Photothermal Effect of Modulating Laser Irradiation on the Thermal Diffusivity of Al2O3 Nanofluids.

Modulated continuous wave (CW) lasers cause photothermal effect that leads to rapid optical absorption and generation of thermal waves around the irradiated nanostructures. In this work, we examined the effect of modulated CW laser irradiation on the particle fragmentation process to enhance the thermal diffusivity of nanofluids. A facile and cost-effective diode laser was applied to reduce the agglomerated size of Al2O3 nanoparticles in deionized water. The thermal wave generation, which was determined by the modulated frequency of the laser beam and the optical and thermal properties of the nanofluid, is also briefly discussed and summarized. The influence of laser irradiation time on nanoparticle sizes and their size distribution was determined by dynamic light scattering and transmission electron microscopy. The thermal diffusivity of the nanofluid was measured using the photopyroelectric method. The data obtained showed that the modulated laser irradiation caused the partial fragmentation of some agglomerated particles in the colloids, with an average diameter close to the original particle size, as indicated by a narrow distribution size. The reduction in the agglomerated size of the particles also resulted in an enhancement of the thermal diffusivity values, from 1.444 × 10-3 to 1.498 × 10-3 cm2/s in 0 to 30 min of irradiation time. This work brings new possibilities and insight into the fragmentation of agglomerated nanomaterials based on the photothermal study.

Influence of pH Adjustment Parameter for Sol-Gel Modification on Structural, Microstructure, and Magnetic Properties of Nanocrystalline Strontium Ferrite.

Synthesis of nanocrystalline strontium ferrite (SrFe12O19) via sol-gel is sensitive to its modification parameters. Therefore, in this study, an attempt of regulating the pH as a sol-gel modification parameter during preparation of SrFe12O19 nanoparticles sintered at a low sintering temperature of 900 °C has been presented. The relationship of varying pH (pH 0 to 8) on structural, microstructures, and magnetic behaviors of SrFe12O19 nanoparticles were characterized by X-ray diffraction (XRD), field emission scanning microscope (FESEM), and vibrating sample magnetometer (VSM). Varying the pH of precursor exhibited a strong effect on the sintered density, crystal structure and magnetic properties of the SrFe12O19 nanoparticles. As the pH is 0, the SrFe12O19 produced relatively largest density, saturation magnetization, Ms, and coercivity, Hc, at a low sintering temperature of 900 °C. The grain size of SrFe12O19 is obtained in the range of 73.6 to 133.3 nm. The porosity of the sample affected the density and the magnetic properties of the SrFe12O19 ferrite. It is suggested that the low-temperature sintered SrFe12O19 at pH 0 displayed Ms of 44.19 emu/g and Hc of 6403.6 Oe, possessing a significant potential for applying in low-temperature co-fired ceramic permanent magnet.

Thermal Wavelength Measurement of Nanofluid in an Optical-Fiber Thermal Wave Cavity Technique to Determine the Thermal Diffusivity.

The application of optical-fiber thermal wave cavity (OF-TWC) technique was investigated to measure the thermal diffusivity of Ag nanofluids. The thermal diffusivity was obtained by measuring the thermal wavelength of sample in a cavity scan mode. The spherical Ag nanoparticles samples were prepared at various sizes using the microwave method. Applying the thermal wavelength measurement in a flexible OF-TWC technique requires only two experimental data sets. It can be used to estimate thermal diffusivity of a small amount of liquid samples (0.3 ml) in a brief period. UV-Vis spectroscopy and transmission electron microscopy were used to measure the characterization of the Ag nanoparticles. The thermal diffusivity of distilled water, glycerol, and two different types of cooking oil was measured and has an excellent agreement with the reported results in the literature (difference of only 0.3%-2.4%). The nanofluids showed that the highest value of thermal diffusivity was achieved for smaller sized nanoparticles. The results of this method confirmed that the thermal wavelength measurement method using the OF-TWC technique had potential as a tool to measure the thermal diffusivity of nanofluids with different variables such as the size, shape, and concentration of the nanoparticles.

Environmental Synthesis of Few Layers Graphene Sheets Using Ultrasonic Exfoliation with Enhanced Electrical and Thermal Properties.

