The first step in the construction of a regression model or a data-driven analysis, aiming to
predict or elucidate the relationship between the atomic-scale structure of matter and its …

Kohn–Sham Density Functional Theory (KSDFT) is the most widely used electronic structure
method in chemistry, physics, and materials science, with thousands of calculations cited …

Kohn-Sham density functional theory (DFT) is a standard tool in most branches of chemistry,
but accuracies for many molecules are limited to 2-3 kcal⋅ mol− 1 with presently-available …

Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …

Density functional theory (DFT) is the standard formalism to study the electronic structure of
matter at the atomic scale. In Kohn–Sham DFT simulations, the balance between accuracy …

Conspectus Density functional theory (DFT) calculations are used in over 40,000 scientific
papers each year, in chemistry, materials science, and far beyond. DFT is extremely useful …

With the growth of computational resources, the scope of electronic structure simulations has
increased greatly. Artificial intelligence and robust data analysis hold the promise to …

Abstract Machine learning (ML) methods have recently been increasingly widely used in
quantum chemistry. While ML methods are now accepted as high accuracy approaches to …

Using an end-to-end differentiable implementation of the Kohn-Sham self-consistent field
equations, we obtain a highly accurate neural network–based exchange and correlation …

There is an increasing demand for free-energy calculations using ab initio molecular
dynamics these days. Metadynamics (MetaD) is frequently utilized to reconstruct the free …