Download Comparison of Adsorbent Behavior in Glucose/Fructose Separation

University of Twente
Faculty of Chemical Technology
Comparison of Adsorbent Behavior in
Glucose/Fructose Separation by Simulated
Moving Bed (SMB) Chromatography
Authors:
J. Blignaut
K. Albataineh
Y. Banat
Z. Abu El-Rub
Supervisor:
Prof. dr. ir. Van der Haam.
Enschede, 2001
Table of Contents
1.
2.
3.
4.
Abstract
i
Introduction
1
The Principles of Simulated Moving Bed Chromatography
3
1.1
Continuous counter current adsorption systems
3
1.2
The simulated moving bed process
4
1.2.1 The four-section SMB cascade
5
Modeling of SMB Column
8
2.1
8
Equivalent counter-current model
Characteristics of Adsorbents and Modeling Results
11
3.1
Ca2+ exchanged ion exchange
11
3.2
Non-polar dealuminated Faujasite zeolite
14
3.3
CaY zeolite
18
3.4
Activated carbon
21
3.5
Adsorbent behavior comparison
24
Conclusions and Recommendations
26
4.1
Conclusions
26
4.1
Recommendations
26
References
27
Nomenclature
29
Appendices
Appendix 1: Ca2+ exchanged ion exchanger simulation
30
Appendix 2: Non-polar dealuminated FAU zeolite simulation
31
Appendix 3: CaY zeolite simulation
34
Introduction
The implementation of high-performance separation units constitutes a key stage in
industrial development. Several chromatographic separation processes have been developed in
the last years, proving this a technique of interest at an industrial scale.
Chromatography is one of the few separation techniques that can separate a
multicomponent mixture into nearly pure components in a single device, generally a column
packed with a suitable sorbent. The degree of separation depends upon the length of the column
and the differences in component affinities for the sorbent.
Although batch chromatography is a relatively simple process offering operating
flexibility, it suffers from a lot of difficulties like requirement of a large difference in the
adsorptive selectivity of components and ineffectively use of adsorbent bed. In order to avoid all
of theses disadvantages, continuous counter-current methods have been developed where mass
transfer is maximized, thus a more efficient usage of the adsorbent is presented. However such
processes have the difficulties involved in circulating a solid adsorbent. Liquid chromatography
in simulated moving bed (SMB) allows us to overcome these difficulties.
The simulated moving bed process is realized by connect a multiple column fixed bed
system, with an appropriate sequence of column switching designed to simulate a counter flow
system. Processes based on this concept have been developed for a number of commercially
important separations of both aqueous and hydrocarbon systems in sugar and petrochemical
industries, respectively.
The separation of fructose-glucose mixtures in the production of high fructose syrup is
generally carried out by simulated counter-current adsorption. The objective of this report is to
compare the behavior of a simulated moving bed by using Ca+2 exchanged ion exchanger, CaY
zeolite, non-polar dealuminized FAU zeolite and activated carbon.
1
This report consists of five chapters. Chapter one discusses the principles of simulated
moving bed chromatography. A steady-state model of the simulated moving bed is derived in
chapter two. Chapter three consists of the characteristics of the adsorbents and the results.
Chapter four discusses the results. Finally conclusions and recommendations are presented in
chapter five.
Finally, We hope that you will find a plain and sufficient coverage concerning the subject
at hand, a simple one as well.
2
Chapter One
The Principles of Simulated Moving Bed Chromatography
Chromatographic processes provide a powerful tool for the separation of multicomponent mixtures in which the components have different adsorption affinities, especially
when, high yields and purities are required. Typical applications are found in the pharmaceutical
industry and in the production of the fine chemicals. An industrially relevant system whose
adsorption thermodynamics can be described by linear isotherms over a specific adsorbent is the
fructose-glucose system [1]. In this area, the simulated moving bed (SMB) technology is
becoming an important technique for large-scale continuous chromatographic separation
processes. It provides the advantages of a continuous counter-current unit operation, while
avoiding the technical problems of a true moving bed. The aim of this chapter is to present a
clear explanation of how the SMB process operates.
1.1 Continuous counter-current adsorption systems
For the bulk separation of liquid mixtures, continuous counter-current systems are
preferred over batch system because they maximize the mass-transfer driving force. This
advantage is particularly important for difficult separations where selectivity is not high and/or
where mass-transfer rates are low. Ideally, a continuous counter-current system involves a bed of
adsorbent moving downward in plug flow and the liquid mixture flowing upward in plug flow
through the bed void space. Unfortunately, such a system has not been successfully developed
because of problems of adsorbent attrition, liquid channelling, and non uniform flow of
adsorbent particles. Successful commercial systems are based on a simulated counter-current
system using a stationary bed.
3
1.2 The simulated moving bed process
As mentioned earlier, most of the benefits of counter-current operations can be achieved
without the problems associated with moving bed adsorbent by using a multiple column fixedbed system, with an appropriate sequence of column switching designed to simulate a counter
flow system. The basic principle is illustrated in Figure (1.1).
Figure (1.1) Schematic diagram showing the sequence of column switching in a SMB countercurrent adsorption system; the shading indicates the concentration profiles just prior to
switching.[2]
At each switch a fully regenerated column is added at the outlet of the adsorption side
which is approaching breakthrough while the fully loaded column at the end of the adsorption
side is switched to the outlet end of the regeneration train. In this way the adsorbent seems to be
moving counter-currently to the fluid flow. With sufficiently small elemental beds switched with
appropriate frequency such a system indeed becomes a perfect analogue of a counter-current
flow system.
