Computational Materials Science2022,Vol.2097.DOI:10.1016/j.commatsci.2022.111381

BELLO: A post-processing tool for the local-order analysis of disordered systems

Dianat, Behnood Tavanti, Francesco Calzolari, Arrigo Padovani, Andrea Larcher, Luca
Computational Materials Science2022,Vol.2097.DOI:10.1016/j.commatsci.2022.111381

BELLO: A post-processing tool for the local-order analysis of disordered systems

Dianat, Behnood 1Tavanti, Francesco 1Calzolari, Arrigo 1Padovani, Andrea 2Larcher, Luca2
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作者信息

  • 1. CNR NANO Ist Nanosci
  • 2. AMAT Appl Mat Italia
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Abstract

The characterization of the atomic structure of disordered systems, such as amorphous, glasses and (bio)molecule in solution, is a fundamental step for most theoretical investigations. The properties of short-and medium-range local order structures are responsible for the electronic, optical and transport properties of these systems. Here, we present the BELLO open source code, a post-processing script-tool created for the automatic analysis and extraction of structural characteristics of disordered and amorphous systems. BELLO is agnostic to the code that generated single configurations or trajectories, it provides an intuitive access through a graphical user interface (GUI), and it requires minimal computational resources. Its capabilities include the calculation of the order parameter q, the folded structure identification, and statistical analysis tools such as atomic coordination number and pair/angle-distribution functions. The working principles of the code are described and tested on ab initio molecular dynamics trajectories of amorphous chalcogenides.

Key words

Python code/Disordered systems/Molecular dynamics/Local-order structures/Statistical analysis/MOLECULAR-DYNAMICS/SUPERCOOLED LIQUIDS/AMORPHOUS-SILICON/ABSORPTION

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出版年

2022
Computational Materials Science

Computational Materials Science

EISCI
ISSN:0927-0256
被引量2
参考文献量53
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