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| mp_id | volume | magnetic_density | curie_temperature | total_magnetic_moment |
|---|---|---|---|---|
| mp-557023 | 113.2718060996685 | 0.02651851977999183 | 82.50138910872064 | 3.0038006 |
| mp-21255 | 104.87418429419712 | 0.053604811165099936 | 309.9822720766458 | 5.621761 |
| mp-1080562 | 200.719047252236 | 0.032923051450321476 | 55.84238840972242 | 6.6082835 |
| mp-19912 | 196.07941064821128 | 0.04765106797760001 | 112.14100739343115 | 9.343393 |
| mp-581471 | 185.90069536559395 | 0.0016121957274016065 | 120.85158343778161 | 0.2997083 |
| mp-11382 | 93.2420526248234 | 0.12760206700643856 | 501.63225091229674 | 11.897879 |
| mp-1206973 | 71.6945563621157 | 0.0606675366733801 | 472.2734806650908 | 4.349532 |
A collection of 5020 magnetic materials from Materials Project, with estimated magnetic density and predicted Curie temperatures.
How this dataset is connected to other assets
We're starting to bring a few of the pieces together in our permanent magnet screening pipeline. In this post we'll look at how well we are able to filter out materials from a list of ~5000 ferro/ferr
Discover other datasets like this one
This is a first draft of a compiled Curie temperature dataset mapping crystal structure (from Materials Project) to Curie temperature. Builds on the work of https://github.com/Songyosk/CurieML. Dataset includes ~6,800 unique materials representing 3,284 unique chemical families.
Evaluation results for the MatterGen fine-tuned model candidates, with new superconducting families labeled.