Plasmonic fingerprinting: next-generation SERS architectures for sensitive heavy metal quantification

Abstract

The global heavy metal crisis demands sensing technologies that transcend traditional analytical limitations, positioning Surface-Enhanced Raman Scattering (SERS) as the transformative solution for real-world environmental and health monitoring challenges. This comprehensive review illuminates the sophisticated engineering principles underlying modern SERS architectures, where nanoscale precision meets molecular recognition to achieve detection limits that challenge the boundaries of single-molecule spectroscopy. Additionally, a systematic analysis of various SERS sensing strategies, including label-free approaches utilizing direct metal-nanoparticle interactions, molecular probe-based systems employing Raman-active chelating agents, and advanced functionalized nanoparticle platforms incorporating DNA aptamers, peptides, and polymeric recognition elements are discussed. Representative case studies include the successful detection of mercury in contaminated fish samples at sub-regulatory levels, lead quantification in urban drinking water systems, and arsenic monitoring in rice cultivation areas, showcasing the versatility and reliability of SERS-based approaches across diverse analytical challenges. The review concludes with a progressive perspective on the merging of SERS technology with microfluidics, Internet of Things architectures, and distributed sensing networks that will replace the current approach of testing samples periodically with continuous monitoring of heavy metals at specific locations.