Kalaam A R Abul, Greeni A Berin, Arockiaraj Micheal
School of Advanced Sciences, Vellore Institute of Technology, Chennai, India.
Department of Mathematics, Loyola College, Chennai, India.
Front Chem. 2024 Sep 25;12:1470231. doi: 10.3389/fchem.2024.1470231. eCollection 2024.
Topological descriptors are widely utilized as graph theoretical measures for evaluating the physicochemical properties of organic frameworks by examining their molecular structures. Our current research validates the usage of topological descriptors in studying frameworks such as metal-butylated hydroxytoluene, NH-substituted coronene transition metal, transition metal-phthalocyanine, and conductive metal-octa amino phthalocyanine. These metal organic frameworks are crucial in nanoscale research for their porosity, adaptability, and conductivity, making them essential for advanced materials and modern technology. In this study, we provide the topological and entropy characterizations of these frameworks by employing robust reverse degree based descriptors, which offer insightful information on structural complexities. This structural information is applied to predict the graph energy of the considered metal organic frameworks using statistical regression models.
拓扑描述符作为一种图论方法被广泛应用,通过研究有机框架的分子结构来评估其物理化学性质。我们目前的研究验证了拓扑描述符在研究诸如金属 - 丁基化羟基甲苯、NH - 取代的并四苯过渡金属、过渡金属 - 酞菁以及导电金属 - 八氨基酞菁等框架中的应用。这些金属有机框架因其孔隙率、适应性和导电性在纳米尺度研究中至关重要,使其成为先进材料和现代技术所必需的。在本研究中,我们通过使用基于反向度的稳健描述符来提供这些框架的拓扑和熵特征,这些描述符提供了有关结构复杂性的深刻见解。此结构信息被应用于使用统计回归模型预测所考虑的金属有机框架的图能量。