Srolovitz, David J

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1981 - 198912010 - 20121
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  • Publication
    Radial Distribution Function and Structural Relaxation in Amorphous Solids
    (1981-12-15) Srolovitz, David J; Vitek, Vaclav; Egami, Takeshi
    A method of interpreting radial distribution functions (RDF) of amorphous metals is proposed in which the role of the local atomic structure is emphasized. It is found that the width and height of the peaks of the RDF are related to the second moment of the atomic-level hydrostatic stress distribution ⟨p2⟩. The results of this analysis are then used to explain the details of the changes that occur in the RDF when structural relaxation takes place. The theoretical ▵RDF is found to be in excellent agreement with the results of a computer study and previous experimental results. It is further proposed that changes in ⟨p2⟩ may be most easily accounted for in terms of changes in the density of the structural defects defined in terms of the local fluctuations in the hydrostatic stress. In this way the changes that occur in the structure of amorphous metal during structural relaxation, as represented by the RDF, may be explained in terms of the motion and annihilation of these structural defects. It is concluded that the number density of defects which could account for the observed changes in the experimental RDF is 10%. It is also found that while the hydrostatic stress distribution may be significantly changed during structural relaxation, the distribution of the atomic-level shear stresses remains unaltered.
  • Publication
    Statistical Topology of Cellular Networks in Two and Three Dimensions
    (2012-11-26) Mason, J. K; Lazar, E. A; MacPherson, R. D.; Srolovitz, David J
    Cellular networks may be found in a variety of natural contexts, from soap foams to biological tissues to grain boundaries in a polycrystal, and the characterization of these structures is therefore a subject of interest to a range of disciplines. An approach to describe the topology of a cellular network in two and three dimensions is presented. This allows for the quantification of a variety of features of the cellular network, including a quantification of topological disorder and a robust measure of the statistical similarity or difference of a set of structures. The results of this analysis are presented for numerous simulated systems including the Poisson-Voronoi and the steady-state grain growth structures in two and three dimensions.