Abstract
Due to the inherent spatial and temporal limitations of atomistic modeling and the lack of efficient mesoscopic models, mesoscale simulation methods for guiding the development of super strong lightweight material systems comprising collapsed carbon nanotubes (CNTs) are currently missing. Here we establish a path for deriving ultra-coarse-grained mesoscopic distinct element method (mDEM) models directly from the quantum mechanical representation of a collapsed CNT. Atomistic calculations based on density functional-based tight-binding (DFTB) extended with Lennard-Jones interactions allow for the identification of the cross-section and elastic constants of an elastic beam idealization of a collapsed CNT. Application of the DFTB quantum treatment is possible due to the simplification in the number of atoms introduced by accounting for the helical and angular symmetries exhibited by twisted and bent CNTs. The multiscale modeling chain established here is suitable for deriving ultra-coarse-grained mesoscopic models for a variety of microscopic filaments presenting complex interatomic bondings.
Original language | English (US) |
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Pages (from-to) | 786-792 |
Number of pages | 7 |
Journal | Carbon |
Volume | 143 |
DOIs | |
State | Published - Mar 2019 |
Bibliographical note
Funding Information:This work was supported by NSF Grant No. CMMI-1332228, NASA's Space Technology Research Grant NNX16AE03G, and by the Institute for Ultra-Strong Composites by Computational Design, Grant NNX17AJ32G. Resources supporting this work were provided by the Minnesota Supercomputing Institute and by NASA High End Computing Program through the NASA Advanced Supercomputing Division at Ames Research Center. T.D. thanks the Hanse Wissenschaftskolleg, Delmenhorst, Germany, for hospitality.
Funding Information:
This work was supported by NSF Grant No. CMMI-1332228 , NASA's Space Technology Research Grant NNX16AE03G , and by the Institute for Ultra-Strong Composites by Computational Design , Grant NNX17AJ32G . Resources supporting this work were provided by the Minnesota Supercomputing Institute and by NASA High End Computing Program through the NASA Advanced Supercomputing Division at Ames Research Center. T.D. thanks the Hanse Wissenschaftskolleg, Delmenhorst, Germany, for hospitality.
Publisher Copyright:
© 2018 Elsevier Ltd