MEIDNet (paper): inverse design¶
The inverse-design campaign reported in the paper: candidates generated from property targets with the published model, screened for stability, uniqueness and novelty, and checked by DFT.
| field | value |
|---|---|
| Dataset | Perov-5, protocol paper |
| Type | model |
| Inputs | structure, property:heat_all, property:dir_gap |
| Parameters | 0.70 M |
| Training data | Perov-5 train (11,356) |
| Status | Reported in the paper |
| Evidence level | DFT validated |
| Added | 2026-05-29 by Anand Babu (UCLouvain) |
| Checkpoint | dual_autoencoder_clip_earlyfusion_propertyaware_2k.pth |
| Links | paper · code · weights |
Inverse design¶
| metric | value | definition |
|---|---|---|
| Generated | 140 | candidates generated (reported in the paper) |
| SUN count | 19 | stable, unique and novel candidates |
| SUN | 0.136 | stable, unique and novel candidates divided by the budget of 54; a candidate that was not delivered counts as a failure |
Evidence¶
- https://doi.org/10.1038/s41524-026-02153-3
examples/perov5/paper_results/
Notes¶
Numbers quoted from the paper: 140 candidates generated from property targets, 19 of them stable, unique and novel (13.6%). The paper's targets and budget differ from the protocol, so this record is not ranked. The candidates shipped with the paper (examples/perov5/paper_results) are screened with the protocol's criteria in the record 'Candidates shipped with the paper, screened here'.