جستجوی مقالات مرتبط با کلیدواژه « کروم شش ظرفیتی » در نشریات گروه « پزشکی »

 Heavy metals such as chromium are among the most common pollutants commonly found in high concentrations in industrial wastewater. They can damage aquatic environments and endanger the health of living organisms, especially humans. This study aims to determine the optimal removal of hexavalent chromium by magnetized activated carbon (AC / Fe3O4) from aqueous solutions.

 The structure and properties of AC/Fe3O4 were investigated by FESEM, FTIR, BET, and VSM techniques. The effect of solution pH parameter (3-11), initial concentration of hexavalent chromium (10-50) mg/L, and adsorbent dose (0.5-2) g/L on hexavalent chromium removal efficiency along with isotherm and kinetics studies was investigated. The concentration of hexavalent chromium was determined by direct reading at 540 nm with a spectrophotometer.

 The optimal conditions for maximum removal of hexavalent chromium at pH=3, contact time of 60 minutes, and adsorbent dose of 1.5 g/L were obtained with an initial concentration of hexavalent chromium of 30 mg/L. The isotherm and kinetics study showed that the experimental data followed the Langmuir and pseudo-second-order kinetics.

 Under desirable conditions, the maximum capacity of AC/Fe3O4 adsorption increased to 21.14 mg/g. The present study illustrated that AC/Fe3O4 could be used as an adsorbent to remove chromium from aqueous solutions.

One of the worrying and increasing environmental problems is urban and industrial waste water pollution, such as chromium (Cr). Given the destructive effects of Cr and nondegradability, its removal is of great importance. Adsorption method by low-cost biosorbents has been a successful method in during the last decade. This study aims to examine the effect of usual and acid-modified fig leaves powder as a biosorbent for removing of Cr (VI) from a synthetic aqueous solution.

 Laboratory tests were designed and implemented, including solution making of Cr (VI) and then in order to study the effect of different parameters, including solution pH, contact time, solution concentration, and adsorbent dosage, the secondary amount of chromium concentration was measured and compared by atomic absorption spectrometer.

 The results showed that for usual adsorbent, optimum parameters included pH 2, 200mg/l initial concentration, 40g adsorbent concentration, and 120min equilibrium time while for the modified adsorbent, optimum parameters were pH 3, 300mg/l initial concentration, 40g adsorbent concentration, and 120min equilibrium time. The maximum adsorption percentage of Cr (VI) in the first case was 54.33% and in the second case was 91.50%. In addition, by examining adsorption isotherms and kinetic models, it was found that Cr adsorption in both cases follows Langmuir isotherm (R2=0.942 for usual and R2=0.975 for modified adsorbent) and pseudo-second order kinetic model (R2=0.976 for usual and R2=0.982 for modified adsorbent).

 More efficient removal of Cr using a modified adsorbent compared to usual adsorbent and previous studies indicates the suitability of modified fig leaves powder as an adsorbent of Cr (VI).

Heavy metals, such as chromium, are the most common pollutants usually found in high concentrations in industrial wastewater and cause damages to aquatic environments and endanger the health of living organisms, especially human. Therefore, the purpose of this research was to investigate the photocatalytic removal of hexavalent chromium from aqueous solution using UV/ZnO-Zeo process in a batch system.

This research was an experimental and applied study conducted in a laboratory scale. At first, the design and construction of the reactor were carried out and then the zinc oxide nanoparticles were synthesized by hydrothermal method and stabilized on zeolite. Then, by changing the content of Zno-Zeolite nanoparticles and keeping the other effective factors constant, the optimum amount of Zno-Zeo was obtained in 1.5 g/l. Subsequently, the effect of pH, contact time and initial concentration of hexavalent chromium were studied at the constant amount of ZnO-Zeo (1.5g/L).

The result showed that photocatalytic removal efficiency increased with elevation in reaction time and ZnO-Zeo dosage. In addition, it was found that with decreasing the pH from 11 to 3, the efficiency of hexavalent chromium removal increased from 36% to 88 %.

The results showed that UV/ZnO-Zeo can be used as an effective and effient method for removal of hexavalent chromium from aqueous solutions.

Chromium is present in two oxidation forms of Cr(III) and Cr(VI). Cr(III) is less toxic than Cr(VI). The aim of this article was to optimize an artificial neural network structure in modeling the photocatalytic reduction of Cr(VI) by TiO2-P25 nanoparticles.

In this work, an artificial neural network (ANN) for the modeling photocatalytic reduction Cr(VI) by TiO2-P25 nanoparticles were used and its structure was optimized. The operating parameters were initial concentration of chromium, amount of photocatalyst, ultraviolet light irradiation time and pH. All the experiments were conducted in a batch photoreactor. The Cr(VI) concentration was measured with a UV/Vis spectrophotometer. ANN calculations were performed using Matlab 7 software and the ANN toolbox.

The results show that the optimization of the ANN structure and the use of an appropriate algorithm and transfer function could significantly improve performance. The proposed neural network in modeling the photoactivity of TiO2-P25 nanoparticles in reducing Cr(VI) was acceptable, based on a good correlation coefficient (0.9886) and a small mean square error (0.00018). All the input variables affected the reduction of Cr(VI), however the effect of pH with an impact factor of 34.15 % was more significant than the others. The results indicated that pH = 2 was the best pH for photocatalytic reduction of Cr(VI). Increasing photocatalyst dosage and irradiation time in the investigated range increased Cr(VI) photocatalytic reduction.

Optimized structure of the ANN includes a three-layer feed-forward back propagation network with 4:10:1 topology and the most appropriate algorithm is a scaled conjugate gradient backpropagation algorithm.