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Assessment of Empirical and Semi-Empirical van der Waals Methods for Halide Perovskites into Density Functional Theory Approach

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Halide-Perovskites Workflow

Assessment of Empirical and Semi-Empirical van der Waals Methods for Halide Perovskites into Density Functional Theory Approach.

In this workflow, the SimStack framework is used to analyze the electronic and structural properties of metal halide perovskites (MHPs) with chemical formula CH3XH3PbI3 (X = N, P, As, and Sb) For this, five different WaNos were combined: Mult-It, UnpackMol, DFT-VASP, DFT-half and DB-Generator. A table containing the total energies and structural parameters is the expected output of this protocol.

To create the workflow depicted in Figure 1, you must use the drag-and-drop standard procedure of Simstack in four steps. In the first, Mult-It Wano was used to create a tar file of all structures investigated. In the second step, we add the Unpackmol Wano inside AdvancedFor loop control to generate the POSCAR files corresponding to the unit cells. In the third step, we insert the DFT-VASP Wano to receive the POSCAR files from the preceding step and execute the DFT calculations. In this step, we need to choose the corresponding van der Waals method to be used, such as D2, D3, D3BJ, TS, TSSCS, MBD, and dDsC. At the end of the protocol, DB-Generator WaNo extracts in a yml file the respective total energy from the OUTCAR file associated with each composition investigated.

This workflow allows us to:

1. From several initial structures, calculate in an automated way several of their properties, such
as stability, gap energy, among others.
2. Compress all structures in the tar file above with Mult-It and uncompress them with UnpackMol.
2. Run the DFT calculations using VASP code (DFT-VASP).
4. Arrange all the total energy values gap energies for a given number of atomic substitutions in a yml file at the end of the protocol (DB-Generator). 

Halide perovskites workflow with AdvancedFor loop control

Figure 1 This workflow aims to perform several DFT calculations of metal halide perovskites with vdW corrections. It is made from Mult-It, UnpackMol, DFT-VASP, and DB-Generator WaNos connected by the AdvancedFor loop control. In step 1, we generate the configurations containing different cations within the cboctahedral voids of MHP structure, represented in red. These were ; Steps 2, and 3 define the group of configurations and set the DFT calculation methods employed in the simulation. In the last step, DB-Generator Wano extracts the required variables of the output files from the previous steps. After this, the DFT-half is used to

1. Python Setup

To get this workflow up and running on your available computational resources, install the below libraries on Python 3.6 or newer.

1. Atomic Simulation Environment (ASE).
2. Python Materials Genomics (Pymatgen).
3. Numpy, os, sys, re, yaml, subprocess.
4. json, csv, shutil, tarfile. 

2. Mult-It Inputs

  • You need to check the box Structures.
  • In the tarfile field, configure the path containing the tarfile with input structures, if it is not properly configured.

3. Mult-It Outputs

  • Configure the' file' name from the file command on the top of the AdvancedFor loop, as indicated in Figure 1.
  • From the in command on the top of the loop, configure list(range(Mult-It.struct_len)).

4. UnpackMol Inputs

  • Check the box Multivariable-mode.
  • The input-file variable should be set as Mult-It/outputs/structure_output_dict.yml.
  • Structures-int variable should be set as ${file}.
  • Structures variable should be set as Mult-It/outputs/Structures.tar.

5. UnpackMol Outputs

  • POSCAR files (named as Mol_geom.xyz) should be passed to DFT-VASP WaNo.

6. DFT-VASP Inputs

  • INCAR tab: as an option, we can set all INCAR flags available within VASP. However, we expose only a few of them, which is essential for the problem. See the GUI of this WaNo. A brief description of each flag pops up when we hover the mouse over the inputs.
  • KPOINTS tab: Here, the user can define two types of KPOINTS, Kpoints_length and Kpoints_Monkhorst.
  • Analysis tab: Aimed to compute Bader charge analysis and DOS.
  • Files_Run tab: Mandatory loads the POSCAR file, and as an option, can load INCAR, POTCAR, KPOINTS, and KORINGA files. The KORINGA file can be any file. In the case of this problem, it loads the Input_data.yml file. Poscar_file variable should be set as AdvancedForEach/${file_ITER}/UnpackMol/outputs/Mol_geom.xyz.

7. DFT-VASP Outputs

  • OUTCAR file.

8. DB-Generator Inputs

  • Imports tab: Search_in_File variable should be set as vasp_results.yml and import this file using AdvancedForEach/*/DFT-VASP/outputs/vasp_results.yml command.
  • Search_Parameters: Set the variables total_energy and title.

9. DB-Generator Outputs

  • Table-dict.yml containing the variables defined in the Search_Parameters field above, as shown in Figure 1.

Acknowledgements

License & Copyright

Developer: Celso Ricardo C. Rêgo, Multiscale Materials Modelling and Virtual Design, Institute of Nanotechnology, Karlsruhe Institute of Technology https://www.int.kit.edu/wenzel.php

Licensed under the KIT License.

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