README.md

---
tags:
- ml-intern
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: power_mW
    dtype: float64
  - name: repetition_rate_kHz
    dtype: float64
  - name: scan_speed_mm_s
    dtype: float64
  - name: pulse_duration_fs
    dtype: float64
  - name: wavelength_nm
    dtype: float64
  - name: num_passes
    dtype: int64
  - name: spot_diameter_um
    dtype: float64
  - name: focal_offset_um
    dtype: float64
  - name: material
    dtype: large_string
  - name: water_content
    dtype: float64
  - name: threshold_fluence_J_cm2
    dtype: float64
  - name: absorption_depth_nm
    dtype: float64
  - name: incubation_coefficient
    dtype: float64
  - name: refractive_index
    dtype: float64
  - name: pulse_energy_uJ
    dtype: float64
  - name: peak_fluence_J_cm2
    dtype: float64
  - name: effective_pulses
    dtype: float64
  - name: overlap_percent
    dtype: float64
  - name: etch_depth_um
    dtype: float64
  - name: etch_width_um
    dtype: float64
  - name: surface_roughness_Sa_um
    dtype: float64
  - name: aspect_ratio
    dtype: float64
  - name: side_wall_angle_deg
    dtype: float64
  splits:
  - name: train
    num_bytes: 2828401
    num_examples: 12000
  download_size: 1580191
  dataset_size: 2828401
---

# TWLAb/femtosecond-laser-hydrogel-etching-data

<!-- ml-intern-provenance -->
## Generated by ML Intern

This dataset repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.

- Try ML Intern: https://smolagents-ml-intern.hf.space
- Source code: https://github.com/huggingface/ml-intern

## Usage

```python
from datasets import load_dataset

dataset = load_dataset('TWLAb/femtosecond-laser-hydrogel-etching-data')
```