Physics-aware graph neural networks for automated tight-binding model construction in quantum transport simulations

Exploring foci of: doi.org Physics-aware graph neural networks for automated tight-binding model construction in quantum transport simulations November 2025 • Lei Liao, Yawei Lv, Shihong Yu, Tang Weimin, Haipeng Lan, Hui‐Xiong Deng, Kenli Li, Changzhong Jiang <title>Abstract</title> Tight-binding (TB) model is crucial for quantum transport simulations of semiconductor devices, critically determining the electrical characteristics of channel materials. Here, we propose a graph neural network (GNN)-based framework for automated TB model construction. By integrating atomic sites (nodes) and chemical bonds (edges) into atomistic graph representations, our method efficiently extracts orbital onsite energies and inter-orbital hopping parameters through supervised learning of… Open Article Page

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