1. closed-cell foam generated by Voronoi tessellation
The algarithm was implemented using a python code with Blender

2. open-cell foam generated by deep learning
The geometry was generated using a deep learning model, 3D conditional generative adversarial network (3D-CGAN).
The dataset was prepared using Voronoi tessellation.
https://doi.org/10.1080/14686996.2022.2157682

3. Gyroid_sheet
The model was generated using a MATLAB code.
https://doi.org/10.1007/s10853-018-2285-5

4. iWp
The model was generated using a MATLAB code.
https://doi.org/10.1007/s10853-018-2285-5

5. mathematically defined 3D auxetic metamaterial
The model was generated using a MATLAB code. The 3D auxetic metamaterial has a negative Poisson's ratio around 0.3.
https://doi.org/10.1016/j.matdes.2020.109313

6. Schwarz Diamond
The model was generated using a MATLAB code.
https://doi.org/10.1007/s10853-018-2285-5

7. CAD-based auxetic metamaterials
The model can be generated using CAD modeling, such as 3Ds max, SolidWorks, and Rhino, etc.
https://doi.org/10.1088/1361-665X/abdada

8. Gyroid_strut
The model was generated using a MATLAB code.
https://doi.org/10.1007/s10853-018-2285-5

9. 2D auxetic metamaterial
The geometry was generated using a deep learning model, conditional generative adversarial network (CGAN).
The dataset was prepared using Voronoi tessellation.
https://doi.org/10.1016/j.matdes.2021.110178