General Learning of the Electric Response of Inorganic Materials
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914171686223872 |
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| author | Martin, Bradley A. A. Ganose, Alex M. Kapil, Venkat Li, Tingwei Butler, Keith T. |
| author_facet | Martin, Bradley A. A. Ganose, Alex M. Kapil, Venkat Li, Tingwei Butler, Keith T. |
| contents | We present MACE-Field, a field-aware $O(3)$-equivariant interatomic potential that provides a compact, derivative-consistent route to dielectric properties (such as polarisation $\mathbf P$, Born effective charges $Z^*$ and polarisability $\boldsymbolα$) and finite-field simulations across chemistry for inorganic solids. MACE-Field preserves the standard MACE readout and can inherit existing MACE foundation weights, turning pretrained models into field-aware ones with minimal change. To demonstrate, we fine-tune MACE-MP-0 on multiple heads covering BECs and polarisabilities ($\sim$6k MP dielectrics spanning 81 elements), polarisations (2.5k MP nonpolar-to-polar polarisation branches), and energies, forces, and stresses (10,000 structure-replay set from MPtraj), resulting in a field-aware foundation model, MACE-Field-MP-0. We show that MACE-Field can evaluate polarisation branches and spontaneous polarisations, predict $Z^*$ and dielectric constants across diverse chemistries, and reproduce finite-field MD simulations, such as BaTiO$_3$ polarisation hysteresis and the IR/Raman and dielectric spectra of $α$-quartz, benchmarking against Allegro-pol and DFPT. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_17870 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | General Learning of the Electric Response of Inorganic Materials Martin, Bradley A. A. Ganose, Alex M. Kapil, Venkat Li, Tingwei Butler, Keith T. Materials Science We present MACE-Field, a field-aware $O(3)$-equivariant interatomic potential that provides a compact, derivative-consistent route to dielectric properties (such as polarisation $\mathbf P$, Born effective charges $Z^*$ and polarisability $\boldsymbolα$) and finite-field simulations across chemistry for inorganic solids. MACE-Field preserves the standard MACE readout and can inherit existing MACE foundation weights, turning pretrained models into field-aware ones with minimal change. To demonstrate, we fine-tune MACE-MP-0 on multiple heads covering BECs and polarisabilities ($\sim$6k MP dielectrics spanning 81 elements), polarisations (2.5k MP nonpolar-to-polar polarisation branches), and energies, forces, and stresses (10,000 structure-replay set from MPtraj), resulting in a field-aware foundation model, MACE-Field-MP-0. We show that MACE-Field can evaluate polarisation branches and spontaneous polarisations, predict $Z^*$ and dielectric constants across diverse chemistries, and reproduce finite-field MD simulations, such as BaTiO$_3$ polarisation hysteresis and the IR/Raman and dielectric spectra of $α$-quartz, benchmarking against Allegro-pol and DFPT. |
| title | General Learning of the Electric Response of Inorganic Materials |
| topic | Materials Science |
| url | https://arxiv.org/abs/2508.17870 |