4
1.2.1
The four-section SMB cascade
For fructose-glucose separation, there are two types of SMB cascades, the three-section
SMB cascade and the four-section SMB cascade.
In the three-section SMB, the adsorbent is contained in a number of identical columns
connected in series through pneumatically controlled switch valves that also allow the
introduction of feed or eluant or withdrawal of product between any pair of columns. At any
given time one column is isolated from the cascade and purged with eluant. The more strongly
adsorbed species (extract product) is recovered in the effluent from the purge column. To
simulate counter-current flow the eluant inlet, feed, raffinate product and purge points are all
advanced by one column in the direction of fluid flow at fixed time intervals.
The separation of fructose-glucose mixtures by this method is relatively straightforward
since adsorbents with reasonably high selectivity are available. There is therefore little difficulty
in achieving a clean separation with a modest number of theoretical stages. With product purity
specifications easily achievable the main economic consideration becomes the maintenance of
adequate product concentration and minimization of dilution. In this respect the four-section
SMB unit is superior to the three-section system and it is therefore adopted in virtually all largescale fructose-glucose separation processes.
The four-section system shown in Figure (1.2) provides a more economical use of
adsorbent than is possible with a three-section cascade. The system is similar to that of threesection SMB except that all columns are connected in series with no isolated purge column. The
cascade is divided into four sections; section I between desorbent inlet and extract withdrawal,
section II between extract and feed, section III between the feed and the raffinate withdrawal and
section IV between raffinate and desorbent recirculation point. As in the three-section SMB
system, by advancing the desorbent, extract, feed, raffinate and recirculation points at specified
time intervals simulates counter-current flow by one column in the direction of the fluid flow.
The basic features of the design and operation of such a system are discussed here with reference
to the fructose-glucose separation.
5
Figure (1.2) Simulated counter-current system of valves and column elements showing
arrangement for operation as four-section separation process[3].
In order to achieve separation of the feed components (F and G) in a system with an
equilibrium selective adsorbent, if KF > KG it is necessary to fulfil the following flow conditions:
Section IV
γF > 1.0,
γG > 1.0
Section III
γF > 1.0,
γG < 1.0
Section II
γF > 1.0,
γG < 1.0
Section I
γF < 1.0,
γG < 1.0
If one elects to satisfy all these constraints by the same margins (α > 1.0) this set of
inequalities translates directly into a set of four simultaneous equations which define the flow
ratios throughout the system:
6
Section IV
(D-E+F-R)/S = KG/α
(1.1)
Section III
(D-E+F)/S = KF/α
(1.2)
(D-E)/S = KG/α
(1.3)
D/S = KFα
(1.4)
Section II
Section I
It is evident that there is a trade-off between the number of stages and the desorbent flow
rates since reducing the flow rate ratio (L/S) reduces the driving force for mass transfer and thus
increasing the height of the column. Under the limiting condition of α near one, with an infinite
number of stages, the extract and raffinate product concentrations may approach but can never
exceed the concentration of the relevant components in the feed. This will always be true for an
isothermal linear, uncoupled system.
7
Chapter Two
Modelling of SMB adsorption column
The problem of modeling the SMB process has attracted a great deal of attention of
researchers. Different approaches have been used to simulate this process. These approaches are
classified according whether the system is simulated directly or represented in terms of an
equivalent true counter current system and whether the system is represented as a continuos flow
or as a cascade of mixing cells [4]. The most widely used model to simulate the SMB process is
called the equivalent counter-current model; this model is discussed in more details below .
2.1. Equivalent counter-current model
Assuming plug flow of the solid and axially dispersed plug flow of the fluid, Ching et al.
[4] have derived the following differential equation which describes the system dynamics, see
Figure (2.1):
Sq
z+dz
dz
z
Lc
Figure (2.1): Differential element on the packed adsorbent
8
DL
∂ 2c
∂c 1 − ε ∂q ∂c 1 − ε ∂q
)u
)
=
+(
−υ
+(
2
∂z
∂z ∂t
ε
ε ∂t
∂z
(2.1)
Where, DL is the axial dispersion coefficient, c and q are liquid and solid phases concentrations
respectively, υ and u are liquid and solid phases velocities respectively and ε is the bed porosity.
The solid and liquid velocities can be estimated using the following equations:
u=
S
Ac (1 − ε )
(2.2)
υ=
L
Ac ε
(2.3)
S=
V
(2.4)
τ
Where, S and L are solid and liquid flow rates respectively, V is column volume and τ is switch
time. If a linear equilibrium relationship (q* = Kc) and a linear driving force mass transfer rate
expression are assumed, at steady state [4]:
dq
dq
= k (q * − q) = k ( Kc − q) = −u
dz
dt
(2.5)
Then eq. (2.1) becomes:
DL
d2
dc 1 − ε
−υ
−(
)k ( Kc − q) = 0
2
dz
ε
dz
(2.6)
A steady state material balance between a plane z in the column and the inlet yields:
(1 − ε )u (q − q o ) = ευ (c − c o )
(2.7)
9
Substitution of this mass balance into the differential equation for the column and
applying Dankwerts boundary condition at the column fluid entrance (z = 0) and zero change of
concentration flux at the column exit (z = L) leads to a formal solution for the concentration
profile given by Ching et al. [4].
