TY  - JOUR
PB  - Elsevier Ltd
AV  - none
JF  - Polyhedron
VL  - 192
SN  - 02775387
N2  - Optimization studies was conducted for the pyrene (PYR) adsorption onto Zr-based metal organic frameworks (MOFs), UiO-66(Zr) and NH2-UiO-66(Zr) in aqueous medium. Central composite design (CCD) model has shown good fittings of the coefficient of determination (R2) with non-significant lack of fit for both UiO-66(Zr) and NH2-UiO-66(Zr) MOFs. The optimized adsorption efficiency achieved by the UiO-66(Zr) and NH2-UiO-66(Zr) were 99.22 and 95.67 respectively. Artificial neural network (ANN) model was able to predict the experimental findings with high precision at topographic node of 5-4-2 structural layer. The kinetics and isotherms of the process was best described by pseudo-second-order Langmuir models respectively. The process was exothermic and spontaneous with the good reusability of the MOFs. © 2020 Elsevier Ltd
Y1  - 2020///
TI  - Optimization studies and artificial neural network modeling for pyrene adsorption onto UiO-66(Zr) and NH2-UiO-66(Zr) metal organic frameworks
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093927924&doi=10.1016%2fj.poly.2020.114857&partnerID=40&md5=a4d4aa27d3698cae58328dbed8eadaee
A1  - Zango, Z.U.
A1  - Ramli, A.
A1  - Jumbri, K.
A1  - Sambudi, N.S.
A1  - Isiyaka, H.A.
A1  - Abu Bakar, N.H.H.
A1  - Saad, B.
N1  - cited By 20
ID  - scholars12411
ER  -