SIESTA Single-Element Density Dataset
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下载链接：
https://zenodo.org/doi/10.5281/zenodo.18925342
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资源简介：
SIESTA Single-Element Density Dataset (30k configurations)
This dataset contains 30,000 fully converged density-functional theory (DFT) calculations for elemental Al, Fe, and Ni (10,000 configurations per element), generated using the SIESTA electronic structure code.
Each configuration consists of:
- Atomic structure (`.fdf`, `.XV`, `.STRUCT_OUT`, `.ion`)
- SCF output (`.out`)
- Electron density grid (`Rho.grid.nc`)
- Electrostatic potential grid (`ElectrostaticPotential.grid.nc`)
All calculations are converged and validated.
Dataset Scope
Element Configurations
Al
10,000
Fe
10,000
Ni
10,000
Total
30,000
Each configuration corresponds to a two-atom FCC-derived primitive cell
subjected to controlled perturbations (see below).
Structure of the Archive
public_core/
├── data/
│ ├── Al/
│ │ ├── cfg_0000/
│ │ │ ├── Al.fdf
│ │ │ ├── Al.ion
│ │ │ ├── Al.ion.xml
│ │ │ ├── Al.out
│ │ │ ├── Rho.grid.nc
│ │ │ ├── ElectrostaticPotential.grid.nc
│ │ │ ├── Al.XV
│ │ │ └── Al.STRUCT_OUT
│ ├── Fe/
│ └── Ni/
│
├── index_core.jsonl
├── index_core.parquet
└── README.md
Configuration Generation
DFT Calculations
Calculations were executed using:
- Code: SIESTA
- Fully self-consistent single-point calculations
- All SCF cycles converged
- Automatic pseudo-copying and convergence validation
The execution pipeline:
- Skips already converged runs
- Validates convergence via parser (`parse_out`)
- Ensures `.RHO` was produced (internal check)
- Uses controlled threading for reproducibility
Grid Data Format
Electron density and electrostatic potential are stored in:
Rho.grid.nc
ElectrostaticPotential.grid.nc
NetCDF variables include:
- `gridfunc` → 3D scalar field
- `cell` → lattice vectors
Example loading (Python)
``` python
from netCDF4 import Dataset
import numpy as np
ds = Dataset("Rho.grid.nc")
rho = np.array(ds.variables["gridfunc"][:])
cell = np.array(ds.variables["cell"][:])
ds.close()
```
Index Files
`index_core.jsonl`
One JSON object per configuration.
Contains:
- `calc_id`
- `element`
- `calc_dir`
- `scf_converged`
- `scf_iterations`
- `final_energy_ev`
- `fermi_ev`
- File paths relative to archive
`index_core.parquet`
Columnar equivalent for efficient ML loading.
Validation
All configurations satisfy:
- SCF convergence: **100%**
- Missing density files: **0**
- Broken index references: **0**
- NetCDF readability: verified
- Size consistency: no outliers
- Deterministic configuration ordering
Intended Uses
- Machine learning on charge density fields
- Learning inverse mappings (structure → density)
- DFT surrogate modeling
- Electronic structure benchmarking
- Representation learning on periodic systems
License
This dataset contains: - Structural perturbations - DFT outputs -
Electron density grids
It does **not** redistribute pseudopotentials.
CC BY 4.0
Citation
If you use this dataset, please cite:
> Irina Arévalo, Pablo Olleros, SIESTA Single-Element Density Dataset, Zenodo,
> 2026. DOI: 10.5281/zenodo.18925343
Contact
For questions, please contact:
Irina Arévalo
Universidad Politecnica de Madrid, Spain
irina.arevalo@upm.es
Pablo Olleros
CUNEF Universidad
pablo.olleros@cunef.edu
提供机构：
Zenodo创建时间：
2026-03-10