In this paper, we report how few layers graphene that can be produced in large quantity with low defect ratio from exfoliation of graphite by using a high intensity probe sonication in water containing liquid hand soap and PVP. It was founded that the graphene powder obtained by this simple exfoliation method after the heat treatment had an excellent exfoliation into a single or layered graphene sheets. The UV-visible spectroscopy, FESEM, TEM, X-ray powder diffraction and Raman spectroscopy was used to analyse the graphene product. The thermal diffusivity of the samples was analysed using a highly accurate thermal-wave cavity photothermal technique. The data obtained showed excellent enhancement in the thermal diffusivity of the graphene dispersion. This well-dispersed graphene was then used to fabricate an electrically conductive polymer-graphene film composite. The results demonstrated that this low cost and environmental friendly technique allowed to the production of high quality layered graphene sheets, improved the thermal and electrical properties. This may find use in the wide range of applications based on graphene.

Scheduling the blended solution as industrial CO2 absorber in separation process by back-propagation artificial neural networks.

It is believe that 80% industrial of carbon dioxide can be controlled by separation and storage technologies which use the blended ionic liquids absorber. Among the blended absorbers, the mixture of water, N-methyldiethanolamine (MDEA) and guanidinium trifluoromethane sulfonate (gua) has presented the superior stripping qualities. However, the blended solution has illustrated high viscosity that affects the cost of separation process. In this work, the blended fabrication was scheduled with is the process arranging, controlling and optimizing. Therefore, the blend's components and operating temperature were modeled and optimized as input effective variables to minimize its viscosity as the final output by using back-propagation artificial neural network (ANN). The modeling was carried out by four mathematical algorithms with individual experimental design to obtain the optimum topology using root mean squared error (RMSE), R-squared (R(2)) and absolute average deviation (AAD). As a result, the final model (QP-4-8-1) with minimum RMSE and AAD as well as the highest R(2) was selected to navigate the fabrication of the blended solution. Therefore, the model was applied to obtain the optimum initial level of the input variables which were included temperature 303-323 K, x[gua], 0-0.033, x[MDAE], 0.3-0.4, and x[H2O], 0.7-1.0. Moreover, the model has obtained the relative importance ordered of the variables which included x[gua]>temperature>x[MDEA]>x[H2O]. Therefore, none of the variables was negligible in the fabrication. Furthermore, the model predicted the optimum points of the variables to minimize the viscosity which was validated by further experiments. The validated results confirmed the model schedulability. Accordingly, ANN succeeds to model the initial components of the blended solutions as absorber of CO2 capture in separation technologies that is able to industries scale up.

The structural and optical constants of Ag2S semiconductor nanostructure in the Far-Infrared.

BACKGROUND: In this paper a template-free precipitation method was used as an easy and low cost way to synthesize Ag2S semiconductor nanoparticles. The Kramers-Kronig method (K-K) and classical dispersion theory was applied to calculate the optical constants of the prepared samples, such as the reflective index n(ω) and dielectric constant ε(ω) in Far-infrared regime. RESULTS: Nanocrystalline Ag2S was synthesized by a wet chemical precipitation method. Ag2S nanoparticle was characterized by X-ray diffraction, Scanning Electron Microscopy, UV-visible, and FT-IR spectrometry. The refinement of the monoclinic ß-Ag2S phase yielded a structure solution similar to the structure reported by Sadanaga and Sueno. The band gap of Ag2S nanoparticles is around 0.96 eV, which is in good agreement with previous reports for the band gap energy of Ag2S nanoparticles (0.9-1.1 eV). CONCLUSION: The crystallite size of the synthesized particles was obtained by Hall-Williamson plot for the synthesized Ag2S nanoparticles and it was found to be 217 nm. The Far-infrared optical constants of the prepared Ag2S semiconductor nanoparticles were evaluated by means of FTIR transmittance spectra data and K-K method. Graphical abstractThe Far-infrared optical constants of Ag2S semiconductor nanoparticles.

Dielectrical Properties of CeO2 Nanoparticles at Different Temperatures.

