Evidence map›Paper›PMID 36077497›Full record

ArticleInternational journal of molecular sciences2022

Cow Dung-Based Biochar Materials Prepared via Mixed Base and Its Application in the Removal of Organic Pollutants.

Xiaoxin Chen, Gengxin Yu, Yuanhui Chen, Shanshan Tang, Yingjie Su

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Mycelium-Doped Straw Biochars for Antibiotic Control.International journal of molecular sciences · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. 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.

Xiaoxin ChenCollege of Life Sciences, Jilin Agricultural University, Changchun 130118, China.
Gengxin YuCollege of Life Sciences, Jilin Agricultural University, Changchun 130118, China.
Yuanhui ChenKey Laboratory of Straw Comprehensive Utilization and Black Soil Conservation, Ministry of Education, Jilin Agricultural University, Changchun 130118, China.ORCID 0000-0003-4408-7016
Shanshan TangCollege of Life Sciences, Jilin Agricultural University, Changchun 130118, China.ORCID 0000-0002-7212-0402
Yingjie SuCollege of Life Sciences, Jilin Agricultural University, Changchun 130118, China.

Funding

Education Department of Jilin Province JJKH20210323KJJilin Scientific and Technological Development Program 20220203108SFNational College Students Innovation and Entrepreneurship Project in China none
6 · The paper itself

Abstract

Cow dung (CD) is a waste product of livestock production. Improper disposal of a large amount of CD will cause environmental pollution. In this work, three biochar materials based on CD (BMCD) were prepared by using three types of base, including KOH, NaOH, and mixed base (MB, a mixture of equal mass NaOH and KOH) as activators to investigate the different physicochemical properties of BMCDs (BMCD-K, BMCD-Na, and BMCD-MB). The objective was to verify the effectiveness of MB activation in the preparation of biochar materials. The results show that MB has an effect on the structural characteristics of BMCDs. In particular, the surface area and total pore volume, the specific surface area, and the total pore volume of BMCD-MB (4081.1 m

Indexed as

Environmental PollutantsWater Pollutants, ChemicalAdsorptionAnimalsCattleCharcoalFemaleKineticsSodium HydroxideTetracyclinebiocharCharcoalEnvironmental PollutantsSodium HydroxideTetracyclineWater Pollutants, Chemicaladsorptionbiochar materialscow dungindustrial wastewaterorganic pollutants

Identifiers

PMID36077497
PMCPMC9456264

What OpenQuestion holds

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LicenceCC BY
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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.