Book

Description

Detecting and differentiating explosives is crucial for security, environmental monitoring, and forensic investigations. While traditional methods have improved the identification of common explosives, detecting insensitive high-energy explosives remains challenging due to their low volatility and chemical stability. Researchers have developed diverse material-based sensing strategies, each with unique advantages and limitations. Fluorescence-based techniques have emerged as a leading approach due to their exceptional sensitivity, simplicity, and rapid response. These sensors detect a broad range of explosives, including nitroaromatic compounds like TNT and RDX. However, real-world detection requires distinguishing structurally similar explosives in complex mixtures, necessitating advanced, multidimensional sensing strategies. To address this, multichannel sensing platforms integrating various fluorescent materials have been developed. A groundbreaking advancement in this field is chemical computing, which employs molecular logic gates and computational algorithms to analyze chemical signatures. This approach enables precise differentiation of closely related explosives. This book critically examines recent progress in material-based explosive detection, focusing on fluorescence-based sensing and molecular computing for explosive differentiation. It also discusses challenges such as material stability, real-world applicability, and emerging sensor fabrication techniques. By integrating materials science and computational chemistry, this book provides valuable insights into next-generation smart detection systems for researchers and security professionals.