A template-free precipitation method was used as a simple and low cost method for preparation of CeO2 nanoparticles. The structure and morphology of the prepared nanoparticle samples were studied in detail using X-ray diffraction, Raman spectroscopy and Scanning Electron Microscopy (SEM) measurements. The whole powder pattern modelling (WPPM) method was applied on XRD data to accurately measure the crystalline domain size and their size distribution. The average crystalline domain diameter was found to be 5.2 nm, with a very narrow size distribution. UV-visible absorbance spectrum was used to calculate the optical energy band gap of the prepared CeO2 nanoparticles. The FT-IR spectrum of prepared CeO2 nanoparticles showed absorption bands at 400 cm(-1) to 450 cm(-1) regime, which correspond to CeO2 stretching vibration. The dielectric constant (εr) and dielectric loss (tan δ) values of sintered CeO2 compact consolidated from prepared nanoparticles were measured at different temperatures in the range from 298 K (room temperature) to 623 K, and at different frequencies from 1 kHz to 1 MHz.

Novel conductive polypyrrole/zinc oxide/chitosan bionanocomposite: synthesis, characterization, antioxidant, and antibacterial activities.

An antibacterial and conductive bionanocomposite (BNC) film consisting of polypyrrole (Ppy), zinc oxide (ZnO) nanoparticles (NPs), and chitosan (CS) was electrochemically synthesized on indium tin oxide (ITO) glass substrate by electrooxidation of 0.1 M pyrrole in aqueous solution containing appropriate amounts of ZnO NPs uniformly dispersed in CS. This method enables the room temperature electrosynthesis of BNC film consisting of ZnO NPs incorporated within the growing Ppy/CS composite. The morphology of Ppy/ZnO/CS BNC was characterized by scanning electron microscopy. ITO-Ppy/CS and ITO-Ppy/ZnO/CS bioelectrodes were characterized using the Fourier transform infrared technique, X-ray diffraction, and thermogravimetric analysis. The electrical conductivity of nanocomposites was investigated by a four-probe method. The prepared nanocomposites were analyzed for antioxidant activity using the 2,2-diphenyl-1-picrylhydrazyl assay. The results demonstrated that the antioxidant activity of nanocomposites increased remarkably by addition of ZnO NPs. The electrical conductivity of films showed a sudden decrease for lower weight ratios of ZnO NPs (5 wt%), while it was increased gradually for higher ratios (10, 15, and 20 wt%). The nanocomposites were analyzed for antibacterial activity against Gram-positive and Gram-negative bacteria. The results indicated that the synthesized BNC is effective against all of the studied bacteria, and its effectiveness is higher for Pseudomonas aeruginosa. The thermal stability and physical properties of BNC films were increased by an increase in the weight ratio of ZnO NPs, promising novel applications for the electrically conductive polysaccharide-based nanocomposites, particularly those that may exploit the antimicrobial nature of Ppy/ZnO/CS BNCs.

Fabrication, characterization, and thermal property evaluation of silver nanofluids.

Silver nanoparticles were successfully prepared in two different solvents using a microwave heating technique, with various irradiation times. The silver nanoparticles were dispersed in polar liquids (distilled water and ethylene glycol) without any other reducing agent, in the presence of the stabilizer polyvinylpyrrolidone (PVP). The optical properties, thermal properties, and morphology of the synthesized silver particles were characterized using ultraviolet-visible spectroscopy, photopyroelectric technique, and transmission electron microscopy. It was found that for the both solvents, the effect of microwave irradiation was mainly on the particles distribution, rather than the size, which enabled to make stable and homogeneous silver nanofluids. The individual spherical nanostructure of self-assembled nanoparticles has been formed during microwave irradiation. Ethylene glycol solution, due to its special properties, such as high dielectric loss, high molecular weight, and high boiling point, can serve as a good solvent for microwave heating and is found to be a more suitable medium than the distilled water. A photopyroelectric technique was carried out to measure thermal diffusivity of the samples. The precision and accuracy of this technique was established by comparing the measured thermal diffusivity of the distilled water and ethylene glycol with values reported in the literature. The thermal diffusivity ratio of the silver nanofluids increased up to 1.15 and 1.25 for distilled water and ethylene glycol, respectively.

Artificial neural network modelling of photodegradation in suspension of manganese doped zinc oxide nanoparticles under visible-light irradiation.

