Atomically thin semiconductors such as tungsten disulfide (WS2) are promising materials for future photonic technologies.

The nonlinear susceptibility is a measure of a material's nonlinear response to an applied electric field. It determines the strength of the nonlinear effects and is related to the crystal's symmetry ...

Photonics is gaining momentum as a platform for high-speed AI computing. Researchers in Singapore have demonstrated a passive, ultrafast, and integration-ready all-optical nonlinear activation ...

A single layer of atoms may seem too thin to meaningfully interact with light, yet materials like tungsten disulfide are reshaping what is possible in nanophotonics. Researchers have now found a way ...

By harnessing two natural timescales in resonator arrays, researchers created photonic chips that reliably produce multiple harmonics without active compensation. For decades, scientists and engineers ...

Nonlinear optics is the branch of photonics that studies material responses wherein the induced polarisation is not directly proportional to the applied electromagnetic field. In these media, intense ...

Nonlinear optics has long relied on high-power lasers, whose spatial and temporal coherence ensures efficient nonlinear frequency conversion. However, a new study challenges the traditional assumption ...

A recent article in Advanced Materials reports a new fabrication method for nonlinear optical components using nanostructured polycrystalline lithium niobate (LN). The study addresses key limitations ...

A new publication DOI 10.29026/oea.2026.250193 discusses electric-field-induced second-harmonic generation paves the ...

When light passes through a material, it often behaves in unpredictable ways. This phenomenon is the subject of “nonlinear optics”, which is now integral to technological and scientific advances – ...

Researchers report building photonic computing chips that use light pulses to train spiking neural networks on robotic-control-style benchmark tasks, aiming to shift more of the learning workload from ...