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The purpose of this paper is to investigate the potential use of the layer-by-layer (LbL) assembly as an intumescent flame retardant for polyester, cotton and their blended fabrics.

In this study, polyester (PET), cotton and their blends were applied with the flame retardant coating via the LbL assembly technique. The flame retardancy, melt dripping, thermal properties and morphology of coated polyester fabrics were then examined.

The scanning electron micrograph of uncoated and coated fabrics revealed that the LbL assembly coating on the fabric surface was successful. The assessment of the flame retardancy and thermal properties of the coated fabrics showed that the after-flame time and melt dripping during the vertical burning test decreased. The char residue at temperatures ranging from 450 to 800°C during thermogravimetric analysis was enhanced as compared with the uncoated fabric. Furthermore, the morphology of the char residual of coated fabrics was rougher and bulkier than the uncoated fabrics, suggesting the typical behavior of intumescence.

The LbL technique generally uses much fewer chemicals, thus making this flame retardant finishing much more environmentally friendly. It is also expected that these fabrics will show better touch characteristics. These fabrics may be tested for their comfort compared to that of conventional coating to enable their use on an industrial scale.

This work demonstrated the ability to apply an effective intumescent coating on polyester, cotton and blend fabric. In order to maintain fabric handle property, the Lbl coating technique is also employed.

The purpose of this paper is to develop a computerized program that can recognize woven fabric structures and simultaneously use the obtained data to 3D re‐visualize the corresponding woven fabric structures.

A 2D bitmap image of woven fabric was initially acquired using an ordinary desktop flatbed scanner. Through several image‐processing and analysis techniques as well as recognition algorithms, the weave pattern was then identified and stored in a digital format. The weave pattern data were then used to construct warp and weft yarn paths based on Peirce's geometrical model.

By combining relevant weave parameters, including yarn sizes, warp and weft densities, yarn colours as well as cross‐sectional shapes, a 3D image of yarns assembled together as a woven fabric structure is produced and shown on a screen through the virtual reality modelling language browser.

Woven fabric structures can now be recognised and simultaneously use the obtained data to 3D re‐visualize the corresponding woven fabric structures.