Abstract:Two biocomposites based on cellulose (UFC) and starch modified urea formaldehyde (UFS) resin (F/U ratio of 0.8) were synthesized using the same procedure. The hydrolitical, thermal, and radiation stability of biocomposites are determined. Also, released formaldehyde during the acid hydrolysis is determined. Biocomposites based on modified UF resin have been irradiated with (50 kGy). Cellulose modified UF resin after γ‐radiation has 1.38% released formaldehyde; unmodified UF resin has 2.21% released formaldehyd… Show more
“…Figure 2 was the infrared spectrum of waterborne acrylic resin microcapsules. The special absorption peaks around 3355 cm −1 , 1560 cm −1 were the absorption peaks of N–H, C–N in urea-formaldehyde resin [ 23 , 24 ]. The 1730 cm −1 represented the characteristic peak of C=O in waterborne acrylic resin [ 25 ].…”
The fluorane thermochromic microcapsules and waterborne acrylic resin microcapsules were added into waterborne coatings at the same time to prepare intelligent waterborne coating film with dual functions of color change and self-repairing. The coating film prepared by adding 15.0% fluorane microcapsules and 5.0% waterborne acrylic resin microcapsules to the primer at the same time had better comprehensive properties. At this time, the coating film changed from yellow to colorless. The repair rate of the coating film was 58.4%. When the temperature was lower than 32 °C, waterborne acrylic resin microcapsules can improve the thermochromic performance of the coating film with fluorane microcapsules. Waterborne acrylic resin microcapsules can alleviate the color change of coating film with fluorane microcapsules. The fluorane microcapsules can improve the self-repairing performance of coating film with waterborne acrylic resin microcapsules. The results lay a theoretical and technical foundation for multifunctional coating film.
“…Figure 2 was the infrared spectrum of waterborne acrylic resin microcapsules. The special absorption peaks around 3355 cm −1 , 1560 cm −1 were the absorption peaks of N–H, C–N in urea-formaldehyde resin [ 23 , 24 ]. The 1730 cm −1 represented the characteristic peak of C=O in waterborne acrylic resin [ 25 ].…”
The fluorane thermochromic microcapsules and waterborne acrylic resin microcapsules were added into waterborne coatings at the same time to prepare intelligent waterborne coating film with dual functions of color change and self-repairing. The coating film prepared by adding 15.0% fluorane microcapsules and 5.0% waterborne acrylic resin microcapsules to the primer at the same time had better comprehensive properties. At this time, the coating film changed from yellow to colorless. The repair rate of the coating film was 58.4%. When the temperature was lower than 32 °C, waterborne acrylic resin microcapsules can improve the thermochromic performance of the coating film with fluorane microcapsules. Waterborne acrylic resin microcapsules can alleviate the color change of coating film with fluorane microcapsules. The fluorane microcapsules can improve the self-repairing performance of coating film with waterborne acrylic resin microcapsules. The results lay a theoretical and technical foundation for multifunctional coating film.
“…To determine the blank, the solution without resin was determined according the same procedure, and the result was taken into account in calculations. The percentage of free FA content was calculated from Equation ) given below:where V is the volume of HCl (cm 3 ), c is the concentration of HCl (mold m −3 ), E is the equivalent weight of FA, and a is the weight of the samples (g) 12 …”
Urea‐formaldehyde resin (F/U ratio of 0.8)/thermally activated montmorillonite (UF/ΔTK10) nanocomposite was synthesized. The hydrolytical, thermal, and UV radiation stability of UF/ΔTK10 nanocomposites are determined. UF hybrid nanocomposites have been irradiated with UV light with a wavelength of 254 nm and 366 nm, and after that, their radiation stability was evaluated. The free formaldehyde (FA) percentage in all prepared samples was determined. The sample was characterized by using X‐ray diffraction analysis (XRD), nonisothermal thermogravimetric analysis (TGA), differential thermal analysis (DTA), and differential thermal gravimetry (DTG), with infrared (FTIR) spectroscopy. Crosslinked UF/ΔTK10 nanocomposite shows the highest resistance to acid hydrolysis after UV irradiation at a wavelength of 254 nm. The values for T5% are identical for the unirradiated and UV irradiated (wavelength of 366 nm) UF/ΔTK10 nanocomposite. It can be concluded that this sample is thermally most stable and shows good resistance to UV irradiation.
“…As a criterion to describe the quality of the chemical bond in wood products, the differential scanning calorimetry (DSC) analysis has proved that the glass-transition temperature decreases due to adding starch to the UF resin because more UF in the adhesive has increased the melting point of the adhesive due to more cross-linkages being created by UF compared to the modified starch [10]. In addition, when applying a stronger treatment of oxidation, instead of the formation of (−CH 2 −O−CH 2 −) ether bridges that are more likely to occur in the more moderate conditions of oxidation treatment, (−CH 2 −) methylene bridges form at high pressure temperature [58] that can increase the bonding strength. However, it seems that it is not unlimited, and the effect of oxidation is that the stronger treatment is reversed due to the destruction of the glycoside bond and opening of hemiacetal loop of starch.…”
The purpose of the present article is to study the bending strength of glulam prepared by plane tree (Platanus Orientalis-L) wood layers adhered by UF resin with different formaldehyde to urea molar ratios containing the modified starch adhesive with different NaOCl concentrations. Artificial neural network (ANN) as a modern tool was used to predict this response, too. The multilayer perceptron (MLP) models were used to predict the modulus of rapture (MOR) and the statistics, including the determination coefficient (R2), root mean square error (RMSE), and mean absolute percentage error (MAPE) were used to validate the prediction. Combining the ANN and the genetic algorithm by using the multiple objective and nonlinear constraint functions, the optimum point was determined based on the experimental and estimated data, respectively. The characterization analysis, performed by FTIR and XRD, was used to describe the effect of the inputs on the output. The results indicated that the statistics obtained show excellent MOR predictions by the feed-forward neural network using Levenberg–Marquardt algorithms. The comparison of the optimal output of the actual values obtained by the genetic algorithm resulting from the multi-objective function and the optimal output of the values estimated by the nonlinear constraint function indicates a minimum difference between both functions.
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