Acoustic emission during the ferroelectric transition Pm3¯m to P4mm in BaTiO3 and the ferroelastic transition R3¯m-C2/c in Pb3(PO4)2

Salje, Ekhard K. H.; Dul’kin, E.; Roth, M.

doi:10.1063/1.4918746

Cited by 28 publications

(23 citation statements)

References 36 publications

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“…Some experimental methods, such as AFM, diffuse X‐ray, or neutron scattering, and some transport measurements, measure N. Other methods explore the dynamics of moving domain walls (DMA, RUS, and RPS ) and find strong singularities near the ferroelastic transition point even when the transition is continuous. The transition always appears stepwise in these experiments, such as a burst of acoustic emission signals when the domain walls form . This observation is similar to the results of random first order transitions (RFOT) discussed by Kirkpatrick and collaborators for structural glasses and in the field of turbulence .…”

Section: Four Domain Glass Temperaturessupporting

confidence: 87%

“…The concept of “Domain Glass” was introduced in 2014 while “domain” related glass states (such as encountered in polar nano‐regions) were long understood to exist in relaxor materials where non‐ergodicity is one of the defining properties of the relaxor state . However, little is known about how the breaking of ergodicity occurs in the limiting case of weakly disordered systems.…”

Section: Introductionmentioning

confidence: 99%

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Domain glasses: Twin planes, Bloch lines, and Bloch points

Salje

Carpenter

2015

Physica Status Solidi (b)

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Ferroelastic materials can develop complex domain structures, which have properties of glassy systems (non-ergodicity, glass dynamics, glass transitions, and freezing). Four characteristic temperatures are defined for such domain glasses: the dynamical nucleation temperature T d where local correlated clusters can form glass states within a (tweed-) nano structure, T o the Vogel-Fulcher temperature of these precursor nanostructures, T pt the phase transition temperature where the (ferroelastic) transition occurs, and T K the Kauzmann temperature where the complex domain structure freezes. T d exists in most ferroelastic materials whereas the other transitions depend on the complexity of the domain patterns and hence on their thermal history. Shear collapse and rapid thermal quench of ferroelastic crystals preferentially lead to domain glasses whereas slow anneal produces mostly highly correlated pattern such as stripe patterns or single domain crystals. Domain glasses are compared with structural glasses and several examples for domain glass features are discussed.

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Section: Four Domain Glass Temperaturessupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Domain glasses: Twin planes, Bloch lines, and Bloch points

Salje

Carpenter

2015

Physica Status Solidi (b)

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“…Baró et al (2013) reported a very complete parallel between the acoustic emissions produced by a porous material under uniaxial compression and earthquakes. The same experimental techniques are widely used for the investigation of device materials such as ferroelectric, ferromagnets, and ferroelastics (Bolgár et al 2016;Dul'kin et al 2015;Guyot et al 1988;Hoffmann et al 2001;Salje et al , 2015Skal's'kyi et al 2009;Vives et al 1994) with a significant increase of published data over recent years on the acoustic emission during force-induced changes of microstructures.…”

Section: Introductionmentioning

confidence: 99%

Collapsing minerals: Crackling noise of sandstone and coal, and the predictability of mining accidents

Jiang

Chen

et al. 2016

American Mineralogist

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Mining accidents are sometimes preceded by high levels of crackling noise, which follow universal rules for the collapse of minerals. The archetypal test cases are sandstone and coal. Their collapse mechanism is almost identical to earthquakes: the crackling noise in large, porous samples follows a power law (Gutenberg-Richter) distribution P ~ E -e with energy exponents e for near critical stresses of e = 1.55 for dry and wet sandstone, and e = 1.32 for coal. The exponents of early stages are slightly increased, 1.7 (sandstone) and 1.5 (coal), and appear to represent the collapse of isolated, uncorrelated cavities. A significant increase of the acoustic emission, AE, activity was observed close to the final failure event, which acts as "warning signal" for the impending major collapse. Waiting times between events also follow power law distributions with exponents 2+x between 2 and 2.4. Aftershocks occur with probabilities described by Omori coefficients p between 0.84 (sandstone) and 1 (coal). The "Båth's law" predicts that the ratio between the magnitude of the main event and the largest aftershock is 1.2.Our experimental findings confirm this conjecture. Our results imply that acoustic warning methods are often possible within the context of mining safety measures, although it is not only the increase of crackling noise that can be used as early warning signal but also the change of the energy distribution of the crackling events.

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“…Avalanches are largely scale invariant and are described by statistical quantities. 15 Jerks were observed in heat flux measurements (thermal jerks), 17 AE (acoustic jerks) and slip avalanches in metallic glasses, [18][19][20][21][22][23][24] spikes in the polarization (electric jerks), and Barkhausen noise 2,14 (magnetic jerks). Each jerk signal is characterized by fairly random, often jagged profiles so that the question arises: is the time evolution predictable if one considers the averaged profiles?…”

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confidence: 99%

Parabolic temporal profiles of non-spanning avalanches and their importance for ferroic switching

Ding

Sun

et al. 2016

Applied Physics Letters

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Computer simulation of a ferroelastic switching process shows avalanche formation with universal averaged temporal avalanche profiles ⟨J(t)⟩, where J(t) is the avalanche “amplitude” at time t. The profiles are derived for the three most commonly used “jerk”-singularities, namely, the total change of the potential energy U via J(t) = (dU(t)/dt)2, the energy drop J(t) = −dU/dt, and the stress drop J(t) = −dτxy/dt. The avalanches follow, within the time resolution of our modeling, a universal profile J(t)/Jmax = 1 − 4(t/tmax − 0.5)2 in the a-thermal regime and the thermal regime. Broadening of the profiles towards a 4th order parabola arises from peak overlap or peak splitting. All profiles are symmetric around t/tmax = 0.5 and are expected to hold for switching processes in ferroic materials when the correlations during the avalanche are elastic in origin. High frequency applications of ferroic switching are constrained by this avalanche noise and its characteristic temporal distribution function will determine the bandwidth of any stored or transmitted signal.

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Acoustic emission during the ferroelectric transition Pm3¯m to P4mm in BaTiO3 and the ferroelastic transition R3¯m-C2/c in Pb3(PO4)2

Cited by 28 publications

References 36 publications

Domain glasses: Twin planes, Bloch lines, and Bloch points

Domain glasses: Twin planes, Bloch lines, and Bloch points

Collapsing minerals: Crackling noise of sandstone and coal, and the predictability of mining accidents

Parabolic temporal profiles of non-spanning avalanches and their importance for ferroic switching

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