Taguchi and ANOVA analysis for the optimization of the microencapsulation of a volatile phase change material

The microencapsulation of volatile phase change materials is an important and challenging area for low-temperature thermal energy storage. Our previous studies have effectively addressed the challenge of long-term volatile core retention and also indicated that the quality of the obtained poly(urea-formaldehyde) microcapsules is highly affected by various process parameters, including reaction temperature, initial pH, reaction time, and homogenization speed. In this paper, the Taguchi orthogonal array has been employed to optimise controllable process parameters to identify the most synergistic combination, in order to maximise the payload, yield, and encapsulation efficiency. The Taguchi signal-to-noise ratio results substantiated that the most efficient combination of parameters was 3 h reaction time, pH 3.5, 55 °C reaction temperature, and 1200 rpm homogenization speed. With this combination of parameters, microcapsules with superbly high payload of 95.2%, as well as a yield of 30.5% and encapsulation efficiency of 71.1% were amalgamated. In addition, Analysis of Variance (ANOVA) was also utilised to demonstrate the mean response magnitudes (% contribution) of each of the four controllable process parameters, in terms of contribution for the payload, yield, and encapsulation efficiency. Overall, it was indicated that the temperature is the most influential parameter at 83.1% contribution, followed by pH at 6.8%, reaction time at 5.2%, and homogenization speed at 4.9%. Such findings in this work postulate the fundamental insights into maximising the output of the formulation conditions, which in turn is aimed to minimise the time and cost of production of the microcapsules

Synthesis and enhanced visible-light activity of N-doped TiO2 nano-additives applied over cotton textiles

To provide photocatalytic textiles, application of TiO2 nanoparticles by surface modifications during the manufacturing process is known as a reliable choice. In this study, nitrogen-doped TiO2 nanoparticles were synthesized by sol–gel route at two different water/triethylamine ratios and applied to the textiles which provides photocatalytic properties that unlike the conventional photocatalytic textiles, does not necessarily need UV radiations of high energy photons. N-doped TiO2 nanoparticles were coated over textiles during the synthesizing process. Microstructure and morphology of synthesized N-doped TiO2 nanoparticles were evaluated by XRD, PSA and SEM/EDS analysis. The results of XRD analysis indicated that the amorphous phase transformed slightly into an anatase crystallite without calcination at high temperature. The morphology confirmed that doping process had significant effect on the appearance of the synthesized nanoparticles and implied the effect of the presence of the N-doped source material on the morphology. The PSA analysis showed narrow distribution of about 15 nm for diameter of synthesized N-doped TiO2 nanoparticles. According to UV–vis spectra, the band gap energy was measured 2.98 eV which exhibits high absorption in visible light range due to its low band gap energy. The results show that adding nitrogen increases the absorption wavelength of the N-doped TiO2 nanoparticles and N-doped TiO2 coated textiles shows super hydrophilic behavior examined by DSA analysis. The photodegradation of methylene blue (MB) over textiles was investigated under UV-radiation, visible light and dark conditions. Super-hydrophilicity and methylene blue photodegradation properties with the most homogenous nanoparticle distribution over textiles were achieved without utilization of UV radiation. Keywords: Sol–gel method, N-doped TiO2, Visible-light, Cotton textile

Investigating the effect of synthesis conditions on the formation of urea–formaldehyde microcapsules

In the current study, a set of urea–formaldehyde microcapsules (UFMs) were synthesized at different conditions via the in situ polymerization method. Encapsulation ability of the UFMs was studied by altering the synthesis parameters, such as formaldehyde to urea molar ratio (0.94, 1.88, 2.81), time (1, 4, 7 h), temperature (25, 55, 85 °C) and pH (3, 7, 11). The capsules were characterized by optical and electron microscopy (OM, SEM and TEM), particle size analysis (PSA), Fourier transform infrared spectroscopy (FTIR) and thermogravimetric/differential thermal analysis (TG/DTA). According to the results, for successful formation of UFMs, the pH value of the synthesis solution must be below 7 and the F/U molar ratio value must exceed 0.94. Effects of temperature and the pH value of the prepared solution were interdependent. To conclude, the results led to determination of the optimum UFM synthesis condition which presented the most effective formation of UFMs. The higher F/U molar ratio as well as higher curing temperatures in UFM-9, increased the UFMs degradation temperature. In order to further investigate the results, the synthesis of the optimized UFM (UFM-Opt.) was conducted, presenting the most effective development of UFMs. Keywords: In situ polymerization, Synthesis condition, Urea–formaldehyde, Microcapsule

Risk identification and prioritization in banking projects of payment service provider companies: an empirical study

Identifying risks and prioritizing is important for payment service provider (PSP) companies to get banking projects and gain more market share. However, studies regarding the identification of risks and causal relationships are insufficient in the Iranian PSP industry and the industry is unique because of its characteristics. In this study, 30 experts involved with PSP companies are employed as the research sample. Eleven key risks and Forty-six sub-risks are also identified. Subsequently, the fuzzy decision-making trial and evaluation laboratory technique is applied to determine the effective and affected risks and the severity of their effects on each other. Finally, all risks are ranked. Due to the internal interrelationships of the main risks, the weight of each risk is calculated via the fuzzy analytic network process. As the second-level risks have no significant interrelationships, they are ranked via the fuzzy analytical hierarchy process. Moreover, the best-worst method is used to ensure that the obtained rankings are reliable. This study identifies the risks affecting the loss of banking projects and determines the impacts of these risks on each. A sensitivity analysis is then conducted on the weights of the criteria, and the results are compared.This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/