Search Results (441)

Photovoltaic Systems have been a long-standing challenge to integrate with electrical Power Grids due to the randomness of solar irradiance. Deep Learning (DL) has potential to forecast solar irradiance; however, black-box DL models typically do not offer interpretation, nor can they easily distinguish between deterministic astronomical cycles, and random meteorological variability. The objective of this study was to develop and apply a new Physics-Aware Deep Learning Framework that identifies and utilizes physical attributes of solar irradiance via Fourier-based signal decomposition. The proposed method decomposes the time-series into polynomial trend, Fourier-based seasonal component and stochastic residual, each of which are processed within different neural network paths. A wide variety of architectures were tested (Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Convolutional Neural Network (CNN)), at multiple historical window sizes and forecast horizons on a diverse dataset from a three-year span. All of the architectures tested demonstrated improved accuracy and robustness when using the physics aware decomposition as opposed to all other methods. Of the architectures tested, the GRU architecture was the most accurate and performed well in terms of overall evaluation. The GRU model had an RMSE of 78.63 W/m² and an $R^2$ value of 0.9281 for 15 min ahead forecasting. Additionally, the Fourier-based methodology was able to reduce the maximum absolute error by approximately 15% to 20%, depending upon the architecture used, and therefore it provided a way to reduce the impact of the larger errors in forecasting during periods of unstable weather. Overall, this framework represents a viable option for both physically interpretive and computationally efficient real-time solar forecasting that provides a bridge between Physical Modeling and Data-Driven Intelligence. Full article

Reducing electrode-related costs is an important step toward the large-scale commercialization of polymer solar cells. In this study, Cu is investigated as a low-cost top electrode in inverted polymer solar cells with the architecture ITO/ZnO/P3HT:PCBM/MoO₃/Cu. The fabricated devices achieved a maximum power conversion efficiency (η) of 2.86%, with an open-circuit voltage (V_oc) of 610 mV, a short-circuit current density (J_sc) of 6.90 mA cm⁻², and a fill factor (FF) of 68%. Long-term stability tests were carried out over a period of 12 weeks under glovebox, desiccator, and ambient room conditions, during which efficiency decreases of 23%, 53%, and 78% were observed, respectively. Structural and spectroscopic analyses suggest that device degradation is closely associated with O₂- and moisture-induced effects on the Cu electrode. The results demonstrate that Cu can be effectively employed as a top electrode in polymer solar cells under controlled environmental conditions, highlighting its potential as a cost-effective electrode material for polymer solar cell applications. Full article

Climate change has intensified summer drought and high solar radiation in Mediterranean ecosystems, generating abiotic stress that limits the establishment of riparian species. We conducted a nursery experiment to evaluate the effects of two levels of water availability and light intensity on the growth and physiological responses of two native riparian species from Mediterranean Chile: Drimys winteri and Persea lingue. A bi-factorial design combined two irrigation treatments (well-watered and water restriction) and two light intensity levels manipulated through a light protection treatment (20% shade mesh and full light exposure). Water restriction was applied gradually until 15–20% (v/v) substrate moisture, defined as maximum water restriction, followed by rehydration. Morphological variables (height, root collar diameter, and shoot-to-root ratio) and physiological traits (predawn water potential, chlorophyll fluorescence, and electron transport rate) were measured. Growth responses were affected by the light protection treatment, which promoted a significant height growth in both species. Water stress affected the global response of both species but they differed in their post-stress hydraulic recovery: P. lingue fully recovered its predawn water potential, whereas Drimys winteri did not. Our study provides measurable and quantifiable values that demonstrate the sensitivity of these species to water stress. Full article

