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=Software and resources=
 
=Software and resources=
 +
 +
Overview of codes from the Materials Design Group at Imperial College London
 +
 +
[https://wmd-group.github.io/codes/ wmd-group.github.io/codes/]
 +
 +
==Installation on Saga==
 +
 +
module load Python/3.9.6-GCCcore-11.2.0
 +
pip install sumo
 +
pip install --upgrade <nowiki>https://github.com/SUNCAT-Center/catmap/zipball/master</nowiki>
 +
 +
This will install the python packages under .local/lib/python3.9/site-packages/
 +
 
==Structure and crystallography==
 
==Structure and crystallography==
 
===ICSD database===
 
===ICSD database===
Line 71: Line 84:
  
 
===OVITO===
 
===OVITO===
[https://www.ovito.org/about/]
+
[https://www.ovito.org/about/| https://www.ovito.org/about/]
  
 
OVITO is a visualization and analysis software for output data generated in molecular dynamics, atomistic Monte-Carlo and other particle-based simulations.
 
OVITO is a visualization and analysis software for output data generated in molecular dynamics, atomistic Monte-Carlo and other particle-based simulations.
 +
 +
===Escher===
 +
http://schooner.chem.dal.ca/wiki/Escher
 +
 +
Escher is a collection of octave and python routines for the visualization and plotting of molecules and crystals. The original idea in escher was to modernize tessel, a program for the representation of crystal structures (and more). Via an interface to POV-Ray, tessel is able to generate very high quality representations of periodic and finite molecular structures.
 +
 +
Code link of a [https://onlinelibrary.wiley.com/doi/abs/10.1002/ente.202070041 cover art example]: https://github.com/heesoopark/Escher-PovRay
  
 
==Packages==
 
==Packages==
Line 82: Line 102:
  
 
===Atomic Simulation Environment (ASE)===
 
===Atomic Simulation Environment (ASE)===
[https://wiki.fysik.dtu.dk/ase/ wiki.fysik.dtu.dk/ase/] (Module available on Saga)
+
[https://wiki.fysik.dtu.dk/ase/ wiki.fysik.dtu.dk/ase/]
  
 
Set of tools and Python modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations.
 
Set of tools and Python modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations.
 +
 +
ASE modules are available on Saga
 +
 +
<code>module avail ase </code>
  
 
Example of a script for generating an (1 1 1) surface slab of palladium
 
Example of a script for generating an (1 1 1) surface slab of palladium
Line 97: Line 121:
 
  slab = fcc111_root('Pd', 3, size=(1,2,7), a=3.9438731474981594, vacuum=5.0)
 
  slab = fcc111_root('Pd', 3, size=(1,2,7), a=3.9438731474981594, vacuum=5.0)
  
  write('Pd-111-gb.cif', slab, 'cif')
+
  write('Pd-111.cif', slab, 'cif')
  
 
===VASPKIT===
 
===VASPKIT===
 +
[https://vaspkit.com/ vaspkit.com/]
 +
 
VASPKIT provides a powerful and user-friendly interface to perform high throughput analysis of various material properties from the raw calculated data using the widely-used VASP code.
 
VASPKIT provides a powerful and user-friendly interface to perform high throughput analysis of various material properties from the raw calculated data using the widely-used VASP code.
 
* Generate KPOINTS, POTCAR and INCAR for a given POSCAR file;
 
* Generate KPOINTS, POTCAR and INCAR for a given POSCAR file;
Line 118: Line 144:
 
* Magnetocrystalline anisotropy energy;
 
* Magnetocrystalline anisotropy energy;
 
* Currently, only VASP raw data are fully supported.
 
* Currently, only VASP raw data are fully supported.
More detail: https://vaspkit.com/index.html
 
  
 
===CatMAP===
 
===CatMAP===
Line 128: Line 153:
 
  <code>pip install --upgrade <nowiki>https://github.com/SUNCAT-Center/catmap/zipball/master</nowiki></code>
 
  <code>pip install --upgrade <nowiki>https://github.com/SUNCAT-Center/catmap/zipball/master</nowiki></code>
  
To use the package add this directory to the PYTHONPATH, e.g. in bash shell:
+
You may need to add the install directory to the PYTHONPATH, e.g. in bash shell or .bash_profile
 
  <code>export PYTHONPATH=$HOME/THIS_FOLDER_PATH:$PYTHONPATH</code>
 
  <code>export PYTHONPATH=$HOME/THIS_FOLDER_PATH:$PYTHONPATH</code>
  
Line 155: Line 180:
  
 
===Phonopy and Phono3py===
 
===Phonopy and Phono3py===
 +
[https://phonopy.github.io/phonopy/ phonopy.github.io/phonopy/]
 +
 
Phonopy is an open source package for phonon calculations at harmonic and quasi-harmonic levels. Phono3py is another open source package for phonon-phonon interaction and lattice thermal conductivity calculations.  
 
