PREDICTION OF THE DENSITY OF STATES (DOS) OF MATERIALS USING CRYSTAL GRAPH CONVOLUTIONAL NEURAL NETWORKS (CGCNN)
This study explores the capability of the Crystal Graph Convolutional Networks (CGCNN) model, which was previously used only for predicting single material properties such as Fermi energy, to predict sequential data properties of materials, such as the Density of States (DOS). The method employed...
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| Main Author: | |
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/86938 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |