

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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