فصلنامه علوم و فناوری نساجی
سال دوم شماره 2 (تابستان 1391)

Some coated nanocomposites containing ZnO and TiO2 nanoparticles were prepared and the antibacterial activity of nanocomposites was evaluated against Escherichia coli and Staphylococcus aurous Nanocomposites were coated by polyamide coating solution. Nano ZnO and nano TiO2 were dispersed using a fixed power sonicator. Polypropylene surface was modified by a corona discharge method. To study the antibacterial effect of the prepared nanocomposites، a film contact method was performed and antibacterial property of the nanocomposites was estimated by dilution method. Coated nanocomposites exhibited excellent antibacterial activity in each of three antibacterial tests.

For many engineering applications، the ability to absorb energy is of highest priority in selection of materials and designing structures، especially structures that go under the impact forces during their application. Body of the vehicles should display high performance to protect passengers against impacts and collisions. This matter، has found double importance with increasing speed and number of vehicles. Auxiliary equipments، such as protective safety helmet، also need to have high energy absorption capacity. Honey combs، sponges، and corals are examples found in nature. Cellular textile composites due to several advantages such as low weight، high strength and energy absorption are frequently used. In this paper، energy absorption capability of PVC-foam reinforced by 3D weft-knitted fabrics has been examined. The energy absorption of 3D weft-knitted fabric composites was investigated based on their tensile and compression properties. From the test results it was found that the foam filled composite egg-box panels showed good energy absorption capacity with smooth stress–strain curves which resembles the ideal energy absorber.

Studies were conducted on durable and rechargeable antibacterial properties of spacer knitted fabrics. To achieve a durable and rechargeable antibacterial properties، spacer fabrics made of cotton، polyester-cotton (65-35) and polyester-viscose (25-75) were treated with dimethylol dimethyl hydantoin (DMDMH)، followed by chlorine bleaching. The methylol groups on DMDMH can either form cross-links with cellulose with both functional sites reacted or grafted onto cellulose with only one reactive site consumed. In each test، cotton، polyester cotton، polyester viscose spacer was separately exposed to treatment baths in two stages. Different concentrations of DMDMH in primary and chlorine in secondary finishing bath، pH، temperature، in both baths were optimized. The biocidal efficacy of such spacer fabrics is high against Staphylococcus aurous، a gram-positive bacterium and Escherichia coli، a gram-negative bacterial according to AATCC test method 100-1993. The findings show that the washing fastness of antibacterial finishing is acceptable and the biocidal effect persists through at least 50 machine washing cycles and can be regenerated by exposure to diluted chlorine solutions. A comparison between the FTIR tests after and before antibacterial finishing shows the covalent bonds between dimethylol dimethyl hydantoin (DMDMH) and spacer fabrics.

Activator is a device that converts a chemical or electrical stimulus to a mechanical movement (response). Polymer gels are the best choice to simulate the behavior and characteristics of natural actuators. This paper reviews the different routes of stimulating polymer gels and the advantages and disadvantages of polymer gel for application as artificial muscles. Due to their low responsetime، large expansion، good mechanical properties and availability، chemically activated polyacrylonitrile fibers are advantageous over other gel-fibers for applications concerning actuators or artificial muscles. Therefore، the behavior of polyacrylonitrile fibers under chemical stimulation is investigated in this work. Moreover، possible applications are discussed.

Extracting appropriate information from infinite number of data requires modern methods. Data mining is one of these tools and approaches that may help in the area of knowledge management in knowledge discovery from the databases. Self-organizing neural network is undoubtedly the most powerful neural networks for data mining. This paper presents a size chart that has been developed based on measurements taken from 2000 women of Yazd. The important input variables have been defined as the chest، waist and hip measurements. In this study، the different size clusters have been investigated through self-organizing neural network model. The results of using the self-organizing neural network indicate that there are four effective size groups that are categorized based on the lowest mean error.

Achieving optimal improvements in mechanical properties of blend fibers is the ultimate goals of polymers blending. To obtain the best properties، optimization of polymer blend ratio takes a long time with high cost due to variation of polymeric constituents in blend fibers. In this study، an experimental design is introduced using response surface methodology (RSM). The fractions of matrix، dispersing agents and compatibilizers were selected as input parameters and mechanical properties included elongation-at-break، tenacity، initial modulus، specific work of rupture of blend fibers and their uniformities which were selected as output response. The blend fiber samples were produced in melt spinning process using a screw equipped with Maddock fluted mixing zone. The optimized blend ratio، based on the most desired mechanical properties، and prediction models were obtained by response results of RSM method. The best blend ratio was obtained as 64. 8/31. 7/3. 5 relative to matrix، dispersing agents and compatibilizers of the blend fiber samples، respectively. Furthermore، the results showed good agreements between experimental and model predictions with high correlation coefficients.

Nowadays، fabrics produced from admixture of different yarns are used for industrial purposes such as composite materials. Since the tensile properties of these fabrics are important، in this research a mechanical model based on Leaf and Kandil model for hybrid plain-woven fabrics is proposed. In this model، the initial load-extension behavior of hybrid fabrics is calculated from the yarn mechanical properties and fabric structure by energy method. In order to evaluate the modeling predictions، the values of experimentally obtained mechanical properties of simple and hybrid fabrics with different admixtures of basalt and nylon، are compared with the theoretical model results. Comparing the results shows that there is a good correlation between the proposed model prediction and experimental results. In addition، comparing the results of simple and hybrid fabrics indicate that difference between theoretical and experimental results is due to other sources of errors and not necessarily due to the proposed model.