An accelerating approach of designing ferromagnetic materials via machine learning modeling of magnetic ground state and Curie temperature
Magnetic materials have a plethora of applications from information technologies to energy harvesting. However, their functionalities are often limited by the magnetic ordering temperature. In this work, we performed random forest on the magnetic ground state and the Curie temperature (TC) to classi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-04-01
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| Series: | Materials Research Letters |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/21663831.2020.1863876 |