Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution
Boron is an essential micronutrient for plants, humans and animals, which is also an important component in various industries. Along with the wide spread of boron application, more boron waste pollutes the water sources, and leads to a series of environment and health...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/84252/1/FK%202019%20102%20-%20ir.pdf |
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| Summary: | Boron is an essential micronutrient for plants, humans and animals, which is also an important
component in various industries. Along with the wide spread of boron application, more
boron waste pollutes the water sources, and leads to a series of environment and health
problems. Adsorption is the most efficient technique among many boron removal technologies; which
can treat solutions containing a very low concentration of boron.
This project aimed to produce amidoxime-modified poly(acrylonitrile-co-acrylic acid)
(AO-modified poly(AN-co-AA)) with optimised method and to investigate the performance of
AO-modified poly(AN-co-AA) on the adsorption of boron ions in batch operation. Batch
adsorption was conducted at the physiochemical parameters of pH, adsorbent dosage and initial boron
concentration. The isotherms and kinetics of adsorption data were studied at various initial
boron concentration. Meanwhile, the Artificial Neural Network (ANN) was simulated from
experimental data and applied to optimize, develop and create prediction models for boron
adsorption by AO-modified poly(AN-co-AA).
As a result, the optimised synthesis method at 55 ºC gave yield of 77% and the
conversion of nitrile group to amidoxime at pH = 8 was 78%. The optimal operating condition for
boron batch adsorption were determined as initial pH ≈ 7. Besides, the process reached its
equilibrium at adsorbent dosage of 4.2 g/L and initial concentration of 41 mg/L.
The best fit model for adsorption isotherm was Sips model with heterogeneity factor (n) =
0.7611. In kinetic study, the adsorption data was well fitted in Pseudo-second order equation with
equilibrium rate constant (k2) = 0.0807 ± 0.0112 g. mg−¹.min−¹. In modelling section, both feed-forward and recurrent artificial neural network
(ANN) have been simulated to predict the adsorption potential of synthesised polymer.
Among several models, radial basis function (RBF) with orthogonal least square (OLS) algorithm
displays good prediction on boron adsorption behaviour with mean square error (MSE) and
coefficient of determination (R²) at 0.000209 and 0.9985, respectively. The adsorption equilibrium
is reached within 57 min with the maximum adsorption capacity at 15.23 ± 1.05 mg/g. The
results indicate that the AO-modified poly(AN-co-AA) is a potential and effective
adsorbent for boron
removal from aqueous solution. |
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