Unravelling the interplay between hydrogen and grain boundary of α-Fe under different concentration and strain rate via neural network interatomic potential

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Nature, Published online: 27 February 2026; doi:10.1038/d41586-026-00538-4

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Transformers solve these using attention (for alignment), MLPs (for arithmetic), and autoregressive generation (for carry propagation). The question is how small the architecture can be while still implementing all three.

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