Generative adversarial networks (GANs) are deep generative models (GMs) that have
recently attracted attention owing to their impressive performance in generating completely …

Current solid state synthesis intrinsically involves a multidimensional space which is
challenging to parametrize and predict. The diversity of extended structures comes from the …

Flux crystal growth has been widely applied to explore new phases and grow crystals of
emerging materials. To accommodate the needs of high-quality single crystals, the flux …

By relating the charge multiplicity distribution and the temperature of a de-exciting nucleus
through a deep neural network, we propose that the charge multiplicity distribution can be …

Previous studies presented the phase diagram induced by the disorder existing separately
either in the higher-order topological states or in the topological trivial states, respectively …

Residual production cross sections in spallation reactions are key data for nuclear physics
and related applications. Spallation reactions are very complex due to the wide range of …

The gamma-graphyne nanoribbons (γ-GYNRs) incorporating diamond-shaped segment
(DSSs) with excellent thermoelectric properties are systematically investigated by combining …

Composition selection and crystal-growth control are the most important issues in material
development. Crystal growth using a molten salt as the solvent, which is otherwise known as …

Kinetic energy (KE) functional is crucial to speed up density functional theory calculation.
However, deriving it accurately through traditional physics reasoning is challenging. We …

The flux method is an efficient liquid-phase crystal growth technique. Accordingly, it is
expected to be one of the key technologies for the development of innovative inorganic …