Anisotropic deformation of strongly bent graphene: A study from machine learning

Read full text
Authors: Song-Chuan Zhou, Jun‐Ding Zheng, Zhi-qiang Bao, Chun-Gang Duan
Cited by: 0
References: 44

Abstract

Bent phenomena such as scrolls, ripples, and bubbles are inherent to the growth and application of graphene and critically influence its properties. The study of the bending behavior is, therefore, essential for the fabrication, functioning, and robustness of graphene-based devices. Here, we investigate the structure and phonon spectrum of bent graphene through deep potential modeling. Our results reveal a pronounced mechanical anisotropy under strong bending. The curvature is distributed uniformly when bent along the armchair direction but becomes highly localized along the zigzag direction. Localized curvature induces significant lattice distortion, which lifts the degeneracy of the longitudinal optical and transverse optical phonon modes. This lifting results in the splitting of the G peak in the Raman spectrum, providing a signature for experimental verification. Our work offers insights into the research on graphene bending and graphene-based devices.

Fields of Study & Subjects

Graphene research and applications Machine Learning in Materials Science 2D Materials and Applications

Publication details

Journal / source
APL Computational Physics
Volume
2
Issue
1
Publication date
11 February 2026
Language
EN