Passive radiative cooling requires materials that combine high mid-infrared (MIR) emissivity within the atmospheric transparency window (8–13 µm) with minimal solar absorption, while maintaining scalability and long-term stability. Porous anodic alumina (PAA) is an attractive dielectric platform due to its intrinsic phonon-polariton infrared emission and electrochemically tunable nanostructure. However, achieving independent control of visible photonic properties and MIR emissivity within a single architecture remains challenging. Here, we demonstrate dual-spectral control of PAA photonic structures integrated with aluminum (Al) substrates using charge density-controlled sinusoidal pulse anodization. Periodic voltage modulation generates well-defined photonic stop bands (PSBs) in the visible range, enabling tunable structural coloration while preserving high MIR emissivity. Systematic pore widening produces a progressive blue shift of the PSB accompanied by non-monotonic reflectance changes, revealing distinct mechanisms governing spectral position and optical coherence. In contrast, MIR emissivity remains robust against variations in the visible photonic response, as confirmed by a constant-voltage reference sample. The PAA architecture provides intrinsic optical impedance matching through a gradual refractive-index transition, while the Al substrate acts independently as a back reflector that suppresses transmission losses. These findings establish PAA as a versatile platform for color-designed radiative cooling surfaces with independently engineered optical and thermal functionalities.

Passive radiative cooling offers energy-free sub-ambient cooling; however, its main challenge is achieving low solar absorption (visible − NIR) while maintaining strong thermal emission in the mid-infrared atmospheric window. In this work, we numerically investigate a planar porous anodic alumina (PAA)/Al bilayer as a spectrally selective emitter for daytime radiative cooling. The optical response of the PAA layer is modeled using an effective-medium approach based on the Maxwell–Garnett (MG) formalism, allowing systematic tuning of porosity. The simulations are conducted using COMSOL software with a highly refined mesh to ensure accuracy. The study demonstrates the influence of PAA thickness, Al thickness, and porosity on thermal emissivity in the mid-infrared range. Furthermore, field intensity, power dissipation, and penetration-depth analyses are consistent with mid-infrared spectral selectivity originating primarily from intrinsic phonon absorption within the Reststrahlen band of alumina, modulated by wavelength-dependent interference effects. At an incident angle of 35◦, where the simulated angular emissivity profile exhibits a local maximum for TM polarization, the PAA/Al bilayer achieves an average emissivity of 0.982 within the atmospheric window (8 − 13 μm) for a porosity of 30%. Moreover, the designed structure shows high PRC performance under normal atmospheric conditions, achieving a maximum temperature reduction of up to 8.3◦C below ambient temperature. Also, at thermal equilibrium, it delivers an anticipated net cooling power of 77.36W/m2. The PAA-based approach proposed here provides a promising route for producing low-cost, efficient radiative coolers at large scales for practical energy conservation

Elevated operating temperatures significantly reduce the efficiency and lifetime of Si photovoltaic (PV) modules, motivating the development of spectrally selective passive radiative cooling (PRC) coatings that dissipate heat without compromising solar energy harvesting. Here, we propose and numerically investigate a multilayer metal–dielectric metasurface composed of a staircase-shaped silica (SiO2) grating integrated onto a Si/Al platform, where the Al layer acts as a reflective back mirror and the Si layer represents the PV absorber. The design addresses the limited emissivity and impedance mismatch of conventional planar dielectric coatings in the 8−13𝑢⁢𝑚 atmospheric transparency window. The structure is engineered by systematically optimizing the grating step heights, lateral widths, and periodicity to promote synergistic excitation of surface phonon-polariton resonances (SPhPs) and guided-mode resonances. Electromagnetic (EM) simulations under TM polarization, using experimentally measured complex refractive indices for SiO2, Si, and Al, were performed to evaluate spectral emissivity, angular response, and solar absorptance. The optimized SiO2/Si/Al metasurface achieves an average emissivity of 0.92 within the 8−13𝑢⁢𝑚 window while maintaining low solar absorptance across 0.3−0.9μ⁢m and preserving absorption near the Si bandgap (∼1.1um). Thermal performance was assessed using a coupled radiative–convective energy balance model under AM1.5G solar irradiation. The proposed structure reduces the equilibrium temperature of the structure by more than 21K relative to bare Si, corresponding to a projected PV efficiency improvement approaching 10%. Although sub-ambient daytime cooling is not achieved due to residual solar absorption inherent to PV integration, the metasurface functions effectively as a radiative heat-rejection coating compatible with real-world Si solar modules. These results demonstrate that engineered dielectric micro-gratings can overcome the emissivity limitations of planar films and provide scalable, all-inorganic solutions for PV thermal management.

