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Atom Classification Model for Total Energy Evaluation of Two-Dimensional Multicomponent Materials

Changchun He, Shao‐Bin Qiu, Ju‐Song Yu, Ji-Hai Liao, Yu‐Jun Zhao, Xiao‐Bao Yang

2020The Journal of Physical Chemistry A22 citationsDOI

Abstract

The tunable properties of materials originate from variety of structures; however, it is still a challenge to give an accurate and fast evaluation of stabilities for screening numerous candidates. Herein, we propose an atom classification model to describe the multicomponent materials based on the structural recognition, in which the atoms are classified to estimate the total energies. Taking two-dimensional planar C1–xBx and C1–2x(BN)x as examples, we have found that the test error of total energies is about 3 meV per atom. Notably, the distributions of classified atoms demonstrate the evolution of configurations as a function of temperature, providing a clearer picture of phase transition. In addition, our method is universal, which can be flexibly extended to the bulk structures with more components.

Topics & Concepts

Atom (system on chip)PlanarVariety (cybernetics)Total energyFunction (biology)Energy (signal processing)Phase (matter)Statistical physicsMaterials scienceAtomic physicsComputer sciencePhysicsArtificial intelligenceQuantum mechanicsEvolutionary biologyBiologyPsychologyPsychotherapistComputer graphics (images)Displacement (psychology)Embedded systemMachine Learning in Materials ScienceElectronic and Structural Properties of Oxides2D Materials and Applications