Transcript Document

Instruments, ultrasound,
and oils
Frank Podd
Procter Department of Food Science
University of Leeds
16/11/2002
Content
• Background
• Ultrasound Velocity
• Ultrasound Spectrometry
• New Developments
 Single particle scattering theory
 Multiple particle scattering theory
 New electronics
 New cell design
Food Processing
David Borrill
Biochemistry
Mike Morgan
Leeds Food Science
Colloids
Eric Dickinson
Emulsions
Brent Murray Malcolm Povey
Interfaces
Ultrasound
Small molecule
interaction
Bronek Wedzicha
Instruments within the colloids group
• Rheometers,
• Brewster angle microscope, Langmuir trough, surface
shear rheometers, bubble expansion chambers,
• Surface layers,
• Simulations,
• Confocal microscopy,
• Atomic force microscopy,
• Acoustic microscopy,
• Ultrasound creaming rig,
• Ultrasound velocity,
• Ultrasound spectroscopy.
Ultrasound & Food Emulsions
Liquid oil particle
coated with
surfactant
1 mm
micelle
surfactant
protein
Overall ultrasound
property depends on:
• Continuous phase
• Dispersed phase
• Surfactant
• Droplet shape &
its size distribution
Thermal property
Viscosity
Compressibility
Ultrasound Velocity
The Wood equation
Bulk modulus
v
Density
B


1

Adiabatic compressibility
Ultrasound Velocity
Urick equation
Phase volume of jth phase
v
1

,
   j j ,    j  j
j
   2  (1   ) 1 ,
j
   2  (1   )  1
Modified Urick Equation
1
1
2
2  2 1     
v
v1
 a 2   a 1
2  1 

 

1 
  a 1
1 
 2

 C
1C p1 
2
p2

R
1





C
1
p
1


2C p 2 2
  (  1)
R
1C p1
  a 2   a1
  2  1  2 2  1 

 
  
