dynamics of confined polymer in flow 陳彥龍 yeng-long chen...
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Dynamics of Confined Polymer in Flow
陳彥龍 Yeng-Long Chen
Institute of Physics and Research Center for Applied Science
Academia Sinica
To understand and manipulate the structure and
dynamics of biopolymers with statistical physics
Fish schooling Blood flow
Micro- and Nano-scale Building Blocks
Nuclei are stained blue with DAPIActin filaments are labeled red with phalloidin Microtubules are marked green by an antibody
Endothelial Cell
F-Actin
DNA
Diameter: 7nm Persistence length : ~10 m
3.4 nm
Persistence length : ~ 50 nm
Rg
p
Organ Printing
Mironov et al. (2003)
Boland et al. (2003)
Forgacs et al. (2000)
Organ printing and cell assembly
• Cells deposited into gel matrix fuse when they are in proximity
of each other
• Induce sufficient vascularization
• Embryonic tissues are viscoelastic
• Smallest features ~ O(mm)
From Pancake to Tiramisu
Edible Paper
Moto restaurant
Chicago
Inkjet printer used as food processor
Food emulsions printed onto edible paper
Edible Menus
Not too far into the future :
“We had to go out for dinner because the printer ran out of ink!”
• High throughput
• Low material cost
• High degree of parallelization
Advantages of microfluidic chips
Efficient device depends on controlled transport
Channel dimension ~ 10nm - 100 m
Fluid plug reactor from Cheng group, RCAS
Confining Macromolecules
Theory and simulations help us understand dynamics of macromolecules
Multi-Scale Simulations of DNA
10 nm
2 nm
3.4 nm
1 nm
Atomistic
C-C bond length
100 nm
Persistence length ≈ 50nm
Nanochannels
Essential physics :
DNA flexibility
Solvent-DNA interaction
Entropic confinement
1F
2F
1F
2F
1F
2F
1F
2F
1 m 10 m
Radius of gyration
Coarse grainingMicrochannels
Multi-component systems : multiple scales for different components
Molecular Dynamics
- Model atoms and molecules using
Newton’s law of motion
Monte Carlo
- Statistically samples energy and configuration
space of systems
Cellular Automata
- Complex pattern formation from simple computer instructions
Large particle in a granular flow
Polymer configuration sampling
Sierpinksi gasket
-If alive, dead in next step
-If only 1 living neighbor, alive
Our Methods
Coarse-grained DNA Dynamics
DNA as Worm-like ChainL = 22 m
Ns = 10 springsNk,s = 19.8 Kuhns/spring
Marko and Siggia (1994)
2a
f S(t)
f ev(t) f W(t) -DNA 48.5 kbps
DNA is a worm-like chain
Model parameters are matched to TOTO-1 stained -DNA
Parameters matched in bulk are valid in confinement !
Expt
Chen et al., Macromolecules (2005)
Brownian Dynamics
))(( xUUf fpf
dtm
tUdttRd
)()(
Explicit inclusion of solvent molecules on the micron scale is extremely computational expensive !!
solvent = lattice fluid (LBE)
How to treat solvent molecules ??
dtm
dttfdttUd
)()(
: particle friction coef.
v1
v2
v3
Brownian motion through fluctuation-dissipation
flucfricwallWLCev ffffff
)'()'(2)','(),( rrttTktrftrf Bflucfluc
Ladd, J. Fluid Mech (1994)
Ahlrichs & Dünweg, J. Chem. Phys. (1999)
Hydrodynamic Interactions (HI)
Free space Wall correction
Particle motion perturbs and contributes to the overall velocity field
Stokes Flow
000W0s00 ),(),(v)(v),,(v frrrrrrfrr Ω
W
W2
v0
v0
ηp
Solved w/
Finite Element Method
For Different Channels
Force
z
velocityfluid.max
velocityDNAavg.fR
)2//(max Hv
Sugarman & Prud’homme (1988)
25 m
Detection points at 25 cm and 200 cm
detector
-DNA in microcapillary flow
Parabolic Flow
DNA Separation in Microcapillary
Longer DNA higher velocity
Chen et al.(2005)
40m
T2 DNA after 100 s oscillatory Poiseuille flow
relaxWe
v
h
V(y,z)
Dilute DNA in Microfluidic Fluid Flow
Chain migration to increase as We increases
-DNA Nc=50, cp/cp*=0.02
We=( relax)
eff = vmax / (H/2)
Non-dilute DNA in Lattice Fluid Flow
Lattice Size = 40 X 20 X 40, corresponding to 20 x 10 x 20 m3 box
As the DNA concentration increases, the chain
migration effect decreases
Nc=50, 200, 400
H = 10 m
We=100 Re=0.14
Ld
40m
oThot
oTcold
Particle Current
Soret Coefficient
y
TccD
y
cDJ Ty
)1(
y
yT
yc
ccD
DS T
T
/
/
)1(
1
Migration of a species due to temperature gradient
Mass Diffusion Thermal Diffusion
Thermal-induced DNA Migration
Thermal fractionation has been used to separate molecules
Many factors contribute to thermal diffusivity –
a “clean” measurement difficult
Wiegand, J. Phys. Condens. Matter (2004)
Hydrodynamic interactions
Experimental Observations
Colloid Particle size
DT ↑ as R ↑ (Braun et al. 2006)
DT ↓ as R ↑ (Giddings et al. 2003, Schimpf et al., 1997)
Factors that affect DT:
Solvent quality :
DT changes sign with good/poor solvent (Wiegand et al. 2003)
DT changes sign with solvent thermal expansion coef.
