Evidence map›Paper›PMID 31035552›Full record

ArticleMicromachines2019

Fabrication, Characterization, and Application of Large-Scale Uniformly Hybrid Nanoparticle-Enhanced Raman Spectroscopy Substrates.

Qi Qi, Chunhui Liu, Lintao Liu, Qingyi Meng, Shuhua Wei, Anjie Ming, Jing Zhang, Yanrong Wang, Lidong Wu, Xiaoli Zhu and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Micromachines, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

12 authors.

Qi QiSchool of Information science and technology, North China University of Technology, No. 5 Jinyuanzhuang Street, Shijingshan District, Beijing 100144, China. qiqi@ime.ac.cn.
Chunhui LiuSchool of Information science and technology, North China University of Technology, No. 5 Jinyuanzhuang Street, Shijingshan District, Beijing 100144, China. lawliet1lch@126.com.
Lintao LiuSchool of Information science and technology, North China University of Technology, No. 5 Jinyuanzhuang Street, Shijingshan District, Beijing 100144, China. liulintao@ime.ac.cn.
Qingyi MengSchool of Information science and technology, North China University of Technology, No. 5 Jinyuanzhuang Street, Shijingshan District, Beijing 100144, China. mengqingyi@ime.ac.cn.
Shuhua WeiSchool of Information science and technology, North China University of Technology, No. 5 Jinyuanzhuang Street, Shijingshan District, Beijing 100144, China. weishuhua@ncut.edu.cn.
Anjie MingState Key Laboratory of Advanced Materials for Smart Sensing, General Research Institute for Nonferrous Metals, No. 11 Xingkedong Street, Huairou District, Beijing 101402, China. mingaj@bu.edu.
Jing ZhangSchool of Information science and technology, North China University of Technology, No. 5 Jinyuanzhuang Street, Shijingshan District, Beijing 100144, China. zhangj@ncut.edu.cn.
Yanrong WangSchool of Information science and technology, North China University of Technology, No. 5 Jinyuanzhuang Street, Shijingshan District, Beijing 100144, China. wangyanrong@ncut.edu.cn.
Lidong WuMinistry of Agriculture, Chinese Academy of Fishery Sciences, No. 150 Qingta Street, Fengtai District, Beijing 100141, China. lidongwu@mit.edu.
Xiaoli ZhuSmart Sensing R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, No. 3 Western Beitucheng Street, Chaoyang District, Beijing 100029, China. zhuxiaoli@ime.ac.cn.
Feng WeiState Key Laboratory of Advanced Materials for Smart Sensing, General Research Institute for Nonferrous Metals, No. 11 Xingkedong Street, Huairou District, Beijing 101402, China. weifeng@grinm.com.
Jiang YanSchool of Information science and technology, North China University of Technology, No. 5 Jinyuanzhuang Street, Shijingshan District, Beijing 100144, China. yangjiang@ncut.edu.cn.

Funding

International Cooperation and Exchange Programme No.81811530114National Natural Science Foundation of China No. 61674003National Natural Science Foundation of China No. 61874002National Natural Science Foundation of China No. 61874137
6 · The paper itself

Abstract

Surface-enhanced Raman spectroscopy (SERS) substrates with high sensitivity and reproducibility are highly desirable for high precision and even molecular-level detection applications. Here, large-scale uniformly hybrid nanoparticle-enhanced Raman spectroscopy (NERS) substrates with high reproducibility and controllability were developed. Using oxygen plasma treatment, large-area and uniformly rough polystyrene sphere (URPS) arrays in conjunction with 20 nm Au films (AuURPS) were fabricated for SERS substrates. Au nanoparticles and clusters covered the surface of the URPS arrays, and this increased the Raman signal. In the detection of malachite green (MG), the fabricated NERS substrates have high reproducibility and sensitivity. The enhancement factor (EF) of Au nanoparticles and clusters was simulated by finite-difference time-domain (FDTD) simulations and the EF was more than 10

Indexed as

Au nanoparticlesmalachite greenreproducibilitysensitivitySERS

Identifiers

PMID31035552
PMCPMC6562888

What OpenQuestion holds

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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.