Evidence map›Paper›PMID 38559930›Full record

ArticleACS omega2024

Separation and Recovery of Valuable Carbon Components and Li/Ga Metals in Coal Gangue by Using a Flotation Flowsheet.

Dan Fang, Yangchao Xia, Yonggai Li, Yaowen Xing, Zhenyong Miao, Xiahui Gui

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ACS omega, 2024. 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
3.5field-weighted citation impact, top 8% of its field
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, 10 citations in OpenAlex.

  1. Article
  2. Review
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 at 1 institution in 1 country.

Dan FangState Key Laboratory of Coking Coal Resources Green Exploitation, China University of Mining and Technology, Xuzhou 221116, China.
Yangchao XiaState Key Laboratory of Coking Coal Resources Green Exploitation, China University of Mining and Technology, Xuzhou 221116, China.ORCID https://orcid.org/0000-0002-7183-0939
Yonggai LiState Key Laboratory of Coking Coal Resources Green Exploitation, China University of Mining and Technology, Xuzhou 221116, China.
Yaowen XingState Key Laboratory of Coking Coal Resources Green Exploitation, China University of Mining and Technology, Xuzhou 221116, China.ORCID https://orcid.org/0000-0001-7930-4725
Zhenyong MiaoState Key Laboratory of Coking Coal Resources Green Exploitation, China University of Mining and Technology, Xuzhou 221116, China.ORCID https://orcid.org/0000-0002-4595-8867
Xiahui GuiState Key Laboratory of Coking Coal Resources Green Exploitation, China University of Mining and Technology, Xuzhou 221116, China.ORCID https://orcid.org/0000-0001-9270-7756
China University of Mining and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coal gangue (CG), an industrial solid waste with high contents of Li and Ga, has attracted the attention of researchers. However, the utilization of CG remains an economic challenge. Pre-enrichment of Li and Ga by flotation was carried out with a view to improving the comprehensive utilization of CG. Mineral composition, time-of-flight secondary ion mass spectrometry (TOF-SIMS), and elemental composition were used to investigate the embeddedness of each mineral and the mode of elemental occurrence in the CG. The results showed that the main mineral compositions of the CG were kaolinite, quartz, and pyrite. Li and Ga were mainly associated with kaolinite and other clay minerals. Li and Ga had a high correlation with Al

Identifiers

PMID38559930
PMCPMC10976372
OpenAlexW4392761868

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.