Micro Open Parallel Plate Separator ( m OPPS) : Performance and Applications
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Micro Open Parallel Plate Separator (OPPS): Performance and Applications
Blanca H. Lapizco-EncinasDepartment of Chemical and Materials
Engineering University of Cincinnati
OutlineIntroduction.Objectives.Comparison of separators with rectangular and circular cross sections.Modeling OPPS and equation for reduced plate height. Concentration of trace species by displacementPrediction of equilibrium isotherms for protein-salt systems.Conclusions.
Liquid ChromatographyLiquid Chromatography (LC) is one of the most important techniques used for separating a chemical mixture into its components.
Traditionally, LC was used for analytical applications. LC is now being used in preparative modes.
Preparative Liquid chromatography is used for scaling up separations of fragile substances.
Preparative modes of chromatography are becoming essential for pharmaceutical, biological and environmental applications.
Liquid ChromatographyBench scale system
A powerful separation technique….
solvent
sample column
pump
detector
waste
data acquisition
Micro OPPS: Integration of Column and Detector
Interconnecting metal line
Channel
Silicon
Signal in/out
Outlet reservoir
Outlet nipple
Inlet reservoir
Top glass wafer
Channel
Signal in/out
Outlet nipple
ElectrodeBottom glass wafer
Channel
Bonding pad
Bonding wire
External bonding pad
Signal in/out
Outlet nippleOutlet through
Inlet through
Inlet nipple
H.T. Henderson, N. deGouvea-Pinto, Liquid Chromatograph on a Chip. US Patent 6,258,263B1, July 10, 2001.
Advantages of OPPS
Detectorcell
Bottom of themicrochannel
Electrode
Top view
WallChannel.
[111]
cross-section
[111][111]
Results Obtained with the Proof-of-Concept OPPS
Cur
rent
(mA
)
1.5
1.4
1.3
1.2
1.1
300 305 310 315 320 325 330 335 340 345 350
Cl- Br- SO4- -
Time (s)
Which Geometry is Better for Micro Separators?
lengthdi
amet
er
OPPS OTS
lengthde
pth
width
Objectives The goal of this research was to develop a mathematical
model to describe the OPPS, and through simulations achieve the following specific objectives:
To define the optimal geometry as a function of the separation characteristics. To develop an equation for the reduced plate height of a OPPS. To investigate the device capabilities for concentrating trace species by displacement. To study the potential of the OPPS for predicting isotherm data for protein-salt systems.
HETPThe first goal was to identify the parameters that influence the performance of the OPPS.The performance of the OPPS was evaluated by using the height equivalent to a theoretical plate.
Plate 1
Plate 2
Plate 3
Plate 4
Plate 5
1 m.
HETP = 20 cm
Plate 1Plate 2Plate 3Plate 4Plate 5Plate 6Plate 7Plate 8Plate 9Plate 10
HETP = 10 cm
Numerical Model for OPPSA 3-dimensional model was developed
2
2
2
2
2
2
2222
2222
22
22
3zC
yC
xCD
dzbxdzbx
dbdbv
yC
tC
avg
Vavg
b
dy
z
x
Mathematical ModelVelocity profile (Spangler, 1998):
Initial condition
zxKdbdb
vv vavgy ,6 2222
2222
2222
21
dzbxdzbxKv
0 C(X,Y,Z)=0 10 , 10 , 10
Mathematical ModelBoundary conditions
Condition 1: At X=1tq
xCD
bx
*
Condition 3: At Y=1 01
C
Condition 2: At Z=1 D
Condition 4: At X=0, 00
X
C
Condition 5: At Z=0,
Condition 6: At Y=0, C(X,0,)= Cfeed feed 0C(X,0,Z)= 0 feed
01
C 00
C
Numerical ProcedureFinite differences method.Peaceman-Rachford scheme- Alternating Dimension Implicit (ADI).
11
11
33313122
2
2
22
,,0,,223
1,,
2
mj
mjyn
mkjyn
mkjzz
yyn
mkjxx
ZXdb
ZXSCCRRCR 131
nn tt
132
nt
333131 ,,0,,223
2,,
2 ymkjymkjz
zx
xnmkjy
y SCCRRCR 1n 3
1n 3
11
11
222
2
22
mj
mj
ZXdb
ZX13
1nt
1nt
11
11
33313122
22
22
,,0,,221
,,2
mj
mjy
mkjymkjyy
xxn
mkjzz
ZXdb
ZXSCCRRCR 2n 3
2n 313
2nt
Simulation ParametersThe following dimensionless parameters were used to characterize the performance of the OPPS.
