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WIREs Comput Mol Sci
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Prediction of two‐dimensional materials by the global optimization approach

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Crystal structure prediction is one of the most fundamental challenges in the physics and chemistry sciences. In recent years, this problem has gained much practical success by the global optimization approach. Here, we survey some recent progress in finding the global minimum of two‐dimensional (2D) materials, and introduce some details of these global optimization approach. Then, we will give some typical examples to demonstrate their advantages for 2D crystal structure prediction. Finally, the future directions and challenges are briefly discussed. WIREs Comput Mol Sci 2017, 7:e1295. doi: 10.1002/wcms.1295

This article is categorized under:

  • Structure and Mechanism > Computational Materials Science
  • Electronic Structure Theory > Density Functional Theory
Top and side views of P4O4 and P2O3 . The P and O atoms are denoted by lavender and orange atoms, respectively. (a) The lowest energy of P4O4 , (b) the lowest energy of P2O3 with thickness less than 1.4 Å, and (c) the lowest energy of P2O3 with thickness less than 3.2 Å. (Adopted from ‘Two Dimensional Phosphorus Oxides as Energy and Information Materials’)
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The lowest energy of different PO Compounds 2D structures with thickness less than 3.2 Å. The P and O atoms are denoted by lavender and orange atoms, respectively. (a) The lowest energy of P8O1 , (b) the lowest energy of P6O1 , (c) the lowest energy of P4O1 , and (d) the lowest energy of P2O1 . (Adopted from ‘Two Dimensional Phosphorus Oxides as Energy and Information Materials’)
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The global minimum structure of FeB2 monolayer from the particle swarm optimization simulations (Color online). The B atoms are arranged in a honeycomb lattice and Fe atoms are located above the center of hexagonal boron rings. (Adopted from ‘Dirac State in the FeB2 Monolayer with Graphene‐Like Boron Sheet’)
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The lowest energy of different BC Compounds 2D structures from the particle swarm optimization simulations (Color online). The C and B atoms are denoted by blue and gray atoms, respectively. (a) The lowest energy of BC5 , (b) the lowest energy of BC3 , (c) the lowest energy of BC2 , (d) the lowest energy of BC, (e) the lowest energy of B2C, (f) the lowest energy of B3C, and (g) the lowest energy of B5C. (Adopted from ‘Predicting Two‐Dimensional Boron‐Carbon Compounds by the Global Optimization Method’)
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Illustration of how the velocity and position updates in particle swarm optimization. The black solid line represents a typical potential energy surface. Arrows represent either the positions or the velocity of a particle. (Adopted from ‘Crystal structure prediction via particle swarm optimization’)
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Illustration of how the mating operator works: parent structures are sliced and combined to form an offspring structure. For clarity, 1 × 2 supercells are shown. (Adopted from ‘Grand‐canonical evolutionary algorithm for the prediction of two‐dimensional materials’)
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Geometrical and electronic structures of Bi4F4 (Color online). (a) Top and side views of Bi4F4 and (b) local density approximation band structures of Bi4F4 without (left) and with (right) SOC. (Adopted from ‘Room Temperature Quantum Spin Hall Insulators with a Buckled Square Lattice’)
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The main flow chart of evolutionary algorithm for the structure prediction.
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Illustration of the potential energy surface. The use of local optimization can reduce the potential energy surface to simple steps.
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Electronic Structure Theory > Density Functional Theory
Structure and Mechanism > Computational Materials Science

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