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Related Concept Videos

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Metallic Solids

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Metallic solids such as crystals of copper, aluminum, and iron are formed by metal atoms. The structure of metallic crystals is often described as a uniform distribution of atomic nuclei within a “sea” of delocalized electrons. The atoms within such a metallic solid are held together by a unique force known as metallic bonding that gives rise to many useful and varied bulk properties.
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The structure of a crystalline solid, whether a metal or not, is best described by considering its simplest repeating unit, which is referred to as its unit cell. The unit cell consists of lattice points that represent the locations of atoms or ions. The entire structure then consists of this unit cell repeating in three dimensions. The three different types of unit cells present in the cubic lattice are illustrated in Figure 1.
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Close-packed structures with finite-range interaction: computational mechanics of layer pair interaction.

Edwin Rodriguez-Horta1, Ernesto Estevez-Rams1, Reinhard Neder2

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Acta Crystallographica. Section A, Foundations and Advances
|June 30, 2017
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Computational mechanics models stacking sequences using an Ising model. This approach analyzes stacking as an information system, revealing phase diagrams and polytypes in materials like ZnS and cobalt.

Keywords:
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Area of Science:

  • Computational mechanics
  • Statistical physics
  • Materials science

Background:

  • The stacking problem in materials science describes the arrangement of layers in crystalline structures.
  • Understanding stacking sequences is crucial for predicting material properties.

Purpose of the Study:

  • To apply computational mechanics to the stacking problem.
  • To develop a general method for analyzing stacking sequences using a symbol-generating process.

Main Methods:

  • Utilized an Ising next-nearest-neighbor model within a computational mechanics framework.
  • Developed and applied a general method for solving the stochastic matrix of the random Gibbs field.
  • Analyzed the phase diagram in terms of the optimal finite-state machine (ℇ-machine).

Main Results:

  • The study presents a novel computational mechanics approach to stacking sequences.
  • A general method for solving stochastic matrices of random Gibbs fields was developed and applied.
  • Phase diagrams were analyzed, revealing higher-order polytypes at their borders.

Conclusions:

  • The computational mechanics model provides a new perspective on stacking sequences as information processing systems.
  • The method is applicable to real systems like ZnS and cobalt.
  • The derived method is generalizable to other one-dimensional models with finite-range interactions.