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Transcript of Aging in amorphous materials Sergio Ciliberto Collaborators: L. Bellon, L.Buisson Laboratoire de...
![Page 1: Aging in amorphous materials Sergio Ciliberto Collaborators: L. Bellon, L.Buisson Laboratoire de Physique, ENS de Lyon UMR5672 CNRS Summer complexity school.](https://reader038.fdocuments.us/reader038/viewer/2022103022/56649d0c5503460f949dfeb5/html5/thumbnails/1.jpg)
Aging in amorphous materials
Sergio Ciliberto
Collaborators: L. Bellon, L.Buisson
Laboratoire de Physique, ENS de Lyon UMR5672 CNRS
Summer complexity schoolWye 9-17 July
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COMPLEXITY AND EXPERIMENTS IN PHYSICS
Test toy models in well controlled experiments
Construct simple experiments to give new insight to the theoretical developments
Examples:
a) Hydrodynamique turbulence and pattern formations
b) Stochastic motion of Brownian particles in a complex environment
c) Material science - crack prediction
- aging of amorphous material
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1) Phenomenologicl introduction to glasses
2) Aging, memory effects and history dependence
3) Thermal fluctuations and the Fluctuation Dissipation Relations during aging
4) The electrical thermal noise of two materials: a) a polymer after a quench b) a colloidal glass during the sol-gel transition.
5) Comparisons of the experimental results with those of other experiments and of models of aging.
6) The mechanical noise.
7) Conclusions
Outline
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Phenomenological introduction to the physics of glasses and to physical aging
Type of glasses
• Structural glasses
• Magnetic glasses
•Colloids
What is a glass ?
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Viscosity as a function of Tg/T
• Tg is the glass transition temperature
• At Tg the viscosity is about 1012 Pa s
• For T>Tg the Young modulus falls down of several orders of magnitude
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Mechanical measurements
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Dielectric measurements
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1) Phenomenologicl introduction to glasses
2) Aging, memory effects and history dependence
3) Thermal fluctuations and the Fluctuation Dissipation Relations during aging
4) The electrical thermal noise of two materials: a) a polymer after a quench b) a colloidal glass during the sol-gel transition.
5) Comparisons of the experimental results with those of other experiments and of models of aging.
6) The mechanical noise.
7) Conclusions
Outline
![Page 9: Aging in amorphous materials Sergio Ciliberto Collaborators: L. Bellon, L.Buisson Laboratoire de Physique, ENS de Lyon UMR5672 CNRS Summer complexity school.](https://reader038.fdocuments.us/reader038/viewer/2022103022/56649d0c5503460f949dfeb5/html5/thumbnails/9.jpg)
Aging and Memory effect in a polymer
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Aging of PMMA ( Tg= 388K )
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= dielectric constant measured with continuous ramp
Tg
Tg
Reference curveCurve with a cooling stop
= dielectric constant measured with a cooling stop
Memory effect in PMMA
Evolution of at f=0.1Hz as a function of T
Reference curve
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Memory effect in PMMA
Evolution of at f=0.1Hz as a function of T
= dielectric constant measured without a cooling stop
= dielectric constant measured with a cooling stop
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Memory effect in spin glasses
From: V. Dupuis, E. Vincent, J.P. Bouchaud, J. Hammann, A.Ito, H. Aruga Katori, Aging, rejuvenation and memory effects in Ising and Heisenberg spin glasses, Phys. Rev B 64 (17),174204,(2001). Also in cond-mat/0104399
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Kovacs Effect
Measure of the Volume
(I) direct quench from T0 to T2
(II) Temperature change from T1 to T2
(III) The same as II but for a larger T1
Fast quench
Slow ramp
- The sample reminds its thermal history - The response of the system depends on the quench speed
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Frustation
What kind of models can be used ?
Important concept
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Energy landscape
Bouchaud trap model
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Memory effects and trap model
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Smart experimental procedures, based either
on multiple cycles of cooling, heating and waiting times
or on the modulation of the applied external fields
have shown the existence of spectacular effects of aging in glassy materials, such as
rejuvenation and memory.
These studies have been extremely useful to fix several important constraints for the phenomenological models of aging.
Aging has been often characterized by studing the response functions of the systems
Question: is the analysis of fluctuations useful ?
Aging in glassy materials
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1) Phenomenologicl introduction to glasses
2) Aging, memory effects and history dependence
3) Thermal fluctuations and the Fluctuation Dissipation Relations during aging
4) The electrical thermal noise of two materials: a) a polymer after a quench b) a colloidal glass during the sol-gel transition.
5) Comparisons of the experimental results with those of other experiments and of models of aging.
6) The mechanical noise.
7) Conclusions
Outline
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V and q are two conjugate variables
V()
q()R() = is the response function
The thermal fluctuation spectrum S()= <| V()| 2 > is
S()= Im{ R()}
4 K T
Typical examples are :
< |U ( ) |> 2
= 4 K T R o
N y q u is t
U
Density fluctuations
L
H
M
< M > 2
m' '
E ''< | L ( ) |>
2
F
(U,q) (L ,F ) (M ,h)
FLUCTUACTION DISSIPATION THEOREM in thermodynamic equilibrium
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In a glass at T < TG the physical properties of the
material depend on the aging time tw after the
temperature quench. Thus FDR takes the following form:
FDR can be used to define an effective temperature of the system
Fluctuation Dissipation Relation (FDR) in a weakly out of equilibrium system
(Cugliandolo,Kurchan 1992.)