When the mass transfer resistance is negligible and dispersed flow prevails, the following
equation gives the concentration at the outlet of each section as a function of inlet concentration
[4]:
q
γq
c
1
=
((1 − o )γe pe (1−γ ) + o − 1)
co (γ − 1)
Kc o
Kc o
(2.8)
Ching et al. have shown that Pe number could be evaluated from the chromatographic
velocity using [5]:
Pe = νL/5(u + ν), where DL = νL/DL
(2.9)
Where the Peclet number Pe = νL/DL, γ = (1-ε)Ku/εν and L is the column height. For a four
column counter current adsorptive fractionating column there are four such equations. In
conjunction with four mass balances over each section and two additional mass balances at the
feed point and over the fluid recircuilating stream. This gives ten equations that define the
system and enable the evaluation of the ten unknowns (qo, qI, qII, qIII, co, cI, cII, cIII, cIV, cII-).
10
Chapter Three
Characteristics of Adsorbents and Modeling Results
3.1 Ca2+ Exchanged ion exchange
Ca2+ polystyrene resin is one of the most widely used adsorbent (fructose selective) in the
separation of fructose-glucose mixtures for the production of high fructose syrup. The adsorption
isotherms of fructose and glucose on Doulite C204 resin (Ca2+ form) can be assumed linear and
uncoupled (Ching et al. 87) with equilibrium constants equal at 30oC to 0.88 and 0.5,
respectively [8]. This resin has a particle diameter of 10 µm and gives a bed porosity of 0.4.
Further properties of this resin can be supplied the manufacturer.
In order to simulate the behavior of the SMB the mathematical model developed in chapter two
has been used with α = 1.1. The flow rates of the solid and liquid in each section have been
evaluated using equations (1.1) – (1.4). Table (3.1) shows the flow rates in each section.
After substituting the constants on the mathematical model, 10 algebraic equations have been
generated, solution of these equation has been done using MathCad program, see appendix one.
Figure (3.1) shows fructose and glucose recoveries as a function of volume, while Figure (3.2)
shows typical concentration profile of fructose-glucose mixture over Doulite C204 resin.
11
Table (3.1): Liquid and solid flow rates at each section.
F = 8.314(L/min), E = 13.97(L/min), R = 11.47(L/min) and S = 33.25(L/min).
Section
Liquid
flow
rate(L/min)
Solid
flow
rate (L/min)
Solid velocity
Liquid
(cm/min)
velocity
γF
γG
Pe
(cm/min)
I
32.26
33.26
8.15
11.86
.91
.51
17.8
II
18.29
33.26
8.15
6.72
1.6
.91
13.5
III
26.60
33.26
8.15
9.78
1.1
.62
16.4
IV
15.13
33.26
8.15
5.56
1.9
1.1
12.2
100
99
Percentage recovery
98
97
96
Fructose recovery
Glucose recovery
95
94
93
92
91
90
0
2
4
6
8
10
12
Column volume(m^3)
Figure (3.1): Recoveries of fructose and glucose as a function of bed volume, T = 30oC.
12
250
Concentration (g/l)
200
150
Cf
Cg
100
50
0
0
0.5
1
1.5
2
2.5
3
3.5
4
Section
Figure (3.2): Concentration profile of fructose- glucose mixture over Ca2+ resin. (1,1,1,1)
configuration.
The recoveries of fructose and glucose are not function of bed volume only, but also
function of the configuration of the bed (number of columns in each section). Table (3.2) gives
fructose and glucose recoveries for different column arrangements.
Table (3.2): Fructose and glucose recoveries for different columns arrangement
Ac = 0.68m2, T = 30oC, τ = 30.5 min, individual column height = 1.5 m.
Configuration
Packing height (m)
Fructose recovery (%)
Glucose recovery (%)
1,1,1,1
6.0
91.74
92.23
2,1,1,1
7.5
94.12
92.24
2,1,2,1
9.0
97.73
92.22
2,2,1,1
9.0
94.12
95.30
3,1,1,1
9.0
94.52
92.23
2,2,2,1
10.5
97.73
95.29
One of the crucial parameters that determine the efficiency of the adsorption column is
the amount of energy needed to regenerate the solvent (water on this system). Table (3.3) shows
the energy needed to evaporate water in order to have 25 wt % of sugar (fructose and glucose) in
the product streams.
13
Table (3.3): Heat needed to regenerate the solvent as a function of columns configuration
Individual column height = 1.5 m
Configuration
1,1,1,1
2,1,1,1
2,1,2,1
2,2,1,1
3,1,1,1
2,2,2,1
Energy needed to
Energy needed to
Total energy needed
concentrate the raffinate
concentrate the extract
(kW)
(kW)
(kW)
87.52
97.68
109.85
85.05
97.82
98.46
192.69
183.99
170.71
195.40
182.50
182.17
280.21
281.68
280.57
280.46
280.33
280.63
3.2 Non-polar dealuminated faujasite zeolite
The chromatographic separation of carbohydrates on zeolite was established on the
industrial scale for more than 10 years [15]. The sugar interacts with zeolite by the complexation
of the multivalent counterions on acidic zeolite sites [16]. Some recent studies showed that the
chromatographic separation of the monosacariedes could be improved by using Y-zeolite
containing less aluminum [17]. The hydrophobicity increases because of the reduction of the
ionic sites, this is important since the carbohydrate molecule consists of hydrophobic and
hydrophilic regions [18]. This interaction of ionic sites with the counterion of the fructose may
describe why fructose is enriched in the zeolite pores while glucose is excluded. [18]
The silica to aluminum ratio is increased during the dealumination procedure, leading to changes
in the structure of zeolite. The FAU (Si/Al = 110, Na+ form) zeolite used in the experimentation
of C. Buttersack et al was produced with SiCl4 treatment, Figure 3.3. [19].
