Estimation of carbon nanotubes and their applications as reinforcing composite materials–an engineering review

A Garg, HD Chalak, MO Belarbi, AM Zenkour… - Composite …, 2021 - Elsevier
The demand for increasing the strength of the structural element without an increase in the
size of the elements leads to the introduction of reinforcements. Employing carbon …

Overview of polymer nanocomposites: Computer simulation understanding of physical properties

J Zhao, L Wu, C Zhan, Q Shao, Z Guo, L Zhang - Polymer, 2017 - Elsevier
Computer simulations are an important implementation to experimental methods working on
polymer nanocomposites (PNCs), which have advanced properties because of their unique …

Understanding the effect of functionalization in CNT-epoxy nanocomposite from molecular level

W Jian, D Lau - Composites Science and Technology, 2020 - Elsevier
The excellent physical, mechanical, thermal and electrical properties of carbon nanotubes
(CNTs) make them the promising reinforcements for polymer materials. The resulting …

Prediction of tensile strength of polymer carbon nanotube composites using practical machine learning method

TT Le - Journal of Composite Materials, 2021 - journals.sagepub.com
This paper is devoted to the development and construction of a practical Machine Learning
(ML)-based model for the prediction of tensile strength of polymer carbon nanotube (CNTs) …

Design rules for enhanced interfacial shear response in functionalized carbon fiber epoxy composites

B Demir, LC Henderson, TR Walsh - ACS applied materials & …, 2017 - ACS Publications
Carbon-fiber reinforced composites are ideal light-weighting candidates to replace
traditional engineering materials. The mechanical performance of these composites results …

Data-driven multiscale finite-element method using deep neural network combined with proper orthogonal decomposition

S Kim, H Shin - Engineering with Computers, 2024 - Springer
In this paper, a data-driven multiscale finite-element method (data-driven FE2) is proposed
using a deep neural network (DNN) and proper orthogonal decomposition (POD) to …

Atomic-scale insights into interface thermal resistance between epoxy and boron nitride in nanocomposites

X Yang, X Wang, W Wang, Y Fu, Q **e - … Journal of Heat and Mass Transfer, 2020 - Elsevier
The out-plane thermal conductivity of hexagonal boron nitride nanosheet (hBNNS)/epoxy
resin (EP) composites in the perpendicular to the lamellar layers direction as well as the …

Improving inherent thermal conductivity of epoxy resins based on contribution components of thermal conductivity: A molecular dynamics study

X Liu, Q Ai, J Xu, Y Shuai - European Polymer Journal, 2023 - Elsevier
The inherent thermal transport properties of epoxy resin are vital factors to be studied in
applications. In the present work, we constructed the amorphous crosslinking structure, the …

Maximizing the toughness of polymer nanocomposites based on the radial strength of carbon nanotubes

B Goh, J Lee, H Shin, J Choi - Surfaces and Interfaces, 2024 - Elsevier
Similarity in the mechanical properties of a matrix and an inclusion is key to designing tough
nanocomposites. Matching the matrix and inclusions with similar mechanical strengths …

Physical and mechanical properties of vulcanized and filled rubber at high strain rate

Z Yan, A Zaoui, F Zaïri - Chinese Journal of Physics, 2023 - Elsevier
The purpose of this study is to investigate-at nanoscale-cis-Polyisoprene (cis-PI), the main
component of natural rubber. This system is vulcanized by adding elemental sulfur to cis-PI …