SnO2 nanoparticle-loaded activated carbon for simultaneous removal of Acid Yellow 41 and Sunset Yellow; derivative spectrophotometric, artificial neural network and optimization approach-Reference-Cited by-同舟云学术

SnO2 nanoparticle-loaded activated carbon for simultaneous removal of Acid Yellow 41 and Sunset Yellow; derivative spectrophotometric, artificial neural network and optimization approach

Published:2015-11 Issue: Volume:150 Page:1002-1012
ISSN:1386-1425
Container-title:Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
language:en
Short-container-title:Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Author:

Hajati S.,Ghaedi M.,Mahmoudi Z.,Sahraei R.

Publisher

Elsevier BV

Subject

Spectroscopy,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference34 articles.

1. Adsorption of binary mixtures of cationic dyes

2. Remediation of dyes in textile effluent: a critical review on current treatment technologies with a proposed alternative

3. Palladium, silver, and zinc oxide nanoparticles loaded on activated carbon as adsorbent for removal of bromophenol red from aqueous solution

4. Color Removal from Wastewater Using Low-Cost Activated Carbon Derived from Agricultural Waste Material

5. Effect of carbon surface chemistry on the removal of reactive dyes from textile effluent

Cited by 25 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Modified graphene oxide as an efficient magnetic adsorbent for the simultaneous removal of Sunset Yellow and Tartrazine dyes;Desalination and Water Treatment;2024-01

2. Comprehensive review on machine learning methodologies for modeling dye removal processes in wastewater;Journal of Cleaner Production;2023-01

3. Facile Synthesis of Barium-Doped Cadmium Sulfide Quantum Dots for the Treatment of Polluted Water: Experimental and Computational Investigations;ACS Omega;2022-12-09

4. Adsorption, photodegradation, and selective removal of reactive red 2 dye onto cuprous oxide nanoparticles;Monatshefte für Chemie - Chemical Monthly;2022-07-18

5. A Review of the Modeling of Adsorption of Organic and Inorganic Pollutants from Water Using Artificial Neural Networks;Adsorption Science & Technology;2022-02-27