math ématiques de la diffusion restreinte dans des milieux poreux
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Math ématiques de la diffusion restreinte dans des milieux poreux. Denis S. Grebenkov Laboratoire de Physique de la Matière Condensée CNRS – Ecole Polytechnique, Palaiseau, France. Séminaire du groupe « Milieux poreux » , 12 Janvier 2007, Paris, France. Outline of the talk. - PowerPoint PPT PresentationTRANSCRIPT
MathMathématiques de la ématiques de la diffusion restreinte dans diffusion restreinte dans
des milieux poreuxdes milieux poreux
Denis S. GrebenkovDenis S. Grebenkov
Laboratoire de Physique de la Matière Laboratoire de Physique de la Matière CondenséeCondensée
CNRS – Ecole Polytechnique,CNRS – Ecole Polytechnique, Palaiseau, Palaiseau, FranceFrance
Séminaire du groupe « Milieux poreux », 12 Janvier 2007, Paris, France
Outline of the talkOutline of the talk
Studying porous structures…Studying porous structures… Basic principles of NMR diffusion Basic principles of NMR diffusion
imagingimaging Pulsed-gradient spin-echo (PGSE) Pulsed-gradient spin-echo (PGSE)
experimentsexperiments General description via matrix General description via matrix
formalismsformalisms Different diffusion regimes Different diffusion regimes Conclusions and perspectivesConclusions and perspectives
Grebenkov, Rev. Mod. Phys. (submitted)
Studying porous Studying porous structures…structures…
• Material sciences: rocks, sols, colloids, tissues, ...• Petrol search: sedimentary rocks
• Medicine: brain, lung, bone, kidney, etc.
Length scales: μm - mmTime scales: ms - s
Schematic principle of Schematic principle of NMRNMR
Nuclei of spin ½ (e.g., protons)
Application of a magnetic fieldB0
Two physical states
B0
Different populations
B0
Local magnetization
B0
m
Schematic principle of Schematic principle of NMRNMR
Phase at time T
Static magnetic field B0
x
z
y
Time-dependent linear magnetic field gradient
x
z
y
Schematic principle of Schematic principle of NMRNMR
is the projection of a 3D Brownian motion of a nucleus onto a given gradient direction
Local magnetization:
Total transverse magnetization:
Example: free diffusionExample: free diffusion
can be seen as 1D Brownian motion
Isotropy of 3D Brownian motion
is a Gaussian variable, therefore
t
f(t)
T1
-1
with the rephasing conditionto cancel the imaginary part
Apparent diffusion Apparent diffusion coefficientcoefficient
Free diffusion:
D is a measure of how fast the nuclei diffuse in space
Apparent diffusion Apparent diffusion coefficientcoefficient
Effective « slow down »of the diffusive motion
Restricting geometrySmaller ADC
Smaller length scale
Apparent diffusion Apparent diffusion coefficientcoefficient
Normal volunteer
Healthy smoker
Patient with severe emphysema
van Beek et al. JMRI 20, 540 (2004)
Can one make a reliable diagnosis at earlier stage?
Pulsed-gradient spin-Pulsed-gradient spin-echo (PGSE)echo (PGSE)
t
f(t)
T1
-1
δ
Tanner & Stejskal, JCP 49, 1768 (1968)
PGSE: diffusive PGSE: diffusive diffractiondiffraction
For T long enough, one “measures’’ a form-factor
Diffusion in a slab of width L:
Coy and Callaghan, JCP 101, 4599 (1994).
PGSE: pro & controPGSE: pro & contro
Direct access to the propagatorDirect access to the propagator Easy experimental implementationEasy experimental implementation Characteristic length scales of the Characteristic length scales of the
geometry via diffusive diffractiongeometry via diffusive diffraction
Assumption of very narrow pulses is not Assumption of very narrow pulses is not always valid, especially for gas diffusionalways valid, especially for gas diffusion
Material inhomogeneity may destroy Material inhomogeneity may destroy diffraction peaksdiffraction peaks
Lost information about the motion Lost information about the motion between 0 and T.between 0 and T.
Pro
Contro
Axelrod & Sen, JCP 114, 6878 (2001); Grebenkov, RMP (submitted)
General descriptionGeneral description
Total dephasing of a diffusing spin:echo
time
gyromagnetic ratio
temporal profile
spatial profile
spin trajectory(Brownian
motion)field intensity
Averaging individual magnetizations:
Moments of the Moments of the dephasingdephasing
Multiple correlation Multiple correlation functionsfunctions
Multiple correlation Multiple correlation functionsfunctions
Multiple correlation Multiple correlation functionsfunctions
Reflecting boundariesReflecting boundaries
First momentFirst moment
Second momentSecond moment
For weak magnetic fields, one has
Slow diffusion regime Slow diffusion regime (small p)(small p)
t
f(t)
T1
-1
Slow diffusion regime Slow diffusion regime (small p)(small p)
Slow diffusion regime Slow diffusion regime (small p)(small p)
10-2
10-1
100
-0.015
-0.01
-0.005
0
0.005
0.01
0.015
p
Grebenkov, RMP (submitted)
Fast diffusion regime Fast diffusion regime (large p)(large p)
Robertson, PR 151, 273 (1966)
Example: cylinderExample: cylinder
10-2
100
102
10-2
100
102
104
p
Dapp
(cm2/s)
experimentinterpolation (165)slow diffusion (160)
Hayden et al. JMR 169, 313 (2004); Grebenkov, RMP (submitted)
Localization regime Localization regime (large q)(large q)
Stoller et al., PRA 44, 7459 (1991); de Swiet & Sen, JCP 100, 5597 (1994)
Hurlimann et al. JMR 113, 260 (1995)
Water proton NMR
Diagram of diffusion Diagram of diffusion regimesregimes
Grebenkov, Rev. Mod. Phys. (submitted)
100
101
102
103
10-2
10-1
100
101
102
q
p
inaccessible experimentally
localization
motional narrowing
slow diffusion
SummarySummary
Geometry and field inhomogeneity: Geometry and field inhomogeneity: Temporal dependence :Temporal dependence : Physical parameters:Physical parameters:
A general theoretical description A general theoretical description of restricted diffusion in of restricted diffusion in
inhomogeneous magnetic fieldsinhomogeneous magnetic fields
Slow diffusion regime (small p): S/VSlow diffusion regime (small p): S/V Fast diffusion regime (large p): Fast diffusion regime (large p):
sensitivity to Lsensitivity to L Localization regime: non-Gaussian Localization regime: non-Gaussian
behaviorbehavior
Open problems and Open problems and questionsquestions
Efficient numerical implementation, in Efficient numerical implementation, in particular, for model structures (sphere particular, for model structures (sphere packs, fractals, …)packs, fractals, …)
Computation of the high moments, Computation of the high moments, transition to the localization regimetransition to the localization regime
Inverse problem: what can one say about Inverse problem: what can one say about the geometry from experimental the geometry from experimental measurements?measurements?
Development and optimization of the Development and optimization of the temporal and spatial profiles to probe temporal and spatial profiles to probe porous structuresporous structures