In spite of the incredible evolutions of advanced material characterization methods, this field of research faces different technical and scientific challenges. Thermal lens spectroscopy is known as a sensitive and nondestructive optical based technique to characterize the opto-Thermal properties of materials and also to diagnose the impurities in the solutions. In this research, by engaging Thermal lens spectroscopy, we investigate the Thermal diffusivity coefficient of ultrathin silver layers, prepared by magnetron sputtering. For this propose, the Shen theoretical model is fitted to the obtained empirical signal and subsequently, the Thermal diffusivity coefficient will be extracted. The results clearly show that, in the investigated interval thickness (<15nm), the Thermal diffusivity coefficient increases by increasing the thickness. Furthermore, our findings reveal that in the very fine thickness region, the Thermal diffusivity coefficient shows a fair dependence on the thickness of the silver layers. This might be explained by 2D behavior of the Thermal diffusivity for ultrathin metal nanolayers.

It is necessary to determine the thermophysical properties of the various types of agricultural products in order to control Thermal operations, as well as processes such as drying, freezing, cooling, and pasteurization. Moreover, most of the products' thermophysical properties vary by the temperature changes and the percentage of water content. Therefore, the mathematical models expressing the relationship of these properties serve as a beneficial tool for designing automatic processes and equipment. The present research entails the examination of the impact of four levels of soluble solid content 15, 20, 25, and 30 %, and nine levels of temperature 28.6, 35.4, 40.5, 47.6, 56.1, 63.3, 72.3, 83.2, and 90 °C on the thermophysical properties of lime juice including density, specific heat, Thermal conductivity coefficient, and Thermal diffusivity coefficient. Based on the results, soluble solid content and temperature had a significant impact (p≤ 0.05) on the thermophysical properties of lime juice. By increasing the percentage of the soluble solid content, the properties such as specific heat (from 3321 to 2897 J/kg°C), Thermal conductivity coefficient (from 0.69 to 0.54 W/m°C), and Thermal diffusivity coefficient (from 2.10×10-7 to 1.61×10-7 m2/s) decreased but the density was increased (from 1013 to 1057 kg/m3). Furthermore, by increasing the temperature, the values of specific heat, Thermal conductivity coefficient, and Thermal diffusivity coefficient increased but the density was decreased. Consequently, to model the thermophysical properties, the multivariable regression method and Matlab software were employed and the results of the examination were fitted. The coefficient of determination of linear models of density 0.94, specific heat 0.93, Thermal conductivity, and Thermal diffusivity 0.98. In accordance with the results, all thermophysical properties had a linear relationship with the independent variables such as temperature and soluble solid content.

High moisture levels in fresh dairy manure provide a suitable environment for growth of pathogens and cause environmental pollution. Dry manure can be used for different purposes in agriculture and in livestock industry. Such heat properties of manure as specific heat, Thermal conductivity and Thermal diffusivity are important needed factors for the design and development of a suitable efficient dryer. In this research the Thermal diffusivity of dairy manure was determined through one-dimensional Fourier solution. Experiments were carried out at 20, 40, 60 and 82% (w.b) moisture contents and at 40, 50, 60 and 70°C temperature levels. Thermal diffusivities of the dairy manure were obtained in a range of from 0.904×10-7 to 2.11×10-7 m2/s. The trend of increase in Thermal diffusivity with by increase in temperature was of a linear type. At a certain constant temperature, Thermal diffusivity increased by increase in moisture content (from 20% to 40% (w.b.)) while decreasing at contents above 40% (w.b). A polynomial model can adequately estimate the Thermal diffusivity coefficient, a, (agreeable with moisture content vs. temperature of dairy manure), with a coefficient of determination of 0.99.

Knowledge of desorption kinetics is essential to predict the behavior of the material during drying process and to design dryer equipment. The main objective of this study is to obtain the effective diffusivity coefficient and activation energy of shelled pistachio. Another goal is to find drying kinetics of shelled pistachio in fluidized bed dryer and so thin-layer characteristics of shelled pistachios were determined experimentally as a function of temperature and air velocity. Accordingly, 6 mathematical models (Two term model, Exponential model, Logarithmic model, Page model, Modified page model and Henderson & Pabis model) for describing the thin-layer drying behavior of shelled pistachios were investigated. Tests were conducted using four air temperature (25, 30, 45 and 60 C), and three air velocities (6, 8 & 10m/s). Out of the 6 models considered, the two term model was considered to be the most suitable for describing the drying behavior of the shelled pistachios. Also, for high air temperature and velocity, Henderson-Pabis model proved to be suitable. Results showed that air velocity and operating temperature enhanced the kinetics of drying of shelled pistachio and the drying air temperature had a great effect on the drying kinetics. By using of Fick’s second Law the effective diffusivity coefficient and activation energy of pistachio was determined.