The artificial neural network (ANN) modeling of m-cresol photodegradation was carried out for determination of the optimum and importance values of the effective variables to achieve the maximum efficiency. The photodegradation was carried out in the suspension of synthesized manganese doped ZnO nanoparticles under visible-light irradiation. The input considered effective variables of the photodegradation were irradiation time, pH, photocatalyst amount, and concentration of m-cresol while the efficiency was the only response as output. The performed experiments were designed into three data sets such as training, testing, and validation that were randomly splitted by the software's option. To obtain the optimum topologies, ANN was trained by quick propagation (QP), Incremental Back Propagation (IBP), Batch Back Propagation (BBP), and Levenberg-Marquardt (LM) algorithms for testing data set. The topologies were determined by the indicator of minimized root mean squared error (RMSE) for each algorithm. According to the indicator, the QP-4-8-1, IBP-4-15-1, BBP-4-6-1, and LM-4-10-1 were selected as the optimized topologies. Among the topologies, QP-4-8-1 has presented the minimum RMSE and absolute average deviation as well as maximum R-squared. Therefore, QP-4-8-1 was selected as final model for validation test and navigation of the process. The model was used for determination of the optimum values of the effective variables by a few three-dimensional plots. The optimum points of the variables were confirmed by further validated experiments. Moreover, the model predicted the relative importance of the variables which showed none of them was neglectable in this work.

Optimization of Bi2O3, TiO2, and Sb2O3 doped ZnO-based low-voltage varistor ceramic to maximize nonlinear electrical properties.

In ZnO-based low voltage varistor, the two essential features of microstructure determining its nonlinear response are the formation Bi-enriched active grain boundaries as well as a controlled ZnO grain size by secondary spinel-type phases. Besides, the microstructure and phase composition are strongly affected by the dopant concentration during sintering process. In this study, the optimal dopant levels of Bi2O3, TiO2, and Sb2O3 to achieve maximized nonlinear electrical property (alpha) were quantified by the response surface methodology (RSM). RSM was also used to understand the significance and interaction of the factors affecting the response. Variables were determined as the molar ratio of Bi2O3, TiO2, and Sb2O3. The alpha was chosen as response in the study. The 5-level-3-factor central composite design, with 20 runs, was used to conduct the experiments by ball milling method. A quadratic model was established as a functional relationship between three independent variables and alpha. According to the results, the optimum values of Bi2O3, TiO2, and Sb2O3 were obtained 0.52, 0.50, and 0.30, respectively. Under optimal conditions the predicted alpha (9.47) was calculated using optimal coded values from the model and the theoretical value is in good agreement with the value (9.43) obtained by confirmation experiment.

Simultaneous optimization of nanocrystalline SnO2 thin film deposition using multiple linear regressions.

A nanocrystalline SnO2 thin film was synthesized by a chemical bath method. The parameters affecting the energy band gap and surface morphology of the deposited SnO2 thin film were optimized using a semi-empirical method. Four parameters, including deposition time, pH, bath temperature and tin chloride (SnCl2·2H2O) concentration were optimized by a factorial method. The factorial used a Taguchi OA (TOA) design method to estimate certain interactions and obtain the actual responses. Statistical evidences in analysis of variance including high F-value (4,112.2 and 20.27), very low P-value (<0.012 and 0.0478), non-significant lack of fit, the determination coefficient (R2 equal to 0.978 and 0.977) and the adequate precision (170.96 and 12.57) validated the suggested model. The optima of the suggested model were verified in the laboratory and results were quite close to the predicted values, indicating that the model successfully simulated the optimum conditions of SnO2 thin film synthesis.

Optimizing Bi2O3 and TiO2 to achieve the maximum non-linear electrical property of ZnO low voltage varistor.

