In recent years, the use of machine learning (ML) in computational chemistry has enabled
numerous advances previously out of reach due to the computational complexity of …

Recent advances in experimental and computational methods are increasing the quantity
and complexity of generated data. This massive amount of raw data needs to be stored and …

Accelerating the discovery of advanced materials is essential for human welfare and
sustainable, clean energy. In this paper, we introduce the Materials Project (www …

Electronically excited states of molecules are at the heart of photochemistry, photophysics,
as well as photobiology and also play a role in material science. Their theoretical description …

Theoretical reactivity indices based on the conceptual Density Functional Theory (DFT) have
become a powerful tool for the semiquantitative study of organic reactivity. A large number of …

Basis sets are some of the most important input data for computational models in the
chemistry, materials, biology, and other science domains that utilize computational quantum …

Graph neural networks that model 3D data, such as point clouds or atoms, are typically
desired to be $ SO (3) $ equivariant, ie, equivariant to 3D rotations. Unfortunately …

In the search for new functional materials, quantum mechanics is an exciting starting point.
The fundamental laws that govern the behaviour of electrons have the possibility, at the …

Ettore Majorana (1906–1938) disappeared while traveling by ship from Palermo to Naples
in 1938. His fate has never been fully resolved and several articles have been written that …

To write an introduction to the dynamics of open quantum systems may seem at first a
complicated, albeit perhaps unnecessary, task. On the one hand, the field is quite broad and …