Evidence map›Paper›PMID 32635490›Full record

ArticleNanomaterials (Basel, Switzerland)2020

Spatial-Tunable Au Nanoparticle Functionalized Si Nanorods Arrays for Surface Enhanced Raman Spectroscopy.

Dongdong Lin, Kunjie Dai, Tianxiang Yu, Wenhui Zhao, Wenwu Xu

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2020. 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

5 authors.

Dongdong LinDepartment of Microelectronic Science and Engineering, School of Physical Science and Technology, Ningbo University, 818 Fenghua Road, Ningbo 315211, China.
Kunjie DaiDepartment of Microelectronic Science and Engineering, School of Physical Science and Technology, Ningbo University, 818 Fenghua Road, Ningbo 315211, China.
Tianxiang YuDepartment of Microelectronic Science and Engineering, School of Physical Science and Technology, Ningbo University, 818 Fenghua Road, Ningbo 315211, China.
Wenhui ZhaoDepartment of Microelectronic Science and Engineering, School of Physical Science and Technology, Ningbo University, 818 Fenghua Road, Ningbo 315211, China.
Wenwu XuDepartment of Microelectronic Science and Engineering, School of Physical Science and Technology, Ningbo University, 818 Fenghua Road, Ningbo 315211, China.

Funding

National Natural Science Foundation of China 11804174Natural Science Foundation of Ningbo 2018A610319Natural Science Foundation of Zhejiang Province LY18B030003
6 · The paper itself

Abstract

In this study, hexagonal-packed Si nanorods (SiNRs) arrays were fabricated and conjugated with Au nanoparticles (AuNPs) in different spatial distributions for surface-enhanced Raman spectroscopy (SERS). The AuNPs were functionalized on the bottom of SiNRs (B-SiNRs@AuNPs), top of SiNRs (T-SiNRs@AuNPs) and sides of SiNRs (S-SiNRs@AuNPs), respectively. Our results demonstrated that the SiNRs conjugated with AuNPs on the sides achieved high reproducibility in detection of R6G molecules, while the AuNPs on the top of the SiNRs obtained the strongest Raman enhancement. In addition, the substrate with S-SiNRs@AuNPs obtained the highest spatial uniformity of enhancement. The finite-difference time-domain simulation gave further evidence that the incident light could be confined in the space of SiNRs arrays and yield a zero-gap enhancement coupled with the AuNPs. Our study provided a spatially tunable SiNRs@AuNPs substrate with high sensitivity and reproducibility in molecular detection.

Indexed as

Au nanoparticlesdetectionSERSSi nanorodssurface plasmon resonance

Identifiers

PMID32635490
PMCPMC7407171

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Registered trials

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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.