Statistics of Dislocation Slip Avalanches in Nanosized Single Crystals Show Tuned Critical Behavior Predicted by a Simple Mean Field Model

Friedman, Nir; Jennings, Andrew T.; Tsekenis, Georgios; Kim, Ju Young; Tao, Molei; Uhl, Jonathan T.; Greer, Julia R.; Dahmen, Karin A.

doi:10.1103/physrevlett.109.095507

Cited by 185 publications

(272 citation statements)

References 29 publications

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“…The often-observed power-law distribution of avalanche sizes is believed to reflect proximity to a nonequilibrium critical point. A simple mean-field model [18] that exhibits tuned critical behavior in the depinning universality class agrees with experimental data on slip avalanches during the slow deformation of crystalline materials [10], amorphous materials [13], and granular materials [7,19], as well as many other systems with yielding behavior [7].…”

Section: Introductionsupporting

confidence: 58%

“…Furthermore, for independent samples, no information is lost: Each "step" in the CCDF estimate is at the location of a data point, so the entire data set can be recovered (except information about the time order of samples, which is irrelevant if they are independent). Key predictions of avalanche models about scaling forms of size and duration PDFs can be cast equally well in terms of the CCDF [10,13].…”

Section: Extracting Avalanche Statistics From Experimental Signalsmentioning

confidence: 99%

“…Avalanches are observed in a variety of dynamical systems, including magnetic materials [1,2], charge density waves [3,4], vortices in superconductors [5], earthquakes [6,7], crystal plasticity [7][8][9][10][11], and amorphous plasticity [7,8,[12][13][14][15][16][17]. For these last two cases, deformation occurs through small jumps caused by slipping weak spots in the material.…”

Section: Introductionmentioning

confidence: 99%

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Avalanche statistics from data with low time resolution

et al. 2016

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Extracting avalanche distributions from experimental microplasticity data can be hampered by limited time resolution. We compute the effects of low time resolution on avalanche size distributions and give quantitative criteria for diagnosing and circumventing problems associated with low time resolution. We show that traditional analysis of data obtained at low acquisition rates can lead to avalanche size distributions with incorrect power-law exponents or no power-law scaling at all. Furthermore, we demonstrate that it can lead to apparent data collapses with incorrect power-law and cutoff exponents. We propose new methods to analyze low-resolution stress-time series that can recover the size distribution of the underlying avalanches even when the resolution is so low that naive analysis methods give incorrect results. We test these methods on both downsampled simulation data from a simple model and downsampled bulk metallic glass compression data and find that the methods recover the correct critical exponents.

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Section: Introductionsupporting

confidence: 58%

Section: Extracting Avalanche Statistics From Experimental Signalsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Avalanche statistics from data with low time resolution

et al. 2016

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“…Crystal plasticity as a critical phenomenon has also been confirmed by other experimental techniques such as highresolution extensometry [17] and compression of nanopillars and micro-pillars [19,20], as well as by numerical simulations of discrete dislocation dynamics [7,[21][22][23]. Moreover, the statistics of slip avalanches-i.e.…”

Section: Introductionmentioning

confidence: 58%

Universal fluctuations and extreme statistics of avalanches near the depinning transition

et al. 2013

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We derive exact predictions for universal scaling exponents and scaling functions associated with the statistics of maximum velocities vm during avalanches described by the mean field theory of the interface depinning transition. In particular, we find a robust power-law regime in the statistics of maximum events that can explain the observed distribution of the peak amplitudes in acoustic emission experiments of crystal plasticity. Our results are expected to be broadly applicable to a broad range of systems in the mean-field interface depinning universality class, ranging from magnets to earthquakes.

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“…The assumption that the rate of small event activity increases with increasing stress emerges naturally from this simple model and has been observed in earthquake faults 5 , deformation experiments 27,28 and other models 4,20-24 . (As mentioned above, however, transient effects from the surrounding region or other fault sections obscure the observed increase of event rates, rendering observed rates alone insufficient to predict the onset of impeding large earthquakes 7,8 ).…”

Section: Resultsmentioning

confidence: 99%

Probing failure susceptibilities of earthquake faults using small-quake tidal correlations

et al. 2015

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Mitigating the devastating economic and humanitarian impact of large earthquakes requires signals for forecasting seismic events. Daily tide stresses were previously thought to be insufficient for use as such a signal. Recently, however, they have been found to correlate significantly with small earthquakes, just before large earthquakes occur. Here we present a simple earthquake model to investigate whether correlations between daily tidal stresses and small earthquakes provide information about the likelihood of impending large earthquakes. The model predicts that intervals of significant correlations between small earthquakes and ongoing low-amplitude periodic stresses indicate increased fault susceptibility to large earthquake generation. The results agree with the recent observations of large earthquakes preceded by time periods of significant correlations between smaller events and daily tide stresses. We anticipate that incorporating experimentally determined parameters and fault-specific details into the model may provide new tools for extracting improved probabilities of impending large earthquakes.

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Statistics of Dislocation Slip Avalanches in Nanosized Single Crystals Show Tuned Critical Behavior Predicted by a Simple Mean Field Model

Cited by 185 publications

References 29 publications

Avalanche statistics from data with low time resolution

Avalanche statistics from data with low time resolution

Universal fluctuations and extreme statistics of avalanches near the depinning transition

Probing failure susceptibilities of earthquake faults using small-quake tidal correlations

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