Polymer molecular weight
DT ~ N0 (Schimpf & Giddings, 1989, Braun et al. 2005, Köhler et al., 2002, …)
DT ↓ as N ↑ (Braun et al. 2007)
Electrostatics ?
Thermally Driven Migration in LBE
2 4 6 8 100y, m
g(y)
T=2
ThotTcold
T=0
T=10
T(y)=temperature at height y )'()'()(2)','(),( rrttyTktrftrf Bflucfluc
TH TC
Thermal migration is predicted with a simple model)(
)/ln(
0
0
TT
cc
D
DT
Thermal Diffusion Coefficient
D(m2/s) DT (x 0.1 m2/s/K)
Duhr et al. (2005)
(27bp & 48.5 kbp)1 (48.5 kbp) 4
67.9 kbp DNA 0.82 4.1±0.6
48.5 kbp DNA 1 4.0±0.6
19.4 kbp DNA 1.7 4.6 ±0.6
Simple model appears to quantitatively predict DT
DT is independent of N – agrees with several expt’s
What’s the origin of this ?
Fluid Stress Near Particles
Thot Tcold
T=4
T=0
T=2
T=7
Dissipation of Y-dependent fluctuations leads to a hydrodynamic stress in Y
))(( xUUf fpf
Momentum is exchanged between monomer and fluid
through friction
Particle Thermal Diffusion Coefficient
Diameter
(m)
D
(m2/s)
DT (m2/K/s)
dT/dy=0.2K/m
DT (m2/K/s)
dT/dy=0.4K/m
0.0385 5.6 2.3±0.4 2.1±0.3
0.0770 2.8 1.1±0.2 1.12±0.05
0.1540 1.4 0.60±0.04 0.59±0.01
DT decreases with particle size 1/R
– agrees with thermal fractionation device experiments
DT independent of temperature gradient
(Many) Other factors still to include …
Thermal and Shear-induced DNA Migration
y/H0 0.4 0.8
g(y)
1.0
1.6
0.2
T=4
y/H0 0.4 0.80.2 0.6 1.0
1.0
2.0),(
),,(
yg
TygTH TC
Thermal gradient can modify the shear-induced migration profile
Thermal diffusion occurs independent of shear-induced migration
40m
)(
)/ln(
CH
CHT
TTD
D
As N ↑, D ↓, ST↑
stronger shift in g(y) for larger polymers
T=4
Summary and Future Directions
• Shear and thermal gradient can be used to control the position of DNA in the microchannel and their average velocity
• Shear and thermal driving forces for manipulating DNA appear to have weak or no coupling => two independent control methods.
• Inclusion of counterions and electrostatics will make things more complicated and interesting.
f ev(t)
f r(t)
f vib(t)
f bend(t) ~2nm
σmHow “solid” should the polymer be when it starts acting as a particle ?
As we move to nano-scale channels, what is the valid model?
How close are we from modeling blood vessels ?
The Lattice Boltzmann Method
Replace continuum fluid with discrete fluid positions xi and discrete velocity ci
collt dt
dnnvn
ni(r,v,t) = fluid velocity distribution function
Hydrodynamic fields are moments of the velocity distribution function
Boltzmann eqn.
)],([),(),( trtrntttcrn iiii n
)()],([ eqj
jjiji nnLtr n
Lij = local collision operator
=1/ in the simplest approx.
3D, 19-vector model
Fluid particle collisions relaxes fluid to equilibrium
Ladd, J. Fluid Mech (1994)
Ahlrichs & Dünweg, J. Chem. Phys. (1999)