Evidence map›Paper›PMID 34035405›Full record

ArticleScientific reports2021

Removal of hexavalent chromium from wastewater by Cu/Fe bimetallic nanoparticles.

Jien Ye, Yi Wang, Qiao Xu, Hanxin Wu, Jianhao Tong, Jiyan Shi

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Saudi journal of biological sciences · 2023
    Article
  8. Article
  9. Article
  10. 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

6 authors.

Jien YeDepartment of Environmental Engineering, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Yi WangDepartment of Environmental Engineering, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Qiao XuDepartment of Environmental Engineering, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Hanxin WuDepartment of Environmental Engineering, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Jianhao TongDepartment of Environmental Engineering, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Jiyan ShiDepartment of Environmental Engineering, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China. shijiyan@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Passivation of nanoscale zerovalent iron hinders its efficiency in water treatment, and loading another catalytic metal has been found to improve the efficiency significantly. In this study, Cu/Fe bimetallic nanoparticles were prepared by liquid-phase chemical reduction for removal of hexavalent chromium (Cr(VI)) from wastewater. Synthesized bimetallic nanoparticles were characterized by transmission electron microscopy, Brunauer-Emmet-Teller isotherm, and X-ray diffraction. The results showed that Cu loading can significantly enhance the removal efficiency of Cr(VI) by 29.3% to 84.0%, and the optimal Cu loading rate was 3% (wt%). The removal efficiency decreased with increasing initial pH and Cr(VI) concentration. The removal of Cr(VI) was better fitted by pseudo-second-order model than pseudo-first-order model. Thermodynamic analysis revealed that the Cr(VI) removal was spontaneous and endothermic, and the increase of reaction temperature facilitated the process. X-ray photoelectron spectroscopy (XPS) analysis indicated that Cr(VI) was completely reduced to Cr(III) and precipitated on the particle surface as hydroxylated Cr(OH)

Identifiers

PMID34035405
PMCPMC8149398

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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.