Introduction to colloidal dispersions R.A.L. Jones, 4
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Introduction to colloidal
dispersions
R.A.L. Jones, 4
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Colloid
A colloid or colloidal dispersion is a system of two or
more components; a type of mixture intermediate between
homogeneous solution and heterogeneous mixtures with
properties also intermediate between a solution and a
mixture. Examples: butter, milk, cream, aerosols (fog, smog,
smoke), asphalt, inks, paints, glues and sea foam, are
colloids.
This field of study was introduced in 1861 by Scottish
scientist Thomas Graham. The size of dispersed phase particles in a colloid range
from 0.001 to 1 micrometers.
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Milk
Cow's milk contains, on average, 3.4% protein, 3.6%
fat, and 4.6% lactose
Milk supplies 66 kcal of energy per 100 grams.
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Butter
Commercial butter is about 80% butterfat and 15% water;
traditionally-made butter may have as little as 65% fat and
30% water.
Butterfat consists of many moderate-sized, saturated
hydrocarbon chain fatty acids. It is a triglyceride, an esterderived from glycerol and three fatty acid groups.
http://www.scientificpsychic.com/fitness/fattyacids.html
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Properties of colloids
High area of interface
Dispersion, aggregation, sedimentation
Stabilation: charge, cover by polymer etc.
Shear thickening or thinning
+
+
+
+-
-
--
-
-
-
- -
--
-
-
-
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A single colloidal particle in a liquid
Fluid mechanics point of view
Gravity
Grag is the force that resists the movement of a solid
object through a fluid (a liquid or gas).
Grag
Gravity
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Randomly moving sphere in a liquid
Expression for the frictional
force exerted on small
spherical objects in a viscous
fluid. The force (Stokes law
1851) can be written asF = 6 a v ,
where v is the velocity, a the
radius of the particle,
viscosity of a liquid.
Reynolds numberRe = va/
where is the density.
The gravitation force for
one sphere is
F g = 4/3 a 3 g,
where is the density
difference between thesphere and the liquid.
In balance F = F g . From this
the terminal velocity isv t = 2a 2 g/(9 ).
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Suspension of colloidal spheres
Particles are in random motion
How this is characterized: random walk
The directions of the successive steps are not correlated.
The mean value of the square of the displacements isproportional to the number of steps and thus the time t .
Denote the displacement vector by R(t). Then
<R(t)2 > = a t.
The factor a is related to the diffusion coefficient D.
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Randomly moving spheres in a liquid
Diffusion coefficient for the particles?
Equation of motion for a particle:
m d 2 R/dt 2 + b dR/dt = F,
where F is random force resulting from collisions of the
spheres with the liquid molecules, m the mass and b thedrag coefficient.
Drag force proportional to the velocity (Stokes law):
b = 6 a.
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Randomly moving sphere in a liquid
Use Cartesian coordinates x, y, z.
The sphere can move in random directions, all
coordinates behave the same way <x 2 > =<y 2 > =<z 2 > :
<R 2 > = 3 <x 2 >
Langevin equation of motion (x -direction)m d 2 x/dt 2 + b dx/dt = F,
The applied force is the random force F resulting from
collisions of the solute molecules with the sphere.
Inserting the relationsd(x 2 )/dt = 2x dx/dt and xd 2 x/dt 2 = d/dt(x dx/dt) – (dx/dt)2
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Randomly moving spheres in a liquid
Equation of motion
m/2 (d 2 x 2 /dt 2 ) -m(dx/dt)2 = -b/2(dx 2 /dt) + Fx
Take the average
b/2 d<x 2 >/dt = <xF> - m d/dt<xdx/dt> + 1/2m<dx/dt> 2 .
Because the direction of the random force is uncorrelated
with the position of the particle, <xF> = 0 .
