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To Study the Colloidal Properties of
Semiconductor Nanoparticles using DynaLight Scattering
Research Report (Chem 751)
Pushpa Chhetri
May 9, 2014
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Importance of DLS in the scientific world
DLS
Study the properties of colloids
Particle size distribution of particles
Observing aggregation effects in colloids
Application in observe the stability with time eg. Emulsi
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Why and when DLS is used
Polymer and particle science: routine characterization
Experimental physicist and physical chemist: study gels, netwliquid crystals, hydrodynamic interactions
Obtaining precise particle size
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Video Display
Autocorrelacin
digital ymicrocomputadora
PMT
Abertura
Lente
LASER
Schematic of DLS Instrument
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Particles move or diffuse in random walk
fashion Collision of neighboring solvent molecules
It Probes density or conc. fluctuations
The fluctuation in scattering intensity oflaser due to the Brownian motion ofparticles in liquid can be recorded andparticle size can be calculated usingStokes-Einstein relation.
+
+
+ +
+
+-
-
--
-
-
+
Brownianmotion
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Ia(t)
Tiempo, t
Pequeo
Mediano
Largo
Effect of Diffusion
Intensity Vs time plotPhase
scatte
PMT
Fluctu
the fl
partic
that s
Becau
interf
the n
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How well a particle can scatter depends on
MW or V
Polarizability of the particle which is related to refraction of particle relative to the solvent.
Is= f(np,ns).(MW)2.I0
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Obtaining particle size
Step 1. Obtaining raw data as intensity of scattered signal
Step 2. diffusion coefficient from fluctuating light scattering signal
T = Temperature
= viscosity of solvent
R = particle radius
Step 3. obtaining autocorrelation function0
0.2
0.4
0.6
0.8
1
1.2
1
1.
33
1.76
2.
33
3.
1
4.
11
5.
45
7.
22
9.58
12.7
1
16.8
6
22.3
6
29.6
6
39.3
4
Relativein
tensity
ofscattered
signal
Diameter (nm)
25 nM DSNPs in Me
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Autocorrelation function: definition
C(t) =
C(t) = averaged over many wigglesof the fluctuating intensity Is
Is(t) = Intensity at given time t
Is(t-t) = Intensity at earlier time t-t
Study of similarity between the values
of Is(t) and Is(t-t)
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5 min duration on 200 nm particles DLS module performs approximately 15 million
multiplications
And obtains C(t) for one value of t (eg. t=20microsecond for channel #1)
The instrument makes 64 such sets of calculationssimultaneously for 64 different values of t.
0
100000
200000
300000
400000
500000
600000
700000
800000
-6 4 14 24
C(t')
# of ch
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Obtaining particle size
Step 1. Obtaining raw data as intensity of scattered signal
Step 2. diffusion coefficient from fluctuating light scattering signal
T = Temperature
= viscosity of solvent
R = particle radius
Step 3. obtaining autocorrelation function
1/= 2DK2
Or D = (1/2K2)*(1/ )
decay
Cha
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Challenges
Challenges in collecting data
- Sample preparation: sonication- Sample purification: dust is big enemy
- Right use of cuvette
Challenges in interpreting data
Intensity weight
Volume weight
Number weight
Distribution of particle size manipulations depends on: x axis sc
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Advantages
Simple experimental set up
Less expensive
Hydrodynamic size range 1nm to 1m
Eg
micro-emulsion
Peptides
Micelles
Macromolecules
Polymer
Paint pigments
disadvantages
Clean samples required
Only transparent samp
Does not work for Settlsamples
Gives data for everythin
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Experimental datainterpretations
0
100000
200000
300000
400000
500000
600000
700000
800000
-6 4 14 24 34 44
C(t')
# of channel
Autocorrelation function
0
0.2
0.4
0.6
0.8
1
1.2
1
1.
33
1.76
2.
33
3.
1
4.
11
5.
45
7.
22
9.58
12.71
16.
86
22.
36
29.
66
39.
34
52.
18
69.
22
91.
81
121.78
161.53
214.
25
284.
19
376.
95
500
Relativ
e
intensity
ofscattered
signal
Diameter (nm)
25 nM DSNPs in MeOH
No TBAP run 102 before EC
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My observations as a DLS data us
The main goal is to determine diffusion coefficient D of partraw data of scattered light intensity signal using decay const
DLS is highly sensitive to aggregation.
Effect of Migration is none.
Brownian motion induced diffusion as well as the natural cois prevalent which constantly fluctuates the net intensity.
Mathematic behind calculations is quite complicated.
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References:
PSS Nicomp ZLS 380 manual Experimental Data obtained using PSS Nicomp ZLS 380 in Dr
lab, UNR.
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Thank You
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C(0) =
C() = 2
> 2
Now the function C(t) for diffusing particles must fall from the value
at t=0 to the baseline value 2 atvery large t
Ideal case of uniform particle size: exponential
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