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MEIDNet (alignment training, seed 3)

One of the seven alignment models: seed 3, the seed with the highest structure matching, chosen for the inverse-design task before any candidate was generated.

field value
Dataset Perov-5, protocol perov5-v1.1
Type model
Inputs structure, property:heat_all, property:dir_gap
Parameters 0.70 M
Training data Perov-5, all 18,928 materials (the test split included: scores on it are not held-out)
Status Computed here on 2026-10-05
Evidence level MLIP validated
Added 2026-10-05 by Anand Babu (UCLouvain)
Alignment space the normalised encoder outputs, before the projection heads
Checkpoint meidnet_paper_rerun_seed3.pth · sha256 205de8b83390…
Links paper · code · weights

Inverse design

metric value definition
SUN 0.611 stable, unique and novel candidates divided by the budget of 54; a candidate that was not delivered counts as a failure
Stable 0.872 fraction of delivered candidates whose MACE-MP-0 formation energy after relaxation is at most 0.10 eV/atom, against elemental reference phases (the criterion of meidnet screen and of the paper)
Unique 1.000 fraction of delivered candidates whose composition does not repeat an earlier one
Novel 0.830 fraction of delivered candidates whose composition is not in the data set (training, validation and test splits)
ΔHf -1.32 eV/atom median MACE-MP-0 formation energy of the delivered candidates
DFT hit 0.250 among candidates whose A, B and X sites match a Perov-5 entry (so their DFT band gap is known), the fraction within 0.5 eV of the target
DFT known 8 candidates with a known DFT band gap (the denominator of DFT hit)
Delivered 47 candidates delivered out of the budget of 54
Valid 0.870 fraction of the budget that passes every rule of the family
SUN count 33 stable, unique and novel candidates
Budget 54 candidates requested

Candidates

Every candidate with its MLIP formation energy, novelty and, where Perov-5 has the same sites, the DFT band gap.

candidate formula target gap (eV) ΔHf (eV/atom) stable novel DFT gap (eV)
oxide_T1_1 NdCrO3 1.5 -2.477 yes yes –
oxide_T1_2 BaPbO3 1.5 -1.970 yes no 0.00
oxide_T1_3 SrSnO3 1.5 -2.475 yes no 3.40
oxide_T1_4 YbGaO3 1.5 -2.336 yes yes –
oxide_T1_5 HoNiO3 1.5 -1.619 yes yes –
oxide_T1_6 BaSnO3 1.5 -2.476 yes no 2.50
oxide_T2_1 SmNiO3 2.5 -1.699 yes yes –
oxide_T2_2 SrZrO3 2.5 -3.478 yes no 6.60
oxide_T2_3 YbCoO3 2.5 -1.655 yes yes –
oxide_T2_4 TbAlO3 2.5 -3.505 yes yes –
oxide_T2_5 YbAlO3 2.5 -3.069 yes yes –
oxide_T2_6 NdVO3 2.5 -2.559 yes yes –
oxide_T3_1 NdFeO3 3.5 -2.033 yes yes –
oxide_T3_2 LuAlO3 3.5 -3.417 yes yes –
oxide_T3_3 CsNbO3 3.5 -2.475 yes no 2.90
oxide_T3_4 SrGeO3 3.5 -2.485 yes no 1.70
oxide_T3_5 RbNbO3 3.5 -2.632 yes no 3.90
oxide_T3_6 CaSnO3 3.5 -2.366 yes no 3.60
chalcogenide_T1_1 SrWSe3 1.5 4.343 no yes –
chalcogenide_T1_2 SrSnSe3 1.5 5.797 no yes –
chalcogenide_T1_3 YbVSe3 1.5 -1.316 yes yes –
chalcogenide_T1_4 BaSnSe3 1.5 -1.413 yes yes –
chalcogenide_T1_5 CaSnSe3 1.5 -1.012 yes yes –
chalcogenide_T1_6 SmCoSe3 1.5 -1.105 yes yes –
chalcogenide_T2_1 EuScSe3 2.5 -1.919 yes yes –
chalcogenide_T2_2 CaWSe3 2.5 -1.033 yes yes –
chalcogenide_T2_3 CaMoSe3 2.5 -1.089 yes yes –
chalcogenide_T2_4 SrTiSe3 2.5 -2209239531516.471 no yes –
chalcogenide_T2_5 SrGeSe3 2.5 -33544873571.535 no yes –
chalcogenide_T2_6 GdVSe3 2.5 -1.323 yes yes –
chalcogenide_T3_1 SmMnSe3 3.5 -1.258 yes yes –
chalcogenide_T3_2 YbFeSe3 3.5 -1.180 yes yes –
chalcogenide_T3_3 YbCoSe3 3.5 -339207415395.052 no yes –
chalcogenide_T3_4 SmFeSe3 3.5 -1.139 yes yes –
chalcogenide_T3_5 SmCrTe3 3.5 -1.267 yes yes –
chalcogenide_T3_6 TbCoSe3 3.5 -9150744981.631 no yes –
halide_T1_1 KPbI3 1.5 -1.186 yes yes –
halide_T1_2 KSnI3 1.5 -1.142 yes yes –
halide_T1_3 NaSnI3 1.5 -0.936 yes yes –
halide_T1_4 KCoI3 1.5 -0.826 yes yes –
halide_T1_5 CsPbI3 1.5 -1.302 yes yes –
halide_T1_6 KFeI3 1.5 -0.737 yes yes –
halide_T2_1 RbMnI3 2.5 -1.123 yes yes –
halide_T2_2 KZnI3 2.5 -1.102 yes yes –
halide_T3_1 KMnI3 3.5 -1.083 yes yes –
halide_T3_2 KNiI3 3.5 -0.883 yes yes –
halide_T3_3 NaNiI3 3.5 -0.723 yes yes –

Outputs

Reproduce

python scripts/benchmarks.py run perov5 --method meidnet-alignment-seed3

Computed on Intel64 Family 6 Model 197 Stepping 2, GenuineIntel (16 threads), CPU only; generating the candidates took 54 min.