Prediction of hydrogen uptake of metal organic frameworks using explainable machine learning
Metal organic frameworks (MOFs) are considered as potential materials for hydrogen storage. The hydrogen uptake is influenced by several parameters (e.g., temperature, pressure, isosteric heat of adsorption, BET surface area). Of late, machine learning (ML) technique is used to assess the role of in...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-04-01
|
| Series: | Energy and AI |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546823000022 |