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Origin of the machine learning forces field errors across metal elements
<p><span lang="EN-US">The overall development of the machine learning force field (MLFF) has advanced rapidly, with a wide range of models emerging in recent years.... -
Stable n-type conduction in WOx-CNT hybrid films
<p>Nanostructured hybrid films composed of tungsten oxide (WO<sub><em>x</em></sub>) nanoclusters and vertically aligned carbon nanotubes (CNTs)... -
Getting the manifold right: The crucial role of orbital resolution in DFT+U f...
<p>This dataset accompanies the study "Getting the manifold right: The crucial role of orbital resolution in DFT+U for mixed d-f electron compounds" and provides input and... -
A universal machine learning model for the electronic density of states
<p>In the last few years several ``universal'' interatomic potentials have appeared, using machine-learning approaches to predict energy and forces of atomic... -
Monolayer Sc2NF2 and Sc2NO2 electrodes for bilayer MoS2: Achieving symmetric ...
<p><span lang="EN-US">Achieving</span><em><span lang="EN-US"> n</span></em><span lang="EN-US">- and... -
Novel fast Li-ion conductors for solid-state electrolytes from first-principles
<p>We present a high-throughput computational screening for fast lithium-ion conductors to identify promising materials for application in all solid-state electrolytes.... -
Dielectric response and excitations of hydrogenated free-standing graphene
The conversion of semimetallic suspended graphene (Gr) to a large-gap semiconducting phase is realized by controlled adsorption of atomic hydrogen (deuterium) on free-standing... -
Computational screening and discovery of Silver–Indium Halide double salts.
<p>This study employed density functional theory in combination with the Materials Project database to systematically screen the unexplored phase space of... -
Determining the optimal structural resolution of proteins through an informat...
<p>The choice of structural resolution is a fundamental aspect of protein modelling, determining the balance between descriptive power and interpretability. Although... -
Benchmarking the plasmon-pole and multipole approximations in the Yambo Code ...
<p>In this work we provide the results for ionization potential (IP) and electron affinity (EA) of all the 100 molecules of the set, as computed at the G0W0 level within... -
Benchmarking physics-inspired machine learning models for transition metal co...
<p>Physics-inspired machine learning (ML) models can be categorized into two classes: those relying solely on three-dimensional structure and those incorporating... -
Importance of non-adiabatic effects on Kohn anomalies in 1D metals
<p>Kohn anomalies are kinks or dips in phonon dispersions which are pronounced in low-dimensional materials. We investigate the effects of non-adiabatic phonon self-energy... -
In search of the electron-phonon contribution to total energy
<p>The total energy is a fundamental characteristic of solids, molecules, and nanostructures. In most first-principles calculations of the total energy, the nuclear... -
Modeling the equilibrium vacancy concentration in multi-principal element all...
<p>This dataset contains a list of <a... -
Comparative study of magnetic exchange parameters and magnon dispersions in N...
<p>Spin-wave excitations are fundamental to understanding the behavior of magnetic materials and hold promise for future information and communication technologies. Yet,... -
Comparing the latent features of universal machine-learning interatomic poten...
<p>The past few years have seen the development of ``universal'' machine-learning interatomic potentials (uMLIPs) capable of approximating the ground-state potential... -
Two-dimensional RMSD projections for reaction path visualization and validation
<p>This record contains the complete optimization trajectories, potential model, and analysis data for the Nudged Elastic Band (NEB) calculation of the ethylene + N$_2$O... -
Extensive band gap tunability in covalent organic frameworks via metal interc...
Covalent organic frameworks (COFs) are materials of growing interest for electronic applications due to their tunable structures, chemical stability, and layered architectures... -
Probing high-energy electronic excitations in the Shastry-Sutherland compound...
<p>The Shastry-Sutherland compound SrCu<sub>2</sub>(BO<sub>3</sub>)<sub>2</sub> (SCBO) is a paradigmatic low-dimensional quantum spin... -
Cobalt-based perovskite oxides as catalysts for acidic oxygen evolution reaction
<p><span>Cobalt-based oxides have been investigated as potential alternatives to Ir/Ru-based oxides for catalyzing the oxygen evolution reaction (OER) in acidic...
