Jacquard-Woven Photonic Bandgap Fiber Displays

Sayed, Imran; Berzowska, Joanna; Skorobogatiy, Maksim

doi:10.1108/rjta-14-04-2010-b011

Cited by 23 publications

(25 citation statements)

References 21 publications

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“…Thus, bandgap guidance mechanism renders Bragg fibers suitable for application in spectral filtering, 118,119 optical sensing, 117,[119][120][121]166 and photonic textiles. 116,122,153 the resultant color of a fiber ribbon was yellow. 116,122 Photonic Textiles Based on Bragg Fibers.…”

Section: Photonic Technologies For Textilesmentioning

confidence: 99%

Nanotechnology in Textiles

et al. 2016

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Increasing customer demand for durable and functional apparel manufactured in a sustainable manner has created an opportunity for nanomaterials to be integrated into textile substrates. Nanomoieties can induce stain repellence, wrinkle-freeness, static elimination, and electrical conductivity to fibers without compromising their comfort and flexibility. Nanomaterials also offer a wider application potential to create connected garments that can sense and respond to external stimuli via electrical, color, or physiological signals. This review discusses electronic and photonic nanotechnologies that are integrated with textiles and shows their applications in displays, sensing, and drug release within the context of performance, durability, and connectivity. Risk factors including nanotoxicity, nanomaterial release during washing, and environmental impact of nanotextiles based on life cycle assessments have been evaluated. This review also provides an analysis of nanotechnology consolidation in the textiles market to evaluate global trends and patent coverage, supplemented by case studies of commercial products. Perceived limitations of nanotechnology in the textile industry and future directions are identified.

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Section: Photonic Technologies For Textilesmentioning

confidence: 99%

Nanotechnology in Textiles

et al. 2016

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“…A number of light emitting fibers have emerged in the literature including side-emitting optical fibers [8][9][10], mechanoluminescent fibers [11], electroluminescent (EL) fibers [12][13][14][15][16][17][18][19], and fibers exhibiting photoluminescence [20][21][22][23]. Electroluminescent and photoluminescent fibers emit light upon the application of electrical or optical power, respectively.…”

Section: Introductionmentioning

confidence: 99%

Effect of Fabric Integration on the Physical and Optical Performance of Electroluminescent Fibers for Lighted Textile Applications

Martin

Fontecchio

2018

Fibers

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The advent of electroluminescent (EL) fibers, which emit light in response to an applied electric field, has opened the door for fabric-integrated light emission and displays in textiles. However, there have been few technical publications over the past few years about the performance of these light emitting fibers inside functional fabrics. Thus, there is limited information on the effect of integration on the physical and optical performance of such devices. In this work, alternating current powder-based EL (ACPEL) fibers were evaluated under a range of operating conditions both inside and outside of a knit matrix to understand how the EL fiber device performance changed inside a functional fabric. The device efficiency, adjustable brightness, and mechanical properties of these fibers are presented. The effects of fabric integration on the light-emitting fibers as well as the supporting knit fabric are discussed as they relate to the practical applications of this technology.

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“…52 Garment-based gesture controls or muscle fatigue detection can be realized by textile-based electromyography sensors. 53,54 Beyond sportswear or healthcare, the attention on connecting people through clothing-based wearable technology has been recently pioneered by incorporating micro-light emitting diode (LED) arrays to create wearable displays and tactile or touching textile sensors 55 and color-tunable textiles for illumination or decoration 56,57 in the fashion and entertainment sectors. Indeed, the product range and vision of the e-textile technology market is constantly improving and enabling more commercial product developments.…”

mentioning

confidence: 99%

Modeling of surface temperature distributions on powered e-textile structures using an artificial neural network

Bahadır

Şahin

Kiraz

2017

Textile Research Journal

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An artificial neural network (ANN) model is constructed to derive the surface temperature of e-textile structures developed for cold weather clothing. A series of textile transmission lines made of different types of conductive yarns, insulated by using different types of seam tapes, were enclosed in a thermoplastic textile structure via hot air welding technology, and then they were powered with different levels of specific voltages in order to obtain different heating levels. The surface temperatures of the powered e-textile structures were measured using a thermal camera. The experimental input variables, sample type, temperature, feeding speed, resistance of samples, applied voltage and current were used to construct an ANN model and the outputs of surface temperature and electric power dissipated were used to test the prediction performance of the developed model. It was concluded that the ANN provided substantial predictive performance. Simulations based on the developed ANN model can estimate the surface temperature distributions of powered e-textile structures under different conditions. The ANN model developed for prediction of electric power dissipated was very successful and can be useful for e-textile product designers as well as textile manufacturers, particularly for cold weather protection products such as jackets, gloves and outdoor sleeping mats.

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Jacquard-Woven Photonic Bandgap Fiber Displays

Cited by 23 publications

References 21 publications

Nanotechnology in Textiles

Nanotechnology in Textiles

Effect of Fabric Integration on the Physical and Optical Performance of Electroluminescent Fibers for Lighted Textile Applications

Modeling of surface temperature distributions on powered e-textile structures using an artificial neural network

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