Back in the old days—the really old days—the task of designing materials was laborious. Investigators, over the course of 1,000-plus years, tried to make gold by combining things like lead, mercury, ...

Accurate prediction of shallow donor electron binding energies is critical for device modeling, dopant activation, and donor-based quantum technologies. Traditional beyond-DFT approaches are ...

KAIST researchers have developed a simulation-based method to predict how small future transistors can ...

Theoretical simulation of phase change materials such as Ge-Sb-Te has suffered from two methodological issues. On the one hand, there is a lack of efficient band gap correction method for density ...

As the global semiconductor industry enters the so-called 2-nanometer process era, the actual size of transistors—the core ...

The arrangement of electrons in matter, known as the electronic structure, plays a crucial role in fundamental but also applied research such as drug design and energy storage. However, the lack of a ...

A new computational method extracts electronic band structures from finite, imperfect, and curved nanomaterials, linking nano ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

CDVAE, a symmetry-aware generative AI framework that embeds space-group information into the generation of crystal structures ...