LD
bvavgX
2
LD
dvavgZ
2
D
LvPe
avg
eqdHh
2
bd
X
Z
ba
Existing Models for OPPS and OTS
Giddings et al. developed two models for predicting the reduced plate height of OTS and OPPS.
v r48
11166 2 avgCOTS D
RRh
105
5184352 22avg
eqOPPS
vDb
dRR
h
SimulationsSimulations for the OPPS and OTS were performed using the parameters shown below.The solute was assumed to be KBr ion exchanging on a PEI activated surface.
Feed volume = 4% of the column volume
3 cm
Vavg 0.2 cm/s
C
q*
iii Caq *ai=0.00792 cm
Cfeed= 1000 mol/cm3
10 – 100 m
10-1000 m
Simulations for OTSThe first simulations were performed by using a program for the OTS in order to compare the simulation results with an existing OTS model (Giddings et al., 1983).
0
2
4
6
8
10
12
14
0 20 40 60 80 100OTS radius rC (m)
h OTS
OTS simulator Giddings et al.
v r48
11166 2 avgC
OTS DRRh
Simulations for OPPSSimulations for the OPPS were performed, and the simulation results were compared with Giddings model for OPPS
0
2
4
6
8
10
12
14
0.0 0.5 1.0 1.5 2.0 2.5
X x 102
h OPP
S
OPPS simulatorGiddings et al.
=1
105
5184352 22avg
eqOPPS
v
Db
d
RRh
Simulations for OPPSSimulations for the OPPS were performed changing the depth to width ratio ()
0
2
4
6
8
10
12
14
0.0 0.5 1.0 1.5 2.0 2.5
X x 102
h OPP
S
2
bd
X
Z
Why is the Depth to Width Ratio Important?
Concentration gradients develop along the microchannel width and depth (10 m wide channel)
At one tenth of the channel length
150.6
150.8
151.0
151.2
151.4
151.6
151.8
152.0
152.2
152.4
0.2
0.4
0.6
0.8
1.0
0.20.4
0.60.8
(Con
cent
ratio
n/C
feed
)x10
3
X (w
idth
pos
ition)
Z (depth position)
=1
=100
center of
the channel
48.5
48.6
48.7
48.8
48.9
49.0
0.2
0.4
0.6
0.8
1.0
0.20.4
0.60.8
(Con
cent
ratio
n/C
feed
)x10
3
X (w
idth
pos
ition
)
Z (depth position)
=1
=100
At the END of the channel length
Why is the Depth to Width Ratio Important?
Concentration gradients develop along the microchannel width and depth (50 m wide channel)
At one tenth of the channel length At the END of the channel length
Our OPPS ModelAfter performing a wide range of simulations, an empirical equation for reduced plate height was developed
92.035.0
27.0
37.381.4
XOPPS PePe
h
105
5184352 22avg
eqOPPS
vDb
dRRh
0
2
4
6
8
10
12
14
0.0 0.5 1.0 1.5 2.0 2.5
Our model
X x 102
hO
PPS
Conclusions: HETP EquationIt was proven that reduced plate height models for OPPS can not be developed by analogy with OTS since concentration gradients along the depth influence the chromatographic characteristics.
A reduced plate height equation must include the following parameters: OPPS geometry, flow and adsorption characteristics.
By using the predictions of the OPPS simulator, an empirical equation has been developed for predicting plate height in OPPS.
Lapizco-Encinas, B.H., and Pinto, N.G., Performance Characteristics of Novel Open Parallel Plate Separator, Separation Science and Technology, Vol. 37, No. 12, 2745-2762, 2002.
Concentration of Trace Species by Displacement
Why concentrate trace species?In drug development it is necessary to concentrate samples of pharmaceuticals in order to continue with the experiments.
What is Displacement Chromatography?
Feed
Displacer
sampledevelopment
Product train
Displacement ChromatographyThe ability to separate and concentrate a sample makes displacement chromatography particularly attractive for the enrichment of trace species.Displacement chromatography has been used extensively in analytical applications.Displacement chromatography has an enormous potential for preparative applications since high product-throughput can be obtained by displacement.
Chen, T.W., N.G. Pinto and L. Van Brocklin, Rapid Method for DeterminingMulticomponent Langmuir Parameters for Displacement Chromatography, of Chromatogr., 484, 167 (1989).
