3D image data of digitally-generated porous material samples
Published: 26 September 2022| Version 1 | DOI: 10.17632/hh7kjk8twz.1
Contributors:
, Shinichi Ookawara, , Description
This dataset contains 3D image data of digitally-generated 528 granular porous material samples, which can be used to train a machine learning model for predicting material performance properties from geometric features of porous material samples. The dataset has been prepared in https://doi.org/10.1016/j.cej.2021.130069.
Files
Institutions
Tokyo Kogyo Daigaku
Categories
Chemical Engineering