Evidence map›Paper›PMID 39861262›Full record

ArticlePolymers2025

Cell Morphology, Material Property and Ni(II) Adsorption of Microcellular Injection-Molded Polystyrene Reinforced with Graphene Nanoparticles.

Minyuan Chien, Shiachung Chen, Kuanyi Huang, Tlou Nathaniel Moja, Shyhshin Hwang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Sol-Gel Synthesized CuFeGels (Basel, Switzerland) · 2025
    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.

Minyuan ChienDepartment of Vehicle Engineering, Chien-hsin University of Science and Technology, Taoyuan 320678, Taiwan.
Shiachung ChenR&D Center for Smart Manufacturing, Chung Yuan Christian University, Taoyuan 32023, Taiwan.ORCID 0000-0001-9367-6031
Kuanyi HuangDepartment of Mechanical Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan.
Tlou Nathaniel MojaInstitute for Nanotechnology and Water Sustainability Research Unit, College of Science, Engineering and Technology, University of South Africa, Florida Campus, Johannesburg 1709, South Africa.ORCID 0000-0001-8875-3573
Shyhshin HwangDepartment of Mechanical Engineering, Chien-hsin University of Science and Technology, Taoyuan 320678, Taiwan.ORCID 0000-0001-8886-3879

Funding

National Science and Technology Council, Taiwan. 111-2221-E-231-001
6 · The paper itself

Abstract

Graphene's incorporation into polymers has enabled the development of advanced polymer/graphene nanocomposites with superior properties. This study focuses on the use of a microcellular foamed polystyrene (PS)/graphene (GP) nanocomposite (3 wt%) for nickel (II) ion removal from aqueous solutions. Adsorption behavior was evaluated through FTIR, TEM, SEM, TGA, and XRD analyses. Key factors, including initial ion concentration, pH, temperature, and sorbent dosage, were examined. Results showed optimal nickel removal at specific pH levels with removal efficiency decreasing from 91 to 80% as Ni (II) concentrations increased from 10 to 100 mg/L. The adsorption capacity improved from 11 to 130 mg/g. Equilibrium data aligned with Langmuir and Freundlich isotherm models, while adsorption kinetics followed a second-order kinetic model. These findings highlight the potential of PS/GP nanocomposites for nickel ion removal, offering a promising solution for small-scale industrial applications.

Indexed as

adsorptiongraphenemicrocellularnanocompositesnickel removalsecond-order kinetic model

Identifiers

PMID39861262
PMCPMC11768097

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.