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Experimental Investigations on Shear Thickening Fluids as "Liquid Body Armors": Non-Conventional Formulations for Ballistic Protection.

Authors :
Alexe F
Sau C
Iorga O
Toader G
Diacon A
Rusen E
Lazaroaie C
Ginghina RE
Tiganescu TV
Teodorescu M
Sobetkii A
Source :
Polymers [Polymers (Basel)] 2024 Aug 15; Vol. 16 (16). Date of Electronic Publication: 2024 Aug 15.
Publication Year :
2024

Abstract

Shear thickening fluids (STFs) have garnered attention as potential enhancers of protective capabilities and for the optimization of Kevlar <superscript>®</superscript> armor design. To assess the possible shear thickening properties and potential application in ballistic protection, ten formulations were developed by employing polyethylene glycol (PEG) or polypropylene glycol (PPG), along with fumed silica or Aerosil HDK <superscript>®</superscript> . Rheological characterization facilitated the identification of formulations displaying shear thickening behavior. The potential integration of the selected shear thickening fluids (STFs) into Kevlar <superscript>®</superscript> -based composites was investigated by studying the impact resistance of Kevlar <superscript>®</superscript> soft armor structures. Also, high-velocity impact testing revealed that the distance between aramid layers plays a crucial role in the impact resistance effectiveness of Kevlar <superscript>®</superscript> -STF composite structures and that there is a very narrow domain between optimal and undesired scenarios in which STF could facilitate the penetration of Kevlar. The introduction of STF between the Kevlar sheets disrupted this packing and the energy absorption capacity of the material was not improved. Only one formulation (PEG400, Aerosil 27 wt.%) led to a less profound traumatic imprint and stopped the bullet when it was placed between layers no.1 and no.2 from a total of 11 layers of Kevlar XP. These experimental findings align with the modeling and simulation of Kevlar <superscript>®</superscript> -STF composites using Ansys simulation software (Ansys® AutoDyn 2022 R2).

Details

Language :
English
ISSN :
2073-4360
Volume :
16
Issue :
16
Database :
MEDLINE
Journal :
Polymers
Publication Type :
Academic Journal
Accession number :
39204525
Full Text :
https://doi.org/10.3390/polym16162305