Bonding alkane attributes with topological indices: a statistical intervention

IF 1.7 3区 化学 Q3 CHEMISTRY, MULTIDISCIPLINARY Journal of Mathematical Chemistry Pub Date : 2024-03-10 DOI:10.1007/s10910-024-01584-x
Nadar Jenita Mary Masilamani Raja, A. Anuradha
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Abstract

This research delves into a comprehensive investigation of a specific group of alkanes, with the primary objective of establishing meaningful associations between their inherent physical attributes and a set of graphical parameters ranging from topological indices to their associated graphical entropies. Though there are countless techniques to relate molecular structure and physical properties of chemical compounds, the pursuit has often been pricey and arduous. With a view to curb the expense and intense labour, this work focuses on attaining some of these properties using graphical interpretations and statistical interventions. Driven by this objective, we compute Sombor index, a recently developed topological tool and some of its variants for all structural isomers of alkanes with carbon range four to nine. Furthermore, our study employs multiple regression analysis to explore their connections with some physical attributes of alkanes while concurrently addressing the challenge posed by multicollinearity. We have adopted the technique of robust regression to scale down the impact of outliers in the dataset, while generating regression models. Further, the established results are justified with a 10-fold cross validation process and a comparison with the results obtained from different topological indices. The results of this research contribute a valuable insight to the fields of chemical informatics and structural analysis, offering an enhanced comprehension of the interplay between molecular structure and physical attributes within alkanes.

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用拓扑指数键合烷烃属性:统计干预
这项研究对一组特定的烷烃进行了全面调查,主要目的是在它们固有的物理属性和一系列图形参数(从拓扑指数到相关的图形熵)之间建立有意义的联系。尽管将化合物的分子结构和物理特性联系起来的技术不胜枚举,但这种研究往往既昂贵又艰苦。为了降低成本和减少劳动强度,这项工作的重点是利用图形解释和统计干预来获得其中的一些特性。在这一目标的驱动下,我们计算了 Sombor 指数(一种最新开发的拓扑工具)及其一些变体,适用于碳原子范围为 4 到 9 的所有烷烃结构异构体。此外,我们的研究还采用了多元回归分析方法来探索它们与烷烃某些物理属性之间的联系,同时解决了多重共线性带来的挑战。在生成回归模型时,我们采用了稳健回归技术来降低数据集中异常值的影响。此外,通过 10 倍交叉验证过程以及与不同拓扑指数得出的结果进行比较,证明了所建立的结果是正确的。这项研究成果为化学信息学和结构分析领域提供了宝贵的见解,使人们能够更好地理解烷烃的分子结构和物理属性之间的相互作用。
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来源期刊
Journal of Mathematical Chemistry
Journal of Mathematical Chemistry 化学-化学综合
CiteScore
3.70
自引率
17.60%
发文量
105
审稿时长
6 months
期刊介绍: The Journal of Mathematical Chemistry (JOMC) publishes original, chemically important mathematical results which use non-routine mathematical methodologies often unfamiliar to the usual audience of mainstream experimental and theoretical chemistry journals. Furthermore JOMC publishes papers on novel applications of more familiar mathematical techniques and analyses of chemical problems which indicate the need for new mathematical approaches. Mathematical chemistry is a truly interdisciplinary subject, a field of rapidly growing importance. As chemistry becomes more and more amenable to mathematically rigorous study, it is likely that chemistry will also become an alert and demanding consumer of new mathematical results. The level of complexity of chemical problems is often very high, and modeling molecular behaviour and chemical reactions does require new mathematical approaches. Chemistry is witnessing an important shift in emphasis: simplistic models are no longer satisfactory, and more detailed mathematical understanding of complex chemical properties and phenomena are required. From theoretical chemistry and quantum chemistry to applied fields such as molecular modeling, drug design, molecular engineering, and the development of supramolecular structures, mathematical chemistry is an important discipline providing both explanations and predictions. JOMC has an important role in advancing chemistry to an era of detailed understanding of molecules and reactions.
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