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Review

Next-Generation SERS Probes: Engineering Hotspots, Intelligent Molecular Targeting, and AI-Driven Spectral Analysis for Emerging Applications

1
Department of Mechanical and Aerospace Engineering, University of Tennessee Knoxville, 1512 Middle Drive, Knoxville, TN 37996, USA
2
Advanced Laser Processing Research Team, RIKEN Center for Advanced Photonics, 2-1 Hirosawa, Wako 351-0198, Saitama, Japan
3
FZU—Institute of Physics of the Czech Academy of Sciences, Na Slovance 1999/2, 182 00 Prague, Czech Republic
4
Department of Electrical Engineering and Computer Science, University of Tennessee Knoxville, 1512 Middle Drive, Knoxville, TN 37996, USA
5
School of Physics, The University of Sydney, Sydney, NSW 2006, Australia
*
Author to whom correspondence should be addressed.
Nanomaterials 2026, 16(10), 628; https://doi.org/10.3390/nano16100628 (registering DOI)
Submission received: 10 April 2026 / Revised: 12 May 2026 / Accepted: 15 May 2026 / Published: 19 May 2026

Abstract

Surface-enhanced Raman spectroscopy (SERS) has evolved from a fundamental optical phenomenon to a powerful, molecule-specific analytical technique capable of detecting ultra-trace-level species across biomedicine, catalysis, environmental monitoring, and national security applications. In this review, we summarize recent advances in SERS probe design and fabrication along three major directions: (i) engineering plasmonic hotspots with enhanced field confinement to achieve stronger and more uniform signals; (ii) analyte-directed strategies that precisely position and retain target molecules via tailored surface chemistries, nanoscale confinement, and on-surface reactions for single hotspot SERS; and (iii) hybrid architectures integrating plasmonic metals with functional materials, including high entropy materials, semiconductors, and graphene and other 2D materials, to synergistically couple electromagnetic and chemical enhancement mechanisms. Despite significant progress, key challenges remain for practical applications outside laboratories, including substrate reproducibility and stability, diverse analyte compatibility, unknown molecule identification and standardized quantitative performance in complex environments. We highlight emerging solutions, such as large-area nanomanufacturing for controlled nanoscale gaps, high-resolution Raman mapping for spatial–temporal characterization, density-functional-theory-guided molecular interpretation, and machine-learning-enabled spectral analysis. Advances in foundational AI models and data-driven discovery are positioning SERS to become an increasingly versatile platform, from decoding unknown molecular structures to analyzing complicated multi-component systems for environmental, biomedical, and national security applications with high sensitivity and selectivity.
Keywords: SERS; plasmonic hotspots; large-area nanomanufacturing; molecular sensing; density function theory; machine learning SERS; plasmonic hotspots; large-area nanomanufacturing; molecular sensing; density function theory; machine learning
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MDPI and ACS Style

Dewanjee, U.; Bai, S.; Ryabchikov, Y.V.; Fieser, D.; Pradakshina, S.; Wu, J.J.; Fronzi, M.; Hu, A. Next-Generation SERS Probes: Engineering Hotspots, Intelligent Molecular Targeting, and AI-Driven Spectral Analysis for Emerging Applications. Nanomaterials 2026, 16, 628. https://doi.org/10.3390/nano16100628

AMA Style

Dewanjee U, Bai S, Ryabchikov YV, Fieser D, Pradakshina S, Wu JJ, Fronzi M, Hu A. Next-Generation SERS Probes: Engineering Hotspots, Intelligent Molecular Targeting, and AI-Driven Spectral Analysis for Emerging Applications. Nanomaterials. 2026; 16(10):628. https://doi.org/10.3390/nano16100628

Chicago/Turabian Style

Dewanjee, Unmanaa, Shi Bai, Yury V. Ryabchikov, David Fieser, Sharma Pradakshina, Jie Jayne Wu, Marco Fronzi, and Anming Hu. 2026. "Next-Generation SERS Probes: Engineering Hotspots, Intelligent Molecular Targeting, and AI-Driven Spectral Analysis for Emerging Applications" Nanomaterials 16, no. 10: 628. https://doi.org/10.3390/nano16100628

APA Style

Dewanjee, U., Bai, S., Ryabchikov, Y. V., Fieser, D., Pradakshina, S., Wu, J. J., Fronzi, M., & Hu, A. (2026). Next-Generation SERS Probes: Engineering Hotspots, Intelligent Molecular Targeting, and AI-Driven Spectral Analysis for Emerging Applications. Nanomaterials, 16(10), 628. https://doi.org/10.3390/nano16100628

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