Deep learning in the context of nano-photonics is mostly discussed in terms of its potential
for inverse design of photonic devices or nano-structures. Many of the recent works on …

Deep artificial neural networks are powerful tools with many possible applications in
nanophotonics. Here, we demonstrate how a deep neural network can be used as a fast …

Deep-learning algorithms enable precise image recognition based on high-dimensional
hierarchical image features. Here, we report the development and implementation of a deep …

Mechanical characterization of two-dimensional (2D) materials has always been a
challenging task due to their extremely small thickness. The current prevailing methods to …

Topological materials discovery has emerged as an important frontier in condensed matter
physics. While theoretical classification frameworks have been used to identify thousands of …

Thin nanomaterials are key constituents of modern quantum technologies and materials
research. The identification of specimens of these materials with the properties required for …

Van der Waals (vdW) heterostructure constructed from atomically thin layered materials
provides quantum material platforms with emergent physical phenomena and novel device …

Advanced photonic probing techniques are of great importance for the development of non-
contact wafer-scale testing of Photonic Integrated Circuits (PICs). The most advanced …