14
Figure 3.3. FAU zeolite framework.
The crystal diameter of FAU zeolite is 6 µm, with a porosity of 0.41. The absolute adsorption
equilibrium constant was calculated by K = KE + e where e (FAU: e = 0.315 ml/g) is the specific
pore volume [19]. According to this relation the adsorption equilibrium constants at 25 °C for
glucose is 0.515 ml/g and for fructose is 1.315 ml/g [20]. The particle density (0.85 g/ml) of
zeolite multiplied by the adsorption constant [21] gives a dimensionless adsorption constant for
glucose (0.44) and fructose (1.12), respectively.
The FAU zeolite adsorbent were evaluated according to a numerical simulation (Chapter 2) to
determine the effect of the adsorbent on the purity, recovery and heat needed to regenerate the
solvent to obtain 25 wt. % sugars. The liquid and solid flowrates of each section are given in
15
Table (3.4) : Liquid and solid flow rates at each section
F = 8.314(L/min), E = 11.60 (L/min), R = 9.59 (L/min) and S = 15.52 (L/min)
Section
Liquid
flow
rate(L/min)
Solid
flow
rate (L/min)
Solid velocity
Liquid
(cm/min)
velocity
γF
γG
Pe
(cm/min)
I
46.32
26.69
3.4
5.9
0.91
0.36
15.33
II
34.72
26.69
3.4
2.3
2.32
0.91
7.37
III
43.03
26.69
3.4
4.9
1.10
0.43
10.69
IV
33.44
26.69
3.4
1.9
2.81
1.11
4.37
The recovery and purity of extract and raffinate respectively are represented in Figure 3.4 at
different adsorbent volumes.
0.96
0.94
0.92
Fructose-Recovery
0.9
E-Purity
0.88
Glucose-Recovery
0.86
R-Purity
0.84
0.82
1.5
2
2.5
3
3.5
4
Volume adsorbent (m^3)
Figure 3.4. Adsorbent effect on purity and recovery.
The recovery in both the extract and raffinate of fructose and glucose tend to level after
92%. The purity of glucose increased from 0.86 to 0.92 corresponding to a 50% increase in
adsorbent volume, while fructose increased from 0.83 to 0.96. These values are further reflected
in the heat required to concentrate the extract and raffinate to 25-wt% of Fructose and Glucose
respectively, see Figure (3.5). This figure shows a definite decline in the heat required in extract
(E-Q) and raffinate (R-Q) respectively, corresponding to the increase in concentration.
16
Heat for Vaporization (kW)
200
150
E-Q
R-Q
100
50
0
1.5
2
2.5
3
3.5
4
Volume adsorbent (m^3)
Figure 3.4. Adsorbent effect on vaporization heat required.
The concentration profile at 90 % recovery of extract and raffinate is given in Figure 3.5. The
extract (E) is withdrawn at column 4, feed (F) at column 7 and raffinate (R) at column 10.
300
C (g/l)
250
200
150
Fructose
Glucose
100
50
0
0
1
2
3
4
5
6
7
8
9 10 11 12
Columns
Figure 3.5. Concentration profile.
17
3.3 CaY zeolite
A CaY synthetic zeolite (UOP Process) is widely used in the separation of fructoseglucose mixture due to its fructose selectivity.
CaY zeolite is prepared from a standard NaY sample (Si/Al ≅ 2.2) by repeated ion
exchange with CaCl2. It has been shown that the CaX zeolite has no selectivity between fructose
and glucose, where as the selectivity and capacity of the CaY zeolite is similar to the Ca
2+
resins [9].
Figure (3.6) shows a schematic of Y zeolite. The pore structure of Y zeolite is very open,
the constructions being twelve-membered oxygen rings with free diameter ~ 7.5 Ao. Molecules
with diameters up to 8.5 Ao can penetrate these channels with little steric hindrance. The nature
of the cation can have a profound effect on the adsorption equilibria in these materials [10].
Figure 3.6. A schematic of CaY zeolite [2].
For the CaY zeolite, it has been shown that the equilibrium relationship remains
essentially linear even up to relatively high concentrations (~50 % wt.) [10]. The dimensionless
equilibrium constants of glucose and fructose at 29 oC are 0.38 and 0.78 respectively. This
adsorbent has an average particle diameter of 1.5 mm with a bed voidage (porosity) of 0.41 [9].
18
A MathCad program is used to simulate the model described in chapter two, see appendix
three. The effect of the amount of used adsorbent on purity and recovery of extract and raffinate
is shown in Figure (3.7). It is found that purity and recovery of both raffinate and extract are
function of amount of adsorbent used and the columns configuration.
98
(%)
96
Fructose-Recovery
94
E-Purity
92
Glucose-Recovery
90
R-Purity
88
4
5
6
7
8
Adsorbent Volume (m^3)
Figure 3.7. Amount of adsorbent effect on extract and raffinate purity and recovery.
For the system of configuration (4,3,3,2) a total volume of 4.24 m3 adsorbent is needed.
The concentration profile of this configuration is shown in Figure (3.8), while glucose and
fructose at purity and recovery shown in Table (3.5).