The position and the velocity of the particle are not
correlated, <x dx/dt> = 0. From the equipartition theorem <1/2 m(dx/dt)2 > = 1/2 kT
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Equipartition theorem
The theorem of classical statistical mechanics and
thermodynamics states: the internal energy of a system
composed of a large number of particles at thermal
equilibrium will distribute itself evenly among each of the
quadratic degrees of freedom allowed to the particles of the system.
For example, the equipartition theorem says that the
mean internal energy associated with each degree of
freedom of a monatomic ideal gas is the same.
For a molecule of gas, each component of velocity has anassociated kinetic energy. This kinetic energy is, on
average, kT/2 , where k is Boltzmann constant and T
temperature.
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Randomly moving spheres in a liquid
Denoting X = <dx 2 /dt>
one obtains a first order equation
(dX/dt) + b/mX = 2kT/m
The general solution is X = 2kT/b + C exp(-b/mt)
Assume that t >> b/m , one obtains
<x 2 > = 2kT/bt or <x 2 > = 2Dt.
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Randomly moving sphere in a liquid
The motion is diffusive.
Einstein formula for the diffusion coefficient D = kT/b.
Sphere diffusing in a liquid D = kT/(6 a)
(Stokes-Einstein equation)
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Light scattering and diffusion coefficient
Let one consider solution of colloidal particles.
The random motion of the particles causes intensity
fluctuations of the scattered light.
The autocorrelation function of the scattering intensity
g(q,t) can be presented asg(q,T) = <I(q,t) I(q, t+T)>/<I(q,t)> 2 .
Magnitude of the scattering vector q = 4 n sin / where n
is the refractive index of the solution, the wavelength
and the scattering angle.
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Light scattering and diffusion coefficient
The correlation function g
can be fitted by a sum of
exponential functions giving
the decay time t which is
related to the diffusioncoefficient of the particles D
as
1/t = q 2 D .
D is affected by the
interaction between the
particles as
D = D 0 (1+a )
where is the concentrationof the particles and a an
interaction parameter.
The hydrodynamic radius R h
of the particles in associated
with D 0 asD 0 = kT/(6 R h )
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Example. SAXS and DLS
For a solution of fluorinated colloidal particles about the
same particle size distribution was obtained by using
SAXS and DLS.
DLS: He/Ne laser SAXS: 1.54 Å
J. Wagner et al. Langmuir 2000, 16, 4080-4085.
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Diffusion Coefficients for Four Hydrocarbons
in Water
Price and Söderman. Self-diffusion coefficients of somehydrocarbons in water: Measurements and scaling relations.
J. Phys.Chem. A 104, 5892-5894, 2000.
0.70 ± 0.06201.3/3.61.450.764o -xylene
0.77 ± 0.06180.5/3.51.420.95c -hexane
0.85 ± 0.33218.5/3.74.260.294n -hexane
0.86 ± 0.10192.8/3.65.720.225n -pentane
D we (10-9 m2 s-1)V (Å3)/R (Å)d D bulk
c (10-9 m2 s-1)b (10-3 kg (ms)-1 )molecule
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Forces between colloidal particles
System with a large amount of surface
Interfacial energy is large.
Jones book estimate: may be much bigger than kT.
Are dispersions then unstable? Other forces between particles of electrostatic origin.
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Interactions in colloidal solution
Excluded Volume Repulsion: This refers to the
impossibility of any overlap between hard particles.
Electrostatic interaction: Colloidal particles often carry an
electrical charge and therefore attract or repel each other.The charge of both the continuous and the dispersed
phase, as well as the mobility of the phases are factors
affecting this interaction.
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Interactions in colloidal solution
van der Waals forces: This is due to interaction between
two dipoles that are either permanent or induced. Even if
the particles do not have a permanent dipole, fluctuations
of the electron density gives rise to a temporary dipole in
a particle. This temporary dipole induces a dipole inparticles nearby. The temporary dipole and the induced
dipoles are then attracted to each other. This is known as
van der Waals force, and is always present, is short-
range, and is attractive.
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Interactions in colloidal solution
Entropic: According to the second law of thermodynamics,
a system progresses to a state in which entropy is
maximized. This can result in effective forces even
between hard spheres.
