QM/MM hybrid simulations of critical failure at the interface in CNT/polymer nanocomposites.
ORAL
Abstract
Functionalized carbon nanotube (CNT)/polymer composites have received significant interest as promising structural materials with applications in the most demanding areas of industry such as aerospace and ballistic protection. Developing a fundamental understanding of failure mechanisms at the CNT/polymer interface is essential to improving their properties. Here, we use a quantum mechanics/molecular mechanics (QM/MM) hybrid approach to show how chemical structure at the CNT/polymer interface determines its strength and propose candidate chemistries to guide further experimental work.
Computational investigation of interfacial failure in composite materials is challenging because it is inherently multi-scale: the bond-breaking processes that occur at the covalently bonded interface and initiate failure involve QM phenomena, yet the mechanisms by which external stresses are transferred through the matrix occur on length and time-scales far in excess of anything that can be simulated with QM. Here, we demonstrate and validate an adaptive QM/MM simulation method that can be used to address these issues. We demonstrate that the hybrid method results are in excellent agreement with fully-QM benchmark simulations and offers qualitative insights missing from classical simulations.
Computational investigation of interfacial failure in composite materials is challenging because it is inherently multi-scale: the bond-breaking processes that occur at the covalently bonded interface and initiate failure involve QM phenomena, yet the mechanisms by which external stresses are transferred through the matrix occur on length and time-scales far in excess of anything that can be simulated with QM. Here, we demonstrate and validate an adaptive QM/MM simulation method that can be used to address these issues. We demonstrate that the hybrid method results are in excellent agreement with fully-QM benchmark simulations and offers qualitative insights missing from classical simulations.
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Presenters
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Jacek Golebiowski
- Imperial College London