# VASP#

At present, most workflows in atomate2 use the Vienna ab initio simulation package (VASP) as the density functional theory code.

By default, the input sets used in atomate2 differ from the input sets used in atomate1 and are inconsistent with calculations performed in the Materials Project. The primary differences are:

• Use of the PBEsol exchange–correlation functional instead of PBE.

• Use of up-to-date pseudopotentials (PBE_54 instead of PBE_52).

• Use of KSPACING for most calculations.

Warning

The different input sets used in atomate2 mean total energies cannot be compared against energies taken from the Materials Project unless the default settings are modified accordingly.

## Configuration#

These workflows require VASP to be installed and on the path. Furthermore, the pymatgen package is used to write VASP input files such as POTCARs. Accordingly, pymatgen must be aware of where the pseudopotentials are installed. Please see the pymatgen POTCAR setup guide for more details.

All settings for controlling VASP execution can be set using the ~/.atomate2.yaml configuration file or using environment variables. For more details on configuring atomate2, see the Installation page.

The most important settings to consider are:

• VASP_CMD: The command used to run the standard version of VASP. I.e., something like mpi_run -n 16 vasp_std > vasp.out.

• VASP_GAMMA_CMD: The command used to run the gamma-only version of VASP.

• VASP_NCL_CMD: The command used to run the non-collinear version of VASP.

• VASP_INCAR_UPDATES: Updates to apply to VASP INCAR files. This allows you to customise input sets on different machines, without having to change the submitted workflows. For example, you can set certain parallelization parameters, such as NCORE, KPAR etc.

• VASP_VDW_KERNEL_DIR: The path to the VASP Van der Waals kernel.

## List of VASP workflows#

### Static#

A static VASP calculation (i.e., no relaxation).

### Relax#

A VASP relaxation calculation. Full structural relaxation is performed.

### Tight Relax#

A VASP relaxation calculation using tight convergence parameters. Full structural relaxation is performed. This workflow is useful when small forces are required, such as before calculating phonon properties.

### Dielectric#

A VASP calculation to obtain dielectric properties. The static and high-frequency dielectric constants are obtained using density functional perturbation theory.

### Transmuter#

A generic calculation that transforms the structure (using one of the pymatgen.transformations) before writing the input sets. This can be used to perform many structure operations such as making a supercell or symmetrising the structure.

### HSE06 Static#

A static VASP calculation (i.e., no relaxation) using the HSE06 exchange correlation functional.

### HSE06 Relax#

A VASP relaxation calculation using the HSE06 functional. Full structural relaxation is performed.

### HSE06 Tight Relax#

A VASP relaxation calculation using tight convergence parameters with the HSE06 functional. Full structural relaxation is performed.

### Double Relax#

Perform two back-to-back relaxations. This can often help avoid errors arising from Pulay stress.

### Band Structure#

Calculate the electronic band structure. This flow consists of three calculations:

1. A static calculation to generate the charge density.

2. A non-self-consistent field calculation on a dense uniform mesh.

3. A non-self-consistent field calculation on the high-symmetry k-point path to generate the line mode band structure.

Note

Band structure objects are automatically stored in the data store due to limitations on mongoDB collection sizes.

### Uniform Band Structure#

Calculate a uniform electronic band structure. This flow consists of two calculations:

1. A static calculation to generate the charge density.

2. A non-self-consistent field calculation on a dense uniform mesh.

Note

Band structure objects are automatically stored in the data store due to limitations on mongoDB collection sizes.

### Line-Mode Band Structure#

Calculate a line-mode electronic band structure. This flow consists of two calculations:

1. A static calculation to generate the charge density.

2. A non-self-consistent field calculation on a high-symmetry k-point path to generate the line mode band structure.

Note

Band structure objects are automatically stored in the data store due to limitations on mongoDB collection sizes.

