Topological indices and patterns in iron telluride networks

Author:

Yang Hong,Hanif Muhammad Farhan,Siddiqui Muhammad Kamran,Hanif Muhammad Faisal,Ahmed Hira,Fufa Samuel Asefa

Abstract

AbstractThis paper explores the complex interplay between topological indices and structural patterns in networks of iron telluride (FeTe). We want to analyses and characterize the distinct topological features of (FeTe) by utilizing an extensive set of topological indices. We investigate the relationship that these indicators have with the network’s physical characteristics by employing sophisticated statistical techniques and curve fitting models. Our results show important trends that contribute to our knowledge of the architecture of the (FeTe) network and shed light on its physiochemical properties. This study advances the area of material science by providing a solid foundation for using topological indices to predict and analyses the behavior of intricate network systems. More preciously, we study the topological indices of iron telluride networks, an artificial substance widely used with unique properties due to its crystal structure. We construct a series of topological indices for iron telluride networks with exact mathematical analysis and determine their distributions and correlations using statistical methods. Our results reveal significant patterns and trends in the network structure when the number of constituent atoms increases. These results shed new light on the fundamental factors that influence material behavior, thus offering a deeper understanding of the iron telluride network and may contribute to future research and engineering of these materials.

Publisher

Springer Science and Business Media LLC

Reference40 articles.

1. Zhang, X., Rauf, A., Ishtiaq, M., Siddiqui, M. K. & Muhammad, M. H. On Degree Based Topological Properties of Two Carbon Nanotubes. Polycyclic Aromat. Compd. 10, 22–35 (2020).

2. Zhang, X. et al. Physical analysis of heat for formation and entropy of Ceria Oiotade using topological indices. Combin. Chem. High Throughput Screen. 25(3), 441–450 (2022).

3. Bonchev D., & Rouvray D. H. Chemical Graph Theory: Introduction and Fundamentals, ISBN 0-85626-454-7, (1991).

4. Chen, C. et al. Design of multi-phase dynamic chemical networks. Nat. Chem. 9(8), 799–804 (2017).

5. Avanzini, F., Freitas, N. & Esposito, M. Circuit theory for chemical reaction networks. Phys. Rev. X 13(2), 021041 (2023).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3