Evidence map›Paper›PMID 31909341›Full record

ArticleACS omega2019

Ethanol-Precipitation-Assisted Highly Efficient Synthesis of Nitrogen-Doped Carbon Quantum Dots from Chitosan.

Jun Zhan, Rujie Peng, Sixuan Wei, Jia Chen, Xianghong Peng, Biao Xiao

Abstract read
In one paragraph

Article in ACS omega, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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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

6 authors.

Jun ZhanKey Laboratory of Optoelectronic Chemical Materials and Devices of Ministry of Education, School of Chemistry and Environmental Engineering, Jianghan University, Wuhan 430056, Hubei, China.
Rujie PengKey Laboratory of Optoelectronic Chemical Materials and Devices of Ministry of Education, School of Chemistry and Environmental Engineering, Jianghan University, Wuhan 430056, Hubei, China.
Sixuan WeiKey Laboratory of Optoelectronic Chemical Materials and Devices of Ministry of Education, School of Chemistry and Environmental Engineering, Jianghan University, Wuhan 430056, Hubei, China.
Jia ChenKey Laboratory of Optoelectronic Chemical Materials and Devices of Ministry of Education, School of Chemistry and Environmental Engineering, Jianghan University, Wuhan 430056, Hubei, China.
Xianghong PengKey Laboratory of Optoelectronic Chemical Materials and Devices of Ministry of Education, School of Chemistry and Environmental Engineering, Jianghan University, Wuhan 430056, Hubei, China.
Biao XiaoKey Laboratory of Optoelectronic Chemical Materials and Devices of Ministry of Education, School of Chemistry and Environmental Engineering, Jianghan University, Wuhan 430056, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nitrogen-doped carbon quantum dots (NCQDs) were prepared from chitosan through a hydrothermal reaction. When ethanol precipitation was used as the purification method, a high product yield of 85.3% was obtained. A strong blue fluorescence emission with a high quantum yield (QY) of 6.6% was observed from the NCQD aqueous solution. Physical and chemical characteristics of the NCQDs were carefully investigated by transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier transform infrared spectra (FTIR), Raman spectra, X-ray photoelectron spectroscopy (XPS), and transient fluorescence spectra. Experimental results showed that diameters of the NCQDs were in the range of 2-10 nm. The carbon quantum dots possess good water dispersibility and precipitation by ethanol. When used for metal ion detection, the detection limit of the NCQDs for Fe

Identifiers

PMID31909341
PMCPMC6941364

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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.