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High-strength fibers are used to produce high-strength-to-weight-ratio materials for applications such as composites, soft and hard body armor, bulletproof vests, and tendons for scientific balloons. Unfortunately, these fibers degrade when they are exposed to ultraviolet–visible (UV–vis) radiation. The objective of this research was to develop systems to improve the UV resistance of such fibers. Composite porous membranes from a polyurethane (PU) matrix loaded with rutile titanium dioxide (TiO2) nanoparticles were developed to protect a braid made of polybenzobisoxazole (PBO) yarns. The PU membranes loaded with TiO2 nanoparticles were prepared by a phase-inversion technique. The effects of the amount of TiO2 nanoparticles on the composite membrane morphological structure and UV–vis light transmission were evaluated. The results show that when the concentration of TiO2 nanoparticles was increased, the porosity of the membrane and its UV–vis blocking effectiveness increased. The UV–vis protection was evaluated by the wrapping of the PBO braid with the composite membranes and exposed to UV–vis radiation. The strength loss of the PBO fiber due to exposure was decreased from 75% for the unprotected sample to 7.8% for the protected sample in the PU loaded with 4% TiO2 nanoparticles. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013

Jacquard woven fabrics are made from colored yarns and different weaves for designing complex pictorial and other patterning effects. The final visualized color effect is the result of assigning weave designs to different areas of the pattern to be created. The current practice in creating Jacquard woven fabric designs is to produce many samples in a trial-and-error attempt to match artwork colors. An ability to simulate accurately the appearance of a design prior to manufacture is highly desirable to reduce trial-and-error sample production. No automated accurate digital color methodology is yet available to assist designers in matching the patterned woven fabric to the desired artwork. To achieve this, we developed a geometrical model to predict the color contribution of each yarn on the face of the fabric. The geometrical model combined with a Kubelka-Munk based color mixing model allowed the prediction of the reflectance properties of the final color for a given design. We compared the predicted and experimental values of the reflectance properties for a range of fabrics using the same geometric model with three separate color mixing models. The geometrical model combined with a log-based color mixing model produced reasonable agreement between predicted and measured ΔEab, with an average ΔEab of approximately five. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 225–232, 2009

A geometric model combined with a colour model to predict the colour contribution of each pre-coloured yarn in terms of colour attributes of each area of a Jacquard pattern was developed. To validate the predicted calculations (colorimetric data), a visual assessment experiment was conducted to evaluate the difference between predicted and the actual colour appearance of the woven pattern. The results from the psychophysical evaluation of the woven samples and their predicted colour values showed high correlation between the predicted and experimental data. Therefore, the model has potential to eliminate subjective evaluations and reduce prototype sample production by automating the process of weave/colour simulation.