different binder content and shapes were described to show the potential of these
materials for the future implementation of adsorptive-based technology at an industrial scale for the separations mentioned. To achieve high performance, it is necessary to take into account the selectivity, working capacity, adsorption affinity, and
regeneration capacity of the adsorbent.
Since adsorption equilibrium data are essential for the process design, the majority of the studies start with its assessment. Toth, SSL, and DSL adsorption isotherm
models and the most used for the two systems have reasonably described the
equilibrium data. Therefore, ExSSL and ExDSL models are selected for the
multicomponent equilibrium prediction, due to their easy implementation and reasonable performance on the prediction of the multicomponent equilibrium on the
different adsorbents. Dynamic studies are also frequently presented on the selected
adsorbents by measuring single- and multicomponent breakthrough curves and used
to obtain important information, not only for the PSA and SMB cyclic pilot-scale
tests but also for the future process modeling. In all the cases, the dynamic results
corroborate the collected adsorption equilibrium data. A robust mathematical model
describing the dynamic behavior of multicomponent adsorption in a fixed bed is
essential for the laboratory-scale results, as well as to the posterior upscale to larger
scales. The model must be composed of material, momentum, and energy balances.
Finally, after the model validation, the developed model can be applied to the design
PSA and SMB cycles for target separations.
The model validation with experimental results, of the pilot-scale VPSA and
SMB experiments, is of utmost importance since it allows the industrial design of a
process, as well as its further optimization.
In summary, both technologies proved to have a high potential for the three target
separations. However, they still can be improved using different configurations and
adsorbents, and in the SMB case, also different desorbents can be used in order to
optimize the process. The desorbent is a third component used in the separation by
SMB that should be easily separated from the components of the binary mixture, for
the sake of the downstream separation effectiveness, necessary to recover the
desorbent. However, the main issue remains to be answered: can any of these
technologies be truly competitive to be implemented on an industrial scale? To
answer this question, it is necessary to evaluate each process from the balance
between energy consumption and process performance point of view and how all
this is reflected in the process economy.
Nomenclature
q
Ã
i
Adsorbed concentration of component i in equilibrium with C p,i, mol kg
À1
q i
Adsorbed concentration of component i in the micropores, mol kg
À1
C p,i
Average concentration of component i in the macropores, mol m fluid
À3
C p,T
Average total concentration in the macropores, mol m fluid
À3
b
C ps
Particle specific heat at constant pressure (per mass unit), J kg solid
À1 K
À1
186
V. F. D. Martins et al.
materials for the future implementation of adsorptive-based technology at an industrial scale for the separations mentioned. To achieve high performance, it is necessary to take into account the selectivity, working capacity, adsorption affinity, and
regeneration capacity of the adsorbent.
Since adsorption equilibrium data are essential for the process design, the majority of the studies start with its assessment. Toth, SSL, and DSL adsorption isotherm
models and the most used for the two systems have reasonably described the
equilibrium data. Therefore, ExSSL and ExDSL models are selected for the
multicomponent equilibrium prediction, due to their easy implementation and reasonable performance on the prediction of the multicomponent equilibrium on the
different adsorbents. Dynamic studies are also frequently presented on the selected
adsorbents by measuring single- and multicomponent breakthrough curves and used
to obtain important information, not only for the PSA and SMB cyclic pilot-scale
tests but also for the future process modeling. In all the cases, the dynamic results
corroborate the collected adsorption equilibrium data. A robust mathematical model
describing the dynamic behavior of multicomponent adsorption in a fixed bed is
essential for the laboratory-scale results, as well as to the posterior upscale to larger
scales. The model must be composed of material, momentum, and energy balances.
Finally, after the model validation, the developed model can be applied to the design
PSA and SMB cycles for target separations.
The model validation with experimental results, of the pilot-scale VPSA and
SMB experiments, is of utmost importance since it allows the industrial design of a
process, as well as its further optimization.
In summary, both technologies proved to have a high potential for the three target
separations. However, they still can be improved using different configurations and
adsorbents, and in the SMB case, also different desorbents can be used in order to
optimize the process. The desorbent is a third component used in the separation by
SMB that should be easily separated from the components of the binary mixture, for
the sake of the downstream separation effectiveness, necessary to recover the
desorbent. However, the main issue remains to be answered: can any of these
technologies be truly competitive to be implemented on an industrial scale? To
answer this question, it is necessary to evaluate each process from the balance
between energy consumption and process performance point of view and how all
this is reflected in the process economy.
Nomenclature
q
Ã
i
Adsorbed concentration of component i in equilibrium with C p,i, mol kg
À1
q i
Adsorbed concentration of component i in the micropores, mol kg
À1
C p,i
Average concentration of component i in the macropores, mol m fluid
À3
C p,T
Average total concentration in the macropores, mol m fluid
À3
b
C ps
Particle specific heat at constant pressure (per mass unit), J kg solid
À1 K
À1
186
V. F. D. Martins et al.