We report a novel deep learning (DL) method for classifying inorganic compounds using 3D electron density data. We transform Density Functional Theory (DFT)-derived CHGCAR files from the Materials ...

Determining the 3D atomic structures of multi-element nanoparticles in their native liquid environment is crucial to understanding their physicochemical properties. Graphene liquid cell (GLC) TEM ...

Electrons move through a conducting material like commuters at the height of Manhattan rush hour. The charged particles may jostle and bump against each other, but for the most part, they're ...

A research team from the Institute of Statistical Mathematics and Panasonic Holdings Corporation has developed a machine learning algorithm, ShotgunCSP, that enables fast and accurate prediction of ...

Researchers have devised a mathematical approach to predict the structures of crystals -- a critical step in developing many medicines and electronic devices -- in a matter of hours using only a ...

Orientational order is important for both liquid crystals and cell assemblies, and experimental and computational techniques can replicate in vivo structure in an in vitro setting.