Investigating topological indices and heat of formation for hemihexaphyrazine using a curve fitting approach

IF 2.5 4区 化学 Q2 Engineering
Iqra Siddique, Sarfraz Ahmad, Muhammad Kamran Siddiqui
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Abstract

This paper delves into the intricate relationship between the hemihexaphyrazine (HHP) network and its connection to topological indices and the heat of formation. By analyzing a variety of topological indices, we utilize a curve fitting model to predict and clarify the heat of formation–a vital thermodynamic factor that impacts the stability and reactivity of HHP. Through a detailed correlation analysis, we uncover significant trends and relationships linking the heat of formation with topological indices like the Gutman, Randić, and Zagreb indices. We have found that the curve fitting model not only allows us to predict the results with high accuracy (the values of \(R^2\) are above 0.98 in some cases) but also helps us to get a better idea about the molecular interactions within the HHP network. The reverse redefined Zagreb indices have been found to be the most predictively reliable of the tested ones. In addition, enthalpy measures were calculated in relation to each index, as a way to understand the complexity of structure, and showed steadfast growth trends in line with the growth of a network. These analyses illustrate the accuracy with which thermodynamic properties have been reproduced using the model; it outlines the relevance that topological descriptors have received in computational chemistry so far. By analyzing these results, several insights were obtained into the energetic behavior of hemihexaphyrazine network and are pointed out with respect to which role graph theoretical approaches so far played for the development of material science and chemical engineering.

用曲线拟合方法研究半己吡嗪的拓扑指数和生成热
本文探讨了半己吡嗪(HHP)网络与拓扑指数和生成热之间的复杂关系。通过分析各种拓扑指标,我们利用曲线拟合模型来预测和澄清生成热,这是影响高温高压稳定性和反应性的重要热力学因素。通过详细的相关分析,我们发现了地层热与古特曼、兰迪奇和萨格勒布指数等拓扑指数之间的重要趋势和关系。我们发现,曲线拟合模型不仅使我们能够以较高的精度预测结果(\(R^2\)的值在某些情况下高于0.98),而且有助于我们更好地了解HHP网络内的分子相互作用。反向重新定义的萨格勒布指数已被发现是最可靠的预测测试。此外,计算了与各指标相关的焓测度,作为了解结构复杂性的一种方式,并显示出与网络增长一致的稳定增长趋势。这些分析说明了使用该模型再现热力学性质的准确性;它概述了拓扑描述符到目前为止在计算化学中所获得的相关性。通过对这些结果的分析,对半己吡嗪网络的能量行为有了一些认识,并指出了图论方法迄今为止在材料科学和化学工程的发展中所起的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Chemical Papers
Chemical Papers Chemical Engineering-General Chemical Engineering
CiteScore
3.30
自引率
4.50%
发文量
590
期刊介绍: Chemical Papers is a peer-reviewed, international journal devoted to basic and applied chemical research. It has a broad scope covering the chemical sciences, but favors interdisciplinary research and studies that bring chemistry together with other disciplines.
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