Steric: between polymer-covered surfaces or in solutionscontaining non-adsorbing polymer can modulate
interparticle forces, producing an additional repulsive
steric repulsion force (which is predominantly entropic in
origin) or an attractive depletion force between them.
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Example. Concentrated Silica ColloidalDispersions
The structure factors of colloidal silica dispersions at
rather high volume fractions (from 0.055 to 0.22) were
determined by small-angle X-ray scattering and fitted with
both the equivalent hard-sphere potential model (EHS)
and the Hayter-Penfold/Yukawa potential model (HPY). Both of these models described the interactions in these
dispersions successfully, and the results were in
reasonable agreement.
D. Qiu et a. A Small-Angle X-ray Scattering Study of the Interactionsin Concentrated Silica Colloidal Dispersions.
. Langmuir, 22 (2), 546 -552, 2006.
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SAXS of Concentrated Silica ColloidalDispersions
The strength and range of the interaction potentials
decreased with increasing particle volume fractions, which
suggests shrinkage of the electrical double layer arising
from an increase in the counterion concentration in the
bulk solution. However, the interactions at the average interparticle
separation increased as the volume fraction increased.
D. Qiu et a. A Small-Angle X-ray Scattering Study of the Interactions inConcentrated Silica Colloidal Dispersions.. Langmuir, 22 (2), 546 -552, 2006.
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Forces between colloidal particles: van der
Waals
Interaction between two atoms (particles)
Potential between two particles is assumed to be of
form -C/r 6
For two macroscopic bodies with separation h :
U(h) = -C/r 6 1 2 dV 1 dV 2
where 1 and 2 are the number densities of the
volume elements dV 1 and dV 2 .
.
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Example.
An atom at the distance D from
medium of density .
The interaction between the molecule
and a ring of radius x whose centre
is z away from the molecule is
-2 x dx dz C/(x 2 +z 2 )3 .
The total interaction energy is
w(D) = -2 C D dz 0
x dx/(x2+z3)3
= -2 C/(12 D 3 ).D
x
x
z
y
r dxdz
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Example.
Assume that instead of one atom there is a sheet of
atoms.
The unit area and thickness of this atomic sheet is dz at
the distance z from the semi-infinite sheet.
The energy per unit area is simply
-22C/12z3,
where is the density.
The constant A = 2C is called the Hamaker constant.
Then the interaction energy is
U(h) = -A/12h2 h z-3 dz.
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van der Waals and Hamaker constant
Surface-surface interaction
The total interaction energy per unit area between two
semi-infinite sheets of the same material was
U = 2 /12D2
The constant A = 2 C is the Hamaker constant. Magnitude
around 10-19 J
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vdW interaction energies between particles of
different geometries
Atoms w ~ -1/r6
Two spheres w ~ -1/r
Atom-surface w ~ -1/r3
Sphere-surface w ~ -1/r
Two parallel cylindersw ~ -1/r3/2
Two surfaces w ~ -1/r2
Israelachvili p 177
;
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-10
12
-1010
-108
-106
-104
-102
-100
r
w ( r )
atoms
spherescylinderssurfaces
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Problems
Pairwise additivity of the forces. In practice all other atoms
in the system have to be taken into account.
For large separations, over 10 nm, the effects of the finite
speed of the propagation of fields arising from the
fluctuating dipoles become significant.
More powerful approach – Lifshitz theory.
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Charged surfaces
Electrostatic interactions are important.
In water: counterions of the colloids float freely: Screening
Screened Coulomb interaction: exponential decay in
strength with distance
Consider two ionized parallel surfaces in the water.
Counter ions are in the solution, but provide charge
neutrality. The counter ions are attracted to the surfaces.
Their concentration profile is diffuse.
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Charged surfaces in water
Temperature T
Let be the electrostatic potential and the number density of
ions of valency z at any point between the surfaces.