In this article, Au nanoparticles in polyvinylpyrrolidone (PVP) solution were prepared by gamma radiation at different concentrations. The solutions were irradiated at doses of 50 kGy for making different sizes. The average sizes of particle in the prepared samples were measured using the nanophox machine. A dual-beam mode-mismatched Thermal lens (TL) method was used to investigate the effect of Thermal diffusivity of samples. The TL measurement was carried out using a green diode laser (wavelength 532 nm, 60 mW) and a He–Ne laser (wavelength 632.8 nm, 0.5 mW) for excitation source and probe beam, respectively. The results showed that the Thermal diffusivity of samples enhances with the growth of particle size and density of solutions. This increment can be attributed to phonon scattering at interface of particles–liquid and contact between the nanoparticles and surrounded liquid.

Introduction: Today, drying of agricultural products is a developed method that removes part of the moisture leads to physicochemical stability of the product, also, produces different products with new qualitative properties and different nutritional and economical value. Moisture diffusivity coefficient is the most crucial property in drying calculations. Materials and Methods: In this study, drying kinetics modeling of Balangu seed gum in an infrared dryer was investigated. The effect of samples distance from the radiation lamp in three levels of 5, 7. 5 and 10 cm and the effect of gum height in the container in three levels of 0. 5, 1. 0 and 1. 5 cm on the mass transfer rate and effective moisture diffusivity coefficient during the dry process of Balangu seed gum was investigated. Standard models (Wang and Singh, Henderson and Pabis, Approximation of diffusion, Page, Modified Page, Newton, Midilli, and Logarithmic) were fitted to experimental data to study the drying kinetics and was analyzed. Results: The results showed that samples distance from the radiation lamp and samples thickness had significant effect on the mass transfer rate during drying of gum. By increasing samples distance from the heat source from 5 to 7. 5 cm and from 7. 5 to 10 cm, the drying time of Balangu seed gum increased by 21. 49% and 15. 20%, respectively. The effect of sample distance from infrared heat lamp and sample thickness on changes in effective moisture diffusivity coefficient of Balangu seed gum was investigated and results showed that this coefficient values were increased with decreasing in distance and increasing samples thickness. By reducing sample distance from the lamp from 10 to 5 cm, it was observed that the effective moisture diffusivity coefficient increased from 4. 82×10-9 m2s-1 to 7. 05×10-9 m2s-1. Conclusion: In drying process modeling of Balangu seed gum, the Page model with the highest coefficient of determination and the lowest error, had closer results to the experimental data than the other models.

The present study investigated the Thermal properties of canola pods (Thermal conductivity, specific heat, and Thermal diffusivity), canola losses (natural losses, platform losses, and total combine harvester losses), and unbroken pods in three common canola varieties cultivated in the North of Iran (Hyola 420, Hyola 401, and Hyola 50) at three times of pre-harvest, harvest, and post-harvest. Furthermore, the relation between the Thermal properties of canola pods and the amounts of losses during harvest was studied. Thermal conductivity coefficient, specific heat, and Thermal diffusivity were determined using line heat source, mixture method, and calculation methods, respectively. Seed losses were calculated, using a built grain collector. The results revealed that adjustments, variety, and sampling time had significant effects on Thermal conductivity and specific heat of canola varieties at the probability level of 1%. The effect of the interaction between variety and time on Thermal conductivity, specific heat, and Thermal diffusivity was considerable at the probability levels of 1% and 5%, respectively. Furthermore, the effects of canola varieties and harvest time on natural losses, total combine harvester losses, as well as unbroken pods were substantial at 1% probability. In addition, a notable relation was observed between Thermal conductivity coefficient and platform losses at 5% and unbroken pods at 1%. However, unbroken pods indicated a substantial relation with specific heat and Thermal diffusivity at 1%.

Correlation of heat transfer coefficients for air flow through the regenerator constructed from randomly packed spheres is reported for the symmetric-balanced mode of operation. The experimental results have been correlated by the least square regression and the following correlation has been obtained: epsilon J(h) = 0.1783 Re-m(-0.2906) The present correlation has been compared with the heat transfer coefficient correlations in the literature.

Most air pollutant dispersion models are analytical models that do not consider the spatial variation of wind velocity and diffusivity coefficient. To obtain an analytical model by considering the spatial variation of wind velocity and diffusivity coefficient, some simplifying assumptions must be made; in addition, the analytical solution is more complicated and less accurate. In this study, by solving the advection-dispersion equation for a steady and elevated pollutant stack, the spatial variation of the wind velocity and diffusivity coefficient is considered and the 2-dimensional distribution of the pollutant concentration is calculated. The model could be applied for both stable and unstable conditions. The advection-dispersion equation has been solved using the finite difference method. The proposed model has been validated using other researcher's experiments data and existing analytical models. The results show a good level of accuracy for the model.