Zakaria Mansouri

Phase‐change metasurfaces have attracted significant attention for reconfigurable photonic devices owing to their ability to tune optical responses between amorphous and crystalline phases. Despite their potential in optical switching, communications, and signal processing, achieving large optical modulation while maintaining low optical loss and strong field confinement remains a major challenge. Here, the unique properties of metasurfaces on monolithic and hybridized /Si platforms are experimentally demonstrated. In the telecommunications spectral range, both phases remain nearly lossless, with a large refractive‐index contrast. The monolithic metasurface enables transmission modulation depths of up to 92% and resonance shifts of 150 nm through laser‐induced phase transitions to 50% polycrystalline state. Integrating a silicon overlayer introduces hybrid resonance with enhanced near‐field confinement, achieving comparable modulation with nearly half the laser switching power required by the monolithic structure. Furthermore, the broad resonance tunability and strong third‐order nonlinearity of metasurface enable tunable third‐harmonic generation over a 40 nm spectral range. The hybrid /Si platform further demonstrates a threefold enhancement in tunable THG emission, benefiting from the combined nonlinear responses and strong resonance field confinement. These results highlight the potential of monolithic and hybrid metasurfaces for compact low‐power optical switching and tunable visible light sources.

This study presents an experimental investigation into the combustion of iron particles over a substantially extended size range (10–250 µm), addressing the limitations of prior research constrained to smaller particles (typically < 100 µm). Using a drop tube burner setup, individual iron particles were released through a fuel‐lean, laminar flat flame, and their combustion dynamics were observed via high‐speed imaging and photomultiplier tube (PMT) measurements. The primary objective was to determine whether a single power‐law scaling (τ _b = mdⁿ) could describe the burn time ( τ _b ) across the full particle size (d) spectrum. The results reveal that a single scaling law is insufficient; instead, two distinct combustion regimes emerge. For particles between 13 and 118 µm, burn time exhibits a weak dependence on particle size, indicative of rapid heating and diffusion‐limited combustion. Above 118 µm, a stronger particle size dependence is observed, reflecting the increasing influence of internal heat conduction. This transition in scaling behaviour aligns with analogous trends found in aluminium and titanium combustion, suggesting a potential shift in the governing mechanisms at critical particle sizes specific to each metal. Additionally, high‐resolution PMT diagnostics identified key sub‐timescales constituting the ignition delay phase, including heating, melting, and thermal runaway. High‐resolution imaging revealed unexpected nanoparticle formation during the burnout phase. This phenomenon challenges the conventional understanding of liquid‐phase iron combustion. Scanning electron microscopy (SEM) confirmed the presence of nanoparticles and explosive fragmentation events, the latter attributed to structural heterogeneities within the iron particles.

Ultra‐lean operation in micro‐combustion‐based thermophotovoltaic systems offers significant benefits including low pollutant emissions and increased longevity due to reduced thermal stresses, but it is hindered by low thermal performance. This paper numerically addresses the potential of oxygen enrichment and preheating to counteract performance losses in a hydrogen‐powered micro‐trapped vortex combustor operating under ultra‐lean conditions. A Taguchi design of 16 cases was conducted at a fixed equivalence ratio of ϕ = 0.3, varying inlet temperature from 300 to 450 K and O ₂ levels from 21% to 30%, to evaluate their impact on radiative power, energy conversion efficiency, combustion efficiency, and NO _x emissions. Results indicate that excessive enrichment (30% O ₂ ) at high inlet temperature (≥ 400 K) leads to flame flashback, establishing an upper safety limit. Within the stable operating region, O ₂ enrichment substantially improved radiative power by up to 56%, while preheating enhanced radiative efficiency by up to 73%, with both factors exhibiting equal influence on combustion efficiency. However, the use of oxygen‐enriched air remarkably increased NOx emissions compared to the baseline case at 21% O ₂ . Moreover, the optimal configuration with T _in = 450 K and X _O2 = 0.27 has achieved 41% higher energy efficiency and 99% lower pollutant emissions compared to the lean case at ϕ = 0.8.

This work contributes to advancing sustainable energy and waste management strategies by investigating the thermochemical conversion of food-based biomass through pyrolysis, highlighting the role of artificial intelligence (AI) in enhancing process modelling accuracy and optimization efficiency. The main objective is to explore the potential of underutilized biomass resources like spent coffee grounds (SCGs) and DSs (date seeds) for sustainable hydrogen production. Specifically, it aims to optimize the pyrolysis process while evaluating the performance of these resources both individually and as blends. Proximate, ultimate, fibre, TGA/DTG, kinetic, thermodynamic, and Py-Micro-GC analyses were conducted for pure DS, SCG, and blends (75% DS-25% SCG, 50%DS-50%SCG, 25%DS–75%SCG). Blend 3 offered superior hydrogen yield potential but had the highest activation energy (Ea: 313.24 kJ/mol), while Blend 1 exhibited the best activation energy value (Ea: 161.75 kJ/mol). The kinetic modelling based on isoconversional methods (KAS, FWO, and Friedman) identified KAS as the most accurate. These approaches work together to provide a detailed understanding of the pyrolysis process with a particular emphasis on the integration of artificial intelligence (AI). An LSTM model trained with lignocellulosic data predicted TGA curves with exceptional accuracy (R²: 0.9996–0.9998).