In terms of correlation function FDR takes the form
At equilibrium
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Experimental study of fluctuations
Why is interesting to study fluctuations and FDR in experiments?
I) The violation of FDT is model dependent.
II) Does it depend on the material ?
III) What is the statistics of the signal?
IV) Are fluctuations Gaussian or not ?
V) Is the effective temperature independent on the observables ?
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1) Phenomenologicl introduction to glasses
2) Aging, memory effects and history dependence
3) Thermal fluctuations and the Fluctuation Dissipation Relations during aging
4) The electrical thermal noise of two materials: a) a polymer after a quench b) a colloidal glass during the sol-gel transition.
5) Comparisons of the experimental results with those of other experiments and of models of aging.
6) The mechanical noise.
7) Conclusions
Outline
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Dielectric measurements
material under study
VRi amplifierV
Rib
Equivalent circuit of the sample
VZ
a
The corresponding noise spectrum Sz of VZ is:
,is the thermal noise voltage of R
The sample impedance is:
VR
RC
a
b
electrodes
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Dielectric Measurement on polycarbonate
Experimental set-up
Electrical features for noise measurements Input voltage noise 5nV/ Hz1/2 for f > 2Hz Input current noise 1fA / Hz1/2
Temperature stability 0.1 % Max cooling rate -1K/s
Dielectric properties are measured by a precise current amplifier.
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a) The sample is heated at Ts=440K=1.05 Tg and quenched at a temperature Tf<Tg.
b) The aging time tw is defined as the time spent at T< Tg
c) At Tf we measure FDR and the noise statistics.
d) This experimental procedure is repeated several times for the same Tf
e) The results of the different quenches are averaged to reduce statistical noise
Typical temperature quench
Fast rate 1K/s Slow rate 0.06 K/s
Experimental procedure
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Noise spectra
Measure at Tf =0.79Tg
Fast quench at 1K/s
Sample is heated at Ts=1.05 Tg and rapidly quenched
(~2min) at Tf =0.79 Tg.
The aging time tw is defined as the time spent at T< Tg.
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Aging at T=333K
T=0.79Tg
T=1.05Tg
T=0.79Tg
T=1.05Tg
Electrical response of the sample
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As a function of frequency at different tw
Effective temperature at Tf =0.79Tg
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1500 s after the quench 75000 s after the quench
Noise signals as a function of time at Tf =0.79Tg
When FDT is violated the fluctuations are not gaussian
PDF of the signal
Polycarbonate polarisation noise
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PDF of the time between two pulses
For the trap model of aging
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Measure at Tf =0.98Tg , slow quench
Noise spectra
tw=200s
FDTexperiment
tw=7200s
FDTexperiment
Time evolution of Teff
Tf
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Tf =0.98 Tg
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Measure at Tf =0.93Tg
Slow quench at 0.06K/s
Tf=0.93Tg
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PDF at Tf =0.93Tg , fast quench
PDF at Tf =0.93Tg , slow quench
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Summary of the results
• Dielectric measurements in a polymer show a violation of the FDT.
• The effective temperature (after a very fast quench) is huge at small tw
• The amplitude and the persistence time of the violation are decreasing functions of frequency.
• The maximum frequency where the violation is observed scales as 1/ tw
•The strong violation is produced by a very intermittent dynamics.
• The statistics of the signal is highly non Gaussian
• The statistics of the time between two peaks is similar to the one assumed by the trap model
• The intermittency depends on the quenching rate
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1) Phenomenologicl introduction to glasses
2) Aging, memory effects and history dependence
3) Thermal fluctuations and the Fluctuation Dissipation Relations during aging
4) The electrical thermal noise of two materials: a) a polymer after a quench b) a colloidal glass during the sol-gel transition.
5) Comparisons of the experimental results with those of other experiments and of models of aging.
6) The mechanical noise.
7) Conclusions
Outline
![Page 38: Aging in amorphous materials Sergio Ciliberto Collaborators: L. Bellon, L.Buisson Laboratoire de Physique, ENS de Lyon UMR5672 CNRS Summer complexity school.](https://reader038.fdocuments.us/reader038/viewer/2022103022/56649d0c5503460f949dfeb5/html5/thumbnails/38.jpg)
Other systems presenting intermittency
Local measurements of polymer dielectric properties using an AFM.
E. Vidal Russel, N. E. Israeloff, Nature 408, 695 (2000).
Time Resolved Correlation in Diffusing Wave Spectroscopy has shown a strong intermittency in the slow relaxation dynamics of a colloidal gel
Cipelletti et al., J.of Phys.: Cond. Matt.
Velocity fluctuations of a particle in a colloidal gel present non Gaussian statistics and are intermittent
Weeks et al. Phys.Rev.Lett.89,95704(2002)
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Interpretation of intermittency• Huge Teff have been observed in numerical simulation of domain growth systems. A. Barrat PRE 57 (1998) 3629
• Intermittency could be an indication of an activated process in a complex landascape For example: - Trap model predicts non trivial violation of FDT associated to an intermittent dynamics. - The system evolves in deeper and deeper valleys - The dynamics is fundamentally intermittent because either nothing moves or there is a jump between two traps.
• Heat exchange process between an aging system and the thermal bath may be intermittent. A. Crisanti, F. Ritort, cond-mat/0307554
• The dependence on the quenching rate is probably related to the fact that: ‘far from equilibrium the system explores regions of the potential energy landscape distinct from that explored in thermal equilibrium’ S. Mossa, F. Sciortino, cond-mat/0305526 E.M. Bertin, J.-P. Bouchaud, J.-M. Drouffe, C. Godreche cond-mat/0306089
Time statistics
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Comparisons between different models.
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Time distributions
Experimental results:
Trap model of ref. : J.P.Bouchaud, J.Phys.,2, 1705,(1992).
Trap model of ref.: P. Sibani, J. Dell, Europhys. Lett. 64, 8, (2003)
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Teff in other experiments
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1) Phenomenologicl introduction to glasses
2) Aging, memory effects and history dependence
3) Thermal fluctuations and the Fluctuation Dissipation Relations during aging
4) The electrical thermal noise of two materials: a) a polymer after a quench b) a colloidal glass during the sol-gel transition.
5) Comparisons of the experimental results with those of other experiments and of models of aging.
6) The mechanical noise.
7) Conclusions
Outline
Question: Have the fluctuations of different observables,the same behaviour ?
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Conclusions• Dielectric measurements show a non trivial violation of FDT during aging, in two very different materials
• The origing of the huge violation is a strongly intermittent dynamics.
• The intermittency depends on the quenching rate
• The dependence on the observables of the fluctuations is unclear. It is not the same for the two materials.
• High order statistics are certainly useful to understand the dynamics of these systems.
• Several models show a qualitative agreement with these observations.
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Cracks
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•May simple models describe the formation of a crack?
• Is the crack formation similar to a critical phenomenon?
• If yes,what are the experimental conditions?
• Is the life time of a sample submitted to a tensile stress predictable?
•What is the role of heterogeneities ?
Motivations:
Crack sound emission and models
Heterogeneous materials
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Sound detected by the piezoelectric detectors
M3
M2
M1
M4
M1,M2,M3,M4 microphones
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0.8<P/Po <1
0.4<P/Po <0.60.2<P/Po <0.40.0<P/Po <0.2
0.6<P/Po <0.8 0.0<P/Po <10.8<P/Po <1
0.4<P/Po <0.60.2<P/Po <0.40.0<P/Po <0.2
0.6<P/Po <0.8 0.0<P/Po <10.8<P/Po <1
0.4<P/Po <0.60.2<P/Po <0.40.0<P/Po <0.2
0.6<P/Po <0.8 0.0<P/Po <10.8<P/Po <1
0.4<P/Po <0.60.2<P/Po <0.40.0<P/Po <0.2
0.6<P/Po <0.8 0.0<P/Po <10.8<P/Po <1
0.4<P/Po <0.60.2<P/Po <0.40.0<P/Po <0.2
0.6<P/Po <0.8 0.0<P/Po <10.8<P/Po <1
0.4<P/Po <0.60.2<P/Po <0.40.0<P/Po <0.2
0.6<P/Po <0.8 0.0<P/Po <1
EVENTS LOCALISATION FOR INCREASING PRESSURE
applied pressure: P = A t Po= pressure at failure
The density of microcracks is very large along the final macroscopic crack
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Micro Crack Localisation
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1) Experimental data show a strong analogy between crack formation in composite materials and percolation models.
2) For any load: Power law distributions of the Acoustic energy N() -
Time intervals t between two acoustic events N(t) t-
3) When the system is loaded at imposed pressure a critical
behavior is found near the critical pressure:
Summary of the experimental results
Robustness of these results?How do they depend on physical properties?
Cumulative acoustic energy
as a function of time
E(t) ( 1- t / ) -
MODEL MATERIALS
(wood and fiber glass large samples)
Glassy polymer foams
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500 µm
Uniaxial tensile test under
X-ray tomography of PU solid foams S. Deschanel, G. Vigier (INSA de Lyon)
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500 µm
Time evolution
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0
5
10
15
20
25
30
0 1000 2000 3000 4000 5000 6000 7000 8000
temps (s)
co
ntr
ain
te (
MP
a)
0
5
10
15
20
25
30
35
40
45
Nb
re d
e s
alv
es
lo
ca
lis
ées
cu
mu
lée
s
0 1000 3000 5000 7000
time (s)
40
30
20
10
0
Cumulative number
of acoustic emissions
30
20
10
0
Str
ess
(Mpa
)Initial state 8.6% strain
16.6% strain12.6% strain
Uniaxial tensile test (1)