Enhanced sampling algorithms have emerged as powerful methods to extend the utility of
molecular dynamics simulations and allow the sampling of larger portions of the …

Large-language models (LLMs) such as GPT-4 caught the interest of many scientists.
Recent studies suggested that these models could be useful in chemistry and materials …

Perovskite solar cells with an inverted architecture provide a key pathway for
commercializing this emerging photovoltaic technology because of the better power …

A simultaneously accurate and computationally efficient parametrization of the potential
energy surface of molecules and materials is a long-standing goal in the natural sciences …

Support-induced strain engineering is useful for modulating the properties of two-
dimensional materials. However, controlling strain of planar molecules is technically …

Acidic electrochemical CO2 reduction (CO2R) addresses CO2 loss and thus mitigates the
energy penalties associated with CO2 recovery; however, acidic CO2R suffers low …

The current high-energy lithium metal batteries are limited by their safety and lifespan owing
to the lack of suitable electrolyte solutions. Here we report a synergy of fluorinated co …

Two major challenges hinder the advance of aqueous zinc metal batteries for sustainable
stationary storage:(1) achieving predominant Zn-ion (de) intercalation at the oxide cathode …

In mammals, interactions between sequences within topologically associating domains
enable control of gene expression across large genomic distances. Yet it is unknown how …

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 …