130
6 Modelling of Packed Bed Column for the Adsorption …
show that G/CR-CS is promising for the adsorption of heavy metal ions because of
its high adsorption efficiency and acid solution stability.
6.9 Merit and Demerit of Different Models in Light
of Shrinking Core Model
During column operations, different distinctive attributes such as adsorbent power,
regeneration time and estimation of the time needed to achieve breakthrough, play a
valuable part. The column of adsorption is open to the axial dispersion, external film
resistance and resistance to intraparticle diffusion. Various mathematical methods
for testing the efficacy and use of column methods for large-scale processes have
been developed. Different models including Thomas model, bed depth service time
(BDST) and shrinking core model were used to predict the adsorbent–adsorbate
device column behaviour. The BDST model is based on the assumption that equilibrium in packed bed is not instantaneous and that the rate of adsorption operation is directly proportional to the fraction of adsorption power remaining in the
column of packed beds. The BDST model ignores the resistance of intraparticle
mass transfer and the external film resistance by adsorbing the metal ions directly to
the binding material surface. The Thomas model agrees with Langmuir adsorption
kinetics without any axial dispersion and kinetics of mass transfer. This is derived
from the premise that the driving force of the rate coincides with reversible reaction
of the second order and according to Simate and Ndlovu [20] that is the primary
limitation of the Thomas model. Most column studies take advantage of the Thomas
and BDST model to forecast experimental data in literature using correlation coefficient values (R
2 ) obtained from a straightline plot without real experimental data
simulation. Authors such as [4, 20, 23, 24, 27] used the Thomas and BDST model
in the past to predict experimental data that exploits the R
2 values as the determinant
of the best fit model. On the other hand, the shrinking core model as described in
Sect. 6.4 takes account of external film resistance and resistance to intraparticle diffusion. The experimental breakthrough curve was in near agreement with the expected
breakthrough curve when the shrinking core model was applied and the model was
modified by changing the value of the effective diffusion coefficient before a strong
agreement was found in a study presented by Osifo et al. [18] on adsorption of
Cu(II) ions in a packed bed column by chitosan beads. Throughout this analysis,
the shrinking core model was used to predict column breakthrough curves for the
adsorption of Cu(II) ions to G/CR-CS throughout conjunction with the adsorption
parameters obtained from the pH equilibrium model. At column activity pH of 5.1,
the model was able to predict the breakthrough curve fairly well, and the diffusion
coefficient was estimated as stated in Sect. 6.5.
6 Modelling of Packed Bed Column for the Adsorption …
show that G/CR-CS is promising for the adsorption of heavy metal ions because of
its high adsorption efficiency and acid solution stability.
6.9 Merit and Demerit of Different Models in Light
of Shrinking Core Model
During column operations, different distinctive attributes such as adsorbent power,
regeneration time and estimation of the time needed to achieve breakthrough, play a
valuable part. The column of adsorption is open to the axial dispersion, external film
resistance and resistance to intraparticle diffusion. Various mathematical methods
for testing the efficacy and use of column methods for large-scale processes have
been developed. Different models including Thomas model, bed depth service time
(BDST) and shrinking core model were used to predict the adsorbent–adsorbate
device column behaviour. The BDST model is based on the assumption that equilibrium in packed bed is not instantaneous and that the rate of adsorption operation is directly proportional to the fraction of adsorption power remaining in the
column of packed beds. The BDST model ignores the resistance of intraparticle
mass transfer and the external film resistance by adsorbing the metal ions directly to
the binding material surface. The Thomas model agrees with Langmuir adsorption
kinetics without any axial dispersion and kinetics of mass transfer. This is derived
from the premise that the driving force of the rate coincides with reversible reaction
of the second order and according to Simate and Ndlovu [20] that is the primary
limitation of the Thomas model. Most column studies take advantage of the Thomas
and BDST model to forecast experimental data in literature using correlation coefficient values (R
2 ) obtained from a straightline plot without real experimental data
simulation. Authors such as [4, 20, 23, 24, 27] used the Thomas and BDST model
in the past to predict experimental data that exploits the R
2 values as the determinant
of the best fit model. On the other hand, the shrinking core model as described in
Sect. 6.4 takes account of external film resistance and resistance to intraparticle diffusion. The experimental breakthrough curve was in near agreement with the expected
breakthrough curve when the shrinking core model was applied and the model was
modified by changing the value of the effective diffusion coefficient before a strong
agreement was found in a study presented by Osifo et al. [18] on adsorption of
Cu(II) ions in a packed bed column by chitosan beads. Throughout this analysis,
the shrinking core model was used to predict column breakthrough curves for the
adsorption of Cu(II) ions to G/CR-CS throughout conjunction with the adsorption
parameters obtained from the pH equilibrium model. At column activity pH of 5.1,
the model was able to predict the breakthrough curve fairly well, and the diffusion
coefficient was estimated as stated in Sect. 6.5.