RESUMEN
The current research is concerned with the adsorption behavior of chromium (IV) ions in an aqueous solution using a novel ferrochrome slag/polyaniline nanocomposite (FeCr-PANI) adsorbent. The effect of process parameters such as temperature, pH solution, initial Cr (VI) ions concentration, adsorbent dosage, and contact time on the adsorption process is experimentally investigated in this study. Furthermore, we have trained a multilayer artificial neural network (ANN) using the experimental data of various process parameters to successfully predict the adsorption behavior of chromium (IV) ions onto the FeCr-PANI adsorbent. The ANN model was trained using the Lavenberg-Marquardt algorithm and ten neurons in the hidden layer and was able to estimate the % removal efficiency of chromium (IV) under the influence of different process parameters (R2 = 0.991). Initial solution pH was observed to have a significant influence on the % removal efficiency. The % removal efficiency was found to be high at 97.10% for the solution with pH 3 but decreased to 64.40% for the solution with pH 11. Cr (VI) % removal efficiency was observed to increase with an increase in solution temperature, adsorbent dosage, and contact time. However, the % removal efficiency was found to decrease from 96.9 to 54.8% with increasing the initial dye concentration from 100 to 400 ppm. Furthermore, the adsorption capacity increased from 9.69 to 21.93 mg/g with an increase in the initial concentration from 100 to 400 ppm, as expected. The Langmuir isotherm model exhibited the best fit with the experimental data (R2 = 0.9977). The maximum adsorption capacity was found to be 22.523 mg g-1 at 298 K. The experimental data fitted well with the pseudo-second-order kinetic model.
Asunto(s)
Nanocompuestos , Contaminantes Químicos del Agua , Adsorción , Cinética , Contaminantes Químicos del Agua/análisis , Concentración de Iones de Hidrógeno , Cromo/análisis , Termodinámica , Iones , Redes Neurales de la ComputaciónRESUMEN
Proper treatment and disposal of industrial pollutants of all kinds are a global issue that presents significant techno-economical challenges. The presence of pollutants such as heavy metal ions (HMIs) and organic dyes (ODs) in wastewater is considered a significant problem owing to their carcinogenic and toxic nature. Additionally, industrial gaseous pollutants (GPs) are considered to be harmful to human health and may cause various environmental issues such as global warming, acid rain, smog and air pollution, etc. Conductive polymer-based nanomaterials have gained significant interest in recent years, compared with ceramics and metal-based nanomaterials. The objective of this review is to provide detailed insights into different conductive polymers (CPs) and their nanocomposites that are used as adsorbents for environmental remediation applications. The dominant types of CPs that are being used as adsorbent materials include polyaniline (PANI), polypyrrole (Ppy), and polythiophene (PTh). The various adsorption mechanisms proposed for the removal of ODs, HMIs, and other GPs by the different CPs are presented, together with their maximum adsorption capacities, experimental conditions, adsorption, and kinetic models reported.