Dye-sensitized solar cells (DSSCs) have attracted significant attention as next-generation photovoltaic devices due to their low cost, simple fabrication process, use of earth-abundant materials, and potential for colour tunability and transparency. p–n tandem DSSCs have garnered particular interest owing to their higher open-circuit voltage compared to single-junction DSSCs. However, the performance of such tandem devices remains limited by relatively low open-circuit voltage and short-circuit current density, primarily due to the scarcity of suitable p-type sensitizers. To address this challenge, we report a novel p–n tandem solar cell integrating a dye-sensitized TiO₂ photoanode with a perovskite-sensitized NiO photocathode, achieving a record power conversion efficiency of 4.02%. By optimizing the thickness of the TiO₂ layer, a maximum open-circuit voltage of 1060 mV and a peak short-circuit current density of 6.11 mA cm⁻² were simultaneously attained. Full article

Freshwater scarcity is a critical global challenge, particularly in arid and semi-arid regions like southern Iraq. This study evaluates the thermal and distillate performance of a conventional single-slope solar still under extreme summer conditions in Basrah, Iraq. The objective is to analyze and validate a coupled theoretical–experimental model for predicting temperature fields and freshwater productivity. The model incorporates transient energy and mass balance equations with temperature- and salinity-dependent thermophysical properties. Experiments were conducted using brackish water from the Shatt al-Arab River (salinity: 5.2 g/kg), and measured temperatures and productivity were compared against simulations over a 24-h period. Strong agreement was achieved between experimental and theoretical results, with $R^2>0.90$ for temperature predictions and $R^2=0.985$ for hourly productivity. Maximum hourly yield reached $0.46\mathrm{L}/{\mathrm{m}}^2$, with a total daily productivity of $3.5\mathrm{L}/{\mathrm{m}}^2$, The daily thermal efficiency was found to be 26.90% experimentally and 28.20% theoretically. A positive linear relation between the thermal gradient $(T_{\mathrm{w}}-T_{\mathrm{g}})$ and hourly productivity was also established. The findings confirm the reliability of the developed model and highlight the potential of solar distillation as a sustainable freshwater source for high-temperature regions. Full article

The use of solar control foils (SCFs) is a minimally invasive method that enables energy savings while preserving the original character of historic building facades. This study analysed the energy reduction potential of four types of window films applied to single-pane glazing. A typical office space at the University of Bologna, located in a historic building, served as a case study. Building performance simulations using DesignBuilder and Berkeley Lab Optics software were applied as research tools. The potential reduction in cooling energy consumption by using SCFs can be up to about 35% in humid subtropical (Bologna) and Mediterranean (Seville) climates. A decrease of about 53% can be achieved in a temperate oceanic climate (Paris). Due to the reduction in heat gains from solar radiation, there is an increase in energy consumption for heating by 6% to even 50% and up to a maximum of about 15% for artificial lighting. Financial indicators such as LCC, NPV, and IRR were used to select the optimal option. The recommended solution was an SCF installed on the inside of the window with SHGC of 0.452, a visible transmittance of 0.361, and an inside reflectance of 0.195. Additionally, this study proposes a method for correcting heating and cooling energy demand results calculated based on data for a typical meteorological year and weather parameters measured over the past 19 years. This allows for the validity of energy simulation results by taking into account current climate changes. Full article

Quantum dots (QDs) composed of the narrow-bandgap semiconductor PbTe were incorporated into the depletion region of p–n junctions based on wide-bandgap II–VI semiconductors (p-ZnTe/n-CdTe). The heterostructures were grown by molecular beam epitaxy (MBE) on semi-insulating GaAs (100) substrates. The depletion region was engineered by depositing 20 alternating thin layers of CdTe and PbTe, then thermal annealing under ultrahigh vacuum. As revealed by cross-sectional scanning electron microscopy (SEM), the initially continuous PbTe layers transformed into arrays of zero-dimensional nanostructures, namely PbTe QDs. The formation of PbTe QDs in a CdTe matrix arises from the structural mismatch between the zinc blende and rock-salt crystal structures of the two materials. Electron beam-induced current (EBIC) scans confirmed that the QDs are localized within the depleted charge region between the p-ZnTe and n-CdTe layers. The resulting wide-gap diodes containing narrow-band QDs show pronounced sensitivity to infrared radiation in the spectral range of 1–4.5 μm, with a peak responsivity of approximately 8 V/W at a wavelength of ~2.0 μm and a temperature of 200 K. A red-shift in the cutoff wavelength when temperature decreases indicates that the infrared (IR) response is governed by band-to-band optical transitions in the PbTe QDs. In addition, the devices show sensitivity to visible radiation, with a maximum responsivity of 20 V/W at 0.69 μm. These results demonstrate that wide-bandgap p–n junctions incorporating narrow-bandgap QDs can function as dual-wavelength (visible and infrared) photodetectors, with potential applications in two-color detection and infrared solar cells. Full article