BACKGROUND: In fabrication of ZnO-based low voltage varistor, Bi2O3 and TiO2 have been used as former and grain growth enhancer factors respectively. Therefore, the molar ratio of the factors is quit important in the fabrication. In this paper, modeling and optimization of Bi2O3 and TiO2 was carried out by response surface methodology to achieve maximized electrical properties. The fabrication was planned by central composite design using two variables and one response. To obtain actual responses, the design was performed in laboratory by the conventional methods of ceramics fabrication. The actual responses were fitted into a valid second order algebraic polynomial equation. Then the quadratic model was suggested by response surface methodology. The model was validated by analysis of variance which provided several evidences such as high F-value (153.6), very low P-value (<0.0001), adjusted R-squared (0.985) and predicted R-squared (0.947). Moreover, the lack of fit was not significant which means the model was significant. RESULTS: The model tracked the optimum of the additives in the design by using three dimension surface plots. In the optimum condition, the molars ratio of Bi2O3 and TiO2 were obtained in a surface area around 1.25 point that maximized the nonlinear coefficient around 20 point. Moreover, the model predicted the optimum amount of the additives in desirable condition. In this case, the condition included minimum standard error (0.35) and maximum nonlinearity (20.03), while molar ratio of Bi2O3 (1.24 mol%) and TiO2 (1.27 mol%) was in range. The condition as a solution was tested by further experiments for confirmation. As the experimental results showed, the obtained value of the non-linearity, 21.6, was quite close to the predicted model. CONCLUSION: Response surface methodology has been successful for modeling and optimizing the additives such as Bi2O3 and TiO2 of ZnO-based low voltage varistor to achieve maximized non-linearity properties.

Artificial neural network modeling of p-cresol photodegradation.

BACKGROUND: The complexity of reactions and kinetic is the current problem of photodegradation processes. Recently, artificial neural networks have been widely used to solve the problems because of their reliable, robust, and salient characteristics in capturing the non-linear relationships between variables in complex systems. In this study, an artificial neural network was applied for modeling p-cresol photodegradation. To optimize the network, the independent variables including irradiation time, pH, photocatalyst amount and concentration of p-cresol were used as the input parameters, while the photodegradation% was selected as output. The photodegradation% was obtained from the performance of the experimental design of the variables under UV irradiation. The network was trained by Quick propagation (QP) and the other three algorithms as a model. To determine the number of hidden layer nodes in the model, the root mean squared error of testing set was minimized. After minimizing the error, the topologies of the algorithms were compared by coefficient of determination and absolute average deviation. RESULTS: The comparison indicated that the Quick propagation algorithm had minimum root mean squared error, 1.3995, absolute average deviation, 3.0478, and maximum coefficient of determination, 0.9752, for the testing data set. The validation test results of the artificial neural network based on QP indicated that the root mean squared error was 4.11, absolute average deviation was 8.071 and the maximum coefficient of determination was 0.97. CONCLUSION: Artificial neural network based on Quick propagation algorithm with topology 4-10-1 gave the best performance in this study.

The effect of laser repetition rate on the LASiS synthesis of biocompatible silver nanoparticles in aqueous starch solution.

Laser ablation-based nanoparticle synthesis in solution is rapidly becoming popular, particularly for potential biomedical and life science applications. This method promises one pot synthesis and concomitant bio-functionalization, is devoid of toxic chemicals, does not require complicated apparatus, can be combined with natural stabilizers, is directly biocompatible, and has high particle size uniformity. Size control and reduction is generally determined by the laser settings; that the size and size distribution scales with laser fluence is well described. Conversely, the effect of the laser repetition rate on the final nanoparticle product in laser ablation is less well-documented, especially in the presence of stabilizers. Here, the influence of the laser repetition rate during laser ablation synthesis of silver nanoparticles in the presence of starch as a stabilizer was investigated. The increment of the repetition rate does not negatively influence the ablation efficiency, but rather shows increased productivity, causes a red-shift in the plasmon resonance peak of the silver-starch nanoparticles, an increase in mean particle size and size distribution, and a distinct lack of agglomerate formation. Optimal results were achieved at 10 Hz repetition rate, with a mean particle size of ~10 nm and a bandwidth of ~6 nm 'full width at half maximum' (FWHM). Stability measurements showed no significant changes in mean particle size or agglomeration or even flocculation. However, zeta potential measurements showed that optimal double layer charge is achieved at 30 Hz. Consequently, Ag-NP synthesis via the laser ablation synthesis in solution (LASiS) method in starch solution seems to be a trade-off between small size and narrow size distributions and inherent and long-term stability.

Room temperature radiolytic synthesized Cu@CuAlO(2)-Al(2)O(3) nanoparticles.

