Progress in the discovery of new materials has been accelerated by the development of
reliable quantum-mechanical approaches to crystal structure prediction. The properties of a …

To fill the gap between accurate (and expensive) ab initio calculations and efficient atomistic
simulations based on empirical interatomic potentials, a new class of descriptions of atomic …

In analogy to natural enzymes, an elaborated design of catalytic systems with a specifically
tailored local chemical environment could substantially improve reaction kinetics, effectively …

The atomic simulation environment (ASE) is a software package written in the Python
programming language with the aim of setting up, steering, and analyzing atomistic …

In metals additive manufacturing (AM), materials and components are concurrently made in
a single process as layers of metal are fabricated on top of each other in the near-final …

Big data and artificial intelligence has revolutionized science in almost every field–from
economics to physics. In the area of materials science and computational heterogeneous …

Crystal structure prediction is a long-standing challenge in condensed matter and chemical
science. Here we report a machine-learning approach for crystal structure prediction, in …

In this critical review we examine the current state of our knowledge in respect of the nature
of the active sites in copper containing zeolites for the selective conversion of methane to …

Global optimization of cluster geometries is of fundamental importance in chemistry and an
interesting problem in applied mathematics. In this work, we introduce a relatively new …

We have developed a software package CALYPSO (Crystal structure AnaLYsis by Particle
Swarm Optimization) to predict the energetically stable/metastable crystal structures of …