The current study presents a holistic technology evaluation and integration methodology for enhancing the aerodynamic efficiency and performance of a tactical, fixed-wing Blended-Wing-Body (BWB) Unmanned Aerial Vehicle (UAV) through the synergetic integration of several aerodynamic and performance-enhancing technologies. Based upon several individual technology investigations conducted in the framework of the EURRICA (Enhanced Unmanned aeRial vehicle platfoRm using integrated Innovative layout Configurations And propulsion technologies) research project for BWB UAVs, a structured Technology Identification, Evaluation, and Selection (TIES) is conducted. That is, a synergetic examination is made involving technologies from three domains: configuration layout, flow control techniques, and hybrid-electric propulsion systems. Six technology alternatives, slats, wing fences, Dielectric Barrier Discharge (DBD) plasma actuators, morphing elevons, hybrid propulsion system and a hybrid solar propulsion system, are assessed using a deterministic Multi-Attribute Decision Making (MADM) framework based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Evaluation metrics include stall velocity (V_s), takeoff distance (s_g), gross takeoff weight (GTOW), maximum allowable GTOW, and fuel consumption reduction. Results demonstrate that certain configurations yield significant improvements in low-speed performance and endurance, while the corresponding technology assumptions and constraints are, respectively, discussed. Notably, the configuration combining slats, morphing control surfaces, fences, and hybrid propulsion achieves the highest ranking under a performance-future synergy scenario, leading to over 25% fuel savings and more than 100 kg allowable GTOW increase. These findings provide quantitative evidence for the potential of several technologies in future UAV developments, even when a novel configuration, such as BWB, is used. Full article

Multiband solar cells offer a promising route to surpass the Shockley-Queisser limit by harnessing sub-bandgap photons through three active energy band transitions. However, realizing their full potential requires overcoming key challenges in material design and device architecture. Here, we propose a novel multiband stacked anti-parallel junction solar cell structure based on highly mismatched alloys (HMAs), in particular dilute GaAsN with ~1–4% N. An anti-parallel junction consists of two semiconductor junctions connected with opposite polarity, enabling bidirectional current control. The structures of the proposed devices are based on dilute GaAsN with anti-parallel junctions, which allow the elimination of tunneling junctions—a critical yet complex component in conventional multijunction solar cells. Semiconductors with three active energy bands have demonstrated the unique properties of carrier transport through the stacked anti-parallel junctions via tunnel currents. By leveraging highly mismatched alloys with tailored electronic properties, our design enables bidirectional carrier generation through forward- and reverse-biased diodes in series, significantly enhancing photocurrent extraction. Through detailed SCAPS-1D simulations, we demonstrate that strategically placed blocking layers prevent carrier recombination at contacts while preserving the three regions of photon absorption in a single multiband semiconductor p/n junction. Remarkably, our optimized five-stacked anti-parallel junctions structure achieves a maximum theoretical conversion efficiency of 70% under 100 suns illumination, rivaling the performance of state-of-the-art six-junctions III-V solar cells—but without the fabrication complexity of multijunction solar cells associated with tunnel junctions. This work establishes that highly mismatched alloys are a viable platform for high efficiency solar cells with simplified structures. Full article

