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- W4353015310 abstract "In this paper, green nanocomposites based on biomass and superparamagnetic nanoparticles were synthesized and used as adsorbents to remove methylene blue (MB) from water with magnetic separation. The adsorbents were synthesized through the wet co-precipitation technique, in which iron-oxide nanoparticles coated the cores based on coffee, cellulose, and red volcanic algae waste. The procedure resulted in materials that could be easily separated from aqueous solutions with magnets. The morphology and chemical composition of the nanocomposites were characterized by SEM, FT-IR, and XPS methods. The adsorption studies of MB removal with UV-vis spectrometry showed that the adsorption performance of the prepared materials strongly depended on their morphology and the type of the organic adsorbent. The adsorption studies presented the highest effectiveness in neutral pH with only a slight effect on ionic strength. The MB removal undergoes pseudo-second kinetics for all adsorbents. The maximal adsorption capacity for the coffee@Fe3O4-2, cellulose@Fe3O4-1, and algae@Fe3O4-1 is 38.23 mg g-1, 41.61 mg g-1, and 48.41 mg g-1, respectively. The mechanism of MB adsorption follows the Langmuir model using coffee@Fe3O4 and cellulose@Fe3O4, while for algae@Fe3O4 the process fits to the Redlich-Peterson model. The removal efficiency analysis based on UV-vis adsorption spectra revealed that the adsorption effectiveness of the nanocomposites increased as follows: coffee@Fe3O4-2 > cellulose@Fe3O4-1 > algae@Fe3O4-1, demonstrating an MB removal efficiency of up to 90%." @default.
- W4353015310 created "2023-03-23" @default.
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- W4353015310 date "2023-03-22" @default.
- W4353015310 modified "2023-10-03" @default.
- W4353015310 title "Green composites based on volcanic red algae Cyanidiales, cellulose, and coffee waste biomass modified with magnetic nanoparticles for the removal of methylene blue" @default.
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- W4353015310 doi "https://doi.org/10.1007/s11356-023-26425-3" @default.
- W4353015310 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36944836" @default.
- W4353015310 hasPublicationYear "2023" @default.
- W4353015310 type Work @default.