Estimating of contact area among carbon nanofibers in nanocomposites by the features of network, tunnel and interphase

A larger contact area (S) among the nanoparticles significantly enhances electron transfer within nanocomposites; however, S remains an indeterminate factor. In this paper, two innovative models for the conductivity of carbon nanofiber (CNF) polymer samples (PCNFs) are integrated to express S as a function of various parameters, including CNF concentration, waviness, percolation onset, CNF dimensions, interphase depth, network fraction, and tunneling diameter. Extensive experimental conductivity data substantiate the robustness of the proposed models. Moreover, the influence of each parameter on S is systematically analyzed to validate the developed equation. The highest contact area is achieved by the maximum CNF concentration, the thinnest and longest nanofibers, minimal waviness, the densest interphase, and the highest network fraction. Specifically, S value of 1400 nm<sup>2</sup> is observed with a contact number of 200 and a percolation onset ([Formula: see text]) of 0.002, whereas the contact area diminishes to zero at [Formula: see text] = 0.03. Thus, a greater number of contacts and a lower percolation onset are favorable to increase the contact area, while minimal contacts and a higher percolation onset result in the absence of contact area.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-10-28
DOI
https://doi.org/10.1038/s41598-025-99703-4
Citations
4
Primary Topic
Carbon Nanotubes in Composites
Type
article
Field-Weighted Citation Impact
2.07
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimating of contact area among carbon nanofibers in nanocomposites by the features of network, tunnel and interphase

Muhammad Naqvi, Yasser Zare, Soo‐Jin Park, Kyong Yop Rhee
4 citations
Scientific Reports
Carbon Nanotubes in Composites
2.07
article

Estimating of contact area among carbon nanofibers in nanocomposites by the features of network, tunnel and interphase

Muhammad Naqvi, Yasser Zare, Soo‐Jin Park, Kyong Yop Rhee
article en
4 citations

Abstract

A larger contact area (S) among the nanoparticles significantly enhances electron transfer within nanocomposites; however, S remains an indeterminate factor. In this paper, two innovative models for the conductivity of carbon nanofiber (CNF) polymer samples (PCNFs) are integrated to express S as a function of various parameters, including CNF concentration, waviness, percolation onset, CNF dimensions, interphase depth, network fraction, and tunneling diameter. Extensive experimental conductivity data substantiate the robustness of the proposed models. Moreover, the influence of each parameter on S is systematically analyzed to validate the developed equation. The highest contact area is achieved by the maximum CNF concentration, the thinnest and longest nanofibers, minimal waviness, the densest interphase, and the highest network fraction. Specifically, S value of 1400 nm<sup>2</sup> is observed with a contact number of 200 and a percolation onset ([Formula: see text]) of 0.002, whereas the contact area diminishes to zero at [Formula: see text] = 0.03. Thus, a greater number of contacts and a lower percolation onset are favorable to increase the contact area, while minimal contacts and a higher percolation onset result in the absence of contact area.

Scientific ReportsVol. 15(1)
Academic Center for Education, Culture and Research (IR), American University of the Middle East (KW), Kyung Hee University (KR), Motamed Cancer Institute (IR)
Openalex Percentile: Top 12%
Carbon Nanotubes in Composites
2.07
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.