Phonopy is an open source package for phonon calculations at harmonic and quasi-harmonic levels. Phono3py is another open source package for phonon-phonon interaction and lattice thermal conductivity calculations.  
  
Line 169: Line 196:
 
* Interfaces to calculators: VASP, VASP DFPT, ABINIT, Quantu ESPRESSO, SIESTA, Elk, WIEN2k, CRYSTAL, DFTB+, TURBOMOLE, CP2K, FHI-aims, CASTEP, Fleur, LAMMPS (external)
 
* Interfaces to calculators: VASP, VASP DFPT, ABINIT, Quantu ESPRESSO, SIESTA, Elk, WIEN2k, CRYSTAL, DFTB+, TURBOMOLE, CP2K, FHI-aims, CASTEP, Fleur, LAMMPS (external)
 
* Phonopy API for Python
 
* Phonopy API for Python
https://phonopy.github.io/phonopy/
 
  
 
===TDEP===
 
===TDEP===
Line 204: Line 230:
  
 
<code> generate_structure -d 2 2 2 </code>
 
<code> generate_structure -d 2 2 2 </code>
 +
 +
===Supercell===
 +
[https://orex.github.io/supercell/ https://orex.github.io/supercell/]
 +
 +
Supercell is a combinatorial structure-generation approach for the local-level modeling of atomic substitutions and partial occupancies in crystals.
 +
 +
Supercell can generate special quasirandom structures (SQS).
 +
 +
===Icet===
 +
Icet is a module in Python that can generate special quasirandom structures. [https://icet.materialsmodeling.org/]
 +
 +
Here is an example of a script to generate an SQS structure of a 3x3x3 supercell of a rocksalt structure ( TiN ) with several H atoms on the N sites (TiN0.75H0.25)
 +
 +
  from ase import Atom
 +
  from ase.build import bulk
 +
  from icet import ClusterSpace
 +
  from icet.tools.structure_generation import (generate_sqs,
 +
                                            generate_sqs_from_supercells,
 +
                                            generate_sqs_by_enumeration,
 +
                                            generate_target_structure)
 +
  from ase.io import write
 +
  #makes a TiN cell
 +
  primitive_structure = bulk('TiN', cubic=True, crystalstructure='rocksalt', a=4.2570)
 +
  #makes a 3x3x3 supercell
 +
  supercells = [primitive_structure.repeat(3)]
 +
  # defines a cluster space. There are 8 brackets because we have 8 atoms in the cell defined earlier (Ti_4N_4). Several aloms in the same bracket mean that they are allowed on the same site
 +
  cs = ClusterSpace(primitive_structure, [7.0,4.5],chemical_symbols=[['Ti'], ['N','H'],['Ti'], ['N','H'],['Ti'], ['N','H'],['Ti'], ['N','H']])
 +
  # x in TiNx
 +
  x = 0.75
 +
  # In this case we want TiN_{0.75}H_{0.25}. We only act on sublattice A because we do not want to change the concentration of Ti. The target concentration has to be compatible with the supercell (i.e. it should correspond to an integer number of atoms in the cell)
 +
  target_concentrations = {'A': {'N': x, 'H': 1-x}}
 +
  #here we use “generate_sqs_from_supercells” because it allows us to make a supercell that has the same geometry as the one in the input
 +
  # With more steps, we generate better structures, it also takes longer
 +
  sqs=generate_sqs_from_supercells(cluster_space=cs,
 +
  supercells=supercells,
 +
  target_concentrations=target_concentrations,
 +
  n_steps=50000 )
 +
  write('TiNH.cif', sqs)
 +
  
 
===Spinney===
 
===Spinney===
Line 209: Line 274:
  
 
Python package dedicated to the study of point defects in solids. Can be used to calculate the correction energy due to electrostatic finite-size-effects in charged supercells, defect formation energies and transition levels, and defects concentrations.
 
