Conditional generative models double the rate of stable novel MAX phase structures by steering generation with MXene derivative counts and A-site binding energy surrogates, yielding five DFT-stable candidates out of ten tested.
Antunes, Ricardo Grau-Crespo, Amil Aligayev, Javier Dominguez, and Keith T
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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PRISMat generates crystal slabs with mean absolute errors of 0.188 eV/A² for cleavage energy and 2.79 eV for work function, reducing error by 4× versus the next best model while using less inference time.
citing papers explorer
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Conditional Generative Models Enable Targeted Exploration of MAX Phase Design Space
Conditional generative models double the rate of stable novel MAX phase structures by steering generation with MXene derivative counts and A-site binding energy surrogates, yielding five DFT-stable candidates out of ten tested.
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PRISMat: Policy-Driven, Permutation-Invariant Autoregressive Material Generation
PRISMat generates crystal slabs with mean absolute errors of 0.188 eV/A² for cleavage energy and 2.79 eV for work function, reducing error by 4× versus the next best model while using less inference time.