Video Experimental Relacionado

Updated: Feb 2, 2026

Preparation of Large-area Vertical 2D Crystal Hetero-structures Through the Sulfurization of Transition Metal Films for Device Fabrication

Preparation of Large-area Vertical 2D Crystal Hetero-structures Through the Sulfurization of Transition Metal Films for Device Fabrication

Published on: November 28, 2017

Análisis comparativo de entropía de tetrahidroxiquinonas de metales de transición 2D mediante enfoques de aprendizaje

Muhammad Irfan¹, Nabeela Bashir¹, AbdulGuddoos S A Gaid²

¹Department of Mathematics, University of Okara, Okara, Pakistan.

Scientific reports

|January 31, 2026

Abstract:

This paper focuses on the study of the framework of transition metal tetrahydroxyquinone (TM-THQ) which is a chemical belonging to the metal-organic framework (MOF) family. These materials are becoming relevant due to their stability and high surface area that makes them prospective in terms of carbon-dioxide conversion and other uses. To explore the structure of TM-THQ, we apply molecular graph theory, in which atoms and bonds are represented as mathematical graphs. We determine some topological indices, the Zagreb indices, Randić index, the atom-bond connectivity index, the geometric-arithmetic index, and the sum-connectivity index to explain the connection between atoms and predict the stability and reactivity of the material used. Moreover, Shannon's entropy model is applied to estimate the entropy of the indices. To this end, we develop and compare three machine learning based regression models: logarithmic, random forest, and XGBoost. All computational work, data analysis, and machine learning modeling were performed using Python. The findings reveal a strong predictive relationship, indicating that the entropy of TM-THQ can be accurately forecasted from its topological descriptors, with the ensemble methods providing superior predictive performance.

Palabras clave:

Basados en grado Entropía Teoría de grafos Aprendizaje automático Estructura TM-THQ

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