Nature

Higher-order equivariant neural networks for charge density prediction in materials

The calculation of electron density distribution using density functional theory (DFT) in materials and molecules is central to the study of their quantum and macro-scale properties, yet accurate and ...
Nature

Rapid thickness distribution prediction of superplastic formed parts based on geometry adapted PSO-BP neural network surrogate model

Rapid and accurate prediction of thickness distribution remains a critical challenge in achieving real-time process optimization for superplastic forming (SPF) operations. Conventional prediction ...
EurekAlert!

Transfer learning-enhanced physics-informed neural network (TLE-PINN): A breakthrough in melt pool prediction for laser melting

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...