In the recent years, a dramatic boost of the research is observed at the junction of photonics,
machine learning and artificial intelligence. A new methodology can be applied to the …

Plasmonic nanomaterials have outstanding optoelectronic properties potentially enabling
the next generation of catalysts, sensors, lasers and photothermal devices. Owing to optical …

Metamaterials are artificial structures with the ability to efficiently control light‐field, attracting
intensive attention in the past few decades. People have studied the working principles …

Surface‐enhanced Raman spectroscopy (SERS), well acknowledged as a fingerprinting
and sensitive analytical technique, has exerted high applicational value in a broad range of …

Nanoparticles composed of metallic cores encapsulated in oxide shells emerged in the last
decade as an attractive class of nanocomposite materials due to their high stability and …

The deep-learning revolution is providing enticing new opportunities to manipulate and
harness light at all scales. By building models of light–matter interactions from large …

The world today is witnessing the significant role and huge demand for molecular detection
and screening in healthcare and medical diagnosis, especially during the outbreak of …

Deep neural networks (DNNs) have been used as a new method for nanophotonic inverse
design. However, DNNs need a huge dataset to train if we need to select materials from the …

The design of scatterers on demand is a challenging task that requires the investigation and
development of novel and flexible approaches. In this paper, we propose a machine …

Despite extensive efforts to predict optimal nanostructures for enhancing optical devices, a
more accurate, efficient, and practical method for nanostructure optimisation is required. In …