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#graph neural networks Open access Sep 2026

GNN- ω PBE: Range-Separation Parameters Learned from Three-Dimensional Structures

This study advances machine learned density functional development from molecule-specific to geometry-specific modeling of conformational effects in electronic structures by introducing GNN-ωPBE, a second machine learned RSH functional that generates geometry-specific ω values directly from atomic numbers and three-dim...

Xi Cheng, Si-Qi Chen, Xian-Qi Deng et al. · 0 citations

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