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Published, Version of Record (VoR)CC BY V4.0, Open
Journal article
Self-Folding Textiles through Manipulation of Knit Stitch Architecture
Fibers, v 3(4), pp 575-587
01 Dec 2015
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This research presents a preliminary study on finding predictable methods of controlling the self-folding behaviors of weft knit textiles for use in the development of smart textiles and garment devices, such as those with shape memory, auxetic behavior or transformation abilities. In this work, Shima Seiki SDS-One Apex computer-aided knitting technology, Shima Seiki industrial knitting machines, and the study of paper origami tessellation patterns were used as tools to understand and predict the self-folding abilities of weft knit textiles. A wide range of self-folding weft knit structures was produced, and relationships between the angles and ratios of the knit and purl stitch types were determined. Mechanical testing was used as a means to characterize differences produced by stitch patterns, and to further understand the relationships between angles and folding abilities. By defining a formulaic method for predicting the nature of the folds that occur due to stitch architecture patterns, we can better design self-folding fabrics for smart textile applications.
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Details
- Title
- Self-Folding Textiles through Manipulation of Knit Stitch Architecture
- Creators
- Chelsea E. Knittel - Drexel Univ, Mat Sci & Engn, Philadelphia, PA 19104 USADiana S. Nicholas - Drexel UniversityReva M. Street - Drexel UniversityCaroline L. Schauer - Drexel UniversityGenevieve Dion - Drexel University
- Publication Details
- Fibers, v 3(4), pp 575-587
- Publisher
- Mdpi
- Number of pages
- 13
- Grant note
- Drexel COE Engineering Design Teaching Fellowship DGE-10028090/DGE-1104459 / National Science Foundation Graduate Research Fellowship; National Science Foundation (NSF)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Fashion Design; Architecture, Design, and Urbanism; Materials Science and Engineering; College of Engineering
- Web of Science ID
- WOS:000367750800013
- Scopus ID
- 2-s2.0-85054249603
- Other Identifier
- 991019168207404721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Materials Science, Multidisciplinary