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Violet phosphorus (VP) is garnering attention for its appealing physical properties and potential applications in optoelectronics. A comprehensive investigation of the photodegradation and thermal effects of exfoliated VP on SiO₂/Si substrates is presented. The degradation rate of VP is strongly influenced by the wavelength and exposure duration of light. Light illumination of VP above the bandgap leads to faster degradation, attributed to interactions with reactive oxygen species. Power‐dependent photoluminescence (PL) measurements at low temperature (T = 4 K) show neutral exciton (X⁰) and trion (T) intensities linearly increase with excitation power, while the energy difference between peak energies decreases. The T/X⁰spectral weight ratio increases from 0.28 at 300 K to 0.69 at 4 K, suggesting enhanced T formation due to reduced phonon scattering. Temperature‐dependent Raman is used to investigate the phonon properties of VP. Tracking peak positions of 9 Raman modes with temperature, the linear first‐order temperature coefficient is obtained and found to be linear for all modes. The results provide a deeper understanding of VP's degradation behavior and implications for optoelectronic applications.

 

Abstract The topological features of optical vortices have been opening opportunities for free-space and on-chip photonic technologies, e.g., for multiplexed optical communications and robust information transport. In a parallel but disjoint effort, polar anisotropic van der Waals nanomaterials supporting hyperbolic phonon polaritons (HP 2 s) have been leveraged to drastically boost light-matter interactions. So far HP 2 studies have been mainly focusing on the control of their amplitude and scale features. Here we report the generation and observation of mid-infrared hyperbolic polariton vortices (HP 2 Vs) associated with reconfigurable topological charges. Spiral-shaped gold disks coated with a flake of hexagonal boron nitride are exploited to tailor spin–orbit interactions and realise deeply subwavelength HP 2 Vs. The complex interplay between excitation spin, spiral geometry and HP 2 dispersion enables robust reconfigurability of the associated topological charges. Our results reveal unique opportunities to extend the application of HP 2 s into topological photonics, quantum information processing by integrating these phenomena with single-photon emitters, robust on-chip optical applications, sensing and nanoparticle manipulation. 

Engineering electronic bandgaps is crucial for applications in information technology, sensing, and renewable energy. Transition metal dichalcogenides (TMDCs) offer a versatile platform for bandgap modulation through alloying, doping, and heterostructure formation. Here, the synthesis of a 2D Mo_xW_1‐xS₂graded alloy is reported, featuring a Mo‐rich center that transitions to W‐rich edges, achieving a tunable bandgap of 1.85 to 1.95 eV when moving from the center to the edge of the flake. Aberration‐corrected high‐angle annular dark‐field scanning transmission electron microscopy showed the presence of sulfur monovacancy, V_S, whose concentration varied across the graded Mo_xW_1‐xS₂layer as a function of Mo content with the highest value in the Mo‐rich center region. Optical spectroscopy measurements supported by ab initio calculations reveal a doublet electronic state of V_S, which is split due to the spin‐orbit interaction, with energy levels close to the conduction band or deep in the bandgap depending on whether the vacancy is surrounded by W atoms or Mo atoms. This unique electronic configuration of V_Sin the alloy gave rise to four spin‐allowed optical transitions between the V_Slevels and the valence bands. The study demonstrates the potential of defect and optical engineering in 2D monolayers for advanced device applications.

 

Polaritons enable subwavelength confinement and highly anisotropic flows of light over a wide spectral range, holding the promise for applications in modern nanophotonic and optoelectronic devices. However, to fully realize their practical application potential, facile methods enabling nanoscale active control of polaritons are needed. Here, we introduce a hybrid polaritonic-oxide heterostructure platform consisting of van der Waals crystals, such as hexagonal boron nitride (hBN) or alpha-phase molybdenum trioxide (α-MoO₃), transferred on nanoscale oxygen vacancy patterns on the surface of prototypical correlated perovskite oxide, samarium nickel oxide, SmNiO₃(SNO). Using a combination of scanning probe microscopy and infrared nanoimaging techniques, we demonstrate nanoscale reconfigurability of complex hyperbolic phonon polaritons patterned at the nanoscale with high resolution. Hydrogenation and temperature modulation allow spatially localized conductivity modulation of SNO nanoscale patterns, enabling robust real-time modulation and nanoscale reconfiguration of hyperbolic polaritons. Our work paves the way towards nanoscale programmable metasurface engineering for reconfigurable nanophotonic applications.

 

Hydrogen-doped perovskites can be reconfigured by electrical pulses to take on all essential functions necessary for artificial intelligence hardware. 

Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence found in nature in the solid state can serve as inspiration for algorithmic simulations in artificial neural networks and potential use in neuromorphic computing. Here, we demonstrate nonassociative learning with a prototypical Mott insulator, nickel oxide (NiO), under a variety of external stimuli at and above room temperature. Similar to biological species such as Aplysia , habituation and sensitization of NiO possess time-dependent plasticity relying on both strength and time interval between stimuli. A combination of experimental approaches and first-principles calculations reveals that such learning behavior of NiO results from dynamic modulation of its defect and electronic structure. An artificial neural network model inspired by such nonassociative learning is simulated to show advantages for an unsupervised clustering task in accuracy and reducing catastrophic interference, which could help mitigate the stability–plasticity dilemma. Mott insulators can therefore serve as building blocks to examine learning behavior noted in biology and inspire new learning algorithms for artificial intelligence.