Colloidal Cu@CuAlO(2)-Al(2)O(3) bimetallic nanoparticles were prepared by a gamma irradiation method in an aqueous system in the presence of polyvinyl pyrrolidone (PVP) and isopropanol respectively as a colloidal stabilizer and scavenger of hydrogen and hydroxyl radicals. The gamma irradiation was carried out in a (60)Co gamma source chamber with different doses up to 120 kGy. The formation of Cu@CuAlO(2)-Al(2)O(3) nanoparticles was observed initially by the change in color of the colloidal samples from colorless to brown. Fourier transform infrared spectroscopy (FTIR) confirmed the presence of bonds between polymer chains and the metal surface at all radiation doses. Results of transmission electron microscopy (TEM), energy dispersive X-ray spectrometry (EDX), and X-ray diffraction (XRD) showed that Cu@CuAlO(2)-Al(2)O(3) nanoparticles are in a core-shell structure. By controlling the absorbed dose and precursor concentration, nanoclusters with different particle sizes were obtained. The average particle diameter increased with increased precursor concentration and decreased with increased dose. This is due to the competition between nucleation, growth, and aggregation processes in the formation of nanoclusters during irradiation.

An investigation on the thermal effusivity of nanofluids Containing Al(2)O(3) and CuO nanoparticles.

The thermal effusivity of Al(2)O(3) and CuO nanofluids in different base fluids, i.e., deionized water, ethylene glycol and olive oil were investigated. The nanofluids, nanoparticles dispersed in base fluids; were prepared by mixing Al(2)O(3), CuO nanopowder and the base fluids using sonication with high-powered pulses to ensure a good uniform dispersion of nanoparticles in the base fluids. The morphology of the particles in the base fluids was investigated by transmission electron microscopy (TEM). In this study, a phase frequency scan of the front pyroelectric configuration technique, with a thermally thick PVDF pyroelectric sensor and sample, was used to measure the thermal effusivity of the prepared nanofluids. The experimental results of the thermal effusivity of the studied solvents (deionized water, ethylene glycol and olive oil) showed good agreement with literature values, and were reduced in the presence of nanoparticles. The thermal effusivity of the nanofluid was found to be particularly sensitive to its base fluid and the type of nanoparticles.

Interactions between photodegradation components.

BACKGROUND: The interactions of p-cresol photocatalytic degradation components were studied by response surface methodology. The study was designed by central composite design using the irradiation time, pH, the amount of photocatalyst and the p-cresol concentration as variables. The design was performed to obtain photodegradation % as actual responses. The actual responses were fitted with linear, two factor interactions, cubic and quadratic model to select an appropriate model. The selected model was validated by analysis of variance which provided evidences such as high F-value (845.09), very low P-value (<.0.0001), non-significant lack of fit, the coefficient of R-squared (R2 = 0.999), adjusted R-squared (Radj2 = 0.998), predicted R-squared (Rpred2 = 0.994) and the adequate precision (95.94). RESULTS: From the validated model demonstrated that the component had interaction with irradiation time under 180 min of the time while the interaction with pH was above pH 9. Moreover, photocatalyst and p-cresol had interaction at minimal amount of photocatalyst (< 0.8 g/L) and 100 mg/L p-cresol. CONCLUSION: These variables are interdependent and should be simultaneously considered during the photodegradation process, which is one of the advantages of the response surface methodology over the traditional laboratory method.

Green formation of spherical and dendritic silver nanostructures under microwave irradiation without reducing agent.

The rapid and green formation of spherical and dendritic silver nanostructures based on microwave irradiation time was investigated. Silver nanoparticles were successfully fabricated by reduction of Ag(+) in a water medium and using polyvinylpyrrolidone (PVP) as the stabilizing agent and without the use of any other reducing agent, and were compared with those synthesized by conventional heating method. UV-vis absorption spectrometry, transmission electron microscopy (TEM), atomic absorption spectroscopy (AAS) and photon correlation spectroscopy (PCS) measurements, indicated that increasing the irradiation time enhanced the concentration of silver nanoparticles and slightly increased the particle size. There was a lack of large silver nanoparticles at a high concentration, but interestingly, the formation and growth of silver dendrite nanostructures appeared. Compared to conventional heating methods, the silver nanoparticle suspension produced by irradiated microwaves was more stable over a six-month period in aqueous solution without any signs of precipitation.