An increased synergy between experimental and theoretical investigations in
heterogeneous catalysis has become apparent during the last decade. Experimental work …

The recent rise of computational, data-driven research has significant potential to accelerate
materials discovery. Automated workflows and materials databases are being rapidly …

Benchmarking is a community-based and (preferably) community-driven activity involving
consensus-based decisions on how to make reproducible, fair, and relevant assessments. In …

Machine learning (ML) is used to derive local stability information for density functional
theory calculations of systems in relation to the recently discovered SnO 2 (110)-(4× 1) …

We present the implementation of GAtor, a massively parallel, first-principles genetic
algorithm (GA) for molecular crystal structure prediction. GAtor is written in Python and …

Tailoring the functional properties of advanced organic/inorganic heterogeneous devices to
their intended technological applications requires knowledge and control of the microscopic …

The identification of low-energy conformers for a given molecule is a fundamental problem
in computational chemistry and cheminformatics. We assess here a conformer search that …

Current advances in synthesizing and characterizing atomically precise monodisperse metal
clusters (AMCs) at the subnanometer scale have opened up new possibilities in quantum …

We predict the structures of neutral gas phase gold clusters (A un, n= 5− 13) at finite
temperatures based on free-energy calculations obtained by replica-exchange ab initio …

The ability to navigate vast energy landscapes of molecules, clusters, and solids is a
necessity for discovering novel compounds in computational chemistry and materials …