Python package dedicated to the study of point defects in solids. Can be used to calculate the correction energy due to electrostatic finite-size-effects in charged supercells, defect formation energies and transition levels, and defects concentrations.
 +
 +
===SUMO===
 +
[https://smtg-ucl.github.io/sumo/ smtg-ucl.github.io/sumo/]
 +
 +
Sumo is a Python toolkit for plotting and analysis of ab initio solid-state calculation data, built on existing Python packages from the solid-state chemistry/physics community. SUMO can plot projected DOS directly from DOSCAR and vasprun.xml
 +
 +
Installation on Saga works with the following python module (consider loading it in ~/.bash_profile)
 +
 +
<code> module load Python/3.9.6-GCCcore-11.2.0 </code>
 +
 +
<code> pip install sumo </code>
 +
 +
The installation folder will be ~/.local/lib/python3.9/site-packages/
  
 
===Pymatgen===
 
===Pymatgen===
https://pymatgen.org/
+
[https://pymatgen.org/ pymatgen.org/]
  
 
Pymatgen (Python Materials Genomics) is a robust, open-source Python library for materials analysis.
 
Pymatgen (Python Materials Genomics) is a robust, open-source Python library for materials analysis.
  
Generate a POTCAR with symbols Li_sv O and the PBE functional
+
Generate a POTCAR with symbols Li_sv O and the PBE functional in a termial
  
 
<code> pmg potcar --symbols Li_sv O --functional PBE </code>
 
<code> pmg potcar --symbols Li_sv O --functional PBE </code>
 +
 +
Python code quick examples:
 +
 +
1) to generate [https://wiki.uio.no/mn/kjemi/vaspwiki/index.php/Main_Page#Nudged_Elastic_Band_.28NEB.29 NEB] images by using IDPP method (image dependent pair potential: J. Chem. Phys. 140, 214106 (2014))
 +
from pymatgen.core import Structure
 +
from pymatgen.analysis.diffusion.neb.pathfinder import IDPPSolver
 +
init_struct = Structure.from_file("POSCAR_start.vasp")
 +
final_struct =Structure.from_file("POSCAR_end.vasp")
 +
obj = IDPPSolver.from_endpoints(endpoints=[init_struct, final_struct], nimages=5,
 +
                                sort_tol=1.0)new_path = obj.run(maxiter=5000,
 +
                                tol=1e-5, gtol=1e-3, species=["Na"])
 +
for i in range(len(new_path)):
 +
    print(new_path[i])
 +
    new_path[i].to(fmt="poscar",filename="POSCAR-"+str(i)+".vasp")
 +
 +
2) to analyze NEB results
 +
from pymatgen.analysis.transition_state import NEBAnalysis
 +
neb = NEBAnalysis.from_dir("./")
 +
nebplot = neb.get_plot()
 +
nebplot.savefig("NEB.png")
 +
 +
===Atomsk===
 +
[https://atomsk.univ-lille.fr/ atomsk.univ-lille.fr]
 +
 +
Atomsk creates, manipulates, and converts data files for atomic-scale simulations in the field of computational materials sciences in CLI. Atomsk can generate common lattice types such as fcc, bcc, hcp, and perform elementary transformations: duplicate, rotate, deform, insert dislocations, merge several systems, create twins, bicrystals and polycrystals, and so on. These elementary tools can be combined to construct and shape a wide variety of atomic systems.
 +
 +
To compile on Saga by using Intel fort/MLK,
 +
 +
<code> git clone https://github.com/pierrehirel/atomsk.git </code>
 +
 +
<code> cd atomsk/src </code>
 +
 +
<code> module load intel-compilers/2022.1.0 </code>
 +
 +
<code> module load imkl/2022.1.0 </code>
 +
 +
<code> make -f Makefile.ifort atomsk </code>
  
 
==References==
 
==References==
 
<references />
 
<references />

Latest revision as of 10:37, 25 August 2023

Software and resources

Overview of codes from the Materials Design Group at Imperial College London

wmd-group.github.io/codes/

Installation on Saga

module load Python/3.9.6-GCCcore-11.2.0
pip install sumo
pip install --upgrade https://github.com/SUNCAT-Center/catmap/zipball/master

This will install the python packages under .local/lib/python3.9/site-packages/

Structure and crystallography

ICSD database

icsd.fiz-karlsruhe.de/

Automatic login through EZproxy (www.ub.uio.no/english/using/remote-access.html).

