The research status of the shear viscosity of nucleonic matter is reviewed. Some methods to
calculate the shear viscosity of nucleonic matter are introduced, including mean free path …

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 …

Lithium ortho-thiophosphate (Li3PS4) has emerged as a promising candidate for solid-state
electrolyte batteries, thanks to its highly conductive phases, cheap components, and large …

Due to the huge composition space, composition screening is of great importance to the
optimization of high‐entropy diborides (HEBs) with exceptional oxidation resistance …

Over the last decade, an increasing body of evidence has emerged, supporting the
existence of a metastable liquid–liquid critical point in supercooled water whereby two …

We study self-interaction effects in solvated and strongly-correlated cationic molecular
clusters, with a focus on the solvated hydroxyl radical. To address the self-interaction issue …

In this paper, we investigate the performance of different machine learning potentials (MLPs)
in predicting key thermodynamic properties of water using RPBE+ D3. Specifically, we …

Understanding water behavior in salt solutions remains a notable challenge in
computational chemistry. Conventional force fields have shown limitations in accurately …

In traditional finite-temperature Kohn–Sham density functional theory (KSDFT), the partial
occupation of a large number of high-energy KS eigenstates restricts the use of first …

As the most important solvent, water has been at the center of interest since the advent of
computer simulations. While early molecular dynamics and Monte Carlo simulations had to …