Evidence map›Paper›PMID 42188523›Full record

ReviewNanomaterials (Basel, Switzerland)2026

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

Unmanaa Dewanjee, Shi Bai, Yury V Ryabchikov, David Fieser, Sharma Pradakshina, Jie Jayne Wu, Marco Fronzi, Anming Hu

Abstract readReview
In one paragraph

Review in Nanomaterials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Unmanaa DewanjeeDepartment of Mechanical and Aerospace Engineering, University of Tennessee Knoxville, 1512 Middle Drive, Knoxville, TN 37996, USA.
Shi BaiAdvanced Laser Processing Research Team, RIKEN Center for Advanced Photonics, 2-1 Hirosawa, Wako 351-0198, Saitama, Japan.ORCID 0000-0002-1701-1166
Yury V RyabchikovFZU-Institute of Physics of the Czech Academy of Sciences, Na Slovance 1999/2, 182 00 Prague, Czech Republic.ORCID 0000-0002-6844-1051
David FieserDepartment of Mechanical and Aerospace Engineering, University of Tennessee Knoxville, 1512 Middle Drive, Knoxville, TN 37996, USA.ORCID 0009-0007-5754-4331
Sharma PradakshinaDepartment of Electrical Engineering and Computer Science, University of Tennessee Knoxville, 1512 Middle Drive, Knoxville, TN 37996, USA.
Jie Jayne WuDepartment of Electrical Engineering and Computer Science, University of Tennessee Knoxville, 1512 Middle Drive, Knoxville, TN 37996, USA.ORCID 0000-0001-5143-9425
Marco FronziSchool of Physics, The University of Sydney, Sydney, NSW 2006, Australia.ORCID 0000-0001-7855-9216
Anming HuDepartment of Mechanical and Aerospace Engineering, University of Tennessee Knoxville, 1512 Middle Drive, Knoxville, TN 37996, USA.ORCID 0000-0001-9794-0549

Funding

U.S. National Science Foundation CMMI-2412544
6 · The paper itself

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.

Indexed as

density function theorylarge-area nanomanufacturingmachine learningmolecular sensingplasmonic hotspotsSERS

Identifiers

PMID42188523
PMCPMC13209856

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.