The global development of LED lighting in all applications for both public and indoor lighting establishes a very important lever for reducing the carbon impact by significantly reducing energy consumption. Smart lighting will therefore constitute an essential lever in the smart city of tomorrow. The latter is more sustainable and less energy-intensive than other light sources, contributing towards the Sustainable Development Goals set forth by the United Nations (SDGs 7 and 11). With its ease of integration, ergonomics, lightness, and high quality of light, this innovative light source has two major qualities: its energy efficiency and its long service life. However, poor thermal management has catastrophic effects on these two essential criteria. This necessarily requires optimizing thermal management and heat sinks. In some cases, thermal models and simulations can lead to considerable calculation times because they implement many parameters. This work therefore aims to reduce the number of these simulations by applying the method of experimental designs (Taguchi) and analysis of variance (ANOVA) to simulations intended to optimize the dissipation of LED luminaires. We applied the method to a simple finned heat sink model for a unit input power and then to a concrete case of a high-power LED. The control parameters and their respective contributions in the proposed model were studied. The ANOVA results corroborated the conclusions of the Taguchi method, demonstrating a strong agreement between these analytical methods, in which the temperature was adjusted by identifying optimal combinations of parameters. The fields of application relevant to this study include both indoor lighting (false ceiling) and confined spaces with severe sealing constraints such as car headlights or the optical blocks of urban luminaires.

Hydrogen fuel cell vehicles are one of the most promising alternatives to achieve transport decarbonization targets, thanks to their moderately high efficiency and low refueling time, combined with their zero-exhaust-emission operation. In order to reach reasonable power density figures, fuel cell systems are generally supercharged by radial compressors, which can encounter significant limitations associated with surge and choke operation, especially at high altitudes. Alternatively, the current paper explores the altitude operation of a fuel cell system combined with a Roots compressor. First, the balance of the plant model is built in the Simscape platform, combining a physical and chemical 1D fuel cell model for the stack, calibrated against literature data at different pressure and temperature values, as well as the characteristic maps of the Roots compressor. Then, the model is used to explore the balance-of-plant operation in a working range between 10 and 200 kW and an altitude range between sea level and 5 km. The results show that the compressor is capable of operating around the highest efficiency area (between 60 and 70%) for a wide range of altitude and power conditions, limiting the negative impact of the altitude on the system efficiency to up to 3%. However, once the compressor efficiency falls below 60%, the balance-of-plant performance rapidly drops, overcoming the benefits of the working pressure on the fuel cell stack operation and limiting the peak net power produced.

Hydrogen fuel cell vehicles are one of the most promising alternatives to achieve transport decarbonization targets thanks to their moderately high efficiency and low refueling time combined with zero exhaust emissions operation. In order to reach reasonable power density figures, fuel cell systems are generally supercharged by radial compressors, which can encounter significant limitations associated to surge and choke operation especially in high altitude. Alternatively, the current paper explores the altitude operation of a fuel cell system combined with a roots compressor. First, the balance of plant model is build in Simscape platform combining a physical and chemical 1D fuel cell model for the stack, calibrated against literature data at different pressure and temperature values, and the characteristic maps of the roots compressor. Then, the model is used to explore the balance of plant operation in a working range between 10 and 200 kW and an altitude range between sea level and 5 km. The results show that the compressor is capable to operate around the highest efficiency area (between 60 and 70%) for a wide range of altitude and power conditions, limiting the negative impact of the altitude in the system efficiency up to 3%. However, once the compressor efficiency falls below 60% the balance of plant performance rapidly drops, overcoming the benefits of the working pressure on the fuel cell stack operation and limiting the peak net power produced.

This article presents a multi-objective optimization framework for fluorescent organic light-emitting diodes (OLEDs), combining numerical simulation with an analysis of exciton populations and the associated loss mechanisms. An ITO/NPB/Alq₃:C545T/Alq₃/LiF–Al structure was modeled, calibrated, and validated against experimental electro-optical characteristics. The influence of the emissive layer thickness ($t_{\mathrm{EML}}$) and the C545T doping concentration ($D_p$) was systematically studied across 25 configurations, with $t_{\mathrm{EML}}$= 20–40 nm and $D_p=1$–$9\%$, under two operating conditions: $J=0.15$ A/cm² and $L=5000$ cd/m². Increasing the dopant concentration led to a marked deterioration in current efficiency (${\eta }_c$) and power efficiency (${\eta }_p$), together with a progressive localization of singlet excitons near the interface between the emissive layer (EML) and the hole transport layer (HTL) in structures with thinner EMLs. This exciton localization was accompanied by an increased contribution from non-radiative deactivation pathways, which were incorporated into a dopant singlet-exciton loss fraction, $F_{\mathrm{loss},d}$. The systematic increase in this loss fraction with increasing dopant concentration and its overall inverse relationship with ${\eta }_c$ and ${\eta }_p$ motivated the development of a three-objective formulation that maximizes ${\eta }_c$ and ${\eta }_p$ while minimizing $F_{\mathrm{loss},d}$. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) identified compromise solutions at the lowest dopant concentration, $D_p=1\%$, with $t_{\mathrm{EML}}=24$–25 nm under both operating conditions. Multi-objective Particle Swarm Optimization (MOPSO) identified a trade-off region comparable to that obtained by NSGA-II, providing a cross-algorithm consistency check of the reported numerical results. The proposed methodology thus establishes a physically grounded link between device design, the spatial redistribution of excitons, the modeled loss pathways, and the macroscopic performance of OLEDs, thereby providing an interpretable framework for the multi-objective optimization of fluorescent OLEDs prior to fabrication.

In this work, SERS is employed as an effective detection technique for Fenazaquin (FEN) due to its notable specificity and sensitivity. The investigation involves a comprehensive analysis using UV–Vis spectroscopy, Raman spectroscopy and SERS on solutions containing varying concentrations of FEN. Different experimental conditions were examined to optimize the detection process, with Raman spectra acquired for FEN powder. SERS analyses were conducted across a concentration range of 9.9 × 10⁻⁸ to 1.9 × 10⁻⁶ mol/L. The selection of suitable substrates is crucial for optimizing SERS performance. Herein, the SERS signals of FEN were studied on Ag nanoparticles reduced by hydroxylamine (AgSH), with aggregation induced by KNO₃ salt. To support the experimental data, the molecular structure and theoretical Raman spectra of FEN were calculated using Density Functional Theory (DFT). Furthermore, to gain insights into the interaction mechanisms between FEN and the Ag substrate, Adsorption Locator Monte Carlo simulations were employed. These simulations predicted the most favorable adsorption configurations and identified the probable site of attack of FEN on the silver surface, revealing key adsorption geometries contributing to SERS enhancement. The theoretical results were essential for assigning the vibrational modes of FEN. The combination of experimental and theoretical analyses led to the successful detection of FEN, with a remarkable limit of quantification (LOQ) of 9.9 × 10⁻⁸ mol/L (30 ppb). This integrated approach provides precise insights into the molecular properties and detection capabilities of FEN.