Adsorption of pesticides onto activated carbons from wood composites

A series of activated carbon was produced from particleboard and medium-density fibreboard monoliths, which are waste originated from the industry, and then characterized and evaluated for potential application for phenoxyacetic acids removals, such 2,4-dichlorophenoxyacetic acid (2,4-D), 2-methyl-4-chlorophenoxy acetic acid (MCPA) and 3-(3,4-dichlorophenyl)-1,1-dimethylurea (diuron), from the liquid phase. All AC retain the shape of the precursor, and displays a microporous structure well-developed, reaching 0.58 cm 3 g -1. The adsorption isotherms for three pesticides were obtained in the optimal conditions and the AC with high superficial area and micropore volume exhibited better performance, allowing to state that, this AC could be a great substitute of those habitually used for this purpose. The pesticides adsorption data were linearized using the Langmuir and Freundlich equation, being the first a very good fit to the experimental data.

Adsorption of pesticides onto activated carbons from wood composites

A series of activated carbon was produced from particleboard and medium-density fibreboard monoliths, which are waste originated from the industry, and then characterized and evaluated for potential application for phenoxyacetic acids removals, such 2,4-dichlorophenoxyacetic acid (2,4-D), 2-methyl-4-chlorophenoxy acetic acid (MCPA) and 3-(3,4-dichlorophenyl)-1,1-dimethylurea (diuron), from the liquid phase. All AC retain the shape of the precursor, and displays a microporous structure well-developed, reaching 0.58 cm 3 g -1. The adsorption isotherms for three pesticides were obtained in the optimal conditions and the AC with high superficial area and micropore volume exhibited better performance, allowing to state that, this AC could be a great substitute of those habitually used for this purpose. The pesticides adsorption data were linearized using the Langmuir and Freundlich equation, being the first a very good fit to the experimental data.

Matlab simulink modeling of photovoltaic cells for understanding shadow effect

Irradiation is the main component for producing the electricity from solar energy. When obstacles come in between the sun and the PV cell then it doesn’t get sufficient irradiance to produce enough electricity. Shadowing has a great impact on photovoltaic cell. The main fuel of PV cell is solar radiation. Using solar radiation, a photovoltaic cell produces electricity. The shadow on a PV cell decreases the output of the photovoltaic cell. It has been already shown in different papers that shadow effect decreases the output of the PV cell. There are different kinds of shadow effects which are observed, some minimize the PV cell output and some reduce the output to zero. There are different types of shadow based on their effects on the photovoltaic cell. The shadow has also effects depending on whether the PV cells are connected in series connection or in parallel connection. In series when one cell is out of order then the whole series of the PV cells will not work but in parallel connection if one cell is damaged, the others will work because they work independently. According to the output requirement the arrangement of the PV cells are made in series or parallel. Simulink modeling is made for series and parallel connection between two PV cells and the shadow effect is analyzed on one of the PV cells. Using SIMULINK, the shadowing is simulated on the two PV cells, where in one system they are in series and in another system they are in parallel. Slowly the irradiance is decreased to simulate the shadow effect. Simulation of the shadow effect gives an idea about the output of the PV cell system when system has shadow on the PV cells. Here the shadow effect on the two PV cells using series and parallel combinations are simulated and analyzed for understanding the effects on output.