@misc{10481/78082,
year = {2022},
month = {10},
url = {https://hdl.handle.net/10481/78082},
abstract = {Intensive greenhouse agriculture annually produces large amounts of residues. The present
work focused on the study of the dynamic adsorption of cobalt from aqueous solutions over a vegetal
residue from intensive greenhouse cultivation. The influence of three operating variables, feed-flow
rate, inlet concentration of cobalt and bed height, was analyzed. According to the results, the variable
that particularly affected the percentage of cobalt adsorbed was the feed-flow rate. The results were
also fitted to an adaptive neuro fuzzy system (ANFIS) model to predict cobalt adsorption from
aqueous solutions and choose the most favorable operating conditions. Results were evaluated using
root mean squared error (RMSE), coefficient of determination (R2) and other typical statistic factors
as performance parameters. The experimental and model outputs displayed acceptable result for
ANFIS, providing R2 values higher than 0.999 for both cobalt removal (%) and biosorption capacity
(mg/g). In addition, the results showed that the best operating conditions to maximize the removal
of cobalt were 4 mL/min of feed-flow rate, 25 mg/L of inlet concentration and 11.5 cm of bed-height.},
publisher = {MDPI},
keywords = {Adaptive neuro fuzzy system},
keywords = {Biosorption},
keywords = {Cobalt},
keywords = {Fixed-bed column},
keywords = {Greenhouse crop residue},
title = {Cobalt Biosorption in Fixed-Bed Column Using Greenhouse Crop Residue as Natural Sorbent},
doi = {10.3390/separations9100316},
author = {Blázquez García, Gabriel and Martín Lara, María Ángeles and Iáñez Rodríguez, Irene and Morales Ortega, Inés and Pérez Muñoz, Antonio and Calero De Hoces, Francisca Mónica},
}