Martinia Ira Glogar

Bio: Martinia Ira Glogar is an academic researcher from University of Zagreb. The author has contributed to research in topics: Dyeing & Medicine. The author has an hindex of 4, co-authored 22 publications receiving 43 citations.

Optimization of Dyeing Process of Cotton Fabric with Cochineal Dye

Abstract: The objective of this research is to optimize the dyeing parameters for cotton fabric with natural dyestuff extracted from Dactylopius coccus. In order to obtain purple hue, the influence of dyeing process conditions i.e. dye bath pH, concentration of dyestuff, and the addition of electrolyte has been studied. Additionally, potassium aluminium sulfate dodecahydrate and iron (II) sulfate heptahydrate were used as mordants on cotton fabrics in order to obtain coloration of specific purple hue. Colorimetric data and fastness properties of the dyed samples have been analyzed. Results indicate that the dyeing parameters as well as pre-treatment has a significant influence on the obtained purple shades and fastness properties.

Trichromatic Vat Dyeing of Cationized Cotton.

Abstract: This article deals with cationization of cotton during mercerization and its effects on trichromatic vat dyeing. If cationization is carried out during the after-treatment, regardless of cotton pretreatment, the reaction takes place on the surface and blocks cellulose groups, subsequently resulting in uneven coloration. However, when cationization is carried out with an epihalohydrin during the mercerization process, new cellulose is formed in which the cationic compound is uniformly distributed and trapped between cellulose chains, resulting in uniform coloration after the dyeing process. The reaction time for the process during mercerization is 24 h, thus a more favorable process was researched. Based on electrokinetic analysis, it was found that 5 h was sufficient for the reaction with 3-chloro-2-hydroxypropyltrimethyl ammonium chloride (CHPTAC). The cationization of cotton contributed to the processes of vat dyeing. The change in charge upon cationization resulted in very high adsorption of vat-dye anions, indicating that ionic bonding occurred in addition to van der Waals forces. The color depth improved by more than 10 times. It should be emphasized that the colors with higher chroma and targeted color hue, especially in trichromatic dyeing, were obtained on cationized cotton, in contrast to standard cotton fabrics. The color differences obtained under the different light sources indicate the occurrence of metamerism. Considering the color fastness to laundering, vat-dyed cationized fabrics of all colors may be used in hospitals or other environments where high hygiene and oxidative bleaching are required.

Application of biomimicry in textiles

Abstract: Nature has created excellent technologies around us, and as such, it is the chief mentor to humans on creativity and technology development. Nature uses fibre as a building block - natural structures like wood, bamboo, bone, muscle, etc. all have fibrous structure. Fibre spinning and weaving technologies are available in nature since time immemorial. Nature has also demonstrated sophisticated technologies useful in the development of technical textiles like functional surfaces, camouflage, structural colour, thermal insulation, dry-adhesion, etc. Thus, biomimicry can be an inspiration to develop innovative textiles. This article reviews some of the important technologies of nature relating to textiles.

Antimicrobial textile: recent developments and functional perspective.

Abstract: Antimicrobial textiles are functionally active textiles, which may kill the microorganisms or inhibit their growth. The present article explores the applications of different synthetic and natural antimicrobial compounds used to prepare antimicrobial textiles. Different types of antimicrobial textiles including: antibacterial, antifungal and antiviral have also been discussed. Different strategies and methods used for the detection of a textile's antimicrobial properties against bacterial and fungal pathogens as well as viral particles have also been highlighted. These antimicrobial textiles are used in a variety of applications ranging from households to commercial including air filters, food packaging, health care, hygiene, medical, sportswear, storage, ventilation and water purification systems. Public awareness on antimicrobial textiles and growth in commercial opportunities has been observed during past few years. Not only antimicrobial properties, but its durability along with the color, prints and designing are also important for fashionable clothing; thus, many commercial brands are now focusing on such type of materials. Overall, this article summarizes the scientific aspect dealing with different fabrics including natural or synthetic antimicrobial agents along with their current functional perspective and future opportunities.

Color matching of fabric blends: hybrid Kubelka-Munk + artificial neural network based method

Abstract: Color matching of fabric blends is a key issue for the textile industry, mainly due to the rising need to create high-quality products for the fashion market. The process of mixing together differently colored fibers to match a desired color is usually performed by using some historical recipes, skillfully managed by company colorists. More often than desired, the first attempt in creating a blend is not satisfactory, thus requiring the experts to spend efforts in changing the recipe with a trial-and-error process. To confront this issue, a number of computer-based methods have been proposed in the last decades, roughly classified into theoretical and artificial neural network (ANN)–based approaches. Inspired by the above literature, the present paper provides a method for accurate estimation of spectrophotometric response of a textile blend composed of differently colored fibers made of different materials. In particular, the performance of the Kubelka-Munk (K-M) theory is enhanced by introducing an artificial intelligence approach to determine a more consistent value of the nonlinear function relationship between the blend and its components. Therefore, a hybrid K-M+ANN-based method capable of modeling the color mixing mechanism is devised to predict the reflectance values of a blend.