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Gene/Protein
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Target Concepts:
Gene/Protein
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Query: UMLS:C0205700 (
ash
)
15,125
document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)
This work attempts to elucidate the effects of different operational variables affecting the mechanistic function of fly
ash
for removal of some priority organic pollutants viz. phenol and its analogues. Thermodynamic parameters like free energy change, enthalpy and entropy of the process, as well as the sorption isotherms for phenols on fly
ash
, were measured and the most suitable isotherm was determined. Results of the study indicate that the extent of solute removal is determined by the initial solute concentration, molecular size and molecular arrangement of the solute. At the fixed set of experimental conditions, a model equation can be developed from which the percent removal corresponding to the load of the particular solute is determined. It is assumed that the mechanism of adsorption is governed by the surface characteristics of fly
ash
; pH has a vital role in influencing the solute removal as both the ionizing power (acidity, pKa) of the solutes and the zero point charge of fly
ash
(pH(
ZPC
)) depend on the solution pH. Isotherm pattern and the free energy change indicate that the process is favorable, as well as spontaneous. The information gathered from the study will serve as a predictive modeling procedure for the analysis and design of the removal of organic pollutants and decontamination of water. The leaching experiment indicates that the retained solutes do not release from fly
ash
. The retained solutes can be recovered and utilized as industrial raw material.
...
PMID:Use of fly ash for the removal of phenol and its analogues from contaminated water. 1651 37
This research optimized the adsorption performance of rice husk char (RHC4) for copper (Cu(II)) from an aqueous solution. Various physicochemical analyses such as Fourier transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FESEM), carbon, hydrogen, nitrogen, and sulfur (CHNS) analysis, Brunauer-Emmett-Teller (BET) surface area analysis, bulk density (g/mL),
ash
content (%), pH, and pH
ZPC
were performed to determine the characteristics of RHC4. The effects of operating variables such as the influences of aqueous pH, contact time, Cu(II) concentration, and doses of RHC4 on adsorption were studied. The maximum adsorption was achieved at 120 min of contact time, pH 6, and at 8 g/L of RHC4 dose. The prediction of percentage Cu(II) adsorption was investigated via an artificial neural network (ANN). The Fletcher-Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and
R
2
of 0.989). The pseudo-second-order kinetic model fitted well with the experimental data, thus indicating chemical adsorption. The intraparticle analysis showed that the adsorption process proceeded by boundary layer adsorption initially and by intraparticle diffusion at the later stage. The Langmuir and Freundlich isotherm models interpreted well the adsorption capacity and intensity. The thermodynamic parameters indicated that the adsorption of Cu(II) by RHC4 was spontaneous. The RHC4 adsorption capacity is comparable to other agricultural material-based adsorbents, making RHC4 competent for Cu(II) removal from wastewater.
...
PMID:Modeling of Cu(II) Adsorption from an Aqueous Solution Using an Artificial Neural Network (ANN). 3270 28