Modern high-pressure turbine (HPT) nozzle guide vanes (NGVs) operate under non-uniform inlet conditions, including hot streaks and swirl, which can induce complex flow phenomena and uneven thermal loading. These effects, particularly at the hub-vane corner, can compromise NGV durability, yet the combined influence of swirl and film cooling remains underexplored. The objective of this study is to investigate the aerothermal behaviour of contoured first-stage NGVs under varying swirl intensities and directions to improve understanding of hub and corner thermal protection and failure mechanisms. Steady, compressible RANS simulations were conducted with the k-ω SST turbulence model. A vane with a contoured hub and multiple film cooling rows was designed and analysed under axial and swirling inflows, both clockwise and counter-clockwise, with swirl numbers of Sn = ±0.2 and ±0.4. Axial flow achieved the highest area-averaged film cooling effectiveness (FCE) of 0.617. Negative swirl (Sn = −0.4) improved suction-side corner FCE to 0.215 but reduced pressure-side cooling, whereas positive swirl (Sn = 0.4) improved pressure-side cooling but reduced suction-side FCE to 0.043. Corner temperatures under positive swirl reached 1780 K, consistent with promoting failure, while negative swirl reduced corner temperatures to 1516 K. Aerodynamic losses increased with swirl, with negative swirl generating 5.78% higher total pressure losses than the axial baseline. Swirl altered the corner vortex topology, affecting boundary layer interactions and local heat transfer. These results highlight a trade-off between thermal protection and aerodynamic efficiency, emphasising that optimising NGV performance requires careful design of hub cooling and consideration of swirl direction and intensity.

Iron powder represents a promising carbon-free, sustainable fuel, yet its practical utilisation in combustion has not yet been realised. Achieving stable, efficient iron-only flames is challenging, and the environmental impact of hybrid iron-hydrocarbon combustion, including particle emissions, is not fully understood. This study investigates hybrid methane–iron powder flames to assess iron’s role in modifying gas and particle phase emissions and its potential as a sustainable energy carrier. The combustion of iron was investigated at both the single particle and powder flow scales. Experimental diagnostics combined high-speed and microscopic imaging, ex situ particle sizing, in situ gas analysis, and aerosol measurements using an Aerodynamic Particle Sizer (APS™) and a Scanning Mobility Particle Sizer (SMPS™). For single particle combustion, high-speed imaging revealed rapid particle heating, oxide shell growth, cavity formation, micro-explosions, and nanoparticle release. For powder combustion, at 0.5 g/min and 1.26 g/min, the experiment yielded oxidation fractions of 15.15% and 23.43%, respectively, and increased CO₂ emissions by 0.22–0.35 vol% relative to methane–air flames, while NOx changes were negligible. Aerosol analysis showed a supermicron mode at ~2 µm and submicron ultrafine particles of 89% 2 emissions while enhancing iron oxidation efficiency.

This study develops an integrated computational fluid dynamics‐artificial neural network (CFD‐ANN) framework to optimize hydrogen production via steam methane reforming (SMR) in a plate reactor. We first established a two‐dimensional CFD model using OpenFOAM to simulate transport phenomena and catalytic SMR reaction kinetics on a nickel‐based catalyst‐coated surface. Experimental validation shows that the model achieves a methane conversion of 90.73% and a hydrogen mass fraction of 2.68 wt.% at the reactor outlet. To overcome the prohibitive computational cost of traditional CFD‐based optimization, we construct and train an ANN with five hidden layers using datasets generated from the validated CFD simulations. The trained ANN demonstrates exceptional predictive performance, achieving a coefficient of determination ( R ² ) of 0.9997 and a mean absolute error of 0.0003 wt.%. Furthermore, the ANN delivers predictions in just 19.1 μ s per case, approximately eight orders of magnitude faster than the 30 min required by CFD simulations. This dramatic speed‐up, combined with near‐perfect predictive accuracy, positions the ANN as a highly efficient and practical surrogate model for real‐time SMR process optimization. The integrated CFD‐ANN framework offers a powerful tool for accelerating the design and control of waste‐heat–driven hydrogen production systems.

The combustion of iron powder, a promising zero‐carbon energy carrier, entails millions of burning particles, a process different from that of conventional fuels. To fully harness this potential, a thorough understanding of the combustion behaviour of individual iron particles is vital. This experimental investigation provides new insights into the combustion time scales, burn rates and oxidation regime transitions governing single iron particle combustion under low‐oxygen environments, representative of conditions in practical metal‐fuel energy systems. For the first time, a broad particle size spectrum ( d = 10−250 μm) was investigated using a vertical drop‐tube burner with a lean diffusion CH ₄ /O ₂ /N ₂ flat flame at oxygen concentrations from 15 to 20 vol%. Combustion timescales were quantified using optical diagnostics, and the oxidised products were characterised via scanning electron microscopy (SEM). The results revealed that both burn time ( t _b ) and ignition delay increase with particle size and decrease with oxygen concentration, following sub‐linear power‐law ( t _b ~ d ⁿ with n < 1) relationships. Analysis of the burn rate ( r _b ~ d ^p ) revealed a clear double‐slope behaviour across the particle size range, indicating a transition from heat and mass transfer oxidation control for smaller particles to kinetically limited oxidation for larger ones. The breakpoint of the double‐slope was found at 124, 109 and 53 µm for O ₂ concentrations of 15, 17 and 20 vol%, respectively. Ex situ characterisation under oxygen‐lean conditions (15 and 17 vol%) revealed naturally quenched particles with iron core and oxide shell (OxS) structures and asymmetric morphologies, evidencing incomplete combustion. These findings support the theoretical hypothesis about the formation of core–shell structures.