The demand for water and energy in today’s developing world is enormous and has become the key to the progress of societies. Many methods have been developed to desalinate water, but energy and environmental constraints have slowed or stopped the growth of many. Capacitive Deionization (CDI) is a very new method that uses porous carbon electrodes with significant potential for low energy desalination. This process is known as deionization by applying a very low voltage of 1.2 volts and removing charged ions and molecules. Using capacitive principles in this method, the absorption phenomenon is facilitated, which is known as capacitive deionization. In the capacitive deionization method, unlike other methods in which water is separated from salt, in this technology, salt, which is a smaller part of this compound, is separated from water and salt solution, which in turn causes less energy consumption. With the advancement of science and the introduction of new porous materials, the use of this method of deionization has increased greatly. Due to the limitations of other methods of desalination, this method has been very popular among researchers and the water desalination industry and needs more scientific research to become more commercial.
One of the new methods in the removal of impurities from the wheat grains is the electrostatic separation of particles based on the differences in their conductivity and permittivity. The moisture content of particles directly influences their electrical properties. In this study, by developing a cylindrical capacitor in an electrical circuit, the electrical capacitance of wheat grain and cluster straw particles in two varieties at four levels of moisture content (8%, 14%, 20%, and 25%) and five frequency levels (1, 10, 20, 100, and 500 kHz) is estimated and their dielectric constant is calculated. Results showed that increasing the moisture content of straw particles and reducing the frequency compared to the seeds had significant effects on dielectric constant. The dielectric constant of grain particles was higher than the straw at lower moisture content and in high values of moisture content, the dielectric constant of straw particles was higher than the seeds.
Sunflower petal is one of the parts of the sunflower which has drawn attention and has several applications these days. These applications justify getting information about physical properties, mechanical properties, drying trends, etc. in order to design new machines and use new methods to harvest or dry the sunflower petals. For three varieties of sunflower, picking force of petals was measured; number of petals of each head was counted; unit mass and 1000-unit mass of fresh petals were measured and length, width, and projected area of fresh petals were calculated based on image processing technique; frequency distributions of these parameters were modeled using statistical distribution models namely Gamma, Generalized Extreme Value (G. E. V), Lognormal, and Weibull. Results of picking force showed that with increasing number of days after appearing the first petal on each head from 5 to 14 and decreasing loading rate from 150 g min-1 to 50 g min-1 values of picking force were decreased for three varieties, but diameter of sunflower head had different effects on picking force for each variety. Length, width, and number of petals of Dorsefid variety ranged from 38.52 to 95.44 mm, 3.80 to 9.28 mm and 29 to 89, respectively. The corresponding values ranged from 34.19 to 88.18 mm, 4.28 to 10.60 mm and 21 to 89, respectively for Shamshiri variety and ranged from 44.47 to 114.63 mm, 7.03 to 20.31 mm and 29 to 89 for Sirena variety. Results of frequency distribution modeling indicated that in most cases, G. E. V and Weibull distributions had better performance than other distributions.
3 November 2019 in Journal of Food Process Engineering