As one of the polymorphs of the gallium oxide family, ε gallium oxide (ε-Ga₂O₃) demonstrates promising potential in high-power electronic devices and solar-blind photodetection applications. However, the synthesis of pure-phase ε-Ga₂O₃ remains challenging through low-energy consumption methods, due to its metastable phase of gallium oxide. In this study, we have fabricated pure-phase and highly oriented ε-Ga₂O₃ thin films on c-plane sapphire substrates via thermal atomic layer deposition (ALD) at a low temperature of 400 °C, utilizing low-reactive trimethylgallium (TMG) as the gallium precursor and ozone (O₃) as the oxygen source. X-ray diffraction (XRD) results revealed that the in situ-grown ε-Ga₂O₃ films exhibit a preferred orientation parallel to the (002) crystallographic plane, and the pure ε phase remains stable following a post-annealing up to 800 °C, but it completely transforms into β-Ga₂O₃ once the thermal treatment temperature reaches 900 °C. Notably, post-annealing at 800 °C significantly enhanced the crystalline quality of ε-Ga₂O₃. To evaluate the optoelectronic characteristics, metal–semiconductor–metal (MSM)-structured solar-blind photodetectors were fabricated using the ε-Ga₂O₃ films. The devices have an extremely low dark current (<1 pA), a high photo-to-dark current ratio (>10⁶), a maximum responsivity (>1 A/W), and the optoelectronic properties maintained stability under varying illumination intensities. This work provides valuable insights into the low-temperature synthesis of high-quality ε-Ga₂O₃ films and the development of ε-Ga₂O₃-based solar-blind photodetectors for practical applications. Full article

Unmanned aerial vehicles (UAVs) are increasingly utilized across civilian and defense sectors due to their versatility, efficiency, and cost-effectiveness. However, their operational endurance remains constrained by limited onboard energy storage. Recent research has focused on electric propulsion systems integrated with hybrid energy sources, particularly the combination of solar cells and advanced battery technologies to overcome this limitation. This review presents a comprehensive analysis of the latest advancements in electric propulsion architecture, solar-based power integration, and hybrid energy management strategies for UAVs. Key components, including motors, electronic speed controllers (ESCs), propellers, and energy storage systems, are examined alongside emerging technologies such as wireless charging and flexible photovoltaic (PV) materials. Power management techniques, including maximum power point tracking (MPPT) and intelligent energy control algorithms, are also discussed in the context of long-endurance missions. Challenges related to energy density, weight constraints, environmental adaptability, and component integration are highlighted, with insights into potential solutions and future directions. The findings of this review aim to guide the development of efficient, sustainable, and high-endurance UAV platforms leveraging electric-solar hybrid propulsion systems. Full article

This study compared the efficacy of three individual lytic phages, PSA_LMAPSA-2T (PSA-2T), PSA_LMAPSA-6F (PSA-6F) and PSA_LMAPSA-7F (PSA-7F) and four phage cocktails (dual and triple combinations) in inactivating Pseudomonas syringae pv. actinidiae. Phages were isolated from kiwifruit leaves and soil samples contaminated with P. syringae pv. actinidiae and characterized by host spectrum, growth parameters, adsorption rate, genomic analysis, inactivation efficiency and viability under variable environmental conditions in orchard environments (temperature, pH and solar radiation). Phage PSA-2T showed the highest in vitro efficacy, achieving a 3.2 log CFU/mL maximum reduction after 18 h, outperforming PSA-6F and PSA-7F (0.6 and 1.5 log reductions, respectively). Phage cocktails achieved reductions of 1.0–2.2 log CFU/mL, but none exceeded the performance of PSA-2T alone. Phage viability was most affected by high temperature and acidic pH, with PSA-7F showing the greatest sensitivity. Nonetheless, all phages remained stable under typical orchard conditions. Phage PSA-2T significantly reduced P. syringae pv. actinidiae levels (1.5-log CFU/mL) on artificially contaminated kiwifruit leaves after a single treatment. These results demonstrate the potential of PSA-2T and phage cocktails as sustainable alternatives to copper and antibiotics, warranting further study of repeated treatments and broad-host-range phage formulations for field use. Full article

