Evidence map›Paper›PMID 34124453›Full record

ArticleACS omega2021

Contactless Method for Electrocoalescence of Water in Oil.

Mohcen Shahbaznezhad, Amir Dehghanghadikolaei, Hossein Sojoudi

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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Mechanistic Insights into Emulsion Destabilization by Electric Fields.Langmuir : the ACS journal of surfaces and colloids · 2025
    Article
  2. Article
  3. Article
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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.

Mohcen ShahbaznezhadDepartment of Electrical Engineering and Computer Science and Department of Mechanical, Industrial, and Manufacturing Engineering, The University of Toledo, Toledo, Ohio 43606, United States.
Amir DehghanghadikolaeiDepartment of Electrical Engineering and Computer Science and Department of Mechanical, Industrial, and Manufacturing Engineering, The University of Toledo, Toledo, Ohio 43606, United States.
Hossein SojoudiDepartment of Electrical Engineering and Computer Science and Department of Mechanical, Industrial, and Manufacturing Engineering, The University of Toledo, Toledo, Ohio 43606, United States.ORCID https://orcid.org/0000-0002-5278-9088

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper discusses an experimental approach to study the effects of a contactless method on electrocoalescence of water-in-oil mixture/emulsion. A positive corona discharge is utilized using a sharp conductive needle without direct contact with the mixture/solution to avoid potential corrosion of the electrode. This creates a nonuniform electric field, which is further used for the coalescence of water droplets in the range of micro to macro in oil. Two approaches are employed in this study: qualitative analysis conducted by visually studying coalescence patterns in videos captured with a high-speed camera and a quantitative analysis based on calculations obtained from dynamic light scattering measurements. From the behavior of the water droplets under the electric field, it is observed that dipole-dipole interaction, migratory coalescence/electrophoresis, and dielectrophoresis have major roles in promoting the coalescence events. The effects of oil viscosity and power consumption on the coalescence rate are also investigated, suggesting an optimal oil-water separation process. The results of this study pave a path for developing a safe, contactless, rapid, and low-power-consuming separation process, potentially suitable for an offsite application.

Identifiers

PMID34124453
PMCPMC8190923

What OpenQuestion holds

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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.