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Unlike noble metals, refractory plasmonic materials can maintain resilient and attractive optical properties even at comparatively extreme temperatures and high current densities. One refractory plasmonic material of interest is TiN, which exhibits an extremely high melting temperature of about 3000 K and noble-metal-like optical properties in the visible and near-infrared regime. Using lithographically fabricated TiN nanowires and leveraging their ability to host plasmon modes, we have examined plasmonic photothermal heating and photothermoelectric response whose anisotropy and magnitude depend on the width of the nanowires. The photothermoelectric response is consistent with changes in the Seebeck coefficient where the wire fans out to wider contact pads. Upon electrically biasing the structures, Joule heating of the TiN wires can produce detectable thermal emission within the visible and near-IR range, with emission intensity growing rapidly with increasing bias. This emission is consistent with local temperatures exceeding 2000 K, as expected from a finite element model of the Joule heating. 

The integration of solid-state single-photon sources with foundry-compatible photonic platforms is crucial for practical and scalable quantum photonic applications. This study explores aluminum nitride (AlN) as a material with properties highly suitable for integrated on-chip photonics and the ability to host defect-center related single-photon emitters. We have conducted a comprehensive analysis of the creation of single-photon emitters in AlN, utilizing heavy ion irradiation and thermal annealing techniques. Subsequently, we have performed a detailed analysis of their photophysical properties. Guided by theoretical predictions, we assessed the potential of Zirconium (Zr) ions to create optically addressable spin defects and employed Krypton (Kr) ions as an alternative to target lattice defects without inducing chemical doping effects. With a 532 nm excitation wavelength, we found that single-photon emitters induced by ion irradiation were primarily associated with vacancy-type defects in the AlN lattice for both Zr and Kr ions. The density of these emitters increased with ion fluence, and there was an optimal value that resulted in a high density of emitters with low AlN background fluorescence. Under a shorter excitation wavelength of 405 nm, Zr-irradiated AlN exhibited isolated point-like emitters with fluorescence in the spectral range theoretically predicted for spin-defects. However, similar defects emitting in the same spectral range were also observed in AlN irradiated with Kr ions as well as in as-grown AlN with intrinsic defects. This result is supportive of the earlier theoretical predictions, but at the same time highlights the difficulties in identifying the sought-after quantum emitters with interesting properties related to the incorporation of Zr ions into the AlN lattice by fluorescence alone. The results of this study largely contribute to the field of creating quantum emitters in AlN by ion irradiation and direct future studies emphasizing the need for spatially localized Zr implantation and testing for specific spin properties. 

The generation of nonequilibrium hot-carriers from the decay of surface plasmons has been attracting intense research attention in the last decade due to both the fundamental aspects of extreme light-matter interactions and potential practical applications. Here, we overview the physics associated with plasmon-assisted hot-carrier generation and outline the key applications of hot-carrier processes for photodetection, photovoltaics and photocatalysis. We also discuss the recent developments in employing molecular tunnel junctions as barriers for extracting hot-carriers and provide an outlook on the potential of this emerging field for sustainable energy. 

Photonic technologies continue to drive the quest for new optical materials with unprecedented responses. A major frontier in this field is the exploration of nonlocal (spatially dispersive) materials, going beyond the local, wavevector-independent assumption traditionally adopted in optical material modeling. The growing interest in plasmonic, polaritonic, and quantum materials has revealed naturally occurring nonlocalities, emphasizing the need for more accurate models to predict and design their optical responses. This has major implications also for topological, nonreciprocal, and time-varying systems based on these material platforms. Beyond natural materials, artificially structured materials—metamaterials and metasurfaces—can provide even stronger and engineered nonlocal effects, emerging from long-range interactions or multipolar effects. This is a rapidly expanding area in the field of photonic metamaterials, with open frontiers yet to be explored. In metasurfaces, in particular, nonlocality engineering has emerged as a powerful tool for designing strongly wavevector-dependent responses, enabling enhanced wavefront control, spatial compression, multifunctional devices, and wave-based computing. Furthermore, nonlocality and related concepts play a critical role in defining the ultimate limits of what is possible in optics, photonics, and wave physics. This Roadmap aims to survey the most exciting developments in nonlocal photonic materials and metamaterials, highlight new opportunities and open challenges, and chart new pathways that will drive this emerging field forward—toward new scientific discoveries and technological advancements. 

The conversion of a photon’s frequency has long been a key application area of nonlinear optics. It has been discussed how a slow temporal variation of a material’s refractive index can lead to the adiabatic frequency shift (AFS) of a pulse spectrum. Such a rigid spectral change has relevant technological implications, for example, in ultrafast signal processing. Here, we investigate the AFS process in epsilon-near-zero (ENZ) materials and show that the frequency shift can be achieved in a shorter length if operating in the vicinity of $\mathrm{R}\mathrm{e}\left\{{\mathrm{\epsilon <\#comment/>}}_r\right\}=0$. We also predict that, if the refractive index is induced by an intense optical pulse, the frequency shift is more efficient for a pump at the ENZ wavelength. Remarkably, we show that these effects are a consequence of the slow propagation speed of pulses at the ENZ wavelength. Our theoretical predictions are validated by experiments obtained for the AFS of optical pulses incident upon aluminum zinc oxide thin films at ENZ. Our results indicate that transparent metal oxides operating near the ENZ point are good candidates for future frequency conversion schemes. 

Abstract A robust process for fabricating intrinsic single‐photon emitters in silicon nitride is recently established. These emitters show promise for quantum applications due to room‐temperature operation and monolithic integration with technologically mature silicon nitride photonics platforms. Here, the fundamental photophysical properties of these emitters are probed through measurements of optical transition wavelengths, linewidths, and photon antibunching as a function of temperature from 4.2 to 300 K. Important insight into the potential for lifetime‐limited linewidths is provided through measurements of inhomogeneous and temperature‐dependent broadening of the zero‐phonon lines. At 4.2 K, spectral diffusion is found to be the main broadening mechanism, while spectroscopy time series reveal zero‐phonon lines with instrument‐limited linewidths. 

Abstract Deterministic nanoassembly may enable unique integrated on‐chip quantum photonic devices. Such integration requires a careful large‐scale selection of nanoscale building blocks such as solid‐state single‐photon emitters by means of optical characterization. Second‐order autocorrelation is a cornerstone measurement that is particularly time‐consuming to realize on a large scale. Supervised machine learning‐based classification of quantum emitters as “single” or “not‐single” is implemented based on their sparse autocorrelation data. The method yields a classification accuracy of 95% within an integration time of less than a second, realizing roughly a 100‐fold speedup compared to the conventional Levenberg–Marquardt fitting approach. It is anticipated that machine learning‐based classification will provide a unique route to enable rapid and scalable assembly of quantum nanophotonic devices.