Evidence map›Paper›PMID 40805347›Full record

ArticleMaterials (Basel, Switzerland)2025

Research on Preventing High-Density Materials from Settling in Liquid Resin.

Lixin Xuan, Zhiqiang Wang, Xuan Yang, Xiao Wu, Junjiao Yang, Shijun Zheng

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 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

6 authors.

Lixin XuanAVIC Research Institute for Special Structures of Aeronautical Composite, Jinan 250023, China.
Zhiqiang WangAVIC Research Institute for Special Structures of Aeronautical Composite, Jinan 250023, China.
Xuan YangAVIC Research Institute for Special Structures of Aeronautical Composite, Jinan 250023, China.
Xiao WuAVIC Research Institute for Special Structures of Aeronautical Composite, Jinan 250023, China.
Junjiao YangCollege of Chemistry, Beijing University of Chemical Technology, Beijing 100029, China.
Shijun ZhengCollege of Materials Science, Beijing University of Chemical Technology, Beijing 100029, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The applications of magnetic particles in anti-counterfeiting and anti-absorbing coatings and other functional materials are becoming increasingly widespread. However, due to their high density, the magnetic particles rapidly settle in organic resin media, significantly affecting the quality of the related products. Thereby, reducing the density of the particles is essential. To achieve this goal, high-density magnetic particles were coated onto the surface of hollow silica using anion-cation composite technology. Further, the silane coupling agent N-[3-(trimethoxysilyl)propyl]ethylenediamine was bonded to the surface of magnetic particles to form an amino-covered interfacial layer with a pH value of 9.28, while acrylic acid was polymerized and coated onto the surface of hollow silica to form a carboxyl-covered interfacial layer with a pH value of 4.65. Subsequently, the two materials were compounded to obtain a low-density composite magnetic material. The morphologies and structural compositions of the magnetic composite materials were studied by FTIR, SEM, SEM-EDS, XRD, and other methods. The packing densities of the magnetic composite materials were compared using the particle packing method, thereby solving the problem of magnetic particles settling in the resin solution.

Indexed as

hollow silicamagnetic particlessurface coating

Identifiers

PMID40805347
PMCPMC12347530

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.