Evidence map›Paper›PMID 41276570›Full record

ArticleScientific reports2025

Impact of ferrofluid droplets on hydrophobic surfaces with presence of magnetic fields.

Ghassan Hassan, Bekir Sami Yilbas, Abba Abdulhamid Abubakar, Abdullah Al-Sharafi, Hussain Al-Qahtani

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ghassan HassanMechanical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), 31261, Dhahran, Saudi Arabia.
Bekir Sami YilbasMechanical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), 31261, Dhahran, Saudi Arabia. bsyilbas@kfupm.edu.sa.
Abba Abdulhamid AbubakarMechanical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), 31261, Dhahran, Saudi Arabia.
Abdullah Al-SharafiMechanical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), 31261, Dhahran, Saudi Arabia.
Hussain Al-QahtaniMechanical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), 31261, Dhahran, Saudi Arabia.

Funding

King Fahd University of Petroleum and Minerals K.A.CARE
6 · The paper itself

Abstract

The motion of ferrofluid droplet on hydrophobic surface has attracted significant research interests due to its potential applications in biomedicine, sensor technologies, and oil-water separation processes. This study investigates ferrofluid droplet impact on a hydrophobic surface and analyzes how ferromagnetic particles in the droplet affect the interaction characteristics of droplet in terms of spreading, retraction, and the formation of secondary droplets during rebound cycles. The results reveal that introducing a magnetic field reduces the droplet spreading factor by approximately 20%. Additionally, increasing ferro particles concentrations to 0.05% (wt%) gives rise to a significant reduction in the spreading factor. The effect on the droplet rebound height is also noteworthy: for a lower particle concentration (0.005%, wt%), the restitution coefficient decreases by 15.5%. However, at high weight concentration (0.05%), this decrease is as much as 69%, which indicates a strong dependency on particle concentration. The analysis shows that the force generated under magnetic field, which is around 2.28 × 10

Indexed as

Droplet impactFerro particlesHydrophobic surfaceMagnet

Identifiers

PMID41276570
PMCPMC12698854

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.