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Open AccessArticle

Computational Analysis of Imbalance-Based Irregularity Indices of Boron Nanotubes

1
School of artificial Intelligence and big data, Hefei University, Hefei 230601, China
2
Department of Mathematics, Division of Science and Technology, University of Education, Lahore 54000, Pakistan
3
Center for Excellence in Molecular Biology, Punjab University Lahore, Lahore 53700, Pakistan
4
School of Mathematics and Physics, Anhui Jianzhu University, Hefei 230601, China
5
School of Mathematics, Southeast University, Nanjing 210096, China
*
Author to whom correspondence should be addressed.
Processes 2019, 7(10), 678; https://doi.org/10.3390/pr7100678
Received: 18 August 2019 / Revised: 18 September 2019 / Accepted: 26 September 2019 / Published: 1 October 2019
(This article belongs to the Section Materials Processes)
. Molecular topology provides a basis for the correlation of physical as well as chemical properties of a certain molecule. Irregularity indices are used as functions in the statistical analysis of the topological properties of certain molecular graphs and complex networks, and hence help us to correlate properties like enthalpy, heats of vaporization, and boiling points etc. with the molecular structure. In this article we are interested in formulating closed forms of imbalance-based irregularity measures of boron nanotubes. These tubes are known as α-boron nanotube, triangular boron nanotubes, and tri-hexagonal boron nanotubes. We also compare our results graphically and come up with the conclusion that alpha boron tubes are the most irregular with respect to most of the irregularity indices.
Keywords: boron nanotube; irregularity measure; complexity of structure; alpha boron tube; triangular boron tube; tri-hexagonal boron nanotube boron nanotube; irregularity measure; complexity of structure; alpha boron tube; triangular boron tube; tri-hexagonal boron nanotube
MDPI and ACS Style

Yang, B.; Munir, M.; Rafique, S.; Ahmad, H.; Liu, J.-B. Computational Analysis of Imbalance-Based Irregularity Indices of Boron Nanotubes. Processes 2019, 7, 678.

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