نشریه علوم و فناوری رنگ
سال شانزدهم شماره 3 (پیاپی 61، پاییز 1401)

Biodegradable polymers are not considered an environmental hazard to the health of living organisms. This research used a nanocomposite adsorbent based on natural (biodegradable) polymer materials. This nanocomposite was made from natural chitin and alginate monomers with graphene oxide, silicon oxide nanoparticles, and strontium metal nanoparticles under reflux and ultrasonic. FTIR, XRD, SEM, TEM, EDX, Zeta potential, and TGA analyses were performed to identify and characterize the synthesized materials. Methylene blue dye was used as a contaminant to remove from the aqueous media. The removal ability of the synthesized adsorbent from aqueous media was studied using methylene blue as an organic pollutant. The maximum removal percentage of methylene blue by the synthesized adsorbent was 98.5 %. The results indicated that the synthesized nanocomposite is an acceptable adsorbent for removing methylene blue dye from aqueous media.</em>

Due to the importance of the color role in communication, production, and trade in the contemporary world, identifying individuals' color preferences and the affective factors are very important to increase the ability of forecasters and planners in this field. This study aims to investigate the relationship between sensation seeking and color preference by the role of gender as moderating variable. Zuckerman sensation seeking (1994) and color preference questionnaire was used to collect research data. The statistical sample includes 402 who were randomly and accessibly selected. The two-way analysis of variance in each color showed that women and men with different levels of sensation seeking concerning blue and pink have different color preferences. Also, the results of multivariate analysis of variance concerning the preference of cool, warm, and neutral colors showed that women and men with different levels of sensation seeking with warm and cool colors have different color preferences. The results of the present study confirmed the need to pay attention to the gender variable and the level of sensation seeking in predicting the color preference pattern of individuals.

In this study, the combined treatment method of coagulation with natural coagulant and catalytic ozonation was used to remove Acid Blue 113 dye from the dye solution. In the first stage, the mucilage extracted from the Balangu (Lallemantia royleana) plant seeds was used to pre-treat the dye-containing solution. In the second stage, catalytic ozonation with Fe3</sub>O4</sub>/MnO2</sub> nanocatalyst was used to completely remove the dye. Response surface methodology with Box-Benken design was used to analyze and optimize the parameters of both processes. Maximum dye removal by the coagulation-flocculation process was 56%, which was obtained in the optimal conditions of pH 5.2, 20 min, and a coagulant amount of 100 ppm. In the catalytic ozonation process at pH 3.5, 18 mg of the nanocomposite, 0.2 g.L-1</sup>.h-1</sup> of ozone, and 12 min, almost complete removal of dye was achieved. The results indicate that the combined treatment method performs excellent dye removal and can also be used to remove other organic pollutants from industrial effluents.

This work has fabricated a nanohybrid catalyst containing H3PW6Mo6O40 heteropolyacid supported on graphitic carbon nitride (PW6Mo6/g-C3N4) via a facile approach. It was developed as a highly active and stable photocatalyst for cationic Rhodamine B dye degradation under visible light irradiation. Graphitic carbon nitride (g-C3N4) is an emerging metal-free catalyst and has attracted considerate research interests in photocatalysis. Compared to pristine g-C3N4 and pristine H3PW6Mo6O40, POMs modified sample (PW6Mo6/g-C3N4) demonstrated enhanced efficiencies in the photodegradation of rhodamine B dye under visible light irradiation. Also, PW6Mo6/g-C3N4 displays higher photocatalytic activity under visible light irradiation for the photodegradation of this dye compared with PW12/g-C3N4 and PMo12/g-C3N4. The influence of reaction parameters such as time, the dependence of degradation on the presence of the catalyst and light irradiation, pH, and the photocatalyst's reusability on the degradation yield have been investigated. The catalyst showed high photocatalytic activity for the degradation of cationic Rhodamine B solution at a concentration of 20 ppm in pH=3 under visible light irradiation.

In this research, cadmium titanate nanoparticles (CdTiO3</sub>) were first synthesized by a fast and simple hydrothermal method. The phase separation method was used to fabricate mixed matrix polyethersulfone ultrafiltration membranes. It contained different concentrations of CdTiO3</sub>. Structural studies through SEM and AFM analysis showed that the modified membranes have differences in morphology, porosity, and surface properties compared to the unmodified membrane due to the addition of CdTiO3 </sub>nanoparticles. Mixed matrix membranes showed higher surface hydrophilicity, water flux, and lower fouling than unmodified PES membranes. In the presence of 0.1 wt. % CdTiO3</sub>, the water flux reached a maximum of 306 L/m2</sup>.h when it was 204 L/m2</sup>.h in the unmodified membrane. The filtration results of colored wastewater showed that the optimized membrane could separate more than 90 % of Reactive yellow 105 and Reactive blue 21 dyes and 80 % of Reactive red 195 dye.

A condition that must be satisfied for digital printers in a color management system is converting device-dependent color values into device-independent color values by a transfer model of high-quality performance. Usually, each transfer model is initially trained with some specified samples as a training set before being tested. In the present study, color charts with different quantities of color patches in an RGB space were selected and printed as training groups.  The spectral reflectances of all samples in printed color charts were measured and converted to an XYZ color space under a standard observer/illuminant combination. Using a matrix method, the RGB to XYZ transformation matrices were obtained with the algebraic operation of different degrees of polynomials and the least-square errors for the training groups.Similar operations were also performed for the well-known ProfileMaker software, which is based on a look-up table method. Finally, the statistical values of color difference (DE2000) were calculated between the actual XYZ from the printed color charts, the predicted XYZ from the matrix method, and those predicted from the ProfileMaker software. The ProfileMaker software showed a significantly lower color difference near the perception threshold for the specified training samples.

In this project, the potential capability of intelligent machine learning methods such as LS-SVM, RBFNN, MLPNN, and ANFIS was investigated for estimating the efficiency of azo dyes removal from wastewater. To this aim, a huge data bank of azo dyes adsorption by metal-organic frameworks as porous adsorbents were collected under different conditions, including adsorbent dosage, initial dye concentration, solution pH, specific surface area, temperature, and contact time. Assessing different statistical parameters and comparing the models showed that LS-SVM approach had the minimum error and, therefore, it conferred the most accurate prediction for the efficiency of azo dyes removal by MOFs among other models. The values of AARE (%), R2</sup>, STD, and RMSE were calculated 1.844 %, 0.9899, 0.0213, and 18.511, respectively for LS-SVM. Also, this model illustrated precise compatibility with adsorption trends by variation of initial dye concentration, pH, and temperature. The sensitivity analysis presented that adsorbent surface area and adsorbent dosage had a positive impact and initial concentration and pH negatively influenced estimating the removal of dyes.</em>