English(EN) Physics Informed Neural Networks for Solving the Drift-Diffusion Equations

PINNs为半导体器件建模提供新方法

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-28 04:00

研究人员开发了一种使用物理信息神经网络（PINNs）求解复杂漂移扩散方程的新方法，这些方程是半导体器件建模的基础。该方法为传统的数值求解器提供了一个强大的替代方案，有可能缩短模拟时间并解决反问题。PINN架构已证明在非平衡条件下具有与现有商业软件相当的准确性，并有望用于微电子学研究和发现。 AI

影响 PINNs为半导体器件建模提供了一种更高效、更通用的方法，有望加速微电子学领域的创新。

排序理由该集群包含一篇学术论文，详细介绍了使用AI求解科学方程的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Luke Ragan, Matteo G. C. Alasio, Enrico Bellotti, Luca Dal Negro · 2026-10-28 04:00

用于求解漂移扩散方程的物理信息神经网络

arXiv:2610.33133v1 Announce Type: new Abstract: The drift-diffusion equations are the fundamental building block for the modeling, design, and optimization of modern semiconductor devices. Solutions of the drift-diffusion equations rarely give way to analytical forms, and exhibit…