Table (3.5): Recovery and purity of the system configuration (4,3,3,2)
Property
Extract
Raffinate
Purity (%)
92.6
89.9
Recovery (%)
89.5
92.6
19
300
250
C (g/l)
200
C-G
150
C-F
100
50
0
0
1
2
3
4
5
6
7
8
9
10 11 12
Column Number
Figure (3.8): Fructose and glucose concentration profiles
Table (3.6) shows a summary of the flowrates and the parameters in each section of the
system. In order to concentrate the fructose in extract and the glucose in the raffinate to a
concentration equal to that of the feed (25 % wt.) about 235 kW is required.
Table (3.6): Summary of the flowrates and parameters in each section of the system.
F = 8.29 l/min, E = 12.53 l/min, R = 10.36 l/min and S = 28.48 l/min.
Section
L
S
u
v
γF
γG
Pe
(l/min)
(l/min)
(cm/min)
(cm/min)
I
24.44
28.48
6.15
7.59
0.909
0.443
19.89
II
11.91
28.48
6.15
3.70
1.865
0.909
10.14
III
20.20
28.48
6.15
6.28
1.100
0.536
13.64
IV
9.83
28.48
6.15
3.05
2.260
1.101
5.94
20
3.4 Activated carbon
Carbonaceous materials have been known for long time to provide adsorptive properties.
Now, activated carbons are used widely in industrial applications, which include decolourizing
sugar solutions, personnel protection, solvent recovery, volatile organic compound control,
hydrogen purification, and water treatment.
Activated carbons compromise elementary microcrystallites stacked in random
orientation and are made by the thermal decomposition of various carbonaceous materials
followed by an activation process. There are two types of activation processes, gas activation or
chemical activation.
The surface of an activated carbon adsorbent is essentially non-polar but surface
oxidation may cause some slight polarity to occur. Surface oxidation can be created, if required,
by heating in air around 300Co or by chemical treatment with nitric acid or hydrogen peroxide.
In general, activated carbons are hydrophobic and organophilic and therefore they are used
extensively for adsorbing compounds of low polarity in water treatment, decolourization, solvent
recovery and air purification applications.
Till now there are no published information about activated carbon as an adsorbent in the
separation of fructose-glucose mixture. This may be due to the complications arising from nonlinearity of the equilibrium isotherms of this system or due to low selectivity at high
concentration
The equilibrium isotherms for glucose and fructose have been studied by Abe et al.[1] at
a temperature of 25 Co, they determined the Freundlich’s adsorption constants of glucose and
fructose from aqueous solutions onto an activated carbon at low concentrations (up to 600 mg/l).
It was found that glucose is the more strongly adsorbed than fructose. The adsorption isotherms
were approximated by the Fruendlich equation and it was found that for glucose, the relation
between the equilibrium concentration (mg/l) and the amount adsorbed (mg/g) could be
represented by:
21
qG=0.1851c0.7552
(3.1)
qF= 0.09401c0.8075
(3.2)
And that of fructose:
These relations can’t be used in the model described in chapter two, so linearization of
these isotherms have been done, the linearized forms of these equations are given in the next two
relations:
qG= 32.5c
(3.3)
qF= 21.75c
(3.4)
Where c is the equilibrium concentration (g/l) and q is the amount adsorbed (g/l
adsorbent), based on particle density of 700 kg/m3 [2].
The mathematical model derived in chapter two has been applied and simulated (using KF
of 32.5,KG of 21.75 and α of 1.1. To study the effects of the amount of adsorbent and the
configurations of the columns on the purity, recovery and heat duty required to concentrate the
output extract (glucose-rich) and raffinate (fructose-rich) to 25 wt%. Mass balance results model
parameters for each section are shown in Table (3.7):
Table (3.7) Mass balance results, and model parameters at a feed of 8.3 L/min and cross
sectional area of the bed of 0.78 m2.
Section
Liquid
flow
rate(L/min)
Solid
flow
rate (L/min)
Solid
Liquid
velocity
velocity
(cm/min)
(cm/min)
γF
γG
Pe
I
54.60
1.54
0.33
16.96
0.61
0.91
5.88
II
36.82
1.54
0.33
11.44
0.91
1.35
5.83
III
45.12
1.54
0.33
14.02
0.74
1.10
5.86
IV
30.43
1.54
0.33
9.45
1.10
1.63
5.80
22
Figure (3.9) represents the concentration profiles for one of the configurations at which
92% purity of extract and raffinate can be achieved.
250
Concentration (g/l)
200
150
F ru c to se
G lu c o se
100
50
0
0
1
2
3
4
5
6
7
8
9
10
11
12
N u m b e r o f c o lu m n s
Figure (3.9) The concentration profiles at 92% purity of extract and raffinate with 91% recovery
of extract and 93% recovery of raffinate.
The recovery and the purity of both extract and raffinate can be improved by increasing
the amount of adsorbent in each column and by changing the configurations. Recovery and
impurity of 97% can be achieved using 4.082 m3 activated carbon. Table (3.8) contains recovery
and purity of glucose and fructose at several amounts of adsorbent.
Table (3.8) Purity and recovery of extract and raffinate at different amount of adsorbent.
Extract Purity
0.92
0.93
0.94
0.96
Raffinate Purity
0.92
0.93
0.94
0.97
Recovery of G in extract
0.91
0.93
0.94
0.96
Recovery of F in raffinate
0.93
0.93
0.94
0.97
3
Volume of adsorbent (m )
2.83
3.06
3.32
4.08
It is noticed that the amount of heat required for concentrating sugar is constant for the
same adsorbent and adsorption conditions, which is about 555 kW in this case. Figure (3.10)
explains the effect of amount of adsorbent on the purity of glucose and fructose.
