Big-data-accelerated aperiodic Si/Ge superlattice prediction for quenching thermal conduction via pattern analysis
Thermal conductivity of material is one of the basic physical properties and plays an important role in manipulating thermal energy. In order to accelerate the prediction of material structure with desired thermal property, machine learning algorithm has been widely adopted. However, in the optimiza...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-03-01
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| Series: | Energy and AI |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S266654682030046X |