Silicon nanowires (SiNWs) fabricated by Ag-assisted metal-assisted chemical etching (MACE) exhibit excellent light-trapping performance, yet their fragile high-aspect-ratio morphology severely limits reliable metallization in photovoltaic devices. Conventional electrode deposition methods often fail on dense SiNW arrays due to poor mechanical stability of the nanowire tips, leading to delamination, inhomogeneous coverage, and high contact resistance. In this work, we introduce a maskless laser-based truncation technique that selectively shortens MACE-derived SiNWs to controlled residual heights of 300–500 nm exclusively within the regions intended for electrode formation, while preserving the full nanowire morphology in active areas. A detailed parametric study of laser power, scanning speed, and pulse repetition frequency allowed the identification of an optimal processing window enabling controlled tip melting without damaging the nanowire roots or the crystalline silicon substrate. High-resolution SEM imaging confirms uniform planarization, well-preserved structural integrity, and the absence of subsurface defects in the laser-processed tracks. Optical reflectance measurements further demonstrate that introducing 2% and 5% truncated surface fractions—corresponding to the minimum and maximum metallized front-grid coverage in industrial Si solar cells—results in only a minimal reflectance increase, preserving the advantageous the light-trapping behavior of the SiNW texture. The proposed laser truncation approach provides a clean, scalable, and industrially compatible route toward creating electrode-ready surfaces on nanostructured silicon, enabling reliable metallization while maintaining optical performance. This method offers strong potential for integration into silicon photovoltaics, photodetectors, and nanoscale electronic and sensing devices. Full article

Soybean seed production in low-altitude subtropical environments in Paraguay is constrained by the antagonism between achieving high grain yields and high physiological seed quality, a relationship governed by the Genotype x Environment x Management (GxExM) interaction. This study aimed to elucidate this trade-off by evaluating three sowing dates (early, normal, late) across genotypes from three relative maturity groups over four growing seasons. Our results demonstrate that sowing date is the primary factor modulating this antagonism. Early and normal sowings maximized yield (up to 62.8% higher than late sowing) by synchronizing the reproductive period with maximum solar radiation but exposed the maturation phase to severe thermal and water stress. This consistently resulted in a high incidence of green seeds (>95% higher than late sowing) and a drastic reduction in seed vigor, with longevity potential reduced by up to 63.6%. In contrast, late sowing functioned as a stress-escape strategy, shifting maturation to milder autumn conditions and consistently producing seeds of high vigor, viability, and greater longevity. Critically, during a season of extreme drought and heat, the late sowing not only preserved quality but also produced the highest grain yield, highlighting its decisive role in risk mitigation. Thus, sowing date is a key management tool for targeted production in these environments. Full article

Machine learning models such as XGBoost show strong potential for predicting pasture quality metrics like crude protein (CP) content in tamani grass (Panicum maximum). However, their ‘black box’ nature hinders practical adoption. To address this limitation, this study applied SHapley Additive exPlanations (SHAP) to interpret an XGBoost model and uncover how management practices (grazing interval, nitrogen fertilization, and pre- and post-grazing heights) and environmental factors (precipitation, temperature, and solar radiation) jointly influence CP predictions. Data were divided into 80% for training/validation and 20% for testing. Model performance was assessed with stratified 5-fold cross-validation, and hyperparameters were tuned via grid search. The XGBoost model yielded a Pearson correlation coefficient (r) of 0.78, a mean absolute error (MAE) of 1.45, and a coefficient of determination (R²) of 0.57. The results showed that precipitation in the range of 100–180 mm increased the predicted CP content. Application of 240 kg N ha⁻¹ year⁻¹ positively affected predicted CP, whereas a lower dose of 80 kg N ha⁻¹ year⁻¹ had a negative impact, reducing predicted levels of CP. These findings highlight the importance of integrated management strategies that combine grazing height, nitrogen fertilization, and grazing intervals to optimize crude protein levels in tamani grass pastures. Full article