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Janaína Oliveira Gonçalves

Researcher at University of Rio Grande

Publications -  32
Citations -  748

Janaína Oliveira Gonçalves is an academic researcher from University of Rio Grande. The author has contributed to research in topics: Adsorption & Chitosan. The author has an hindex of 12, co-authored 30 publications receiving 488 citations. Previous affiliations of Janaína Oliveira Gonçalves include Universidade Federal de Santa Maria.

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Adsorption of FD&C Red No. 40 by chitosan: isotherms analysis.

TL;DR: In this article, the effects of pH (5.7, 6.6 and 7.5), particle size ranges (0.10−± 0.02, 0.18−±−0.02 and 0.26−±-0.2), deacetylation degree (42 −±−5, 64 −± −3% and 84 −±-3%) and temperature (25, 35 and 45 −°C) were investigated.
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Development of chitosan based hybrid hydrogels for dyes removal from aqueous binary system

TL;DR: In this paper, crosslinked hydrogel with glutaraldehyde (HyCG) was developed, characterized and applied for the adsorption of Food Blue 2 (FBL2) and Food Red 17 (FR17) from aqueous binary system.
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Synthesis of a bio–based polyurethane/chitosan composite foam using ricinoleic acid for the adsorption of Food Red 17 dye

TL;DR: The results showed that polyurethane foams are capable to support chitosan, generating an adsorbent with better mechanical characteristics and high potential to remove anionic dyes from aqueous media.
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Removal of fluoride from fertilizer industry effluent using carbon nanotubes stabilized in chitosan sponge

TL;DR: The adsorbent capacity was around 975.4 mg g-1, showing the potential of the hybrid material to remove fluoride from a real matrix, and the high adsorption capacity was attributed to the chitosan functional groups and thehigh interaction area promoted by sponge form and the carbon nanotube.
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Single and competitive dye adsorption onto chitosan-based hybrid hydrogels using artificial neural network modeling.

TL;DR: A predictive artificial neural network (ANN) was implemented and proved to be effective in predicting dye adsorption capacity of each hydrogel, even for the competitive adsor adaptation, as the R values were close to unity for all simulation systems.