Joquempo/Metamaterial-Dataset
Python codes for generating a dataset with topology optimization results for the base cell of a periodic metamaterial
This project helps materials scientists and mechanical engineers create specialized datasets for designing metamaterials. It takes desired material properties, specifically target Poisson's ratio and Young's modulus, and outputs a comprehensive dataset of topology optimization results, including detailed structural and sensitivity data. This dataset is then used to train AI models that can improve the efficiency and accuracy of metamaterial design processes.
No commits in the last 6 months.
Use this if you need to generate a large, detailed dataset of topology optimization results for periodic metamaterial base cells to train machine learning models for design automation.
Not ideal if you are looking for a pre-trained AI model or a tool to directly perform metamaterial design without custom dataset generation.
Stars
11
Forks
1
Language
Python
License
GPL-3.0
Category
Last pushed
Jun 05, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Joquempo/Metamaterial-Dataset"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
kaanaksit/odak
Scientific computing library for optics, computer graphics and visual perception.
NVIDIA/torch-harmonics
Differentiable signal processing on the sphere for PyTorch
PreFab-Photonics/PreFab
Artificial nanofabrication of integrated photonic circuits using deep learning
MatthewFilipovich/torchoptics
Differentiable wave optics simulation library built on PyTorch
artificial-scientist-lab/XLuminA
XLuminA, a highly-efficient, auto-differentiating discovery framework for super-resolution microscopy.