Evidence map›Paper›PMID 40767094›Full record

ArticleApplied spectroscopy2025

Plasmonic Hybrid Heterostructure Based on Reduced Graphene Oxide-Gold Nanostars Composite for Sensitive Surface-Enhanced Raman Spectroscopy Sensing.

Supriya Atta, Tamer Sharaf, Tuan Vo-Dinh

Abstract read
In one paragraph

Article in Applied spectroscopy, 2025. 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

3 authors.

Supriya AttaDuke University, Fitzpatrick Institute for Photonics, 101 Science Drive, Durham, North Carolina, 27708-0187, USA.
Tamer SharafDuke University, Fitzpatrick Institute for Photonics, 101 Science Drive, Durham, North Carolina, 27708-0187, USA.
Tuan Vo-DinhDuke University, Fitzpatrick Institute for Photonics, 101 Science Drive, Durham, North Carolina, 27708-0187, USA.ORCID 0000-0003-3701-3326

Funding

Integrated Acoustofluidic Plasmonic Molecular Diagnostic System for Detecting MicroRNA BiomarkersR01GM135486 · NIGMS · DUKE UNIVERSITY · PI VO-DINH, TUAN · 2020 to 2023
$1.8M
Gates Foundation INV-040790NIGMS NIH HHS R01 GM135486
6 · The paper itself

Abstract

In this study, we have developed a plasmonic hybrid heterostructure integrating two elements: Two-dimensional (2D) reduced graphene oxide-gold nanostars composite (rGO-GNS), and gold nanostars (GNS) substrate. By harnessing the unique plasmonic properties of rGO in chemical enhancement and that of GNS in electromagnetic enhancement, the hybrid heterostructure offers synergistic enhancement effects that enable ultra-low sensitivity and accurate identification and analysis of trace quantities of target substances. It is noteworthy that the high-density hotspots generated by strong plasmonic coupling of rGO-GNS and GNS results in ultra-high surface-enhanced Raman spectroscopy (SERS) enhancement compared to individual substrate either GNS or rGO-GNS substrate. Moreover, the uniformity and reproducibility of the GNS@rGO-GNS substrate were studied by using thiophenol (TP) as a model analyte, which indicates that the SERS sensor exhibited superior signal reproducibility with an RSD value 5% and long-term stability with a minimal signal loss after 30 days. To demonstrate a potential application of our SERS substrate, SERS detection of the pesticide thiram in river water was realized with a limit of detection (LOD) up to 50 pM, showing the potential for new opportunities for efficient chemical and biological sensing applications.

Indexed as

GNSGOGold nanostarsgraphene oxidepesticidessensingSERSsurface-enhanced Raman spectroscopythiram

Identifiers

PMID40767094
PMCPMC12768889

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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.