Impact of chirality on nanotube fracture strain: comprehensive machine learning potential calculations

Q: What type of study is this?

This is a Quantitative Study study.

Sherif Abdulkader Tawfik; Tri Minh Nguyen; Truyen Tran; Sunil Gupta; Svetha Venkatesh

doi:10.1039/d5nr02768c

January 1, 2025Nanoscale

Impact of chirality on nanotube fracture strain: comprehensive machine learning potential calculations

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Key Points

Fracture strain in carbon nanotubes depends significantly on their chirality, with distinct variances observed.
The study utilizes the direct integration of the exchange potential machine learning potential to calculate strain values.
Comparative analysis shows that different chiralities result in varied fracture behavior under stress conditions.
Understanding these relationships may enhance the development of carbon nanotube-based materials for various applications.

Implication

Comprehensive analysis reveals how chirality impacts fracture strain in carbon nanotubes, indicating potential applications.

Abstract

We present a comprehensive study of fracture strains in carbon nanotubes (CNTs) as a function of their chirality using the direct integration of the exchange potential (DIEP) machine learning potential...

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Cite This Study

Tawfik et al. (2025) studied this question.

synapsesocial.com/papers/68d454c531b076d99fa59fb4 https://doi.org/10.1039/d5nr02768c

View Full Paper

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Impact of chirality on nanotube fracture strain: comprehensive machine learning potential calculations

Key Points

Implication

Abstract

Discussion

Cite This Study

Impact of chirality on nanotube fracture strain: comprehensive machine learning potential calculations

Key Points

Implication

Abstract

Discussion

Cite This Study

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