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Updated: Jul 28, 2025

Picometer-Precision Atomic Position Tracking through Electron Microscopy
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在大型GNN原子模型中超越独立错误假设

Janghoon Ock1, Tian Tian1, John Kitchin1

  • 1Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA.

The Journal of chemical physics
|June 1, 2023
PubMed
概括

图形神经网络 (GNN) 现在可以准确预测相对能量差异,与密度函数理论 (DFT) 相比. 通过分析相关错误,GNN实现了显著的错误减少,改善了催化剂选和反应能量计算.

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