### HSE06 Band Structure#

Calculate the electronic band structure using HSE06. This flow consists of three calculations:

1. A HSE06 static calculation to generate the charge density.

2. A HSE06 calculation on a dense uniform mesh.

3. A HSE06 calculation on the high-symmetry k-point path using zero weighted k-points.

Note

Band structure objects are automatically stored in the data store due to limitations on mongoDB collection sizes.

### HSE06 Uniform Band Structure#

Calculate a uniform electronic band structure using HSE06. This flow consists of two calculations:

1. A HSE06 static calculation to generate the charge density.

2. A HSE06 non-self-consistent field calculation on a dense uniform mesh.

Note

Band structure objects are automatically stored in the data store due to limitations on mongoDB collection sizes.

### HSE06 Line-Mode Band Structure#

Calculate a line-mode electronic band structure using HSE06. This flow consists of two calculations:

1. A HSE06 static calculation to generate the charge density.

2. A HSE06 non-self-consistent field calculation on a high-symmetry k-point path to generate the line mode band structure.

Note

Band structure objects are automatically stored in the data store due to limitations on mongoDB collection sizes.

### Relax and Band Structure#

Perform a relaxation and then run the Band Structure workflow. By default, a Double Relax relaxation is performed.

### Elastic Constant#

Calculate the elastic constant of a material. Initially, a tight structural relaxation is performed to obtain the structure in a state of approximately zero stress. Subsequently, perturbations are applied to the lattice vectors and the resulting stress tensor is calculated from DFT, while allowing for relaxation of the ionic degrees of freedom. Finally, constitutive relations from linear elasticity, relating stress and strain, are employed to fit the full 6x6 elastic tensor. From this, aggregate properties such as Voigt and Reuss bounds on the bulk and shear moduli are derived.

See the Materials Project documentation on elastic constants for more details.

Note

It is strongly recommended to symmetrize the structure before running this workflow. Otherwise, the symmetry reduction routines will not be as effective at reducing the number of deformations needed.

### Optics#

Calculate the frequency dependent dielectric response of a material.

This workflow contains an initial static calculation, and then a non-self-consistent field calculation with LOPTICS set. The purpose of the static calculation is to determine i) if the material needs magnetism set, and ii) the total number of bands (the non-scf calculation contains 1.3 * number of bands in the static calculation) as often the highest bands are not properly converged in VASP.

### HSE06 Optics#

Calculate the frequency dependent dielectric response of a material using HSE06.

This workflow contains an initial static calculation, and then a uniform band structure calculation with LOPTICS set. The purpose of the static calculation is to determine i) if the material needs magnetism set, and ii) the total number of bands (the uniform contains 1.3 * number of bands in the static calculation) as often the highest bands are not properly converged in VASP.

## Modifying input sets#

The inputs for a calculation can be modified in several ways. Every VASP job takes a VaspInputGenerator as an argument (input_set_generator). One option is to specify an alternative input set generator:

from atomate2.vasp.sets.core import StaticSetGenerator
from atomate2.vasp.jobs.core import StaticMaker

# create a custom input generator set with a larger ENCUT
my_custom_set = StaticSetGenerator(user_incar_settings={"ENCUT": 800})

# initialise the static maker to use the custom input set generator
static_maker = StaticMaker(input_set_generator=my_custom_set)

# create a job using the customised maker
static_job = static_maker.make(structure)


The second approach is to edit the job after it has been made. All VASP jobs have a maker attribute containing a copy of the Maker that made them. Updating the input_set_generator attribute maker will update the input set that gets written:

static_job.maker.input_set_generator.user_incar_settings["LOPTICS"] = True


Finally, sometimes you have a workflow containing many VASP jobs. In this case it can be tedious to update the input sets for each job individually. Atomate2 provides helper functions called “powerups” that can apply settings updates to all VASP jobs in a flow. These powerups also contain filters for the name of the job and the maker used to generate them.