23
0.98
0.97
Purity
0.96
0.95
Extract purity
R affinate purity
0.94
0.93
0.92
0.91
2.50
3.50
4.50
3
A m ount of adsorbent (m )
Figure (3.10): The effects of amount of adsorbent on the purity of extract and raffinate.
3.5 Adsorbents behaviour comparison
Table (3.9) compares the performance of the used adsorbents in terms of purity, recovery,
volume of adsorbent and energy required for the water recovery system. It is shown that
dealuminated FAU zeolite and activated carbon give the minimum volume while the CaY zeolite
gives the higher volume. If both recovery and energy requirement are considered as comparison
criteria, then the FAU zeolite is the most efficient adsorbent for fructose-glucose separation. If
results reliability is considered, activated carbon is the least. The results of activated carbon have
been generated using K values valid at low concentrations.
24
Table (3.9): Comparison of the behavior of the four adsorbents
Adsorbent Type
Fructose
Glucose
Adsorbent
Energy
Recovery
Recovery
Volume
Consumption
3
(%)
(%)
(m )
(kW)
Ca exchanged ion exchanger
91.7
92.2
4.08
280
Non-polar dealuminated FAU
90
90
2.83
228
CaY zeolite
92.6
89.5
4.23
235
Activated carbon
93
91
2.83
555
2+
zeolite
25
Chapter Four
Conclusions and Recommendations
4.1 Conclusions
•
The adsorbent that gives the minimum adsorbent volume are ranked in the following order:
Non-polar dealuminated FAU zeolite > activated carbon > Ca2+ exchanged ion exchanger >
CaY zeolite
•
The adsorbent that gives the minimum energy requirement are ranked in the following order:
Non-polar dealuminated FAU zeolite > CaY zeolite > Ca2+ exchanged ion
exchanger > Activated carbon.
•
Activated carbon cannot be compared to the others due to non-linearity of adsorption
isotherms and extrapolation to high concentration.
•
SMB technology can be used to separate fructose-glucose aqueous mixtures up to high
purity.
•
Column configuration plays a basic rule on the degree of separation.
•
The higher the ratio between the equilibrium constants of the solutes, the better separation
that could be achieved.
4.2 Recommendations
•
Further efforts have to be done to study the adsorption isotherms of fructose-glucose mixture
over activated carbon at high concentrations.
•
For the lowest amount of adsorbent and energy consumption; non-polar dealuminated FAU
zeolite is recommended to be used.
•
In order to have more reliable results, mass transfer resistance should be taken into account.
•
Further studies have to be done on FAU zeolite adsorbent for fructose-glucose separation.
26
References
1. G. Dunnebier, I. Weirich and K. U. Klatt, Chemical Engineering Science, 1998, 53 (14),
2537-2546,
2. Barry Crittenden and W. John Thomas, ”Adsorption Technology and Design”, ButterworthHeinemann, 1998.
3. Douglas M.Ruthven and C. B. Ching, “ Counter-Current and Simulated Counter-Current
Adsorption Separation Processes”, Chemical Engineering Science, 44(5), 1011-1038.
4. D. Ruthven and C. Ching, Chemical Engineering Science, 1989, 44, 1011-1038.
5. D. Ruthven and C. Ching, Chemical Engineering Science, 1985, 40, 877-885.
6. C. Ching, D. Ruthven and K. Hidajat, Chemical Engineering Science, 1985, 40, 1411-1417.
7. C. Ching and D. Ruthven, Chemical Engineering Science, 1986, 41, 3063-3071.
8. C. Ching, C. Ho and K. Hidajat, Chemical Engineering Science, 1987, 42, 2547-2555
9. Cecilia Ho, et al., Ind. Eng. Chem. Res. 1987,26,1407-1412
10. K. Hashimoto, et al., J. Chem. Eng. Jpn. 1983,16,400.
11. Julius Scherzer, “Octane-Enhancing Zeolitic FCC Catalysts: Scientific and Technical
aspects”, 1990, Marcel Dekker Inc.: New York and Basel.
12. R. A., Le Febre, “High-Silica Zeolites and their Use as Catalyst in Organic Chemistry”, Ph.
D. Thesis,1989, the Netherlands.
13. Abe and K. Hayashi, “Adsorption of Saccharides Aqueous Solution onto Activated Carbon”,
Caron, 21(3) 1981.
14. Barry Crittenden and W. John Thomas,”Adsorption Technology and Design”, ButterworthHeinemann, 1998.
15. Johnson, J.A.; Oroskar, A.R. Stud. Surf. Sci. Catal. 1989, 46, 451
16. Sherman, J.D.; Chao, C.C. Stud. Surf. Catal. 1986, 28, 1025.
17. Kulprathiapanja, S. U.S. Patent 5,000,794 1991.
18. Yano, Y.; Tanaka, K.; Doi, Y.; Janado, M. J. Solution Chem. 1988, 17, 347.
19. Buttersack, C., Wach W. & Buchholz K., J. Phys. Chem. 1993, 97, 11861-11864.
27
20. Buttersack, C., Fornefett I., Mahrholtz J. & Buchholz K. Progress in Zeolite and Micropous
Materials, 1997, 105, 1723.
