Exercise 0

Exercise 0#

Aim

  1. Make sure that you have installed all the tools properly.

  2. You can access the computer cluster

  3. You can perform basic tasks on the computer cluster

Part 1#

  1. Go to your network directory and create a directory called ex0

  2. Create the following subdirectories inside the ex0 directory: lammps,ase

You will execute small simulations in each of the above subdirectories

Part 2: ASE#

  1. Copy the following code to a file named test.py

from ase.spacegroup import crystal
from ase.visualize import view
from ase.build import surface
from ase import Atoms
import numpy as np
from ase.io import read, write

gAl2O3 = crystal(['Al','Al','Al',
                 'Al','Al','Al',
                 'O','O','O','O',
                 'O','O','O','O'],
                 basis=[(0.377,3./4.,0.126),(0.868,1./4.,0.498),(0.875,3./4.,0.125),(0.615,3./4.,0.745),(0.367,0.075,0.612),(0.116,0.579,0.862),(0.881,3./4.,0.874),(0.614,1./4.,0.640),(0.364,3./4.,0.889),(0.132,1./4.,0.627),(0.889,0.406,0.899),(0.605,0.917,0.614),(0.357,0.406,0.853),(0.138,0.916,0.637)],
                 spacegroup=11,
                 cellpar=[5.577, 8.401, 8.069, 90, 90.59, 90])
gAl2O3_110 = surface(gAl2O3, (1, 0, 0), 2)

gAl2O3_110 = gAl2O3_110.repeat((4,2,1))

del gAl2O3_110[gAl2O3_110.positions[:, 2] > 8.9]

write('al2o3.xyz',gAl2O3_110)

  1. Activate the python environment using following two commands

    • module load anaconda3/2021.11

    • conda activate ase

Note

You will have to perform the two steps above every time you want to execute a python script

  1. Execute the file using the following command inside the folder ase

python test.py

  1. Download the al2o321.xyz file and visualize it using OVITO. (You can access your files using files tab here)

Create an image using OVITO showing the top and two side views of the structure in the downloaded file.

Part 3: LAMMPS#

  1. Copy the following code to a file named in.lammps

units           lj
atom_style      atomic

lattice         fcc 0.8442
region          box block 0 30 0 30 0 30
create_box      1 box
create_atoms    1 box
mass            1 1.0

velocity        all create 1.0 87287

pair_style      lj/cut 2.5
pair_coeff      1 1 1.0 1.0 2.5

neighbor        0.3 bin
neigh_modify    every 20 delay 0 check no

fix             1 all nve
fix             2 all langevin 1.0 1.0 1.0 48279

timestep        0.005

thermo          500
run             10000

  1. Use the following text to make a file named job.slurm

#!/bin/bash
#SBATCH --job-name=lj-melt       # create a short name for your job
#SBATCH --nodes=1                # node count
#SBATCH --ntasks=4               # total number of tasks across all nodes
#SBATCH --cpus-per-task=1        # cpu-cores per task (>1 if multi-threaded tasks)
#SBATCH --mem-per-cpu=1G         # memory per cpu-core (4G is default)
#SBATCH --time=00:05:00          # total run time limit (HH:MM:SS)
#SBATCH --mail-type=begin        # send email when job begins
#SBATCH --mail-type=end          # send email when job ends
#SBATCH --mail-user=<YourNetID>@princeton.edu

module purge
module load intel/19.1.1.217
module load intel-mpi/intel/2019.7
export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK

srun /home/al9001/.local/bin/lmp_adroit -in in.lammps

  1. Execute the job using the command

sbatch job.slurm

You can take a look at this guide to learn more about job monitoring.

  1. Plot the energy as a function of time using gnuplot or Python. You can use log.lammps file.

Some useful commands

gnuplot
plot "log.lammps" using 1:8

f(x) = m * x + q
fit [100000:500000][0:0.01] f(x) 'log.lammps' using 1:8 via m, q
plot [100000:500000][0:0.01] "log.lammps" using 1:8, f(x)
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