Materials project

www.materialsproject.org

Contains structures optimized by DFT that can be downloaded in several formats including .cif or POSCAR. Choose 'Conventional Standard' CIF.

Login with a Google account (available with UiO username www.uio.no/english/services/it/store-collaborate/gsuite/).

International Tables for Crystallography

it.iucr.org

Complete overview of space-group symmetry and more.

Shannon Ionic Radii

abulafia.mt.ic.ac.uk/shannon/

Reference [1]

Binding energies of molecules

Todo: Table of binding energies with reference (e.g., NIST)

Catalysis

Catalysis Hub

www.catalysis-hub.org

Database of reaction energies and barriers from DFT calculations.

No entropy found

Visualization

VESTA

jp-minerals.org/vesta/en/ (Windows, macOS, Linux)

View periodic structures, charge densities and more.

Recommended settings for improved figures

Objects > Properties > Atoms/Bonds/Polyhedra
Specular: 40 40 40
Shininess (%): 1 

View > Overall Appearance...
Ambient: 10
Diffuse: 70

Avogadro

avogadro.cc (Windows, macOS, Linux)

View and edit molecular structures and optimize molecular geometry through molecular mechanics.

Diamond

www.crystalimpact.com/diamond/ (Windows: Licence)

View and edit periodic and molecular structures.

VMD

www.ks.uiuc.edu/Research/vmd/ (Windows, macOS, Linux)

View and animate structures from molecular dynamics simulations.

P4vasp

github.com/orest-d/p4vasp (macOS, Linux)

Visualizing periodic structures, density of states and band structures.

OVITO

https://www.ovito.org/about/

OVITO is a visualization and analysis software for output data generated in molecular dynamics, atomistic Monte-Carlo and other particle-based simulations.

Escher

http://schooner.chem.dal.ca/wiki/Escher

Escher is a collection of octave and python routines for the visualization and plotting of molecules and crystals. The original idea in escher was to modernize tessel, a program for the representation of crystal structures (and more). Via an interface to POV-Ray, tessel is able to generate very high quality representations of periodic and finite molecular structures.

Code link of a cover art example: https://github.com/heesoopark/Escher-PovRay

Packages

Spyder

www.spyder-ide.org (Windows, macOS, Linux)

Scientific python developer environment.

Atomic Simulation Environment (ASE)

wiki.fysik.dtu.dk/ase/

Set of tools and Python modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations.

ASE modules are available on Saga

module avail ase

Example of a script for generating an (1 1 1) surface slab of palladium

#!/opt/local/bin/python
from ase.io import read
from ase.io import write
from ase.build import fcc111
from ase.build import fcc100
from ase.build import fcc111_root
slab = fcc111_root('Pd', 3, size=(1,2,7), a=3.9438731474981594, vacuum=5.0)
write('Pd-111.cif', slab, 'cif')

VASPKIT

vaspkit.com/

VASPKIT provides a powerful and user-friendly interface to perform high throughput analysis of various material properties from the raw calculated data using the widely-used VASP code.

  • Generate KPOINTS, POTCAR and INCAR for a given POSCAR file;
  • Elastic-constants of 2D and bulk materials using stress-strain or energy-strain methods;
  • Equation-of-state fitting;
  • Suggested k-paths for a given crystal structure;
  • Optical adsorption coefficient of 2D and bulk materials;
  • Band structure unfolding;
  • Fermi surface;
  • Density-of-states and band-structure;
  • Charge/spin density, Charge density difference;
  • Vacuum level and work function;
  • Wave-function analysis;
  • Molecular-dynamics analysis;
  • Effective mass of carrier;
  • Symmetry finding and operations;
  • 3D band structures;
  • Magnetocrystalline anisotropy energy;
  • Currently, only VASP raw data are fully supported.