Chemical potential = ze + kT ln
Boltzmann distribution for the density of ions at any point = 0 exp(-ze /kT) (0 is assumed 0)
Poisson-Bolzmann equation gives the
concentration profile for the counter ions.-
-
-
-
-
-
-
-D
+
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Poisson-Bolzmann equation
The charge of the ions is ze.
Poisson equation for the net charge density at point x:
ze = - 0 d 2 /dx 2
Combine with the Boltzmann distribution
d 2
/dx 2
= - ze 0 = -(ze 0 0 ) exp(-ze /kT)
PB: d 2 /dx 2 = -(ze 0 0 ) exp(-ze /kT)
Poisson-Bolzmann equation is a non-linear second-order
differential equation.
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Surface charge
PB equation
d 2 /dx 2 = -(ze 0 0 ) exp(-ze /kT)
Boundary conditions
Symmetry requirement: the field must vanish at the midplane /dx = 0
Overall electroneutrality: total charge in the gap must be
equal (opposite sign) to that at surfaces.
Let be the charge density at surfaces. Then
= - 0 D/2
ze dx = 0 0 D/2
d 2
/dx 2
dx = 0 (d /dx)D/2
= 0 (d /dx)s
The field E s at the surface is (d /dx)s = / 0 .
-D/2 D/2
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Counterion concentration profile away from a
surface
PB equation d 2 /dx 2 = -(ze 0 0 ) exp(-ze /kT)
Solution (x,T) = (kT/ze) ln( cos2 Kx),
where K(T)2 = (ze)2 0 0 kT
At x=0, =0 and /dx = 0 for all K At any point x
E x = d /dx = 2kTK/ze tanKx
The counter ion distribution profile
(x,T) = 0 exp(-ze /kT)
= 0 / cos2 Kx
-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 11
1.05
1.1
1.15
1.2
1.25
1.3
1.35
x
1 / c o s
2 K
x
K=0.5, 0.3333, 0.25, 0.2, 0.1667
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Limitations of PB equation
Continuum, mean field
Breaks down at small distances
Ion-correlation effects (polarization, vdW)
Finite-ion size
Discreteness of surface charges Solvation forces
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Electrostatic double layer forces
Consider pair of parallel ionized surfaces
Overall charge neutralization achieved by counter ions.
Electrostatic potential (x) at a distance x from the
surface.
Boltzmann equation gives the density of ions: n = n(0)exp (-ze (x)/(kT)) where k Boltzmann constant and T
temperature, ze ion charge and the potential (x).
The potential is determined by the distribution of net
charge (z) by the Poisson equation = d2 /dx2.
Counter ions balance the surface charge = ze.
Poisson-Boltzmann equation
d2 /dx2 = -(ze n(0)/ ) exp(-ze /kT)
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Electrostatic double layer forces
Example. Surface is in contact with a solution of an
electrolyte which is a solution of a univalent salt (e.g.
sodium chloride).
Concentration of positive ions n + = n(0) exp(-ze /kT)
Concentration of negative ions n - = n(0) exp(ze /kT) The net charge density = ze(n + +n - )
d 2 /dx 2 = -(ze n(0)/ ) sinh (-ze /kT)
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Debye-Hückel approximation
Boundary conditions for solution:
Isolated plate: and /dx approach 0 as x approaches
infinity.
If the potential is small one can approximate sinh x ~ x.
Debye-Hückel approximation for the potential(x) = (0) exp(- x)
where
= (2e 2 n(0)z 2 /( 0 kT) )1/2 .
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Debye screening length
Electric fields are screened in an electrolyte.
Screening is the damping of electric fields caused by the
presence of mobile charge carriers.
The length which characterizes the screening 1/ is calledthe Debye screening length.
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Stabilizing colloids
Coating with a polymer layer.
When two particles approach each other, the
concentration of the polymer inside the gap increases.
This increases the osmotic pressure and causes a
repulsive force.
