TY - JOUR
T1 - Comparative adsorption of Eriochrome Black T and Tetracycline by NaOH-modified steel dust
T2 - Kinetic and process modeling
AU - Saood Manzar, Mohammad
AU - Ahmad, Tauqir
AU - Ullah, Nisar
AU - Velayudhaperumal Chellam, Padmanaban
AU - John, Juliana
AU - Zubair, Mukarram
AU - Brandão, Rodolfo J.
AU - Meili, Lucas
AU - Alagha, Omar
AU - Çevik, Emre
N1 - Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/4/15
Y1 - 2022/4/15
N2 - This study focuses on the use of chemically modified steel dust-based adsorbent to remove Eriochrome Black-T (EBT) and Tetracycline (TC) from water. The adsorption isotherm, kinetic modeling, thermodynamic and regeneration studies were conducted. The adsorption process was modeled using Artificial Neural Network. The adsorption kinetics were well fitted by a pseudo-second-order kinetic model and Redlich-Peterson model. The maximum adsorption capacity for TC was 19.78 mg.g−1 (Mod-AL) and 14.37 mg.g−1 (ModAR), and for EBT was 90.71 mg.g−1 (Mod-AL) and 119.02 mg.g−1 (Mod-AR). The thermodynamic evaluation indicated the adsorption was endothermic, spontaneous, and did not cause modification onto an adsorbent surface. The artificial neural based network has predicted the adsorption capacity at equilibrium with a high degree of accuracy quantified with minimum mean squared error of 1.2240 and coefficient of determination of 0.9990. FTIR spectra of free and dye adsorbed adsorbents revealed a slight shift in the peak positions, indicative of the interaction of adsorbents functionalities with the EBT and TC. The XRD spectra of Mod-AL and Mod-AR exhibited fewer sharp peaks signals, suggesting the amorphous nature of these adsorbents. The thermogravimetric analysis (TGA) of these adsorbents revealed their higher thermal stablity, with less than 10 % weight loss up to heating to 900 °C.
AB - This study focuses on the use of chemically modified steel dust-based adsorbent to remove Eriochrome Black-T (EBT) and Tetracycline (TC) from water. The adsorption isotherm, kinetic modeling, thermodynamic and regeneration studies were conducted. The adsorption process was modeled using Artificial Neural Network. The adsorption kinetics were well fitted by a pseudo-second-order kinetic model and Redlich-Peterson model. The maximum adsorption capacity for TC was 19.78 mg.g−1 (Mod-AL) and 14.37 mg.g−1 (ModAR), and for EBT was 90.71 mg.g−1 (Mod-AL) and 119.02 mg.g−1 (Mod-AR). The thermodynamic evaluation indicated the adsorption was endothermic, spontaneous, and did not cause modification onto an adsorbent surface. The artificial neural based network has predicted the adsorption capacity at equilibrium with a high degree of accuracy quantified with minimum mean squared error of 1.2240 and coefficient of determination of 0.9990. FTIR spectra of free and dye adsorbed adsorbents revealed a slight shift in the peak positions, indicative of the interaction of adsorbents functionalities with the EBT and TC. The XRD spectra of Mod-AL and Mod-AR exhibited fewer sharp peaks signals, suggesting the amorphous nature of these adsorbents. The thermogravimetric analysis (TGA) of these adsorbents revealed their higher thermal stablity, with less than 10 % weight loss up to heating to 900 °C.
KW - Artificial Neural Networks
KW - Chemical modification
KW - Iron industry
KW - Steel slag
KW - Water treatment
UR - http://www.scopus.com/inward/record.url?scp=85124037007&partnerID=8YFLogxK
U2 - 10.1016/j.seppur.2022.120559
DO - 10.1016/j.seppur.2022.120559
M3 - Article
AN - SCOPUS:85124037007
SN - 1383-5866
VL - 287
JO - Separation and Purification Technology
JF - Separation and Purification Technology
M1 - 120559
ER -