Fig. 5 | npj Computational Materials

Fig. 5

From: Identification of advanced spin-driven thermoelectric materials via interpretable machine learning

Fig. 5The alternative text for this image may have been generated using AI.

Spin-driven thermopower SSTE of CoPtN thin films. SSTE increases with increasing X2X8 in CoPtN, which was selected by material screening guided by the knowledge obtained from the FAB/HMEs model, namely, the positive correlation between SSTE and X2X8. SSTE of Co48.9Pt51.1N7.2 thin film reaches 13.04 μV/K, which is larger than all other known STE materials

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