Over the past few decades, molecular dynamics simulations and first-principles calculations
have become two major approaches to predict the lattice thermal conductivity (κ L), which …

Ternary metal oxides are crucial components in a wide range of applications and have been
extensively cataloged in experimental materials databases. However, there still exist cation …

We present NeuralIL, a model for the potential energy of an ionic liquid that accurately
reproduces first-principles results with orders-of-magnitude savings in computational cost …

An atomistic understanding of dry-etching processes with reactive molecules is crucial for
achieving geometric integrity in highly scaled semiconductor devices. Molecular dynamics …

One of the most exciting tools that have entered the arsenal of modern science and
technology in recent years is machine learning, which can efficiently solve problems of …

With the development of the density functional theory (DFT) and ever-increasing
computational capacity, an accurate prediction of lattice thermal conductivity based on the …

Response of the electronic density at the electrode–electrolyte interface to the external field
(potential) is fundamental in electrochemistry. In density-functional theory, this is captured by …

The determination of catalyst nanostructures with first-principles accuracy using genetic
algorithms (GA) is very demanding due to the cubic scaling of the computational cost of …

While several studies confirmed that machine-learned potentials (MLPs) can provide
accurate free energies for determining phase stabilities, the abilities of MLPs for efficiently …

Ions and radicals serve as key intermediates in molecular transformation, with their chemical
properties being essential for understanding and predicting reaction reactivity and …