from atomate2.vasp.powerups import update_user_incar_settings
from atomate2.vasp.flows.elastic import ElasticMaker
from atomate2.vasp.flows.core import DoubleRelaxMaker
from atomate2.vasp.jobs.elastic import ElasticRelaxMaker

# make a flow to calculate the elastic constants
elastic_flow = ElasticMaker().make(structure)

# update the ENCUT of all VASP jobs in the flow
new_flow = update_user_incar_settings(elastic_flow, {"ENCUT": 200})

# only update VASP jobs which have "deformation" in the job name.
new_flow = update_user_incar_settings(
elastic_flow, {"ENCUT": 200}, name_filter="deformation"
)

# only update VASP jobs which were generated by an ElasticRelaxMaker
new_flow = update_user_incar_settings(
elastic_flow, {"ENCUT": 200}, class_filter=ElasticRelaxMaker
)

# powerups can also be applied directly to a Maker. This can be useful for makers
# that produce flows, as it allows you to update all nested makers. E.g.
relax_maker = DoubleRelaxMaker()
new_maker = update_user_incar_settings(relax_maker, {"ENCUT": 200})
flow = new_maker.make(structure)  # this flow will reflect the updated ENCUT value


Note

Powerups return a copy of the original flow or Maker and do not modify it in place.

In addition to the ability to change INCAR parameters on-the-fly, the VaspInputGenerator, Maker object, and “powerups” allow for the manual modification of several additional VASP settings, such as the k-points (user_kpoints_settings) and choice of pseudopotentials (user_potcar_settings).

If a greater degree of flexibility is needed, the user can define a default set of input arguments (config_dict) that can be provided to the VaspInputGenerator. By default, the VaspInputGenerator uses a base set of VASP input parameters from BaseVaspSet.yaml, which each Maker is built upon. If desired, the user can define a custom .yaml file that contains a different base set of VASP settings to use. An example of how this can be done is shown below for a representative static calculation.

from atomate2.vasp.sets.core import StaticSetGenerator
from atomate2.vasp.jobs.core import StaticMaker
from atomate2.vasp.jobs.base import VaspInputGenerator
from monty.serialization import loadfn

# read in a custom config file

# create a custom static set generator with user-defined defaults. Also change the
# NELMIN parameter to 6 (for demonstration purposes)
my_custom_set = StaticSetGenerator(
user_incar_settings={"NELMIN": 6},
config_dict=user_config_dict,
)

# initialise the static maker to use the custom input set generator
static_maker = StaticMaker(input_set_generator=my_custom_set)

# create a job using the customised maker
static_job = static_maker.make(structure)


## Chaining workflows#

All VASP workflows are constructed using the Maker.make() function. The arguments for this function always include:

• structure: A pymatgen structure.

• prev_vasp_dir: A previous VASP directory to copy output files from.

There are two options when chaining workflows:

1. Use only the structure from the previous calculation. This can be achieved by only setting the structure argument.

2. Use the structure and additional outputs from a previous calculation. By default, these outputs include INCAR settings, the band gap (used to automatically set KSPACING), and the magnetic moments. Some workflows will also use other outputs. For example, the Band Structure workflow will copy the CHGCAR file (charge density) from the previous calculation. This can be achieved by setting both the structure and prev_vasp_dir arguments.

These two examples are illustrated in the code below, where we chain a relaxation calculation and a static calculation.

from jobflow import Flow
from atomate2.vasp.jobs.core import RelaxMaker, StaticMaker
from pymatgen.core.structure import Structure

si_structure = Structure.from_file("Si.cif")

# create a relax job
relax_job = RelaxMaker().make(structure=si_structure)

# create a static job that will use only the structure from the relaxation
static_job = StaticMaker().make(structure=relax_job.output.structure)

# create a static job that will use additional outputs from the relaxation
static_job = StaticMaker().make(
structure=relax_job.output.structure, prev_vasp_dir=relax_job.output.dir_name
)

# create a flow including the two jobs and set the output to be that of the static
my_flow = Flow([relax_job, static_job], output=static_job.output)