143 datasets found

The electronic and vibrational properties and electron-phonon couplings of one-dimensional materials will be key to many prospective applications in nanotechnology....

Graph neural networks have enjoyed great success in the prediction of material properties for both molecules and crystals. These networks typically use the atomic positions...

Graph neural networks have enjoyed great success in the prediction of material properties for both molecules and crystals. These networks typically use the atomic positions...

Fast, empirical potentials are gaining increased popularity in the computational fields of materials science, physics and chemistry. With it, there is a rising demand for...

Fast, empirical potentials are gaining increased popularity in the computational fields of materials science, physics and chemistry. With it, there is a rising demand for...

Material-specific calculations based on density functional theory play a major role in understanding and designing the properties of quantum matter. In the field of topological...

We present a first-principles investigation of the structural, electronic, and magnetic properties of pyrolusite (β-MnO2) using conventional and extended Hubbard-corrected...

The production of hydrogen fuels, via water splitting, is of practical relevance for meeting global energy needs and mitigating the environmental consequences of...

We present JuDiT (Jülich Database of impurities embedded into a Topological insulator) which collects first principles calculation of impurities embedded into the prototypical...

We present JuDiT (Jülich Database of impurities embedded into a Topological insulator) which collects first principles calculation of impurities embedded into the prototypical...

Materials that can host Majorana zero modes gained a lot of attention in recent years due to the possibility to engineer topologically protected quantum computing platforms....

Materials that can host Majorana zero modes gained a lot of attention in recent years due to the possibility to engineer topologically protected quantum computing platforms....

This study employed density functional theory with doubly screened dielectric-dependent hybrid (DSH) functional to predict the band gaps of Pb- and Sn-based inorganic and hybrid...

We performed a computational study using Density Functional Theory calculations on a copper-graphene system. A global minima search was performed using the Minima Hopping...

Field-effect transistors (FETs) based on two-dimensional materials (2DMs) with atomically thin channels have emerged as a promising platform for beyond-silicon electronics....

Classical turning surfaces of Kohn-Sham potentials separate classically-allowed regions (CARs) from classically-forbidden regions (CFRs). They are useful for understanding many...

We show that, contrary to popular assumptions, predictions from machine learning potentials built upon high-dimensional atom-density representations almost exclusively occur in...

This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we...

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture...

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture...