Predicting plasticity in disordered solids from structural indicators

Riedl, David; Ozawa, Masakuni; Patinet, Sylvain; Stanifer, Ethan; Shang, Bruce Z.; Ridout, Sean A.; Xu, Bin; Zhang, G.; Morse, Peter K.; Barrat, Jean‐Louis; Berthier, Ludovic; Falk, Michael L.; Guan, Ping; Liu, A.J.; Martens, Kirsten; Sastry, Srikanth; Vandembroucq, Damien; Lerner, Edan; Manning, M. Lisa

doi:10.1103/physrevmaterials.4.113609

Cited by 159 publications

(158 citation statements)

References 82 publications

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“…accuracy for faster cooling rate was observed before 22,35,38,52 , as the critical structural difference becomes increasingly difficult to distinguish 38 . The more relaxed glasses, on the other hand, have a much smaller population of fertile sites that exhibit larger shear susceptibility, making the recognition easier and prediction more robust.…”

Section: Resultsmentioning

confidence: 96%

Predicting orientation-dependent plastic susceptibility from static structure in amorphous solids via deep learning

Fan

2021

Nat Commun

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It has been a long-standing materials science challenge to establish structure-property relations in amorphous solids. Here we introduce a rotationally non-invariant local structure representation that enables different predictions for different loading orientations, which is found essential for high-fidelity prediction of the propensity for stress-driven shear transformations. This novel structure representation, when combined with convolutional neural network (CNN), a powerful deep learning algorithm, leads to unprecedented accuracy for identifying atoms with high propensity for shear transformations (i.e., plastic susceptibility), solely from the static structure in both two- and three-dimensional model glasses. The data-driven models trained on samples at one composition and a given processing history are found transferrable to glass samples with different processing histories or at different compositions in the same alloy system. Our analysis of the new structure representation also provides valuable insight into key atomic packing features that influence the local mechanical response and its anisotropy in glasses.

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Section: Resultsmentioning

confidence: 96%

Predicting orientation-dependent plastic susceptibility from static structure in amorphous solids via deep learning

Fan

2021

Nat Commun

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“…However, it remains difficult to predict which particles will be associated to the cores. Devising a more general, unsupervised approach to identify structural defects is crucial to predict plastic events in glasses under shear [63] and also dynamic heterogeneities in supercooled liquids [58,61,64].…”

Section: Local Structure Of Unstable and Stable Coresmentioning

confidence: 99%

Spatial structure of unstable normal modes in a glass-forming liquid

et al. 2021

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The phenomenology of glass-forming liquids is often described in terms of their underlying, high-dimensional potential energy surface. In particular, the statistics of stationary points sampled as a function of temperature provides useful insight into the thermodynamics and dynamics of the system. To make contact with the real space physics, however, analysis of the spatial structure of the normal modes is required. In this work, we numerically study the potential energy surface of a glass-forming ternary mixture. Starting from liquid configurations equilibrated over a broad range of temperatures using a swap Monte Carlo method, we locate the nearby stationary points and investigate the spatial architecture and the energetics of the associated unstable modes. Through this spatially-resolved analysis, originally developed to study local minima, we corroborate recent evidence that the nature of the unstable modes changes from delocalized to localized around the mode-coupling temperature. We find that the displacement amplitudes of the delocalized modes have a slowly decaying far field, whereas the localized modes consist of a core with large displacements and a rapidly decaying far field. The fractal dimension of unstable modes around the mobility edge is equal to 1, consistent with the scaling of the participation ratio. Finally, we find that around and below the mode-coupling temperature the unstable modes are localized around structural defects, characterized by a disordered local structure markedly different from the liquid's locally favored structure. These defects are similar to those associated to quasi-localized vibrations in local minima and are good candidates to predict the emergence of localized excitations at low temperature.

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“…They look commonly decorrelated from the local values of the residual stresses (Figure 2). However, they play a more important role on the relaxation processes and irreversible motion in glasses [14,[44][45][46][47]. Incremental stresses are indeed related to local elastic moduli in Hooke's description of elasticity, and thus to the Hessian matrix (second order derivative) of the Hamiltonian, or indirectly to the dynamical matrix of the system used to determine the instability thresholds at a microscopic level [48].…”

Section: Figurementioning

confidence: 99%

“…Moreover, the signature of plasticity is not always visible neither in the structure factor, due to the fact that, in amorphous materials, the related structural changes if any are far from being homogeneously distributed, and also because plasticity in amorphous samples does not always induce easily recognizable structural changes [6]. In this context, numerical simulations at the atomic scale [7][8][9][10][11][12][13][14] combined with theories based on the existence of localized plastic rearrangements identified by their residual strains [15,16] have allowed building in the last thirty years a theoretical picture of plasticity in amorphous materials without referencing to structurally visible defects such as dislocations. The precise signature of plasticity is however strongly dependent on the composition of the glass, that is on the nature of the bonding (degree of covalency for example [6]), on the atomic composition [17,18], as well as on its thermo-mechanical history [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Elasto-plastic behavior of amorphous materials: a brief review

Tanguy¹

2021

Comptes Rendus. Physique

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Disordered materials, like metallic glasses or silicate glasses, have an atomistic amorphous structure preventing the formation of extended defects such as dislocations. Irreversible deformation in these materials is thus localized, but can organize along shear bands. In this brief review, based on recent publications, we will see if local plasticity can be measured and predicted in disordered atomic assemblies, and in what conditions it can be related to preexisting structural defects. We will then draw a general picture of the plastic mechanical behaviour within the theoretical framework of mechanical instabilities. Finally, we will focus our attention on different scenarii for shear banding in glasses.

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Predicting plasticity in disordered solids from structural indicators

Cited by 159 publications

References 82 publications

Predicting orientation-dependent plastic susceptibility from static structure in amorphous solids via deep learning

Predicting orientation-dependent plastic susceptibility from static structure in amorphous solids via deep learning

Spatial structure of unstable normal modes in a glass-forming liquid

Elasto-plastic behavior of amorphous materials: a brief review

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