31 2
  a1
  1 
2
Sound velocity in margarine
1650
Velocity / m s
-1
1600
1550
1500
1450
I
II
III
1400
-10
0
10
20
Temperature / °C
30
40
Detecting adulteration in olive oil?
The velocity profile during
crystallisation for virgin
olive oil shows a smooth
curve.
This adulterated virgin
olive oil displays a spikier
velocity curve
Crystallization in cocoa butter emulsions
Figure 4: Plot of solids against temperature for 20.75% (v/v) WACB-in- w ater
emulsions cooled at 5°C/hour (0.8% Tw een 20 & 1.0% sodium caseinate).
Figure 7: Plot of solids against time for 20.75% (v/v) WACB-in-water emulsions (0.8% Tween 20)
crystallised isothermally at 14.2, 15.0, 15.5 and 15.8°C. Heterogeneous volume particle size
distribution models are fitted.
1
0.3
0.6
0.4
0.2
14.2°C
Het vol psd model
15.0°C
Het vol psd model
15.5°C
Het vol psd model
15.8°C
Het vol psd model
0.25
0.2
Sodium
caseinate
Solids
Solids
0.8
0.15
Tween 20
0.1
0
0.05
15
10
5
Temperature (°C)
0
0
2
4
6
Time (minutes)
8
10
Do surfactants affect crystallisation?
Plot for 20% v/v WACB oil-in-water emulsion cooled at 5°C / hour. A three
stage process occurs with sodium caseinate during the
crystallisation:
1.
Bulk volume crystallisation initially,
2.
Surface crystallisation (the sodium caseinate macromolecule
protects the droplets more than Tween 20),
3.
Instability stops the sodium caseinate from preventing droplet
collisions, thus the crystallisation rate increases.
1500
Ultrasonic velocity (m/s)
1495
1490
1485
1480
Sodium caseinate
1475
Tween 20
1470
1465
1460
1455
0
5
10
15
Temperature (°C)
20
25
Does crystallisation occur due to
micelle transport?
Plot of solid content for an 32% v/v n-hexadecane oil-in-water emulsion
crystallised at 6°C. In the first 7 days a dialysis tube was used as a barrier to
prevent collisions between supercooled liquid and solid droplets. Thereafter, the
contents of the dialysis tube were mixed with the liquid.
Solids (n -hexadecane fraction)
1
0.8
0.6
Mixing of
emulsion
droplets
0.4
0.2
0
0
5
10
15
Time (days)
20
US spectroscopy
Particles scatter ultrasound…
The effect of scattering can be a frequency
dependence in the ultrasonic velocity and attenuation
Ultrasound spectroscopy has opened a new
dimension in food emulsion study
• Rheology
• Component analysing
• Stability monitoring (flocculation, creaming,
coalescences, etc.)
• Particle sizing ( particle size distribution, PSD)
New Developments @ Leeds
(in the ultrasound group)
New stable scattering theory with known
error bounds.
Multi-particle theory enabling an
estimation of particle spacing.
New US instrumentation
New US sensors
Scattering background
Later Epstein and Carhart (J. Acous. Soc. Am. 1953) and
Allegra and Hawley (J. Acous. Soc. Am. 1972) developed a
model for the attenuation of sound through a
suspension of isolated spheres due to thermal and
viscous effects.
Ultrasound propagation was first formulated by
Lord Rayleigh (The Theory of Sound 1892) .
Although the theory is exact it is prone to
numerical difficulties and so an alternative
solution technique is required.
Results of new single particle
scattering theory
Magnitude of error known
Well conditioned numerically
Not constrained to geometry
Single Particle System
Incident plane wave
Thermal fields.
1mM particle at
1MHz generates a
thermal field of 1mM
depth
Reflected wave
Transmitted wave
Single oil droplet suspended in medium
The Multiple Scattering Problem
Multiple scattering of the thermal field is different to multiple scattering of
the acoustic field. If the particles stay together for the period of the wave
thermal fields will scatter coherently. If the particles move in less than
this time then the thermal scattering will be incoherent.
Oil particle
(1 mm diameter)
in water
Thermal field ( 1 mm
thick in water at 1
MHz) generated by
particle pulsation in
the presence of the
excitation field
Results of new multiple particle
scattering theory
Enables the determination
of inter-particle spacing?
New Cell Design
Designed for crystallisation experiments
• Small sample volume (2ml)
• Low coefficient of thermal expansion
• Small heat capacity
• High thermal conductivity
• Cell designed for high pressure experiments
• Choice of transducers - 1MHz to 30MHz frequency range
New Electronics
• Measure the pulse amplitude in addition to the group velocity
• Velocity and attenuation spectrometry
• Accurate temperature measurement – detect heat from
crystallisation?
• Aiming for inline use
• Low cost!
Monitoring stability and creaming
The Acoustiscan builds up a profile
of property differences along the
cell height. It uses both pitch catch
and pulse-echo techniques
Colloidal stability can be quantifiably determined using the Acoustiscan. A major factor in colloidal stability is the
particle size distribution. This can also be determined ultrasonically, by using the FSUPER for example.
FSUPER
This type of characterisation can be peformed by the Frequency
Scanning Ultrasound Pulse Reflectometer (FSUPER)
The particle size distribution can be estimated from the analysis of
the frequency dependent ultrasonic velocity and attenuation data.
The system can also monitor emulsion stability, measure the
amount of surfactant covering the emulsion droplets and identify
substances spectroscopically.
The method has the potential to characterise emulsions on-line, and
in real time.
The FSUPER has several advantages, such as: Rapid and accurate measurement
 Wide frequency range (1-15MHz)
 A small amount of sample required ( ~ 15ml)
Acknowledgements
Many thanks go to Malcolm Povey, Scott
Hindle, and Toni Crosthwaite for supplying
data and providing help and advice.