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Modeling of Cu(II) Adsorption from an Aqueous Solution Using an Artificial Neural Network (ANN)
This research optimized the adsorption performance of rice husk char (RHC4) for copper (Cu(II)) from an aqueous solution. Various physicochemical analyses such as Fourier transform infrared spectroscopy (FTIR), field-emission scanning electron microscopy (FESEM), carbon, hydrogen, nitrogen, and sulf...
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| Publicado no: | Molecules |
|---|---|
| Main Authors: | , , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7397182/ https://ncbi.nlm.nih.gov/pubmed/32708928 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/molecules25143263 |
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