Evidence map›Paper›PMID 36234382›Full record

ArticleMaterials (Basel, Switzerland)2022

Modeling of Electrical Conductivity for Polymer-Carbon Nanofiber Systems.

Sajad Khalil Arjmandi, Jafar Khademzadeh Yeganeh, Yasser Zare, Kyong Yop Rhee

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2022. 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. Informatics-Based Design of Virtual Libraries of Polymer Nano-Composites.International journal of molecular sciences · 2025
    Article
  2. 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

4 authors.

Sajad Khalil ArjmandiDepartment of Polymer Engineering, Faculty of Engineering, Qom University of Technology, Qom 371951519, Iran.
Jafar Khademzadeh YeganehDepartment of Polymer Engineering, Faculty of Engineering, Qom University of Technology, Qom 371951519, Iran.
Yasser ZareBiomaterials and Tissue Engineering Research Group, Breast Cancer Research Center, Department of Interdisciplinary Technologies, Motamed Cancer Institute, ACECR, Tehran 1125342432, Iran.ORCID 0000-0002-1293-8878
Kyong Yop RheeDepartment of Mechanical Engineering (BK21 Four), College of Engineering, Kyung Hee University, Yongin 17104, Korea.ORCID 0000-0001-7269-9728

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is not a simple model for predicting the electrical conductivity of carbon nanofiber (CNF)-polymer composites. In this manuscript, a model is proposed to predict the conductivity of CNF-filled composites. The developed model assumes the roles of CNF volume fraction, CNF dimensions, percolation onset, interphase thickness, CNF waviness, tunneling length among nanoparticles, and the fraction of the networked CNF. The outputs of the developed model correctly agree with the experimentally measured conductivity of several samples. Additionally, parametric analyses confirm the acceptable impacts of main factors on the conductivity of composites. A higher conductivity is achieved by smaller waviness and lower radius of CNFs, lower percolation onset, less tunnel distance, and higher levels of interphase depth and fraction of percolated CNFs in the nanocomposite. The maximum conductivity is obtained at 2.37 S/m by the highest volume fraction and length of CNFs.

Indexed as

carbon nanofiberelectrical conductivityinterphaseparametric analysispercolationpolymer nanocompositestunnelingvolume fraction

Identifiers

PMID36234382
PMCPMC9571830

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.