Artificial intelligence and regression analysis for Cd(II) ion biosorption from aqueous solution by Gossypium barbadense waste

Artificial intelligence and regression analysis for Cd(II) ion biosorption from aqueous solution... In this study, batch biosorption experiments were conducted to determine the removal efficiency of Cd(II) ion from aqueous solutions by Gossypium barbadense waste. The biosorbent was characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) connected with energy dispersive X-ray (EDX). The sorption mechanism was described by complexation/chelation of Cd2+ with the functional groups of O–H, C=O, –COO–, and C–O, as well as, cation-exchange with Mg2+ and K+. At initial Cd(II) ion concentration (C o), 50 mg/L, the adsorption equilibrium of 89.2% was achieved after 15 min under the optimum experimental factors of pH 6.0, biosorbent dosage 10 g/L, and particle diameter 0.125–0.25 mm. Both Langmuir and Freundlich models fitted well to the sorption data, suggesting the co-existence of monolayer coverage along with heterogenous surface biosorption. Artificial neural network (ANN) with a structure of 5–10–1 was performed to predict the Cd(II) ion removal efficiency. The ANN model provided high fit (R 2 0.923) to the experimental data and indicated that C o was the most influential input. A pure-quadratic model was developed to determine the effects of experimental factors on Cd(II) ion removal efficiency, which indicated the limiting nature of pH and biosorbent dosage on Cd(II) adsorption. Based on the regression model (R 2 0.873), the optimum experimental factors were pH 7.61, biosorbent dosage 24.74 g/L, particle size 0.125–0.25 mm, and adsorption time 109.77 min, achieving Cd2+ removal of almost 100% at C o 50 mg/L. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental Science and Pollution Research Springer Journals

Artificial intelligence and regression analysis for Cd(II) ion biosorption from aqueous solution by Gossypium barbadense waste

Loading next page...
 
/lp/springer_journal/artificial-intelligence-and-regression-analysis-for-cd-ii-ion-betPzB8Pl7
Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by Springer-Verlag GmbH Germany, part of Springer Nature
Subject
Environment; Environment, general; Environmental Chemistry; Ecotoxicology; Environmental Health; Atmospheric Protection/Air Quality Control/Air Pollution; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution
ISSN
0944-1344
eISSN
1614-7499
D.O.I.
10.1007/s11356-017-0922-1
Publisher site
See Article on Publisher Site

Abstract

In this study, batch biosorption experiments were conducted to determine the removal efficiency of Cd(II) ion from aqueous solutions by Gossypium barbadense waste. The biosorbent was characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) connected with energy dispersive X-ray (EDX). The sorption mechanism was described by complexation/chelation of Cd2+ with the functional groups of O–H, C=O, –COO–, and C–O, as well as, cation-exchange with Mg2+ and K+. At initial Cd(II) ion concentration (C o), 50 mg/L, the adsorption equilibrium of 89.2% was achieved after 15 min under the optimum experimental factors of pH 6.0, biosorbent dosage 10 g/L, and particle diameter 0.125–0.25 mm. Both Langmuir and Freundlich models fitted well to the sorption data, suggesting the co-existence of monolayer coverage along with heterogenous surface biosorption. Artificial neural network (ANN) with a structure of 5–10–1 was performed to predict the Cd(II) ion removal efficiency. The ANN model provided high fit (R 2 0.923) to the experimental data and indicated that C o was the most influential input. A pure-quadratic model was developed to determine the effects of experimental factors on Cd(II) ion removal efficiency, which indicated the limiting nature of pH and biosorbent dosage on Cd(II) adsorption. Based on the regression model (R 2 0.873), the optimum experimental factors were pH 7.61, biosorbent dosage 24.74 g/L, particle size 0.125–0.25 mm, and adsorption time 109.77 min, achieving Cd2+ removal of almost 100% at C o 50 mg/L.

Journal

Environmental Science and Pollution ResearchSpringer Journals

Published: Dec 12, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off