A Theoretical Study of Metalloporphyrin-Based Fluorescent Array Sensor using Density Functional Theory.

Area of Science:

• Computational Chemistry
• Materials Science
• Chemical Sensing

Background:

• Metalloporphyrins are utilized in fluorescent array sensors.
• Trimethylamine (TMA) detection is crucial for food quality assessment.
• Understanding metal atom influence is key to sensor performance.

Purpose of the Study:

• To investigate the impact of various metal atoms on the performance of metalloporphyrin-based fluorescent array sensors.
• To establish a theoretical basis for designing sensors for trimethylamine detection.
• To correlate metal identity with sensor sensitivity and binding affinity.

Main Methods:

• Density Functional Theory (DFT) calculations were performed.
• The B3LYP/LAN2DZ level of theory was employed.
• Optimized geometry, relative energies, molecular orbitals, and binding energies were computed.

Main Results:

• Metal atom selection significantly influences sensor performance for trimethylamine determination.
• A clear order of binding energies was established for different metalloporphyrins.
• Zinc porphyrin exhibited the lowest binding energy, while manganese porphyrin showed the highest.

Conclusions:

• The study provides a design mechanism for choosing appropriate metal atoms for detecting varying concentrations of trimethylamine.
• Theoretical insights can guide the development of efficient metalloporphyrin-based sensors.
• This research supports the rapid detection of trimethylamine in food products.