Evidence map›Paper›PMID 29053627›Full record

ArticleSensors (Basel, Switzerland)2017

Silicon Nanocrystals with pH-Sensitive Tunable Light Emission from Violet to Blue-Green.

Jing Wang, Junhong Guo, Jing Chen

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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.

Jing WangDepartment of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China. IreneWang@njupt.edu.cn.
Junhong GuoDepartment of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China. jhguo@njupt.edu.cn.
Jing ChenDepartment of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China. jchen@njupt.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We fabricated a silicon nanocrystal (NC) suspension with visible, continuous, tunable light emission with pH sensitivity from violet to blue-green. Transmission electron microscopy (TEM) images and X-ray diffraction (XRD) pattern analysis exhibit the highly crystalline nanoparticles of silicon. Photoluminescence (PL) spectra and photoluminescence excitation (PLE) spectra at different pH values, such as 1, 3, 5, 7, 9, and 11, reveal the origins of light emission from the silicon NC suspension, which includes both the quantum confinement effect and surface bonding. The quantum confinement effect dominates the PL origins of silicon NCs, especially determining the tunability and the emission range of PL, while the surface bonding regulates the maximum peak center, full width at half maximum (FWHM), and offsets of PL peaks in response to the changing pH value. The peak fitting of PLE curves reveals one of the divided PLE peaks shifts towards a shorter wavelength when the pH value increases, which implies correspondence with the surface bonding between silicon NCs and hydrogen atoms or hydroxyl groups. The consequent detailed analysis of the PL spectra indicates that the surface bonding results in the transforming of the PL curves towards longer wavelengths with the increasing pH values, which is defined as the pH sensitivity of PL. These results suggest that the present silicon NCs with pH-sensitive tunable light emission could find promising potential applications as optical sources, bio-sensors, etc.

Indexed as

nanocrystalsphotoluminescencepH sensitivesilicon

Identifiers

PMID29053627
PMCPMC5677222

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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.