107 datasets found

Elemental gallium possesses several intriguing properties such as a low melting point, a density anomaly and an electronic structure in which covalent and metallic features...

Data analyses based on linear methods constitute the simplest, most robust, and transparent approaches to the automatic processing of large amounts of data for building...

One of the main applications of atomistic computer simulations is the calculation of ligand binding free energies. The accuracy of these calculations depends on the force field...

A highly appealing strategy to modulate a catalyst's activity and/or selectivity in a dynamic and non-invasive way is to incorporate a photoresponsive unit into a catalytically...

By combining metal nodes and organic linkers, an infinite number of metal organic frameworks (MOFs) can be designed in silico. When making new databases of such hypothetical...

Weyl semimetals are crystals in which electron bands cross at isolated points in momentum space. Associated with each crossing point (or Weyl node) is an integer topological...

The most successful and popular machine learning models of atomic-scale properties derive their transferability from a locality ansatz. The properties of a large molecule or a...

Molecular dipole moments of the QM7b dataset, a random sample of 21'000 molecules from the QM9 dataset, and the MuML showcase set (including the four challenge series) described...

The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of...

Designing an appropriate set of collective variables is crucial to the success of several enhanced sampling methods. Here we focus on how to obtain such variables from...

Pyrene is one of the most widely investigated aromatic hydrocarbons due to its unique optical and electronic properties. Hence, pyrene-based ligands have been investigated for...

This work combines a machine learning potential energy function with a modular enhanced sampling scheme to obtain statistically converged thermodynamical properties of flexible...

We present a workflow that traces the path from the bulk structure of a crystalline material to assessing its performance in carbon capture from coal’s postcombustion flue...

We present a workflow that traces the path from the bulk structure of a crystalline material to assessing its performance in carbon capture from coal’s postcombustion flue...

We present a workflow that traces the path from the bulk structure of a crystalline material to assessing its performance in carbon capture from coal’s postcombustion flue...

Metal-Organic Frameworks (MOFs) are highly versatile materials owing to their vast structural and chemical tunability. These hybrid inorganic-organic crystalline materials offer...

The study of chemical reactions in aqueous media is very important for its implications in several fields of science, from biology to industrial processes. However, modeling...

Non-covalent bonding patterns are commonly harvested as a design principle in the field of catalysis, supramolecular chemistry, and functional materials to name a few. Yet,...

The on-top pair density [Π(r)] is a local quantum chemical property, which reflects the probability of two electrons of any spin to occupy the same position in space. Simplest...

Data analyses based on linear methods constitute the simplest, most robust, and transparent approaches to the automatic processing of large amounts of data for building...