21. Yang H., Ping Z., Niu G., Jiang H. & Long Y., Langmuir 1997, 13, 4094.
22. Lin Y.S. & Ma Y.H., Stud Surf. Sci. Catal. 1989, 84, 1363.
28
Nomenclature
Symbol
Definition
Unit
A
Cross-sectional area of the column
m2
c
Fluid phase concentration of sorbate
g/l
co
Value of c at z = 0
g/l
D
Desorbent flow rate
l/min
DL
Axial dispersion coefficient
-
E
Extract flow rate
l/min
F
Feed flow rate
l/min
K
Adsorption equilibrium constant based on particle volume
l/min
l
Length (of individual column of section)
m
L
Liquid flow rate
l/min
q
Sorbate concentration in adsorbed phase (particle volume basis)
g/l
S
Hypothetical adsorbent recirculation rate in equivalent counter-
l/min
current system
u
Hypothetical solid velocity
m/min
v
Hypothetical liquid intestitial velocity in counter-current model
m/min
z
Distance measured from bed inlet
m
Z
z/l fractional distance
-
Pe
vL/DL
-
∝
Separation factor
-
γ
(1-ε )Ku/ εv
-
ε
Bed voidage
-
τ
Switch time
min
29
Appendix one
x
.01
y
.5
z
1
t
.8
i
.1
l
.5
f
.8
r
.9
m
2.5
n
.9
given
10.753 . i .
l
f
1.667 . l .
r
10 . m.
y
x
y
m
l
.88 . m
2.212 .
1
i)
.55 . ( f
l)
t
r
. 27.30
1.03 .
y
1
.88 . l
. .1947
i
. .0000000857293
1.254 .
t
1
x
.88 . r
z
m
. .00001161
.687 . f
t
z
0.797 . ( r
x
t
.454 . ( n
i
.y
z
1
.97 . ( l
96.11
.88 . i
1.818
1
1.071 . r .
x
1
1
n
z
1
m)
r)
0.454 . n
rev
find ( x, y , z , t , i , l , f , r , m, n )
rev =
0
0
0.996
1
167.567
2
194.209
3
5.361
4
0.527
5
172.25
6
220.69
7
10.775
8
247.724
9
1.161
Mathcad program to solve for Fructose concentration across the SMB column for Ca2+
(2,2,1,1, configuration) adsorbent, the table gives the result of this simulation.
30
Appendix two
2.1. Fructose
x := .01
y := .5
z := 1
t := .8
i := .1
l := .5
f := .8
r := .9
p := 2.5
n := .9
Given
⎞ ⋅ 3.91926316057970+ 0.812991095⋅ x⎤
⎥
i⎦
l
−11.22597580468810
⋅ i⋅ ⎡⎢−1 + ⎛⎜ 1 −
f
y
y ⎞
⎤
0.75548589341629
⋅ l⋅ ⎡⎢ −1 + 2.07468879668150
⋅ + ⎛⎜ 1 −
⋅ 0.00005784682925
⎥
l ⎝
1.12⋅ l ⎠
⎣
⎦
r
9.78336942554319
⋅ p ⋅ ⎡⎢−1 + ⎛⎜ 1 −
n
t
t ⎞
⎤
0.55124653739607
⋅ r⋅ ⎡⎢ ⎛⎜ −1 + 2.51256281407052
⋅ ⎞ + ⎛⎜ 1 −
⋅ 0.00036071528103
⎥
r⎠ ⎝
1.12⋅ r ⎠
⎣⎝
⎦
⎣
⎣
⎝
⎝
x
1.12⋅ i ⎠
z
⎞ ⋅ 0.33533356391448+ 0.98411988721657
⋅ ⎤⎥
1.12⋅ p ⎠
p⎦
z
31
2.2. Glucose
x := .01
y := .5
z := 1
t := .8
i := .1
l := .5
f := .8
r := .9
p := 2.5
n := .9
Given
⎞ ⋅ 18957.85682+ 0.812991095⋅ x⎤
⎥
i⎦
l
−1.556943855⋅ i⋅ ⎡⎢−1 + ⎛⎜ 1 −
f
−11.48648649⋅ l⋅ ⎡⎢ −1 + 2.07486631⋅
r
−1.763745359⋅ p ⋅ ⎡⎢−1 + ⎛⎜ 1 −
n
9.460784314r
⋅ ⋅ ⎡⎢ ⎛⎜ −1 + 2.512953368⋅
⎣
⎝
x
.44⋅ i ⎠
⎣
⎣
⎣⎝
⎝
y
l
+ ⎛⎜ 1 −
⎝
y
⎞ ⋅ 1.89980074⎤
⎥
⎦
.44⋅ l ⎠
⎞ ⋅ 428.6624563+ 0.984147115⋅ z ⎤
⎥
.44⋅ p ⎠
p⎦
z
t⎞
r⎠
+ ⎛⎜ 1 −
⎝
t
⎞ ⋅ 0.63011228⎤
⎥
⎦
.44⋅ r ⎠
32
y
x + 1.22952499999917000l
⋅ ( − i)
z
y + 0.48199999999976800f
⋅ ( − l)
f
−340.2071837+ 2.108166722p
⋅
t
z + 1.01613636000015000r
⋅ ( − p)
x
t + 0.39799999999997400n
⋅ ( − r)
n
3.089258794i
⋅
