A modeling study by response surface methodology (RSM) and artificial neural network (ANN) on Cu2+ adsorption optimization using light expended clay aggregate (LECA)-Reference-Cited by-同舟云学术

A modeling study by response surface methodology (RSM) and artificial neural network (ANN) on Cu2+ adsorption optimization using light expended clay aggregate (LECA)

Published:2014-05 Issue:3 Volume:20 Page:870-880
ISSN:1226-086X
Container-title:Journal of Industrial and Engineering Chemistry
language:en
Short-container-title:Journal of Industrial and Engineering Chemistry

Author:

Shojaeimehr Tahereh,Rahimpour Farshad,Khadivi Mohammad Ali,Sadeghi Marzieh

Publisher

Elsevier BV

Subject

General Chemical Engineering

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1. Rice husk as a potentially low-cost biosorbent for heavy metal and dye removal: an overview

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4. Biosorption of copper(II) ions on Enteromorpha prolifera: Application of response surface methodology (RSM)

5. Copper removal from oil-field brine by coprecipitation

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