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Spatial Correlation of Spherical Polyelectrolyte
Brushes in Salt-Free Solution As Observed by
Small-Angle X-ray Scattering
Linear chains of poly(acrylic acid) (PAA) are chemically
grafted onto the surface of a colloidal poly(styrene)
particle.
Robillard et al. Macromolecules33, 9109-9114, 2000
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Depleting interactions
A solution contains both particles and e.g. dissolvedpolymer.
Polymer coils are excluded from a depletion zone bear the
surface of the colloid particles. When the depletion zones
of two particles overlap there is a net attractive force
between the particles arising from unbalanced osmoticpressure.
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Depleting interactions
Dilute solution of particles
Osmotic pressure P osm = N/V kT
N number of polymers in volume V of solution.
The net potential F dep = -P osm V dep
V dep is the total volume of particles from which thepolymers are excluded.
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Model potential describing the depletion effect
First theoretical consideration Asakura and Oosawa J.
Chem Phys. 22, 1255, 1954
Suspension of colloidal particles, radius a , and non-
absorbing polymer
Depletion potential U = infinity for r 2a
U = A for 2a < r < 2a+rg
U = 0 for r > 2a+rg
Here rg is the radius of the polymer molecule
The constant A is related to the polymer osmotic pressureand the volume of the overlapping depletion zones
between two particles.
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Results
With the model potential the phase behaviour of the
mixture could be predicted.
At low polymer concentrations fluidlike arrangement of
colloidal particles
At high polymer concentrations colloidal fluid-crystalcoexistence
Also metastable gel phases
S.MiIlett et al. Phys. Rev. E, 1995, 51, 1344-1352.
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Stability and phase behaviour of colloids
Interaction from repulsive to attractive
Adding salt
Add poor solvent
Remove grafted chains from the surface
Add non-adsorbing polymer to increase the size of thedepletion zone.
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Crystallization of hard sphere colloids
Stable suspension: the forces between colloidal particles
are repulsive at all distances.
Spherical particles: The systems crystallizes as the
concentration of particles reaches high enough level.
Colloidal crystals: true long range order
Simplest model: hard sphere model
Good model for colloidal particles stabilized by polymer
coating. The coating need to be thin compared to the
radius of the particles.
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Origin of the phase transition
A way of thinking: excluded volume
Two spheres cannot overlap. This leads to repulsive force
between the spheres.
Ideal gas of N atoms in a volume V: S i = k ln(aV/N)
Gas atoms have a finite volume b . The volume accessibleto any given atom is V-Nb.
Now the entropy S = k ln(a(V-nb)/N) = S i – k ln(1-bN/V)
If the free volume of atoms is low S = S i – k b N/V
The corresponding free energy F = F i + k T b N/V
There is effective repulsion between particles whichcauses the crystallization.
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Structures
Close packed: HCP or FCC
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Colloids with weakly attractive interactions
Grafted colloids
Weak interaction: liquid-solid transition
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Colloids with strongly attractive interactions
Aggregation
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Crystal-nucleation rate (Auer and Frenkel
Nature 2001, 1020-1023
Probability (per particle) that a spontaneous fluctuation
will result in formation of a critical nucleus depends on the
free energy
G c as P c = exp(- G c /kT)
Free energy needed to form the nucleus G(r) = 4/3 r 3 + 4 r 2 ,
where is the number density of the solid and the solid-
liquid interfacial energy density.
The maximum of G at r = 2 /( |) where | is the
difference in chemical potential of the solid and the liquid. The nucleation rate f per unit volume is proportional to the
probability P :
f = c P c = c exp(- G c /kT) = c exp(-16 /3 3 /( |)2 )
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Complementary Use of Simulations and Molecular-
Thermodynamic Theory to Model Micellization
Brian C. Stephenson, Kenneth Beers, and Daniel
Blankschtein. LANGMUIR Volume: 22 Issue: 4 Pages:
1500-1513 Published: 2006
Computersimulation
Molecular-thermodynamic
model
ThermodynamicDescription of
Micelle aggregation
Property
predictiongmic