Evidence map›Paper›PMID 34308081›Full record

ArticleACS omega2021

Enrichment Characteristics of Macerals during Triboelectrostatic Separation in the View of Surface Microstructure, Pore distribution, and Typical Electrical Parameters.

Xin He, Hao Sun, Mengya Ma, Xinxi Zhang, Wenfeng Wang

Abstract read
In one paragraph

Article in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Xin HeKey Laboratory of Coalbed Methane Resource & Reservoir Formation Process, Ministry of Education, China University of Mining & Technology, Xuzhou 221008, China.ORCID https://orcid.org/0000-0003-3352-8832
Hao SunNational Engineering Research Center of Coal Preparation and Purification, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China.
Mengya MaKey Laboratory of Coalbed Methane Resource & Reservoir Formation Process, Ministry of Education, China University of Mining & Technology, Xuzhou 221008, China.
Xinxi ZhangSchool of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.
Wenfeng WangKey Laboratory of Coalbed Methane Resource & Reservoir Formation Process, Ministry of Education, China University of Mining & Technology, Xuzhou 221008, China.ORCID https://orcid.org/0000-0002-2200-0250

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vitrinite and inertinite, respectively, are the reactive and inert macerals for coal liquefaction, which could be effectively enriched in triboelectrostatic separation specialized in particle processing. Inertinite has a higher specific surface area and more pores than vitrinite and a more balanced mesopores distribution, while the mesopores in vitrinite are mainly focused in the 4 nm × 7 nm range. As for electrical properties, inertinite has a higher relative dielectric constant than vitrinite in all granularities, while its resistivity is only higher than vitrinite in the <74 μm fraction, which means inertinite and vitrinite tend to have negative and positive charges, respectively, in their mutual friction, but inertinite (<74 μm) has a stronger ability to maintain surface charge. During triboelectrostatic separation, the 105 μm × 150 μm fraction of clean coal has the highest vitrinite content, whereas inertinite tends to concentrate at tailings <74 μm under the co-effect of separation granularity limit and electrical characteristics of macerals; this conclusion has a certain guiding significance to maceral separation.

Identifiers

PMID34308081
PMCPMC8296598

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LicenceCC BY-NC-ND
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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.