Abstract

Numerous approaches have been incorporated into electrochemical (EC) and fluorescence (FLS) sensors to develop sensing systems for detecting targets of interest in various applications. Theoretical sciences aid in designing experiments and have been integrated into them to serve as ideal sensors, reducing optimization time and waste generation. This review summarizes recent EC, FLS-based rapid and portable detection platforms for clinical analysis and environmental monitoring, focusing on the contribution of Density Functional Theory (DFT) to improve their accuracy, precision, selectivity, and rapidity. The purpose of using DFT in the fabrication of EC and FLS sensors, assessing molecule interactions at the molecular level, accelerating the optimization of molecularly imprinted polymers (MIP) and material components, and designing molecular configurations of organic and inorganic compounds will be discussed. Furthermore, obstacles and future trends in developing sensors with the use of hybrid experimental designs, machine learning, and artificial intelligence for green chemistry will also be covered. In addition, computational science's transformational significance in enhancing health quality and environmental responsibility will be highlighted.