CatMAP

CatMap is a catalyst Micro-kinetic Analysis Package for automated creation of micro-kinetic models used for studying kinetics and screening new catalysts.

https://catmap.readthedocs.io/en/latest/index.html

CatMap can be installed directly via pip:

pip install --upgrade https://github.com/SUNCAT-Center/catmap/zipball/master

You may need to add the install directory to the PYTHONPATH, e.g. in bash shell or .bash_profile

export PYTHONPATH=$HOME/THIS_FOLDER_PATH:$PYTHONPATH

Input File Structure

The TableParser accepts inputs in a tab-separated text file. An example of the header and first few lines are provided below:

Image.png

The following column titles are required for a functional input file:

  • surface_name
  • site_name
  • species_name
  • formation_energy
  • frequencies
  • reference

Generating input file for formation energy

You can use the python script under /CATMAP/catmap/tutorials/1-generating_input_file/generate_input.py

Creating a Microkinetic Model

Check the example of CO oxidation in the path of /CATMAP/catmap/tutorials/2-creating_microkinetic_model

One of the most important aspects of the “setup file” is the “rxn_expressions” variable which defines the elementary steps in the model. For this simplified CO oxidation model we will specify these as:

rxn_expressions = [               '*_s + CO_g -> CO*',               '2*_s + O2_g <-> O-O* + *_s -> 2O*',               'CO* +  O* <-> O-CO* + * -> CO2_g + 2*',                   ] 

The first expression includes CO adsorption without any activation barrier. The second includes an activated dissociative chemisorption of the oxygen molecule, and the final is an activated associative desorption of CO2. More complex models for CO oxidation could be imagined, but these elementary steps capture the key features. Note that we have only included “*” and “*_s” sites since this is a single-site model for CO oxidation. This means that all intermediates will be adsorbed at a site designated as “s”. These reaction expressions will be parsed automatically in order to define the adsorbates, transition-states, gasses, and surface sites in the model.

Phonopy and Phono3py

phonopy.github.io/phonopy/

Phonopy is an open source package for phonon calculations at harmonic and quasi-harmonic levels. Phono3py is another open source package for phonon-phonon interaction and lattice thermal conductivity calculations.

Features

  • Phonon band structure, phonon DOS and partial-DOS
  • Phonon thermal properties: Free energy, heat capacity (Cv), and entropy
  • Phonon group velocity
  • Thermal ellipsoids / Mean square displacements
  • Irreducible representations of normal modes
  • Dynamic structure factor for INS and IXS
  • Non-analytical-term correction: LO-TO splitting (Born effective charges and dielectric constant are required.)
  • Mode Grüneisen parameters
  • Quasi-harmonic approximation: Thermal expansion, heat capacity at constant pressure (Cp)
  • Interfaces to calculators: VASP, VASP DFPT, ABINIT, Quantu ESPRESSO, SIESTA, Elk, WIEN2k, CRYSTAL, DFTB+, TURBOMOLE, CP2K, FHI-aims, CASTEP, Fleur, LAMMPS (external)
  • Phonopy API for Python

TDEP

ollehellman.github.io

Extract force constants, phonon dispersion relations, thermal conductivity, and generate special quasirandom structures (SQS)

Available on Saga (/cluster/shared/tdep/bin). Use the following modules

module purge
module load Anaconda3/2019.03
module load intel/2018b
module load imkl/2018.3.222-iimpi-2018b
module load HDF5/1.10.2-intel-2018b

Generate SQS supercell from from a unit cell POSCAR file named 'infile.ucposcar'

Example of 'infile.ucposcar' for a A-site doped SrTiO3 unit cell where the disordered site is designated 'ALLOY' (2 elements: 52% Sr and 48% Ca)

 Sr1 Ti1 O3
 1.0
 3.945130 0.000000 0.000000
 0.000000 3.945130 0.000000
 0.000000 0.000000 3.945130
 ALLOY Ti O
 1 1 3
 direct
 0.000000 0.000000 0.000000 2 Sr 0.52 Ca 0.48
 0.500000 0.500000 0.500000
 0.500000 0.000000 0.500000
 0.500000 0.500000 0.000000
 0.000000 0.500000 0.500000

Generate 2x2x2 SQS supercells (five supercells will be generated outfile.sqs_001-005)

generate_structure -d 2 2 2

Supercell

https://orex.github.io/supercell/

Supercell is a combinatorial structure-generation approach for the local-level modeling of atomic substitutions and partial occupancies in crystals.

Supercell can generate special quasirandom structures (SQS).