Refractive index sensing based on photonic crystal structures has emerged as a powerful platform for label-free and highly precision detection in chemical and biological applications. Here, we present a high-performance one-dimensional photonic crystal (1D PC) heterostructure tailored for ultra-sensitive refractive index sensing. The design leverages a symmetric, reverse-stacked cavity configuration to achieve an exceptionally high-quality factor ($\text{Q}-\text{f}\text{a}\text{c}\text{t}\text{o}\text{r}\text{s}$) and near-unity transmission in the telecom band. The structure comprises two mirror-symmetric 1D PCs arranged in reverse order to generates a localized interface state at their junction, giving rise to a sharp resonance within the photonic bandgap (PBG). Impedance-matching layers composed of silicon and air are added at both input and output interfaces to enhance light–matter interaction and transmission efficiency. We employ finite-element-method (FEM) simulations with lossless materials to realize a sharply defined resonance, yielding a $\text{Q}-\text{f}\text{a}\text{c}\text{t}\text{o}\text{r}$ of 1.32 × 10⁸, sensitivity of 1197.2 nm/RIU, figure of merit ($\text{F}\text{O}\text{M}$) of $9.04\times {10}^4$, and detection limit ($\text{D}\text{L}$) of $\sim 1.1\times {10}^{-8}$ RIU. The structure exhibits near-unity transmission, polarization insensitivity, and operates in the telecom band ($𝜆\approx 1512𝑛𝑚$). Despite their idealized nature, these findings lay a high-performance foundation for the design of practical 1D PCs sensors targeting trace gas or low-concentration biochemical detection

Social interactions rely on the integration of information across multiple sensory modalities. In many species, individuals recognize conspecifics through combinations of auditory, olfactory, tactile, and visual cues, reflecting the capacity of neural systems to integrate diverse streams of sensory input. The naked mole-rat (Heterocephalus glaber) provides a powerful model system for understanding how social living shapes the evolution of such communication systems, particularly under conditions where visual information is largely absent. Naked mole-rats represent a rare example of mammalian eusociality, living in large multigenerational colonies organized around a strict reproductive hierarchy and cooperative care of offspring [1]. Here, we review evidence that naked mole-rats integrate multiple sensory modalities, focusing on audition, olfaction, and somatosensation to encode social identity.

Groundwater (GW) represents a critical resource for sustaining agriculture and rural communities across the arid regions of many developing countries. This study assesses three predictive approaches boosted classification tree (BCT), the bivariate frequency ratio (FR), and a hybrid BCT–FR ensemble for mapping Potential Zones (GWPZ) in arid environments. The modelling framework integrates satellite-derived variables with pumping-test measurements (specific capacity (SPC) and transmissivity (T)) and incorporates topographic, geological, hydrogeological, and anthropogenic factors using an inventory of forty-two wells divided into calibration (70%) and validation (30%) datasets across the West El-Minia region of Upper Egypt. Change-detection analysis over the study period (2000–2025) indicated a substantial increase in agricultural activity, with cultivated lands expanding by more than 560 km². This expansion was accompanied by an observed level decline of approximately five meters over the same period, based on field measurements from 42 wells and calculated using observed water table differences. Based on SPC predictions, the BCT and hybrid FR–BCT models achieved relatively high area under the curve (AUC) values. For transmissivity, the corresponding accuracy values were 83.38% for BCT and 92.58% for FR–BCT. Model outputs were assessing their reliability by comparing the GW potential map generated with available borehole information and daily GWproductivity data from the aquifer system. The study area was classified into four GW potential categories: very high (8%), high (26%), moderate (54%), and low (12%), with the northeastern sector exhibiting the highest recharge and storage potential. Overall, the applied machine-learning techniques demonstrated good performance for GW potential assessment in data-limited environments. The results provide important guidance for GW resource management by identifying zones with substantial recharge and development potential.