کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1552649 1513207 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Nanomechanics analysis of perfect and defected graphene sheets via a novel atomic-scale finite element method
ترجمه فارسی عنوان
تجزیه و تحلیل نانومکانیک ورق های گرافن کامل و نقص از طریق یک روش عنصر محدود با مقیاس اتمی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی مواد مواد الکترونیکی، نوری و مغناطیسی
چکیده انگلیسی


• Performance of perfect and defected SLGSs is analyzed by a novel AFEM.
• Evaluation of the proposed method is conducted through MD simulations.
• The computational cost of the method is much reduced (∼100 times) compared to MD.
• The continuum-based method is successfully used to model the cracks and defects.

Due to their accuracy and reliability, atomistic-based methods such as molecular dynamics (MD) simulations have played an essential role in the field of predictive modeling of single layered graphene sheets (SLGSs) at the nanoscale. However, their applications are limited due to the computational costs. Additionally, consistent with the discrete nature of SLGSs, conventional continuum-based methods cannot be utilized to study the mechanical characteristics of these nanostructures. To overcome these issues, a new Atomic-scale Finite Element Method (AFEM) based on the Tersoff-Brenner potential has been developed in this study. Efficiency of the proposed method is demonstrated employing several numerical examples and its applicability is carefully testified in the case of perfect and defected SLGSs. To facilitate a better comparison, the mechanical behavior obtained by this method is compared with the one determined via MD simulation in various case studies. The results reveal that the proposed method has the accuracy of MD simulations and the speed of continuum-based approaches, simultaneously.

Figure optionsDownload as PowerPoint slide

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Superlattices and Microstructures - Volume 94, June 2016, Pages 1–12
نویسندگان
, ,