1,345 datasets found

<p>Molecular dynamics (MD) provides insights into atomic-scale processes by integrating over time the equations that describe the motion of atoms under the action of...

<p>Understanding electrical resistivity in metals remains a central challenge in quantifying charge transport at finite temperature. Current first-principles calculations...

<div> <p><span><span lang="EN-US">PROTACs are of high interest because of their ability to target previously challenging disease-related proteins....

This dataset contains the optimized structures of hole polarons in anatase and rutile TiO₂, calculated using the DFT+U and PBE0(α) functionals, with parameters tuned to satisfy...

Cu(In,Ga)Se2 (CIGSe) is a highly efficient absorber material in thin-film solar cells that demonstrates a unique ability to tolerate massive Cu deficiency, which is often...

We reassess the modeling of amorphous silica bilayers as a two-dimensional classical system whose particles interact with an effective pairwise potential. We show that it is...

<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...

<p>Microgels made of poly(<span>N</span>-isopropylacrylamide) are the prototype of soft, thermoresponsive particles widely used to study fundamental problems...

<p>Core-shell (CS) microgels–comprising a solid core chemically linked to a crosslinked polymer shell–are an important class of stimuli-responsive colloids...

<p><span lang="EN-GB">Understanding how oxide nanomorphology directs metal–support interactions is key to designing selective, low-cost catalysts. The...

<p>Strongly correlated physics arises from electron-electron scattering within partially filled orbitals. Organic molecules in open-shell configurations are therefore...

We develop a convolutional neural network (NN) approach able to predict the elastic contribution to chemical potential μₑ at the surface of a 2D strained film given its profile...

We develop a convolutional neural network (NN) approach able to predict the elastic contribution to chemical potential μₑ at the surface of a 2D strained film given its profile...

Recent advances in the synthesis of graphene fragments that possess unpaired π-electrons and display high-spin ground states have unlocked possibilities to explore exotic...

<p>Diboron trioxide (B2O3) represents an unusual case among polymorphic oxides, for its vitrified state features superstructural units – planar boroxol...

<p>We perform a high-throughput computational search for novel phonon-mediated superconductors, starting from the Materials Cloud three-dimensional database (MC3D) of...

Understanding how the vibrational and thermal properties of solids are influenced by atomistic structural disorder is of fundamental scientific interest, and paramount to...

Traditional atomistic machine learning (ML) models serve as surrogates for quantum mechanical (QM) properties, predicting quantities such as dipole moments and polarizabilities,...

<p>In this paper, we present and benchmark our first-principles calculations of magnon dispersions and wave functions in monolayer Cr trihalides using the finite-momentum...

<p>In this paper, we present and benchmark our first-principles calculations of magnon dispersions and wave functions in monolayer Cr trihalides using the finite-momentum...