Evidence map›Paper›PMID 39759347›Full record

ArticleHeliyon2024

Enhanced drilling waste-water treatment through magnetic nano-composite coagulant application: A central composite design study.

Behrad Shadan, Arezou Jafari, Reza Gharibshahi

Abstract read
In one paragraph

Article in Heliyon, 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
–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

2 citing papers in PubMed.

  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

3 authors.

Behrad ShadanFaculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran.
Arezou JafariFaculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran.
Reza GharibshahiFaculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A magnetic nano-composite coagulant has been designed, originally applied in a specific industrial waste-water treatment, and statistically investigated using Central Composite Design (CCD). The generated polynomial models were utilized to achieve a comprehensive understanding of the impact of each ingredient of PolyAluminum Chloride (PAC), PolyAcrylAmide (PAM), and Iron (III) oxide magnetic nano particles (MNP) regarding optimum limits and conditions. The concentration of each of those components has been considered as the main effective factors, which are found to be significantly correlated, affecting the Total Dissolved Solid (TDS) removal (%), the Total Suspended Solid (TSS) removal (%), and the Turbidity Reduction Rate (TRR) NTU/min. The reliable statistical model for each response underscored the pivotal role of MNP in shaping each response variable. The influence of MNP and PAC, emerged as crucial in enhancing TDS removal, by increasing the kinetic energy of charged ions and the chance of the successful displacement reaction, helping to dissolve with a high surface activity, and the adsorption of magnetic heavy ions. The correlated concentration of MNP also exhibited a significant impact on TSS elimination, and TRR, concurrently, which revealed the importance of controlling the bulk density of generated flocs, to prevent premature and immature settling to optimize pollution removal. The highest recorded results are 72.00 %, 77.01 %, and 23.82 NTU per minute for TDS and TSS removal and TRR, respectively. The experimental records, along with the statistical investigation remarked a promising potential of the achieved Magnetic Nano-composite Coagulant (MNC), and generated practical knowledge of its novel application for drilling waste-water management.

Indexed as

CoagulantDrillingMagnetic nano-compositeTDS removalTSS removalWaste-water treatment

Identifiers

PMID39759347
PMCPMC11696650

What OpenQuestion holds

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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.