3D image data of digitally-generated porous material samples

Published: 26 September 2022| Version 1 | DOI: 10.17632/hh7kjk8twz.1
Contributors:
Tomoki Yasuda, Shinichi Ookawara, Shiro Yoshikawa, Hideyuki Matsumoto

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.

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Institutions

  • Tokyo Kogyo Daigaku

Categories

Chemical Engineering

Licence