Density Functional Theory in Forensic Science: Applications and Challenges

Forensic science is evolving to tackle increasingly complex criminal investigations, where traditional methods may fall short. This review examines how computational chemistry enhances forensic techniques by providing detailed insights into molecular interactions, reaction mechanisms, and spectroscopic properties. A particular focus is placed on density functional theory (DFT), which has emerged as a powerful, cost‐effective tool that balances computational efficiency and accuracy, making it ideal for studying a wide range of forensic compounds without the need for physical samples. Applications discussed include the analysis of new psychoactive substances (NPS), detection of food adulterants, development of chemical sensors, and forensic examination of luminol for blood detection, fingerprint visualization, and the analysis of explosives. Key advances in various DFT functionals are highlighted, along with prospects for integrating DFT with machine learning and sustainable practices to further expand its impact in forensic science.