4.7 Article

Calculations of the structure of basin volumes for mechanically stable packings

Journal

PHYSICAL REVIEW E
Volume 85, Issue 6, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.85.061307

Keywords

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Funding

  1. National Science Foundation [CBET-0967262, CBET-0968013]
  2. Directorate For Engineering
  3. Div Of Chem, Bioeng, Env, & Transp Sys [0967262] Funding Source: National Science Foundation
  4. Div Of Chem, Bioeng, Env, & Transp Sys
  5. Directorate For Engineering [0968013] Funding Source: National Science Foundation

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Experimental and computational model systems composed of frictionless particles in a fixed geometry have a finite number of distinct mechanically stable (MS) packings. The frequency of occurrence for each MS packing is highly variable and depends strongly on preparation protocol. Despite intense work, it is extremely difficult to predict a priori the MS packing probabilities. We describe a novel computational method for calculating the volume and other geometrical properties of the basin of attraction for each MS packing. The basin of attraction for an MS packing contains all initial conditions in configuration space that map to that MS packing using a given preparation protocol. We find that the basin is a highly complex structure. For a compressive-quench-from-zero-density protocol, we show the existence of a small core volume of the basin around each MS packing for which all points map to that MS packing. However, in contrast to previous studies for supercooled liquids, glasses, and over-compressed jammed systems, we find that the MS packing probabilities are very weakly correlated with this core volume. Instead, MS packing probabilities obtained from compression protocols that use initially dilute configurations and do not allow particle overlaps (i.e., those relevant to granular media) are determined by complex geometric features of the basin of attraction that are distant from the MS packing. In particular, we find that the shape of the average basin profile function S(l), which gives the probability for a point on a hyperspherical shell a distance l from a given MS packing to map back to that packing, can be described by a Gamma distribution with a peak that increases as the system size increases and as the quench rate decreases. We find a simple model which predicts S(l) for the extreme cases of very slow and fast quench rates.

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