Minimal descriptions of cyclic memories

Paulsen, Joseph D.; Keim, Nathan C.

doi:10.1098/rspa.2018.0874

Cited by 23 publications

(40 citation statements)

References 44 publications

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“…Indeed, similar memory effects have been found in experiments and simulations of model amorphous systems [2,9,10], granular systems [11], and glasses [12][13][14][15]. The interactions between particles can vary and even the nature of the reversibility can vary for different systems [9,[16][17][18][19][20]. The core idea of particles rearranging and exploring possible states to find a reversible one still applies, regardless of the specifics of the system.…”

Section: Introductionmentioning

confidence: 55%

Embedding orthogonal memories in a colloidal gel through oscillatory shear

et al. 2020

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It has recently been shown that in a broad class of disordered systems oscillatory shear training can embed memories of specific shear protocols in relevant physical parameters such as the yield strain. These shear protocols can be used to change the physical properties of the system and memories of the protocol can later be read out. Here we investigate shear training memories in colloidal gels, which include an attractive interaction and network structure, and discover that such systems can support memories both along and orthogonal to the training flow direction. We use oscillatory shear protocols to set and read out the yield strain memories and confocal microscopy to analyze the rearranging gel structure throughout the shear training. We find that the gel bonds remain largely isotropic in the shear-vorticity plane throughout the training process suggesting that structures formed to support shear along the training shear plane are also able to support shear along the orthogonal plane. Orthogonal memory extends the usefulness of shear memories to more applications and should apply to many other disordered systems as well.

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Section: Introductionmentioning

confidence: 55%

Embedding orthogonal memories in a colloidal gel through oscillatory shear

et al. 2020

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“…2b), we observe a memory at γ read = 3%, but we also see evidence for a memory above 3%: MSD in that region is distinct from the "3" curve. The result is very different when we exchange γ 1 , γ 2 and apply the larger amplitude last ("3, 4"): the signature of the smaller value is gone, which differs from the expected behavior of a dilute suspension [2,6,28]. These results bear a resemblance to return-point memory (RPM).…”

Section: Application Of Cyclic Shear Deformation With Di↵erent Amplitmentioning

confidence: 85%

“…Measuring relative to TS4 ("4,3 from TS4"), or applying the 4% amplitude last before readout ("3,4"), shows a 4% memory only. [6,20,21,28]. In the rest of this paper, we explore the possibility that RPM could at least partially explain memory in amorphous solids.…”

Section: Application Of Cyclic Shear Deformation With Di↵erent Amplitmentioning

confidence: 99%

Global memory from local hysteresis in an amorphous solid

Keim

Hass

Kroger

et al. 2020

Phys. Rev. Research

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A disordered material that cannot relax to equilibrium, such as an amorphous or glassy solid, responds to deformation in a way that depends on its past. In experiments we train a 2D athermal amorphous solid with oscillatory shear, and show that a suitable readout protocol reveals the shearing amplitude. When shearing alternates between two amplitudes, signatures of both values are retained only if the smaller one is applied last. We show that these behaviors arise because individual clusters of rearrangements are hysteretic and dissipative, and because different clusters respond differently to shear. These roles for hysteresis and disorder are reminiscent of the returnpoint memory seen in ferromagnets and many other systems. Accordingly, we show how a simple model of a ferromagnet can reproduce and key results of our experiments and of previous simulations. Unlike ferromagnets, amorphous solids' disorder is unquenched; they require "training" to develop this behavior.We are familiar with our own memory and forgetfulness, and digital memories are woven into our lives. But throughout our environment, matter is being driven without relaxing to equilibrium, potentially forming memories of its own: specific information about past conditions that can be recalled later. As a simple example, rubber "remembers" the extrema of all deformations since it was cured [1]; the material stiffens as it is driven beyond those limits, allowing the memory to be read. Further afield, dilute non-Brownian suspensions that are sheared cyclically [2, 3] and charge density-wave conductors given electrical pulses [4,5] share distinctive rules for remembering multiple input values. Studying memory can thus reveal unexpected connections between systems and prompt new examinations of their physics [6].Recently, a new memory behavior was discovered in amorphous solids [7]. This vast class of materials features atoms or particles packed with a minimum of the regular placement found in crystals. Amorphous solids made of molecules, bubbles, macroscopic grains, or colloidal particles ( Fig. 1a) deform in remarkably similar ways: applied stress tends to cause localized clusters of particles ("soft spots") to rearrange, marking transitions among a vast set of metastable states [8][9][10]. Yet under oscillatory shear, after many cycles these rearrangements can become periodic; particles' trajectories become loops [7,[11][12][13][14][15]. Molecular dynamics simulations of glasses [7,16,17] and experiments on bubble rafts [18] showed that after a strain amplitude γ 1 has been applied repeatedly to reach a "trained" steady state, the material retains an imprint of its training: a readout protocol can reveal γ 1 . This protocol is illustrated in Fig. 1b: cycles of increasing amplitude γ read are applied, beginning with an amplitude below the training value [2, 3, 18]. After each cycle, one measures the mean squared displacement (MSD) of the particles, relative to the trained state. A local minimum in the MSD as a function of γ read shows evidence of the t...

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“…These can be modeled as hysterons, twostate elements which switch between phases "0" and "1" when the global driving field U passes through the upper and lower "bare" switching fields u + i or u − i (Fig. 1) [13,[15][16][17][18][19][20][21][24][25][26][27]. Indeed, collections of noninteracting hysterons-the well-studied Preisach model-describe surprisingly complex sequences of transitions and satisfy RMP [13,16,17,20,21,27].…”

Section: Introductionmentioning

confidence: 99%

Profusion of transition pathways for interacting hysterons

Hecke

2021

Phys. Rev. E

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The response, pathways, and memory effects of cyclically driven complex media can be captured by hysteretic elements called hysterons. Here we demonstrate the profound impact of hysteron interactions on pathways and memory. Specifically, while the Preisach model of independent hysterons features a restricted class of pathways which always satisfy return point memory, we show that three interacting hysterons generate more than 15 000 transition graphs, with most violating return point memory and having features completely distinct from the Preisach model. Exploring these opens a route to designer pathways and information processing in complex matter.

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Minimal descriptions of cyclic memories

Cited by 23 publications

References 44 publications

Embedding orthogonal memories in a colloidal gel through oscillatory shear

Embedding orthogonal memories in a colloidal gel through oscillatory shear

Global memory from local hysteresis in an amorphous solid

Profusion of transition pathways for interacting hysterons

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