Icet

Icet is a module in Python that can generate special quasirandom structures. [1]

Here is an example of a script to generate an SQS structure of a 3x3x3 supercell of a rocksalt structure ( TiN ) with several H atoms on the N sites (TiN0.75H0.25)

 from ase import Atom
 from ase.build import bulk
 from icet import ClusterSpace
 from icet.tools.structure_generation import (generate_sqs,
                                            generate_sqs_from_supercells,
                                            generate_sqs_by_enumeration,
                                            generate_target_structure)
 from ase.io import write
 #makes a TiN cell
 primitive_structure = bulk('TiN', cubic=True, crystalstructure='rocksalt', a=4.2570)
 #makes a 3x3x3 supercell 
 supercells = [primitive_structure.repeat(3)]
 # defines a cluster space. There are 8 brackets because we have 8 atoms in the cell defined earlier (Ti_4N_4). Several aloms in the same bracket mean that they are allowed on the same site
 cs = ClusterSpace(primitive_structure, [7.0,4.5],chemical_symbols=[['Ti'], ['N','H'],['Ti'], ['N','H'],['Ti'], ['N','H'],['Ti'], ['N','H']])
 # x in TiNx
 x = 0.75
 # In this case we want TiN_{0.75}H_{0.25}. We only act on sublattice A because we do not want to change the concentration of Ti. The target concentration has to be compatible with the supercell (i.e. it should correspond to an integer number of atoms in the cell)
 target_concentrations = {'A': {'N': x, 'H': 1-x}} 
 #here we use “generate_sqs_from_supercells” because it allows us to make a supercell that has the same geometry as the one in the input
 # With more steps, we generate better structures, it also takes longer
 sqs=generate_sqs_from_supercells(cluster_space=cs,
 supercells=supercells,
 target_concentrations=target_concentrations,
 n_steps=50000 )
 write('TiNH.cif', sqs)


Spinney

spinney.readthedocs.io/

Python package dedicated to the study of point defects in solids. Can be used to calculate the correction energy due to electrostatic finite-size-effects in charged supercells, defect formation energies and transition levels, and defects concentrations.

SUMO

smtg-ucl.github.io/sumo/

Sumo is a Python toolkit for plotting and analysis of ab initio solid-state calculation data, built on existing Python packages from the solid-state chemistry/physics community. SUMO can plot projected DOS directly from DOSCAR and vasprun.xml

Installation on Saga works with the following python module (consider loading it in ~/.bash_profile)

module load Python/3.9.6-GCCcore-11.2.0

pip install sumo

The installation folder will be ~/.local/lib/python3.9/site-packages/

Pymatgen

pymatgen.org/

Pymatgen (Python Materials Genomics) is a robust, open-source Python library for materials analysis.

Generate a POTCAR with symbols Li_sv O and the PBE functional in a termial

pmg potcar --symbols Li_sv O --functional PBE

Python code quick examples:

1) to generate NEB images by using IDPP method (image dependent pair potential: J. Chem. Phys. 140, 214106 (2014))

from pymatgen.core import Structure
from pymatgen.analysis.diffusion.neb.pathfinder import IDPPSolver
init_struct = Structure.from_file("POSCAR_start.vasp")
final_struct =Structure.from_file("POSCAR_end.vasp")
obj = IDPPSolver.from_endpoints(endpoints=[init_struct, final_struct], nimages=5,
                               sort_tol=1.0)new_path = obj.run(maxiter=5000, 
                               tol=1e-5, gtol=1e-3, species=["Na"])
for i in range(len(new_path)):
   print(new_path[i])
   new_path[i].to(fmt="poscar",filename="POSCAR-"+str(i)+".vasp")

2) to analyze NEB results

from pymatgen.analysis.transition_state import NEBAnalysis
neb = NEBAnalysis.from_dir("./")
nebplot = neb.get_plot()
nebplot.savefig("NEB.png")

Atomsk

atomsk.univ-lille.fr

Atomsk creates, manipulates, and converts data files for atomic-scale simulations in the field of computational materials sciences in CLI. Atomsk can generate common lattice types such as fcc, bcc, hcp, and perform elementary transformations: duplicate, rotate, deform, insert dislocations, merge several systems, create twins, bicrystals and polycrystals, and so on. These elementary tools can be combined to construct and shape a wide variety of atomic systems.

To compile on Saga by using Intel fort/MLK,

git clone https://github.com/pierrehirel/atomsk.git

cd atomsk/src

module load intel-compilers/2022.1.0

module load imkl/2022.1.0

make -f Makefile.ifort atomsk

References

  1. R.D. Shannon, Revised Effective Ionic Radii and Systematic Studies of Interatomic Distances in Halides and Chalcogenides, Acta Cryst. 1976 (A32) 751-767