Jen, S.C.D. and N.G. Pinto, Use of Sodium Salt of Poly(vinylsufonic acid)as a Low Molecular Weight Displacer for Protein Separations by Ion-Exchange Displacement Chromatography, J. of Chromatogr., 519, 87 (1990).
Jen, S.C.D. and N.G. Pinto, Theory of Optimization of Ideal Displacement Chromatography of Binary Mixtures, J. Chromatogr., 590, 3 (1992).
Jen, S.C.D. and N.G. Pinto, Influence of Displacer Properties on the Displacement Chromatography of Proteins:A Theoretical Study, Reactive Polymers, 19, 145 (1993).
Why Combine Displacement Chromatography with the OPPS?Preparation on conventional bench-scale systems is impractical in cases where the sample amount is limited or expensive. Preparative separations of trace species are often performed using microbore columns: detection sensitivity solvent
consumption.
column capacity pressure-drop.
ObjectivesTo investigate the capability of the OPPS for concentrating trace species.
To make a comparison with OTS, and quantify the performance of the microdevices by using the throughput and pressure drop
To perform a parametric study with the objective of maximizing throughput.
Equations
Throughput was calculated as follows:
jj
nc
j
ii
jj
nc
j
iiii
CK
Ca
CK
CKVmq
11
11*
DFT
S
TTmTH
The Langmuir isotherm model was used for simulating the non-linear behavior:
Comparing OPPS and OTS, Different Pe
0
2
4
6
8
10
12
14
16
18
2.4 2.6 2.8 3.0 3.2 3.4
Time/T0
C/C
F1
tracedisplacer
OTS, Pe = 1.5 x 10 4
0
2
4
6
8
10
12
14
16
18
1.5 1.7 1.9 2.1 2.3 2.5
Time/T0
C/C
F1
trace displacer
OPPS, Pe = 7.5 x 10 4
= 1
0
2
4
6
8
10
12
14
16
18
2.4 2.6 2.8 3.0 3.2 3.4
Time/T 0
C/C
F1
tracedisplacer
OTC, Pe = 7.5 x 10 4
2
4
6
8
10
12
14
16
18
1.5 1.7 1.9 2.1 2.3 2.5
Time/T0
C/C
F1
trace displacer
OPPS, Pe = 1.5 x 10 4
= 1
Comparing OPPS and OTS, Different
Pe x 10
0
1
2
3
4
5
6
7
8
0 1 2 3 4 5 6 7 8 9
- 4
THO
PPS
/ TH
OTS
OPPS, a= 1
OPPS, a= 4
OPPS, a= 9
OPPS, a= 25
Purity = 99%
Channel width or diameter = 50 m
Comparing OPPS and OTS, Different
Channel width or diameter = 20 m
0
5
10
15
20
25
30
0 1 2 3 4 5 6 7 8 9
Pe x 10- 4
THO
PPS
/ TH
OTS
OPPS, a= 1OPPS, a= 4OPPS, a= 9OPPS, a= 25
Purity = 99%b = r C= 10 m
Comparing OPPS and OTS, Different SameP
0
2
4
6
8
10
12
14
16
18
20
0 1 2 3 4 5 6 7 8 9 10 11 12 13
P x 102 (psia)
THO
PPS
/ TH O
TC
OPPS, a= 1OPPS, a= 4OPPS, a= 9OPPS, a= 25
Purity = 99%
Channel width or diameter = 50 m
Conclusions: Concentration of Trace Species
Simulations demonstrated that the rectangular geometry of the OPPS offers advantages over the circular geometry of the OTS for concentrating trace species.
It was proven that the OPPS has an enormous potential for concentrating trace species.
Product throughput increases with high depth-to-width ratios.
Lapizco-Encinas, B.H., and Pinto, N.G., A Comparison of Preparative Characteristics of OPPS and Microbore Columns for Concentration of Trace Species by Displacement Chromatography, in press, Journal of Chromatography A, 2002.
Conclusions: Concentration of Trace Species
Massively parallel OPPS offers significant advantages for high throughput. Silicon wafers can be stacked to create a larger microchannel.
5 stacked wafers make each channel five times larger.
• A single 5 cm wafer can have 1000 microchannels.
• By stacking up wafers we increase the cross-section area which increases the production tremendously.
chan
nel
chan
nel
1 mm
Adsorption IsothermsAdsorption Isotherm expresses the equilibrium between the amount of solute in the mobile phase and the solute adsorbed in the stationary phase.The shape of the adsorption isotherm can determine the chromatographic behavior of the solute.
