Title of article
Predicting the mechanical characteristics of hydrogen functionalized graphene sheets using artificial neural network approach
Author/Authors
Vijayaraghavan, Venkatesh School of Mechanical and Aerospace Engineering - Nanyang Technological University - Nanyang Avenue, Singapore , Garg, Akhil School of Mechanical and Aerospace Engineering - Nanyang Technological University - Nanyang Avenue, Singapore , How Wong, Chee School of Mechanical and Aerospace Engineering - Nanyang Technological University - Nanyang Avenue, Singapore , Tai, Kang School of Mechanical and Aerospace Engineering - Nanyang Technological University - Nanyang Avenue, Singapore , Bhalerao, Yogesh MIT Academy of Engineering (MAE) - Pune - Maharashtra, India
Pages
5
From page
1
To page
5
Abstract
The mechanical properties of hydrogen functionalized graphene (HFG) sheets were predicted in this work by using
artificial neural network approach. The predictions of tensile strength of HFG sheets made by the proposed approach
are compared to those generated by molecular dynamics simulations. The results indicate that our proposed
computing technique can be used as a powerful tool for predicting the tensile strength of the HFG sheet.
Keywords
Hydrogen functionalized graphene , Tensile , Atomistic simulation , Nanomechanics , Artificial neural network
Journal title
Astroparticle Physics
Serial Year
2013
Record number
2436049
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