Alenka Šalej (Author), Peter Fajfar (Author), Goran Kugler (Author), Tatjana Rijavec (Author)

Abstract

A prototype of a new shape-memory nitinol knitted fabric intended for use as an active thermal insulating interlining in firefighting protective clothing was developed in the study presented in this paper. Weft knitted fabrics were made from commercially available cold-worked nickel titanium alloy monofils. Knits were made on a manual knitting machine from a monofil measuring 0.1 mm in diameter, while a hand-made knit was prepared from a monofil measuring 0.2 mm in diameter. Nitinol fabrics were annealed at 500 °C to achieve an austenite transition temperature of 75 °C. A special constructed mould made of a steel frame and aluminium domes measuring 30 and 20 mm in height was used to give the nitinol fabrics a new temporary shape. A two-way, shape-memory effect of the nitinol fabrics was achieved using a 15-cycle training process. The achieved shape-memory effect was tested in a heated chamber at 100 °C, where bulges measuring 12–25 mm in height occurred. NiTi knits made from finer monofil were the most successful shape-memory knits. They were machine knitted and achieved sufficiently high bulges, measuring 18 or 12 mm, that facilitated large enough air gaps for effective thermal protection. A smart textile system was prepared by inserting the trained nitinol fabric into a pocket made from two textile fabric layers sewn together. When it was exposed to environmental temperatures of 75 °C and higher, it instantly changed its form from a two-dimensional shape to a three-dimensional shape, while increasing the air gap in the pocket. A quilted fabric made from such a smart textile system could be used in firefighting protective clothing to locally improve thermal insulation and protect the human skin from overheating or burns.

Keywords

interlining;personal protective garment;smart textile;shape-memory alloys (SMAs);

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL NTF - Faculty of Natural Sciences and Engineering
UDC: 669
COBISS: 1805151 Link will open in a new window
ISSN: 0964-1726
Views: 387
Downloads: 104
Average score: 0 (0 votes)
Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Type (COBISS): Article
Pages: str. 1-10
Volume: ǂVol. ǂ28
Issue: ǂno. ǂ6
Chronology: 2019
DOI: 10.1088/1361-665X/ab18b9
ID: 13163786