1,430 datasets found

<p>Deep Generative models have shown impressive capabilities in several applications, e.g., image, video, and audio synthesis. Importantly, they can infer probability...

Machine Learning (ML) can be conveniently applied to continuum materials simulations, allowing for the investigation of larger systems and longer timescales, pushing the limits...

<p>Crafting neural-network interatomic potentials (NNIPs) remains a complex task, demanding specialized expertise in both machine learning and electronic-structure...

<p>We present a combined density-functional theory and dynamical mean-field theory (DFT+DMFT) study of the full structural phase space of rutile-based vanadium dioxide...

We analyze the effects on the structural and electronic properties of vanadium dioxide (VO₂) of adding an empirical inter-atomic potential within the density-functional theory+V...

<p>Strain soliton networks strongly influence the structural and electronic properties of heterodeformed bilayer systems, yet their design remains challenging due to the...

<p>This dataset presents the results of a comprehensive crystal structure search for ternary compounds in the Lu–N–H system. Thousands of candidate structures...

<p>The strongly constrained and appropriately normed (SCAN) meta-GGA functional is a milestone achievement of electronic structure theory. Recently, a revised and restored...

<p>Physics-inspired machine learning (ML) models can be categorized into two classes: those relying solely on three-dimensional structure and those incorporating...

<p><span lang="EN-US">Electron-phonon interactions in a solid are crucial for understanding many interesting material properties, such as transport properties and...

Combinatorial and guided screening of materials space with density-functional theory and related approaches has provided a wealth of hypothetical inorganic materials, which are...

<p>This archive provides the AiiDA workflows, metadata, and computational datasets associated with the study of vibrational frequencies and Stark tuning rates at...

<p>We use the self-consistent harmonic approximation (SSCHA) with machine learning interatomic potentials to calculate the effect of ¹⁸O...

<p>Hydrogen carriers that enable efficient transport and on-demand release of molecular hydrogen (H₂) are crucial for practical hydrogen-based...

<p>Mechanical properties of ultrathin coatings can deviate from bulk values due to growth-stage and interface effects. Elastic moduli of bulk amorphous alumina were...

We use symmetry analysis and density functional theory to show that changes in magnetic order at a surface with respect to magnetic order in the bulk can be generically...

<p>The quality, consistency, and information content of training data is often what determines the practical value of machine-learning models for atomistic simulations....

<p>We study the electronic structure and dynamical correlations in antiferromagnetic BiFeO₃, a prototypical room-temperature multiferroic, using a...

<p>Photothermal (photonic) sintering crystallizes as-deposited amorphous LiCoO2 (LCO) cathodes for solid-state thin-film batteries using millisecond, surface-localized...

<p>Gaussian process (GP) regression provides a strategy for accelerating saddle point searches on high-dimensional energy surfaces by reducing the number of times the...