rev := Find( x, y , z, t , i , l, f , r , p , n )
0
0
5.353
1
18.092
2
119.673
q0
q1
q2
3
85.135
q3
rev = 4
12.166
5
22.527
6
233.275
7
238.039
8
272.029
9
37.583
co
c1
c2
c3
( c2)
c4
33
Appendix three
MOLECULAR SEPARATION
CaY SMB MODEL
* Definition of Symbols:
Conentration of sugar in adsorbent and solvent (g/l):
Co = a , C1 = b, C2 = c , C2' = d , C3 = e , C4 = f ,
qo = j , q1 = h , q2 = i , q3 = g
Input and Output flow rates (l/min):
feed := 8.29
S := 28.48
D := 24.44
R := 10.37
E := 12.53
System Configuration: (4,3,3,2)
Length of Section (cm)
L1=180
L2=135
L3=135
L4=90
Col Diam=100 cm
Col Length = 45 cm
Total volume = 4.24 m^3
The system model consists of 10 equations and 10 unknowns
1- Modeling of Fructose
KF=0.78
γ1 = 0.909, γ2 = 1.865 , γ3 = 1.10 , γ4 = 2.26
Initial Guess:
a := 100
34
b := 100
c := 100
d := 100
e := 100
f := 100
g := 100
h := 100
i := 100
j := 100
Given
⎞ + 1.1654⋅ j − 1⎤ 0
⎥
.78⋅ a ⎠
a
⎣
⎝
⎦
h
h
−4
⎞ + 2.391⋅ − 1⎤ 0
c − 1.156⋅ b ⋅ ⎡⎢1.545⋅ 10 ⋅ ⎛⎜ 1 −
⎥
.78⋅ b ⎠
b
⎣
⎝
⎦
i
i
⎞ + 1.410⋅ − 1⎤ 0
e − 10⋅ d ⋅ ⎡⎢.25576⋅ ⎛⎜ 1 −
⎥
.78⋅ d ⎠
d
⎣
⎝
⎦
g
−4
⎞ + 2.897⋅ g − 1⎤ 0
f − 0.794⋅ e⋅ ⎡⎢5.598⋅ 10 ⋅ ⎛⎜ 1 −
⎥
.78e ⎠
e
⎣
⎝
⎦
b + 10.99⋅ a⋅ ⎡⎢6.0496⋅ ⎛⎜ 1 −
j
h j + 0.858⋅ ( b − a)
i h + .418⋅ ( c − b )
g i + .709( e − d )
j g + .345⋅ ( f − e)
d .59⋅ c + 126
f 2.486⋅ a
Fructose modeling
⎛ 2.2201501762168959285⎞
⎜
⎜ 188.64308497151933350⎟
⎜ 235.92883949789520513⎟
⎜ 265.19801530375817103⎟
⎟
⎜
17.595915391027451505
⎟
⎜
vec := Find( a , b , c , d , e , f , j , h , i, g ) →
⎜ 5.5192933380752032782⎟
⎜ 4.3055697222253015144⎟
⎟
⎜
⎜ 164.25644777659479295⎟
⎜ 184.02189316861990729⎟
⎜
⎝ 8.4720043304938271527⎠
35
0
0
2.22
1
188.643
2
235.929
3
265.198
vec = 4
17.596
5
5.519
6
4.306
7
164.256
8
184.022
9
8.472
recovery := 0.4907vec
⋅
1
recovery = 92.567
(%)
2- Modeling of Glucose
KG=0.38
γ1=0.443, γ2=.909 , γ3=.536 , γ4=1.101
Initial Guess:
a := 100
b := 120
c := 200
d := 100
e := 100
f := 100
j := 100
h := 100
i := 100
g := .008
Given
b + 1.795332a
⋅ ⋅ ⎡⎢6.421610
⋅ ⋅ ⎛⎜ 1 −
⎞ + 1.16579⋅ j − 1⎤
⎥
.38⋅ a ⎠
a
⎣
⎝
⎦
h ⎞
h
c + 10.989b
⋅ ⋅ ⎡⎢2.5144⋅ ⎛⎜ 1 −
+ 2.392105⋅ − 1⎤⎥ 0
.38
⋅
b
b
⎣
⎝
⎠
⎦
4
j
0
36
e + 2.15517d
⋅ ⋅ ⎡⎢562.00⋅ ⎛⎜ 1 −
⎞ + 1.410526⋅ i − 1⎤
⎥
.38⋅ d ⎠
d
⎣
⎝
⎦
g ⎞
g
⎡
⎛
⎤
f − 9.901⋅ e⋅ ⎢0.548⋅ ⎜ 1 −
+ 2.8974⋅ − 1⎥ 0
.38e ⎠
e
⎣
⎝
⎦
i
0
h j + 0.858⋅ ( b − a)
i h + .418⋅ ( c − b )
g i + .709( e − d )
j g + .3455⋅ ( f − e)
d .59⋅ c + 126
f 2.486⋅ a
⎛ 11.807845558305351259⎞
⎜
⎜ 21.135508523848093986⎟
⎜ 228.13134188471452392⎟
⎜ 260.59749171198156911⎟
⎜
⎟
220.34199835624860347
⎜
⎟
vec := Find( a , b , c , d , e , f , j , h , i, g ) →
⎜ 29.354304057947103231⎟
⎜ 4.4870120569548472364⎟
⎜
⎟
⎜ 12.490146881390520495⎟
⎜ 99.014405226232688207⎟
⎜
⎝ 70.473260437018015571⎠
0
0
11.808
1
21.136
2
228.131
3
260.597
vec = 4
220.342
5
29.354
6
4.487
7
12.49
8
99.014
9
70.473
recovery := .4061⋅ vec 4
recovery = 89.481
(%)
37
38