Structure and dynamics of supercooled liquid Ge2Sb2Te5 from machine‐learning‐driven simulations
Studies of supercooled liquid phase‐change materials are important for the development of phase‐change memory and neuromorphic computing devices. Here, we use a machine‐learning‐based interatomic potential for Ge2Sb2Te5 (GST) to carry out large‐scale molecular‐dynamics simulations of liquid and supe...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Wiley
2020
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