Datasets:
File size: 3,634 Bytes
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license: cc-by-4.0
task_categories:
- image-to-image
- unconditional-image-generation
tags:
- microscopy
- electron-microscopy
- HAADF-STEM
- nanoparticles
- simulation
- materials-science
- webdataset
size_categories:
- 100K<n<1M
configs:
- config_name: default
data_files:
- split: train
path: "train-*.tar"
---
# Nanoparticle Size Estimation Dataset (WebDataset)
100,000 simulated HAADF-STEM images of nanoparticles with three image variants per sample (raw simulation, normalized, and CycleGAN style-transferred), paired with per-structure metadata including atomic coordinates, morphology, and simulation parameters.
## Dataset Description
Synthetic HAADF-STEM images of Pt nanoparticles on various support interfaces, generated for nanoparticle size and morphology prediction. Each sample includes the raw simulation output, a set-normalized version, and a CycleGAN-transferred version that emulates experimental noise characteristics. Associated with the paper [Nanoparticle size estimation](https://pubs.acs.org/doi/10.1021/acs.nanolett.4c06025).
Original data: [Zenodo record 14608502](https://zenodo.org/records/14608502)
## Format
WebDataset format: 20 TAR shards (~1 GB each), 19 GB total.
Each sample in a shard contains:
- `{idx:06d}.sim_raw.npy` — raw simulated HAADF-STEM image (128x128, float32)
- `{idx:06d}.sim_norm.npy` — set-normalized simulation (128x128, float32)
- `{idx:06d}.cyclegan.npy` — CycleGAN style-transferred image (128x128, float32)
- `{idx:06d}.json` — metadata
### Metadata Fields
| Field | Type | Description |
|-------|------|-------------|
| `sample_id` | int | Original sample index |
| `original_filename` | string | Original .npy filename |
| `width` | int | Image width (128) |
| `height` | int | Image height (128) |
| `pixel_size` | float | Pixel size in Angstroms |
| `beam_offset_x` | float | Beam offset in x |
| `beam_offset_y` | float | Beam offset in y |
| `particle_rotation` | float | Particle rotation angle (radians) |
| `structure_type` | string | Nanoparticle morphology (cluster, wulff, random, etc.) |
| `support_interface` | string | Support surface orientation (e.g., 111, 100, random) |
| `particle_interface` | string | Particle surface orientation |
| `element` | string | Atomic species (Pt) |
| `subset` | string | Dataset subset label (e.g., AC_111_111) |
| `n_atoms` | int | Number of atoms in the structure |
| `raw_min` | float | Minimum pixel intensity (raw image) |
| `raw_max` | float | Maximum pixel intensity (raw image) |
| `raw_mean` | float | Mean pixel intensity (raw image) |
| `raw_std` | float | Std dev of pixel intensity (raw image) |
### Image Properties
- **Count:** 100,000 samples (300,000 images total across 3 variants)
- **Format:** NumPy arrays (.npy), float32
- **Resolution:** 128x128
- **Modality:** Synthetic HAADF-STEM
- **Element:** Pt nanoparticles
- **Morphologies:** cluster, wulff, random
## Usage
```python
import webdataset as wds
import numpy as np
from torch.utils.data import DataLoader
url = "path/to/nanoparticle_wds/train-{0000..0019}.tar"
dataset = wds.WebDataset(url).decode().shuffle(1000)
dataloader = DataLoader(dataset, batch_size=64, num_workers=4)
for sample in dataloader:
raw_image = sample[".sim_raw.npy"]
norm_image = sample[".sim_norm.npy"]
cyclegan_image = sample[".cyclegan.npy"]
metadata = sample[".json"]
```
## Source
Original data from [Zenodo record 14608502](https://zenodo.org/records/14608502). Associated paper: [Nano Letters (2024)](https://pubs.acs.org/doi/10.1021/acs.nanolett.4c06025).
## License
CC-BY-4.0
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