Skip to content

PointNet-based 3D deep learning model designed for decoding the structure-property relationship for generic crystalline materials.

License

Notifications You must be signed in to change notification settings

raymond-yiqunwang/deepKNet

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

deepKNet

PointNet-based 3D deep learning model designed for decoding the structure-property relationship for generic crystalline materials.

Readers with interest should directly contact the corresponding author Raymond Wang for more information and we are open for collaborations.

Please cite the following work if you want to use the deepKNet.

@article{wang2021learning,
  title={Learning the Crystal Structure Genome for Property Classifications},
  author={Wang, Yiqun and Zhang, Xiao-Jie and Xia, Fei and Olivetti, Elsa A and Seshadri, Ram and Rondinelli, James M},
  journal={arXiv preprint arXiv:2101.01773},
  year={2021}
}

About

PointNet-based 3D deep learning model designed for decoding the structure-property relationship for generic crystalline materials.

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages