From Reinforcement to Prediction: Mechanical Behavior and Modeling of CNT-Reinforced Cementitious Composites
- 1Department of Applied Science and Technology (DISAT), Politecnico di Torino, c.so Duca degli Abruzzi 24, 10129 Torino, Italy
Abstract
Cement-based materials are among the most widely used substances in the construction industry owing to their widespread availability and reliable performance. However, their quasi-brittle behavior and limited tensile capacity often lead to the initiation and propagation of microcracks, which can compromise durability and structural integrity. In this context, the incorporation of carbon nanotubes (CNTs), owing to their exceptional stiffness and strength, has emerged as a promising strategy to enhance the mechanical performance of cementitious matrices and mitigate their intrinsic brittleness. This comprehensive review critically assesses the reinforcing mechanisms associated with CNT addition, with particular emphasis on hydration promotion and nucleation effects, pore-filling and microstructural densification, CNT–matrix interfacial interaction and crack propagation inhibition. Furthermore, this work critically examines modeling approaches for predicting the mechanical properties of CNT-reinforced cementitious composites, including analytical formulations, numerical methods and recent advances based on machine learning and artificial intelligence. This review aims to consolidate the current state of knowledge while highlighting current limitations and outlining future research directions for the development of high-performance cementitious composites.
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BibTeX
@article{rimondotto2026from,
title = {{From Reinforcement to Prediction: Mechanical Behavior and Modeling of CNT-Reinforced Cementitious Composites}},
author = {Nicolò Rimondotto and Alice Rossi and Matteo Pavese and Luca Lavagna},
journal = {Nanomaterials},
year = {2026},
month = oct,
doi = {10.3390/nano16211371},
url = {https://www.mdpi.com/2079-4991/16/21/1371},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - From Reinforcement to Prediction: Mechanical Behavior and Modeling of CNT-Reinforced Cementitious Composites
AU - Nicolò Rimondotto
AU - Alice Rossi
AU - Matteo Pavese
AU - Luca Lavagna
PY - 2026
DA - 2026/10/27
JO - Nanomaterials
DO - 10.3390/nano16211371
UR - https://www.mdpi.com/2079-4991/16/21/1371
AB - Cement-based materials are among the most widely used substances in the construction industry owing to their widespread availability and reliable performance. However, their quasi-brittle behavior and limited tensile capacity often lead to the initiation and propagation of microcracks, which can compromise durability and structural integrity. In this context, the incorporation of carbon nanotubes (CNTs), owing to their exceptional stiffness and strength, has emerged as a promising strategy to enhance the mechanical performance of cementitious matrices and mitigate their intrinsic brittleness. This comprehensive review critically assesses the reinforcing mechanisms associated with CNT addition, with particular emphasis on hydration promotion and nucleation effects, pore-filling and microstructural densification, CNT–matrix interfacial interaction and crack propagation inhibition. Furthermore, this work critically examines modeling approaches for predicting the mechanical properties of CNT-reinforced cementitious composites, including analytical formulations, numerical methods and recent advances based on machine learning and artificial intelligence. This review aims to consolidate the current state of knowledge while highlighting current limitations and outlining future research directions for the development of high-performance cementitious composites.
SN - 2079-4991
ER -