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Nuwan Dewapriya's blog

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Characterizing fracture stress of defective graphene samples using shallow and deep artificial neural networks

Abstract: Advanced machine learning methods could be useful to obtain novel insights into some challenging nanomechanical problems. In this work, we employed artificial neural networks to predict the fracture stress of defective graphene samples. First, shallow neural networks were used to predict the fracture stress, which depends on the temperature, vacancy concentration, strain rate, and loading direction.

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Performing Uniaxial Tensile Tests of Graphene in LAMMPS

I would like to share the codes required to perform an end-to-end molecular dynamics simulation, which will be useful to the novice researchers in the filed of atomistic simulations. I focus on simulating uniaxial tensile tests of a graphene sample in the LAMMPS molecular dynamics simulator, and I have attached two MATLAB scripts to create the input files for LAMMPS and to extract data from the LAMMPS output file.

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Modelling fracture of graphene using Griffith’s criterion and quantized fracture mechanics

In armchair graphene sheets, crack propagates perpendicular to the applied strain, whereas crack propagation in zigzag sheets occurs at an angle to the straining direction. This occurs due to different bond structure along armchair and zigzag directions as shown in Fig. 1. Videos 1 and 2 show the fracture of armchair and zigzag sheets, respectively.

 

Fig. 1: Armchair and zigzag directions of graohene

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Visualizing LAMMPS molecular dynamics trajectories using visual molecular dynamics (VMD)

It is very important to visualize molecular dynamics (MD) trajectories since there are many aspects of MD simulations which are difficult to identify without a proper visualization tool. Improper bounday condition in MD is one of such examples. I use Visual Molecular Dynamics (VMD) to visualize my MD simulations. Some of my movies, created using VMD, are shown below.

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Running MD simulations with LAMMPS

In appendix A of my PhD thesis, I share a MATLAB code to get coordinates of carbon atoms in a graphene sheet. The code also generates the data file required for LAMMPS. In addition, I included a sample input and the corresponding output files from LAMMPS. I hope this will be useful for those who would like to learn MD simulations.

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