Computational Simulation of Post-Transition Metals Using Bond Length and Molecular Weight for IoT-Enabled Sensing Applications

This study investigates special abilities of 1,4- benzene dicarboxylic acid (terephthalic acid, or TPA) to form stable carbon bonds with post-transition metals, in order to create Metal-Organic Frameworks (MOFs) that are ideal for environmental sensing. When it comes to identifying analytes like carbon (C), these MOFs show excellent selectivity, stability, and sensitivity. They improve real-time environmental monitoring and data analytics when included into IoT platforms, which makes them appropriate for applications in smart cities, agriculture, and industrial pollution management. Novel materials with high porosity and electrochemical efficiency are produced when TPA and post-transition metals are combined, which makes them useful for catalysis. Because of its effectiveness and ease of use, the study used Avogadro software to model and evaluate the chemical structures, utilizing the Universal Force Field (UFF) for optimal energy estimations. With an emphasis on aluminum (Al), indium (In), lead (Pb), gallium (Ga), tin (Sn), bismuth (Bi), germanium (Ge), polonium (Po), thorium (Tl), and arsenic (As), post-transition metals were selected because to their significant alloying tendencies. The findings show that because of their larger surface area, MOFs containing indium (In) have better stability, lower potential energy. With an optimum energy of 57.02 kJ mol-1 and bond length of 1.65 Å in UFF, indium was the most stable choice among the metals that were evaluated. These results demonstrate the promise of post-transition metal MOFs in sophisticated sensing applications, especially when included into monitoring systems powered by the Internet of Things. The Indium metal took high precision and recall towards the F- measure