Structurally different from conventional oxide ferroelectrics with rigid lattices, van der Waals
(vdW) ferroelectrics have stable layered structures with a combination of strong intralayer …

To fill the gap between accurate (and expensive) ab initio calculations and efficient atomistic
simulations based on empirical interatomic potentials, a new class of descriptions of atomic …

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics
simulations using machine learning potentials known as Deep Potential (DP) models. This …

Strontium titanate (SrTi O 3) is regarded as an essential material for oxide electronics. One
of its many remarkable features is the subtle structural phase transition, driven by the …

Our recent study has found that physics-informed neural networks (PINN) tend to be local
approximators after training. This observation led to the development of a novel physics …

With their celebrated structural and chemical flexibility, perovskite oxides have served as a
highly adaptable material platform for exploring emergent phenomena arising from the …

In the last few decades, deep learning (DL) has afforded solutions to macroscopic problems
in petroleum engineering, but mechanistic problems at the microscale have not benefited …

Magic-angle twisted bilayer graphene (TBG) has attracted significant interest recently due to
the discoveries of diverse correlated and topological states. In this work, we study the …

To fill the gap between accurate (and expensive) ab initio calculations and efficient atomistic
simulations based on empirical interatomic potentials, a new class of descriptions of atomic …

Two-dimensional (2D) ferroelectric semiconductors present opportunities for integrating
ferroelectrics into high-density ultrathin nanoelectronics. Among the few synthesized 2D …