Datasets:
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.
Original data: Zenodo record 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
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. Associated paper: Nano Letters (2024).
License
CC-BY-4.0