Latest Articles for Density Functional Theory

DiffCSP improves the efficiency of predicting crystal structures using generative models.

Lattice DFT enhances understanding of complex electronic systems and interactions.

Exploring the electronic properties and interactions in nickel dichalcogenides.

New insights reveal how charge-density waves influence superconductivity in specific materials.

Machine learning improves the accuracy of predicting crystal structures for new material development.

Discover how excitons influence the future of electronic and optical devices.

Research reveals important energy differences in atomic nuclei with advanced modeling techniques.

New automated approach enhances vibrational spectroscopy calculations for complex materials.

A software package for studying materials' electronic structures through simulations.

A deep look into the classification of electronic excitations and new methods.

Researchers confirm unique band splitting in manganese telluride, revealing altermagnetic behavior.

A new method enhances efficiency in data collection for scientific machine learning.

New methods in materials science enhance alloy discovery using machine learning.

A new method improves predictions of material strength under stress.

Combining machine learning and OFDFT enhances molecular analysis efficiency and accuracy.

Exploring the potential of halide double perovskites in solar cells and LEDs.

CrTe shows promise for advanced technology with its magnetic and electrical traits.

DBBSC offers a fresh approach to improve calculations in quantum chemistry.

A technique improves understanding of electron structures in organic materials.

Explore the impact of spin-orbit coupling on electronic properties and applications.

Exploring the role and applications of Green's function theory in modern physics.

Research reveals insights on water interactions with metal oxide surfaces.

Recent studies improve estimates of carbon monoxide adsorption energy on magnesium oxide surfaces.

Researchers develop stochastic methods to study quasiparticles efficiently in complex materials.

Explore how DFPT advances the study of phonons in materials.

A novel approach enhances accuracy in predicting Hamiltonians for materials.

Insights into the Eisenbud-Wigner-Smith time delay and its implications.

New method speeds up DFT calculations, enhancing materials research.

X-ray absorption spectroscopy reveals electronic structures of ferrites for improved applications.

Research on HeC60 reveals important behaviors of trapped helium in fullerenes.

A fresh approach improves the study of magnetic metals using advanced simulations.

Research examines the structure and magnetic behavior of copper-substituted lead oxyapatite.

Researchers uncover unique electronic properties of twisted bilayer graphene.

This article discusses improvements in self-interaction correction methods within density-functional theory.

A new model enhances accuracy and efficiency in predicting electron density.

Research uses machine learning to quickly predict properties of organic salt crystals.

Discovering efficient routes of atomic movement in chemical processes.

Research highlights new methods to study vanadium dioxide's unique properties.

Machine learning enhances accuracy in predicting chemical properties using adaptive hybrid density functionals.

Research sheds light on aluminum's properties in extreme conditions.