++ Isotherm data
C
q* == Design of
separation process Product AByproduct B
Prediction of IsothermsIsotherm data are essential for scaling-up chromatographic processes.
The need for accurate equilibrium isotherm data is critical in preparative chromatography.
Traditionally, isotherms are obtained by batch methods, which are time consuming as they require significant amount of chemicals.
Dynamic methods based on chromatography can be used for the prediction of isotherm data with the advantages of higher accuracy and speed.
Why Use the OPPS for Isotherm Prediction
Low sample consumption, an advantage of microsystems, is very significant when dealing with expensive substances such as: proteins, pharmaceuticals, antibodies, etc.
Microsystems allow fast response.
Isotherm data obtained from the OPPS have the potential to be used for scaling up chromatographic operations.
Objectives for Isotherm Prediction
To predict equilibrium data for protein-salt systems by using the H-Root Method (HRM) and the numerical model of the OPPS.
To check the validity of the assumptions made in HRM.
To explore the capabilities of the OPPS as a tool for isotherm prediction.
H-Root MethodHRM was derived from the H-Transformation Theory (HTT) of chromatography (Helfferich and Klein, 1970).
HTT was developed to predict the chromatographic response.
HRM mainly consists of performing a back-calculation of HTT
0
2
4
6
8
10
12
14
16
18
1.5 1.7 1.9 2.1 2.3 2.5
Time/T0
C/C
F1
Operating conditionsLangmuir parameters
HTT
HRM
HRM HRM is restricted to compounds obeying the Langmuir isotherm model.
HRM consists of two main parts: linear elution experiments used to calculate the linear isotherm coefficient ai, and nonlinear frontal experiments to calculate the competitive interference parameter Kmi.
jj
nc
j
ii
jj
nc
j
iiii
CKm
Ca
CKm
CKmVmq
11
11*
HRM CalculationsLinear elution experiments: obtain retention time
Nonlinear frontal experiments: obtain breakthrough time
Time
Con
cent
ratio
n
TR3
TR2
TR1
Time
Con
cent
ratio
n TB3 TB2 TB1
0
0,
T
TTk iRi
linear capacity factor
0
0,
T
TTK iBi
frontal capacity factor
HRM Equations Linear elution experiments: calculation of ai
Nonlinear frontal experiments: calculation of Kmi
iii Caq *
bTTa iR
i
1
0
,
n
i
n
i
ii
KkCFKm
1
011
nj 11
n
i
j
i
j
j
ii
k
k
K
KCFKm
1
1
1
01
1
Simulations
Simulations were carried out for 3 protein-salt systems:1. Conalbumin-NaCl CON-NaCl. -Lactoglobulin-NaCl LAC-NaCl3. Myglobin-NaCl MYG-NaCl
%100%
realpredictedrealdeviation
Linear Elution ExperimentsResults Prediction of ai
iii Caq *
X,NaCl
0%
1%
2%
3%
4%
5%
6%
7%
8%
0 2 4 6 8 10 12 14 16
x 10 4
devi
atio
n p
redi
ctio
n of
ai
CONLACMYGNaCl
Pe NaCl = 1500
Nonlinear Frontal Experiments Results Prediction of Kmi
iii Caq *
-200%
-150%
-100%
-50%
0%
50%
100%
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
X,NaCl x 104
devi
atio
n p
redi
ctio
n of
Km
i
CONLACMYGNaCl
PeNaCl = 150
Conclusions: Isotherm Prediction by Using HRM and OPPS
It was found that operating and geometrical conditions have an effect on the accuracy of the isotherm predictions.
It was found that the HRM has an enormous potential for isotherm prediction under appropriate operating and geometrical conditions.
The application of the HRM is simple and it produces satisfactory results.
Lapizco-Encinas, B.H., and Pinto, N.G., Characterization of Equilibrium Adsorption Behavior of Protein-Salt Systems Using Micro Separators and H-Root Method, to be submitted, Journal Separation Science, 2002.
Concluding RemarksBy using the predictions of the OPPS simulator, an empirical equation has been developed for predicting plate height in OPPS. It was proven that geometry of the separator has an influence on the chromatographic performance.
It was found that that the OPPS has an enormous potential for concentrating trace species since it offers higher throughputs than the traditional circular columns.
Isotherm data were predicted successfully by employing the OPPS and the H-Root Method (HRM). The OPPS offers the advantage of saving time and chemicals. The application of the HRM is simple and it produces satisfactory results.
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